e-Learning Environment Tools to Address Online

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e-Learning Environment Tools to Address Online and Open Distance Education Context Challenges Conference Paper · June 2016

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Proceedings of the 11th International Conference on e- Learning Universiti Sains Islam Malaysia (USIM) Kuala Lumpur Malaysia

2 - 3 June 2016

Edited Edit d by b Rozhan M. Idrus Nurkhamimi Zainuddin

A conference managed by ACPI, UK

Proceedings of The 11th International Conference on e- Learning ICEL 2016 2-3rd June 2016

Hosted by Universiti Sains Islam Malaysia Kuala Lumpur Malaysia

Edited by Prof. Dr. Rozhan M. Idrus and Dr Nurkhamimi Zainuddin Universiti Sains Islam Malaysia Kuala Lumpur Malaysia

Copyright The Authors, 2016. All Rights Reserved. No reproduction, copy or transmission may be made without written permission from the individual authors. Review Process Papers submitted to this conference have been double-blind peer reviewed before final acceptance to the conference. Initially, abstracts were reviewed for relevance and accessibility and successful authors were invited to submit full papers. Many thanks to the reviewers who helped ensure the quality of all the submissions. Conference Proceedings The Conference Proceedings is a book published with an ISBN and ISSN. The proceedings have been submitted to a number of accreditation, citation and indexing bodies including Thomson ISI Web of Science and Elsevier Scopus. Author affiliation details in these proceedings have been reproduced as supplied by the authors themselves. The Electronic version of the Conference Proceedings is available to download from DROPBOX (http://tinyurl.com/ICEL2016) Select Download and then Direct Download to access the Pdf file. Free

download is available for conference participants for a period of 2 weeks after the conference. The Conference Proceedings for this year and previous years can be purchased from http://academicbookshop.com Print version ISSN: 2048-8882 Print version ISBN: 978-1-910810-91-0 E-Book ISSN: 2048-8890 E-Book ISBN: 978-1-910810-92-7 Published by Academic Conferences and Publishing International Limited Reading, UK. 44-118-972-4148. www.academic-publishing.org

Contents Paper Title

Author(s)

Page no

Preface

iv

Committee

v

Biographies

viii

Research papers Efficient Instructor Feedback: Perceptions of Online UAE Undergraduate and Postgraduate Public Health Learners

Niyi Awofeso and Moyosola Bamidele

1

Dilemmas Facing Universities in Implementing Online Learning Programmes

Mammed Bagher and Aileen Sibbald

13

ICT Tools Usage’s Effectiveness by Communities of Practice in Promoting Knowledge Management Innovation

Kay Bandlow and Sheryl Buckley

21

Invisible Pedagogy: Developing Learners’ Self-Responsibility in Digital Environments Through Problem-Based Learning

Wendy Barber and Sherry King

26

Engagement in Online Asynchronous Discussions: Roles of Students' Interests and Preferences

Kevin Chan, Simon Lai, Hildie Leung and Kelvin Wan

32

Exploring the Experiences of Learners in a Large Scale Distance Language Learning Program Offered in Countries Across Latin America

Paula Charbonneau-Gowdy

37

Teachers’ Knowledge and Technology Acceptance: A Study on the Adoption of Clickers

George Cheung, Kevin Chan, Ian Brown and Kelvin Wan

46

E-Learning in Higher Education: Challenges and Tribulations for Social Justice

Teresa Chikerema, Golden Chikari and Primrose Chikerema

52

Support for Lifelong Learning at the University of West Bohemia

Jakub Jirasko and Martin Hynek

61

Designing a Sign Language Intelligent Game-Based Learning Framework with Kinect

Teerawat Kamnardsiri, Ler-on Hongsit and Noppon Wongta

64

Evaluation of E-Learning Materials Created at the University of West Bohemia

Tomáš Keckstein, Petr Votápek and Jakub Jirásko

74

…From the Other Side of Moodle/Technology in Education of Postgraduate Students’ Reflections

Simon Bheki Khoza

79

Peer Interaction and Students’ Perceptions Towards Constructivist-Collaborative Learning Environment: Motivation and Affective Factor

Fui-Theng Leow and Mai Neo

87

E-learning in the Teaching of Technical Disciplines

Antonín Max, Šimon Pušman and Martin Hynek

96

Mobile Tutorial System With Tablet Computer and Digital Pen

Kazuhiro Muramatsu, Yeshi Wangchuk, Karma Kelzang Eudon Chencho and Sangay Pem

102

Are my Students Ready: A Case of Flipped Learning in an IT Subject

Vincent Ng, Rufus LiFeng Huang, Lung Chi Hong and Liu KunHong

107

i

Paper Title

Author(s)

Page no

A Semantic web Solution for Circumventing Disparities Between Electronic-Learning Systems and Mobile-Learning Systems

Sibangiso Ngwenya, Sikhulumani Bayeza Mangena and Khesani Richard Chilumani

115

Teaching and Learning Innovations on Blackboard: What Form and Function?

Vuyisile Nkonki and Siyanda Ntlabathi

120

Robotic Workmates: Hybrid Human-Robot-Teams in the Industry 4.0

Anja Richert, Mohammad Shehadeh, Sarah Müller, Stefan Schröder and Sabina Jeschke

127

More time, more Assessments, the Impact on Programming Students in an E-Learning Environment

Dalize van Heerden

132

Cultivating Problem-Solving Skills in Malaysian Undergraduates: An Authentic Blended Learning Approach

Heidi Yeen-Ju Tan and Mai Neo

139

Transforming From Conventional Teaching Environment to Learner-Centred Teaching Environment With the use of Interactive Multimedia Module in Tertiary Education

Wei-Li Yap, Mai Neo and Tse-Kian Neo

147

Innovative Utilization of the Moodle in Postgraduate ODL Courses at Universiti Sains Islam Malaysia

Nurkhamimi Zainuddin, Rozhan Idrus and Ahmad Farid Mohd Jamal

157

PHD Research Papers

165

Accepting Social Networks in Learning and Teaching

Elham Akbari, Ahmad Naderi, , Mahdi Hosseinzadeh Yazdi Robert-Jan Simons and Albert Pilot

167

E-learning Strategies in the Workplace That Supports Speed to Proficiency in Complex Skills

Raman Attri and Wing Wu

176

Individualization of Pedagogical Paths via Traces Analysis

Mohamed Bendahmane, Brahim El Falaki and Mohammed Benattou

185

The Gesture Triggered Face Tracking for Enhanced eLearning Systems

Ramkumar Narayanan, Venkat Rangan, Uma Gopalakrishnan and Balaji Hariharan

190

A Continuum of Teachers’ e-Learning Practices

Osman Sadeck

198

Masters Research Papers

201

An e-Learning Environment Using Automated Development of Domain Ontology

Vidyashree B N and Sandeep Kumar

Effects of the Design Factors of Skill Training Game on Learning Performance and Emotio

Chun-Yi Chen Chih-Ming Chen, Wan-Chi Hu

219

Effects of Attention Monitoring and Alarm Mechanism on Promoting e-Learning Performance

Yi-Chen Huang, Chih-Ming Chen and Jian-Cheng Guo

229

An Optimized Group Formation Scheme Considering Knowledge Level, Learning Roles, and Interaction Relationship for Promoting Collaborative Problem-Based Learning Performance

Chen-Yu Liu, Chih-Ming Chen and Chi-Hsiung Kuo

238

ii

,

209

Paper Title

Author(s)

Assessing Effects of Information Architecture of Digital Museums on Supporting e-learning

Hsien-Chieh Sun and Chih-Ming Chen

247

Effects of Mobile Game-Based English Vocabulary Learning APP on Learners’ Perceptions and Learning Performance: A Case Study of Taiwanese EFL Learners

Lin Yen, Chih-Ming Chen and Hong-Bin Huang

255

Work In Progress Paper

Page no

263

A-Z: A Recipe for a Successful MOOC

Ian Brown, Indie Chung and Anthony Ho

Late Submission Papers

265 273

e-Learning Environment Tools to Address Online and Open Distance Education Context Challenges

Leila Goosen and Dalize van Heerden

275

Information Injection in Education: Syndrome of One-Way Dialogue

Taikulakova Gulnura, Kenjebayeva Zaure, Alex Polyakov and Agashkina Irina

285

iii

Preface These proceedings represent the work of researchers participating in the 11th International Conference on eLearning (ICEL 2016) which is being hosted this year by the Universiti Sains Islam Malaysia (USIM), Kuala Lumpur, Malaysia, on the 2 - 3rd June 2016. ICEL is a recognised event on the International research conferences calendar and provides a valuable platform for individuals to present their research findings, display their work in progress and discuss conceptual advances in the area of e-Learning. It provides an important opportunity for researchers and managers to come together with peers to share their experiences of using the varied and expanding range of e-Learning available to them. With an initial submission of 104 abstracts, after the double blind, peer review process there are 24 Academic Research papers, 5 PhD Research papers, 6 Master’s Research papers, 1 Work In Progress paper published in these Conference Proceedings. These papers come from some many different countries including: Australia, Bhutan, Botswana, Canada, Chile, China, Czech Republic, Germany, Hong Kong, India, Indonesia, Ireland, Kazakhstan, Malaysia, Morocco, Netherlands, Republic of Macedonia, Saudi Arabia, South Africa, Taiwan, R. O. C., Thailand, UK, United Arab Emirates, and Zimbabwe. A selection of the best papers – those agreed by a panel of reviewers and the editor will be published in a conference edition of EJEL (the Electronic Journal of e-Learning www.ejel.org). These will be chosen for their quality of writing and relevance to the Journal’s objective of publishing papers that offer new insights or practical help into the application e-Learning. Finally, sincere thanks to all the Keynote Speakers for their insights and to the academics and students who took time to produce their papers. We wish you a most interesting conference. Enjoy the ambiance, the networking and continue to communicate with each other in the future. Prof. Dr. Rozhan M. Idrus and Dr Nurkhamimi Zainuddin June 2016

iv

Conference Committee Conference Executives Dr Rozhan M. Idrus, Universiti Sains Islam Malaysia (USIM), Nilai, Negeri Sembilan, Malaysia. Dr Nurkhamimi Zainuddin, Universiti Sains Islam Malaysia (USIM), Nilai, Negeri Sembilan, Malaysia. Dr. Najwa Hayaati Mohd Alwi, Universiti Sains Islam Malaysia (USIM), Nilai, Negeri Sembilan, Malaysia. Mini track chairs Dr. Paula Charbonneau-Gowdy, Universidad Andres Bello, Santiago Chile Chuck Sigmund, Amazon Mohd Helmy Abd Wahab (Universiti Tun Hussein Onn Malaysia, Malaysia); Dr. Peter Aborisade (The Federal University of Technology Akure, Nigeria); Dr. Bulent Acma (Anadolu University, Eskisehir, Turkey); Dr. Chigona Agnes (Cape Peninsula University of Technology, South Africa); Dr. Osamah AL Qadoori (ECAE, UAE); Dr Hamid Alasadi (Basra University, Iraq); Dr. Ali Alawneh (Philadelphia University, Jordan); Prof. Saleh Alhalalat (King Saud University, Saudi Arabia); Lisa Allen (The University of British Columbia, Canada); Naji AlQbailat (Al-Balqa' Applied Uinversity, PAUC, Jordan); Nabeel Al-Qirim (UAE University, United Arab Emirates); Kalid Alshahrani (King Fahad Naval Academy , Saudi Arabia); Prof. Abdullah Al-Zoubi (Princess Sumaya University for Technology, Amman, Jordan); Dr. Anca-Olga Andronic (Faculty of Psychology and Educational Sciences, Spiru Haret University, Romania); Dr. Razvan-Lucian Andronic (Faculty of Psychology and Educational Sciences, Spiru Haret University, Romania); Dr Teresita Arenas Yanez (Technical University Federico Santa Maria UTFSM,, Chile); Dr. Ezendu Ariwa (London Metropolitan University, London, UK); Peter Arthur (University of British Columbia Okanagan, Kelowna, British Columbia,, Canada); Dr. Kallol Bagchi (University of Texas at El Paso, USA); Prof. Philip Leon Balcaen (University Of British Columbia, Kelowna, Canada); Dr Wendy Barber (University of Ontario Institute of Technology, Canada); Karen Barnstable (UBC Okanagan, Canada); Dr. Tshepo Batane (University of Botswana, Botswana); Dr. Patricia Beckenholdt (University of Maryland University College (UMUC), USA); Dr. Gary Bell (London South Bank University, UK); Jennifer Bergh (Eiffel-Corp - (Blackboard partners and resellers), South Africa); Prof. Sonia Berman (University of Cape Town, South Africa); Prosper Bernard (University of Quebec, Canada); dr. Igor Bernik (University of Maribor, Slovenia); Prof. Dr. Amine Berqia (University of Algarve, Faro, Portugal); Karen Bjerg Petersen (The Danish School of Education, University of Aarhus, Denmark); Dr. Patrick Blum (inside Business Group, Aachen, Germany); Dr. Mads Bo-Kristensen (Resource Center for Integration, Vejle, Denmark); David Bond (University of Technology, Sydney, Australia); Prof. Luis Borges Gouveia (University Fernando Pessoa, Portugal); Lynn Bosetti (University of British Columbia Okanagan, Kelowna, British Columbia,, Canada); Dr. Tharrenos Bratitsis (University of Western Macedonia, Greece); Ian Brown (Hong Kong Polytechnic University, Hong Kong); Dr. Sheryl Buckley (Unisa, South Africa); Jekaterina Bule (Riga Technical University, Latvia); Pasquina Campanella (University of Bari "Aldo Moro", Italy); Dr. Paula Charbonneau-Gowdy (Universidad Andres Bello, Chile); Prof. Phaik Kin Cheah (Universiti Tunku Abdul Rahman (UTAR), Malaysia); Dr. Adeline Chia (Taylor's University, Malaysia); Satyadhyan Chickerur (B V Bhoomaraddi College of Engineering and Technology, Hubli,, India); Chinnapaka Chitharanjandas (Information systems and e business, Bang college of business, Republic of Kazakhstan); Dr. Mohammad Chizari (Tarbiat Modarres University, Iran); Chee-Keong Chong (Universiti Tunku Abdul Rahman (UTAR), Malaysia); Hal Christensen (Christensen/Roberts Solutions, Forest Hill, NY, USA); Dr. Jaesam Chung (Ewha W. University, Rep. of Korea); Prof. Delaine Cochran (Indiana University, USA); Dr. Glenn Cockerline (Brandon University, Canada); David Comiskey (University of Ulster, Ireland); Dr. Caroline Crawford (University of Houston-Clear Lake, USA); Susan Crichton (University of British Columbia , Canada); Johannes Cronje (Cape Peninsula University of Technology, South Africa); Prof. Laura Czerniewicz (University of Cape Town, South Africa); Ramiza Darmi (Universiti Putra Malaysia, Australia); Annemarie Davis (University of South Africa, Pretoria, South Africa); Dr. Pieter De Vries (Delft University of Technology, The Netherlands); Prof. Rhena Delport (University of Pretoria, South Africa); Christina Dinsmore (Southampton Solent University, UK); Dr. Gilles Doiron (Zayed University, Abu Dhabi, United Arab Emirates); Jerome Dooga (University of Jos, Nigeria); Dr. Martina A. Doolan (Univeristy of Hertfordshire, UK); Dr. Laurent Dukan (PHD International, France); Dr. Judith Enriquez (University of North Texas, USA); Prof. Dr. Alptekin Erkollar (ETCOP, Austria); Prof. Jean-Louis Ermine (Telecom Business School, Evry Cedex, France); Nima Fallah (BETA - Strasbourg University, France); Stephen Farrier (University of Edinburgh, UK); Dr. Omid Fatemi (University of Tehran, Iran); Dr. Aikyna Finch (Strayer University, Huntsville, USA); Dr. Titi Fola-Adebayo (Fed Univ of Tech, Nigeria); Prof. Joseph Fong (City University of Hong Kong, Hong Kong,

v

China); Marga Franco-Casamitjana (Universitat Oberta de Catalunya, Spain); Daniela Gachago (Cape Peninsula University of Technology, South Africa); Fenella Galpin (Open University, UK); Dr. Grisel Garcia Perez (UBC Okanagan, Canada); Apostolos (Paul) Giannakopoulos (Unisa, South Africa, South Africa); Prof. Henrique Gil (School of Education -Polytechnic Institution of Castelo Branco, Portugal); Dr. Judy Gnarpe (University of Alberta, Canada); Gerald Goh (Multimedia University, Melaka, Malaysia); Dr. Andrew Goh (International Management Journals, Singapore); Dr. Andrea Gorra (Leeds Metropolitan University, UK); Jivesh Govil (Cisco Systems Inc, USA); Dr. Sue Greener (University of Brighton, UK); Dr. David Guralnick (Columbia University and Kaleidoscope Learning, New York, USA , USA); Dr. Rajaram Gurusamy (DMI ST. John the Baptist University, Malawi); Dr. Rugayah Gy Hashim (Universiti Teknologi MARA (UiTM), Malaysia); zuwati Hasim (University of Malaya, Malaysia); Dr. Mahmoud Hassanin (Pharos University in Alexandria, Egypt); Thanos Hatziapostolou (International faculty of the university of sheffield, Greece); Dr. Stylianos Hatzipanagos (King’s College London, UK); Alan Hilliard (University of Hertfordshire, UK); Mr Emmanuel Howe (Institute of Development Management (IDM), Swaziland); Dr. Eun Hwang (Indiana University of Pennsylvania, USA); Avi Hyman (University of Toronto, Canada); Dr. Amr Ibrahim (American University of Cairo, Egypt); Prof. Rozhan Idrus (Universiti Sains Malaysia, Penang, Malaysia); Dr. Michael Ievers (Stranmillis University College, N. Ireland, UK); Dr. Marina Ismail (Universiti Teknologi MARA, Malaysia); Issham Ismail (Universiti Sains Malaysia, Penang, Malaysia); Dr. Eunice Ndeto Ivala (Cape Peninsula University of Technology, South Africa); Sheila Jagannathan (World Bank Institute, Washington, USA); Prof. Dinesh Chandra Jain (Computer Science & Engineering, S.G.I., India); Dr. Jill Jameson (University of Greenwich , UK); Katherine Janzen (Mount Royal University, Canada); Nicolae Jascanu (University Dunarea de Jos Galati, Romania); Kanthi Jayasundera (Simon Fraser University, Canada ); Amor Jebali (University of Manouba, Tunisia); Runa Jesmin (Global Heart Forum, UK); Dr Pandora Johnson (College of The Bahamas, The Bahamas); Phillip Jones (Hong Kong Institute of Education, Hong Kong); Prof. Leila Kajee (University of Johannesburg, South Africa); Prof. Leila Kajee (University of Johannesburg, South Africa); Prof. Konstantinos Kalemis (National Centre of Local Goverment and Administration, Greece); Dr. Michail Kalogiannakis (University of Crete, Faculty of Education, Crete); Pankaj Kamthan (Concordia University, montreal, canada, Canada); Dr. Haijun Kang (Kansas State University, USA); Saba Khalil Toor (T.E.C.H Society, Pakistan); Dr. Mohammad Ayoub Khan (C-DAC, India); Dr. Yu-Ju Kuo (Indiana University of Pennsylvania, USA); Prof. Reggie Kwan (Caritas Institute of Higher Education, Hong Kong, China, China); Dr. Hok Yin Jean Lai (Hong Kong Baptist University , Hong Kong); Kamaljit Lakhtaria (Atmiya Institute of Technology & Science, India); Paul Lam (Centre for Learning Enhancement And Research,The Chinese University of Hong Kong, Hong Kong, , China); Prof. David Lamas (Tallinn University, Estonia); Dr. Maria Lambrou (University of the Aegean, Greece); Dr. Mona Laroussi (Institut National des Sciences Appliquées et de la Technologie, Tunisia); Debora Larson (Kaleidoscope Learning, New York, USA); Jno Baptiste Laurelle (OISE/ University of Toronto, Canada); Kenneth Lee (Delaware Valley College, Pennsylvania, USA); Stella Lee (Athabasca University, Canada, Canada); Victor Lee (School of Continuing and Professional Studies, The Chinese University of Hong Kong,, China); Christine Levy (Kaleidoscope Learning, New York, USA); Dr. Ken Li (Hong Kong Institute of Vocational Education, China); Dr. Rita Yi Man Li (Hong Kong Shue Yan University, Hong Kong); Dr. Ying Liu (Cambridge University, Uk); Jenny Lorimer (University of Hertfordshire, UK); Dr. Pam Lowry (Lawrence Technological University, USA); Prof. Sam Lubbe (NWU, South Africa); Dr. Grace Lynch (University of New England, Australia); Prof. Lachlan MacKinnon (University of Greenwich, UK); Maria Madiope (University of South Africa, South Africa); Dr. Chittaranjan Mandal (School of IT,IIT Kharagpur, India); Robert Manderson (University of Roehampton, UK); Phebe Mann (University of Reading, UK); Dr Mourad Mars (University of Monastir, Tunisia); Jorge Martins (Information School, University of Sheffield, UK); Dr. Gianina-Ana Masari (Alexandru Ioan Cuza University of Iasi, Romania); Matava Matava (University of Toronto, Canada); Prof. Hassan Mathkour (King Saud University, Saudi Arabia); Dr. Jeton McClinton (Jackson State University, USA); Dr. Cherifa Mehadji (University of Strasbourg, France); Mandia Mentis (Massey University, Auckland, New Zealand); Dr. Cecilia Mercado (Saint Louis University, USA); Bente Meyer (The Danish University of Education, Denmark); Sunilkumar Mistry (Johnson Group, Ahmedabad, India); Ali Moeini (University of Tehran, Iran); Sahel Mohammad Esa (Kabul Education University, Afghanistan); Dr. Gholam Ali Montazert (Tarbiat Modares University, IRAN); Dr. Begoña Montero-Fleta (Universitat Politecnica de Valencia, Spain); Dr. Jane Moore (Liverpool Hope University, UK); Jolanda Morkel (Cape Peninsula University of Technology, South Africa); Molefe Motshegwe (University of Botswana, Gaborone, Botswana); Dilawer Mowzer (College of Cape Town, South Africa); Manabu Murakami (Tokyo University of Science, Japan); Dr. Minoru Nakayama (Tokoyo Institute of Technology, Japan); Dr. Mike Nantais (Brandon University, Canada); Dr. Vincent Ng (The Hong Kong Polytechnic University, China); Dr. Dick Ng'ambi (Uiversity of Cape Town, South Africa); Prof. Roger Nkambou (Université du Québec à Montréal, Canada); Grace O’Malley (National College of ireland, Ireland); Prof. Birgit Oberer (Kadir Has University, Turkey); Dr. Maruff Akinwale Oladejo (Department of Educational Administration, University of Lagos, Akoka, Nigeria); Francisca Onaolapo

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Oladipo (Nnamdi Azikiwe University, Awka, Nigeria); Dr. Roxana Ologeanu (Universite Montpellier 2, France); Smart Odunayo Olugbeko (Adeyemi College Of Education, Ondo, Nigeria); Prof. Abdelnaser Omran (School of Economics, Finance and Banking, Universiti Utara Malaysia, Malaysia); Dr. Jacinta Agbarachi Opara.In (School of Science, Federal College of Education(Technical),Omoku, Nigeria); Dr. Addin Osman (Najran University, Saudi Arabia); Maria Osuna Alarcón (Salamanca University, Spain); Dr. David Owen (University of Bedfordshire, UK); Dr. Ecaterina Pacurar Giacomini (Louis Pasteur University, FRANCE); William Painter (NCC Education Ltd, UK); Prof. Bamidis Panagiotis (Aristotle University of Thessaloniki, Greece); Dr. Shireen Panchoo (University of Technology, Mauritius, Mauritius); Masouras Panicos (Cyprus University of Technology, Limassol, Cyprus); Dr. Arna Peretz (Ben Gurion Univeristy of the Negev, Israel); Dr. Beth Perry (Athabasca University, Canada); Dr. Donatella Persico (National Reserach Council, Institute fo Educational Technology, Italy); Prof. Selwyn Piramuthu (University of Florida, Gainesville, USA); Dr. Michel Plaisant (University of Quebec in Montreal, Canada); Dr. Carmen Prez-Sabater (Universitat Politcnica de Valencia, Spain); Paul Prinsloo (University of South Africa (Unisa), South Africa); Zahra Punja (University of Toronto , Canada); Anne Quinney (Bournemouth University, UK); Dr Brenda Ravenscroft (Queen's University in Kingston ON, Canada); Dr. Ronald Robberecht (University of Idaho, Moscow, USA); Dr. Melissa Saadoun (MS Institute , Paris, France); Osman Sadeck (Cape Education Department, South Africa); Dr. S.R. Balasundaram Sadhu Ramakrishnan (National Institute of Technology, INDIA); Khalid Saifuddin (Aalborg University, Denmark); Dr. Florin Salajan (North Dakota State University , Canada); Gustavo Santos (University of Porto, Portugal); Dr Daniyar Sapargaliyev (International Academy of Business, Kazakhstan); Prof. Chaudhary Imran Sarwar (Mixed Reality University, Pakistan); Prof. Jeanne Schreurs (Hasselt University, Diepenbeek, Belgium); Dr Nima Shahidi (Islamic Azad University- Nourabad Mamasani branch, Iran); Dr. Khitam Shraim (Birzeit University, Ramallah, Palestine); Mr. Charles Sigmund (University of Phoenix, USA); Sibongile Simelane (Tshwane University of Technology, Pretoria, South Africa); Dr. Deena Slockett (ADU (Adventist University of Health Sciences), USA); Dr. Keith Smyth (University of the Highlands and Islands, UK); ƌ ŶĞƚĂ ^ŽŬěǏ (University of Szczecin, Poland); Thorsten Sommer (IMA/ZLW & IfU, Germany); Dr. Yeong-Tae Song (Towson University, Maryland, USA); Dr. Elsebeth Sorensen (Aarhus University, Denmark); :ĂĐĞŬ^ƚĂŷĚŽ (Lodz University of Technology, Poland); :ĂĐĞŬ^ƚĂŷĚŽ (Lodz University of Technology, Poland); Dr. Mark Stansfield (University of West of Scotland, UK); Juliet Stoltenkamp (University of Western Cape, South Africa); Yana Tainsh (University of Greenwich,, UK); Dr. Ken Takeuchi (Tokyo University of Science, Japan); Dr. Jyothi Thallur (University of South Australia, Australia); Dr. John Thompson (Buffalo State College,, USA); Prof. Ramayah Thurasamy (University Sains Malaysia, Penang, Malaysia); Prof. Christopher Turner (University of Winchester , UK); Karin Tweddell Levinsen (Aalborg University, Denmark); Dr. Sapna Tyagi (Institute of Management Studies(IMS), India); Duan Van der Westhuizen (University of Johannesburg, South Africa); Dalize van Heerden (Unisa, Pretoria, South Africa); Prof. Dr. Asaf Varol (Firat University, Turkey); Paduri Veerabhadram (Vaal University of Technology, south africa); Dr. Steven Verjans (Open Universiteit of The Netherlands, The Netherlands); Maggy Minhong Wang (The University of Hong Kong, Hong Kong); Dr Carlton Watson (College of The Bahamas, The Bahamas); Dr. Anita Welch (Emirates College for Advanced Education, Abu Dhabi, UAE); Dr Gerald (Gerry) White (Australian Council for Educational Research, Australia); Stephen White (University of Huddersfield, UK); Robert Wierzbicki (University of Applied Sciences Mittweida, , Germany); Roy Williams (University of Portsmouth, UK); Shirley Williams (University of Reading, UK); Dr. Noeline Wright (University of Waikato, Hamilton, New Zealand); Daniel Yakmut (Federal University Lafia, Nigeria); Dr. Ruth Yeung (Institute for Tourism Studies, China); Aw Yoke Cheng (UNITAR International University, Malaysia, Malaysia); Dr. Roxanne Ward Zaghab (University of Maryland School of Pharmacy, USA); Dr. Nabil Zary (Karolinska Institutet, Sweden); Dr Xiangmin Zhang (Wayne State University, USA)

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Biographies Conference and Programme Chairs Dr Rozhan M. Idrus is the first Professor of Open and Distance Learning (ODL) appointed in a public institution of higher learning in Malaysia. He holds a PhD in Solid State Physics and was trained in various aspects of ODL including instructional designer. He has published more than 170 scholarly works and has presented 31 Keynote and Plenary addresses in all over the globe. He has given a definition to the term ‘technogogy’ and is passionately promoting it. He is the Founding Chief Editor of the Malaysian Journal of Educational Technology and the International Journal of Excellence in e-Learning. Dr Nurkhamimi Zainuddin is currently the Coordinator of the Global Open Access Learning (GOAL) Centre in USIM. Holding a PhD in Arabic Linguistics Study and Computer Assisted Language Learning and Instructional Technology and Teaching Arabic as a Second Language. His has several chapters in book and conference proceedings in and outside Malaysia. He is also actively involved in various types of research grants. He has completed four research grants focusing on Open Editing, Arabic E-book Development, Online Discussion Assessment and Screen Capture. Currently he is spearheading research grant related to the development of MOOC, OER and Online Distance Learning.

Keynote Speakers Dr Norrizan Razali has over 20 years of experience in program management, government relations, transformation programs, people management and consulting. With a unique blend of experience from working with a multinational organization, government-linked corporation and the academia, she brings an extensive commercial and government network. Currently, at Microsoft Malaysia, she directs the sales and program operations of the education business segment and serves as industry advisor in a number of higher education institutions and continues to receive guest lecture invitations on 21st century development topics. Her niche expertise is in transformational strategies for organizational development with extensive experience within the education industry. Her core competencies are with innovating and strategizing around the development of businesses, organizations and people through IT, content, training and other wide ranging programs. Dr Alaa Sadik is an associate professor of educational technology and currently work at the Department of Instructional & Learning Technology, College of Education, Sultan Qaboos University, Sultanate of Oman. He received his Ph.D. degree in educational technology from the University of Hull, UK, in 2003. Alaa worked at the Arab Open University, Oman, South Valley University, Egypt, and Partners for Competitive Egypt project, funded by the USAID Egypt. Dr Sadik has more than 10 years of experience in teaching and research in the fields of e-learning, distance education, and multimedia and published many papers in refereed journals and international conferences. Alaa received many regional and international awards for my contribution to the use of technology in teaching and learning.

Executive Committee Dr Najwa Hayaati Mohd Alwi is a senior lecturer in Information Security Assurance at Faculty Science and Technology, Universiti Sains Islam Malaysia (USIM). Currently she is also a coordinator of Content Development Unit for E-learning centre in USIM. She had obtained her PhD from Cranfield University, UK. She has a high interest in strategic level of information security management focusing on people perspectives. Her research and publications also include e-services especially e-learning domain. She also has experiences in conducting socio-technical researches.

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Mini-Track Chairs Dr. Paula Charbonneau-Gowdy is Assistant Professor and researcher in EFL teacher education at the Universidad Andres Bello in Santiago, Chile. She formerly worked as Senior Advisor in Learning and Technology to the Government of Canada where she designed national and international blended and distance language programs. A seasoned educator, she has experience at all levels of education from elementary to university. Her research interests lie in traditional and virtual classroom-based research and the sociocultural implications of emerging technologies on teaching, learning and learners. She has published extensively in the field of e-learning while seeking to push the boundaries of technology to promote democratic change. Chuck Sigmund is passionate about creating environments that bring out the best in learners and encourage them to fully engage and optimize their learning experience. His recent work has focused on how to use creative training techniques such as gamification, stories, flipped classrooms, and project-based learning to increase learner engagement and success. He holds a Masters of Arts in Adult Education and Training and is a Senior Learning Systems Strategist for Amazon.

Contributing Authors Raman Attri is a learning strategist and researcher with focus on implementing next-generation competitive training strategies to accelerate time-to-expertise. Currently he is serving as Senior Global Technical Training Manager for KLA-Tencor, a $10B semiconductor corporation, named as one of the top 10 training organizations worldwide. He is pursuing doctorate from Sothern Cross University, Australia. Niyi Awofeso is currently a Professor of Health Administration at Hamdan Bin Mohammed Smart University in Dubai, Niyi Awofeso commenced his public health career as an infectious disease physician in Nigeria and worked as a public health officer in Australia prior to embarking on his current academic career. His research interests include improving online learning efficiency. Wendy Barber is the Director of the B.Ed. Program at the University of Ontario Institute of Technology in Oshawa, Canada. Her research interests lie in Health and Physical Education, and Creating Online Communities. Dr. Barber is a passionate advocate for teacher education, teaches Authentic Assessment and Adult Education, and Psychological Foundations in Digital Technology. Moses Basitere is Lecturer at the Cape Peninsula University of Technology, Chemical Engineering Department. He is currently lecturing Mathematics and Physics at the Extended Curriculum Program. His research focus area is in treatment of industrial wastewater and he is also involved in educational research in promoting the use of emerging technology in teaching and learning in higher education. Vidyashree B N has a masters from Indian Institute of Technology Roorkee with Computer Science as my specialization. Vidyashree’s area of interest include Natural La Mohamed Bendahmane received a diploma of advanced graduate(DESA) in computer science, telecommunication and multimedia(ITM) from university of Mohammed-V Rabat in 2005. He is cuurently a PhD student in LASTID laboratory at faculty of sciences in Ibn Tofail University. His research interests are e-learning, learner path, traces analysis, learner model. Ian Brown has been involved in education for over 20 years. A qualified and experienced international educationalist with a background in education, Ian has trained people in many parts of the world. Ian has been working in HK since 2009 as an Instructional Designer with responsibility for key eLearning initiatives includes LMS support and MOOC development.

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Vanco Cabukovski is Full Professor of Software Engineering at Faculty of Natural Sciences and Mathematics, Sts. Cyril and Methodius University in Skopje, Republic of Maceddonia. His main research interests include intelligent systems, e-learning systems and information systems. He has published over 70 scientific papers and over 25 books in informatics and ICT. He is author of 30 software applications and has participated in over 20 domestic and international projects. Kevin Chan is a Research Assistant Professor at the Department of Applied Social Sciences of the Hong Kong Polytechnic University. With support of the PolyU Teaching & Learning Development Grant (TDG). Dr. Chan’s current interests are in the psychology of technology adoption, attention and engagement in learning, and applied psychology in the community settings. He also serves as a member in the PolyU’s Advisory Committee on e-Learning and the Working Group on Development and Operation of eLearning (WGDOE) under the institution’s University Learning & Teaching Committee. Chun-Yi Chen is currently a master student at the Graduate Institute of Library, Information and Archival Studies at National Chengchi University, Taipei, Taiwan. His research interests include e-learning and business intelligence. George Cheung pursued his undergraduate studies at University of California, Los Angeles where he received his Bachelor’s Degree in Psychology and Minor in Cognitive Science. He then furthered his education at the Hong Kong Polytechnic University as an M Phil. His research interests focus on employability, mobile learning and education. Matt Glowatz is college lecturer at University College Dublin, Ireland researching eLearning and Social Media related themes. Matt is member of the College’s T&L committee and UCD’s Centre for the Future of Learning. He is co-chair of the Bled e-Conference SIG focusing on Education in the Digital Economy and has published numerous eLearning research articles. Yi-Chen Huang is currently a master student at the Graduate Institute of Library, Information and Archival Studies at National Chengchi University, Taipei, Taiwan. His research interests include e-learning and data mining. Eunice Ndeto Ivala is an Associate professor and Coordinator Educational Technology Unit, Centre for eLearning, at the Cape Peninsula University of Technology (CPUT). The Educational Technology Unit is responsible for promoting appropriate use of technologies in teaching and learning at the institution. Her Research focus is in ICT–mediated teaching and learning in developing contexts. Currently, she is a team member in an international digital storytelling project dealing with foreign youth and employability, which is supported by the European Union, and a team leader of the ICT curriculum appraisal of the National Senior Certificate for Adults (NASCA). Previously a project manager at the Media in Education Trust Africa, an educational specialist at the South African Institute for Distance Education and a lecture at the University of KwaZulu Natal. Jakub Jirasko is a PhD student of Machine Design at the University of West Bohemia. The subject of his doctoral study is: Methods for optimizing reliability and renovation of production facilities. He is engaged in a number of collaborative projects with industry and university projects. Teerawat Kamnardsiri is an experienced animation lecturer of College of Arts, Media and Technology, Chiang Mai University, Thailand. Prior to his Ph.D. study, Mr. Teerawat had completed his Erasmus Mundus “E-tourism Project” (2011-2014) which he has extensively developed to his own lecture courses in animation program. His research projects are centered in Game-Based learning, Image Processing and Computer Vision. Tomáš Keckstein is a Ph.D. student in Department of Machine Design at the Faculty of Mechanical Engineering at the University of West Bohemia in Pilsen in Czech Republic. He received his master degree at the same academic institution in 2014 and from that time he study, work and teach there. In addition to writing scholarly publication, he enjoys traveling, sports, music and good food. Simon Bheki. Khoza (PhD) is a Senior Lecturer: Discipline of Curriculum Studies & Educational Technology at the University of KwaZulu-Natal, South Africa. He coordinates different undergraduate and postgraduate pro-

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grammes, and teaches and supervises postgraduate research in Curriculum Studies & Educational Technology. He has published in local and international journals. Chen-Yu Liu is currently a master student at the Graduate Institute of Library, Information and Archival Studies at National Chengchi University, Taipei, Taiwan. His research interests include e-learning and eye tracking technology. Antonín Max is a PhD student of Machine Design at the University of West Bohemia. The subject of his doctoral study is: Development of methods and processes-linking 3D CMM measurements with CAD. He is included in a number of projects with industry and university projects. Kazuhiro Muramatsu is a Senior Lecturer at Electronics and Communication Engineering Department, College of Science and Technology, Royal University of Bhutan. His research interests include collaborative e-Learning and m-Learning environments. Mai Neo is Professor and Head of the Master of Multimedia (e-Learning Technologies) in Faculty of Creative Multimedia, Multimedia University, Malaysia, and Chair of the Centre for Adaptive Multimedia, Education and Learning cOntent Technologies (CAMELOT). Her research areas include multimedia constructivist learning environments, problem-solving learning, and collaborative and authentic learning Vuyisile Nkonki is an Academic Development practitioner and Manager of the Teaching and Learning Centre (TLC) at the University of Fort Hare. Vincent Ng is an Associate Professor in the Department of Computing, The Hong Kong Polytechnic University. His research interests include social media analysis, learning analytics, and medical image analysis. Dr. Ng is also active in consultancy service for companies, government agencies and voluntary associations. He was a board member of the Public Examination Board of the HKEAA and worked with many local schools in Hong Kong. Osman Sadeck is the Chief Education Specialist: e-Learning in the Western Cape Education Department, South Africa. He holds a MEd (e-Learning) from the University of Technology, Sydney, Australia, and is currently a Doctoral student at the Cape Peninsula University of Technology. He has presented papers at numerous national and international conferences. Mohammad Shehadeh is a researcher at IMA/ZLW & IfU at the RWTH Aachen University since August 2015. In September 2012, he finished his Master's degree in Computer Aided Conception and Production in Mechanical Engineering at the RWTH Aachen University. Before that, he finished his Bachelor in Mechatronics Engineering at the Hariri Canadian University in Lebanon. Hsien-Chieh Sun is currently a master student at the Graduate Institute of Library, Information and Archival Studies at National Chengchi University, Taipei, Taiwan. His research interests include e-learning and digital reading. Sibangiso Ngwenya a computer science lecturer at the National University of Science and Technology, Bulawayo City, Zimbabwe. He spends most of his time teaching and researching. Currently he is doing a PHD in computer science focussing on ontology and semantic web technologies. He also assists schools in implementing e-learning systems. Narayanan Ramkumar did his bachelor’s in Electronics and Communication Engineering in Coimbatore, India. Currently he is involved in cutting edge research done in the field of multimedia and computer vision in eLearning to enhance the classroom experience in the Amrita Wireless Networks and Applications Department at Amritapuri, India. Gulnura Taikulakova in 1980 - Karaganda Polytechnic institute. Of 1992-1995. Kazakh State Academy of Management, specialty "Economics and Business". 2007 - Defended his thesis on the specialty 08.00.05 - "Economy and management of national economy" on the "Optimization methods for the economic evaluation of the effectiveness Oil production. 2012 - Head of Department "Economics and Logistics" Almaty Management Univer-

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sity. 2013 - Training at Kaplan, University of California, Berkeley, Haas School of Business. Currently Professor of Economy and Assessment in Almaty Management University. Heidi Tan Yeen-Ju is a lecturer with the Faculty of Creative Multimedia at Multimedia University, Malaysia. She is currently pursuing a PhD in the area of authentic problem-solving learning environments. She is a senior researcher at the Centre for Adaptive Multimedia, Education and Learning COntent Technologies (CAMELOT) and is part of the University’s BLEND initiative. Dalize van Heerden is a Lecturer within the School of Computing at the University of South Africa. She started working for UNISA in 1999 and has been teaching programming modules ever since. Her main research interests include e-learning, m-learning and technology-enhanced learning. She is currently busy with her masters degree in Technology Education. Wei Li Yap is a Senior Lecturer in Faculty of IT, Mathematics and Sciences in INTI International University. She was the Head of Programme from 2003 – 2010. Wei has attained her Phd from Multimedia University. Wei is currently the Project Leader in Centre of Multimedia Applications and Technologies. Wei’s research interests are educational technology, multimedia learning, learner-centred teaching and e-learning. Lin Yen is currently a master student at the Graduate Institute of Library, Information and Archival Studies at National Chengchi University, Taipei, Taiwan. His research interests include digital archives, e-learning and digital curation.

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Efficient Instructor Feedback: Perceptions of Online UAE Undergraduate and Postgraduate Public Health Learners Niyi Awofeso1 and Moyosola Bamidele2 1School of Health and Environmental Studies, Hamdan Bin Mohammed Smart University, Dubai Academic City, UAE 2USAID/John Snow Research & Training Inc, Abuja, Nigeria [email protected] [email protected] Abstract: Effective course facilitator feedback is particularly important in online learning as learners are more likely to withdraw from online learning environments due to delayed, or inadequate feedback, compared with students enrolled in physical classes. Diligent learners engaged in online learning programs expect feedback to be contextual, supportive, constructive, timely, substantive, summative and formative. This study examined the perceptions of 66 undergraduate and postgraduate learners on feedback provided in eight online courses facilitated by the same instructor at the School of Health and Environmental Studies, Hamdan Bin Mohammed Smart University, Dubai, UAE between August 2014 and December 2015. Data collection from learners was anonymized and participation was voluntary. The survey sought to elicit learners’ perceptions on the extent to which feedback provided in specified courses were motivational, timely, frequent, supportive, and individualized. A polytomous Rasch model was utilized to analyze the data with Winsteps and STATA. Analysis of the 20 survey questions revealed a real person reliability of 0.82 and a Cronbach Alpha test reliability of 0.96, suggesting that the scale discriminates well between the persons. The real item separation reliability of 0.77 suggests that the questions are reliable in measuring the specified items. Descriptive analyses revealed general agreement among the majority of learners on the effectiveness of feedback provided by the instructor, although Infit and Outfit Z-standard deviation statistics revealed two questions with unexpected rare (i.e. “mostly disagree” or “completely disagree”) extremes in several learners’ responses. The survey instrument used in this study has a reliability coefficient of 0.96 and has been validated in previous studies internationally. Our results indicate that systematic collection and analysis of learners’ feedback comments have a strong potential to enhance feedback competencies of course facilitators, as well as provide a common platform for both learners and course facilitators vis-à-vis the diverse objectives of instructor feedback. Keywords: instructor feedback survey, learner-centricity public health courses, technology-mediated learning, United Arab Emirates

1. Introduction and conceptual framework The importance constructive feedback in enhancing learning has its theoretical origins in the communication theories described in the book titled; “The mathematical theory of communication” (Shannon and Weaver 1964). The authors analysed diverse communication problems at three levels: How accurately can the symbols of communication be transmitted? (The technical problem); How precisely do the transmitted symbols convey the desired meaning? (The semantic problem); How effectively does the received meaning affect conduct in the desired way? (The effectiveness problem). In the learning context, feedback may be defined as any communication given to inform a learner of the accuracy of a response, usually to some form of instructional question (Sales, 1993). In online learning contexts, both web-based technology factors and basic instructional factors play significant roles in the efficiency of the feedback process. The 2011 survey titled Going the Distance: Online Education in the United States 2011, estimated that 6.1 million tertiary education students (i.e. 31%) enrolled in at least one online course during 2010 (Allen and Seaman, 2011). With the expansion of online learning programs globally, peer-feedback is increasingly becoming a common approach to providing feedback, with its generally sub-optimal quality somewhat compensated for by frequency and volume (Suen, 2014). Instructor feedback takes several forms. Corrective instructor feedback, which is usually focused on specific content of the task performance, may be categorized as; no feedback given, simple verification or knowledge of results, knowledge of correct response, elaborated feedback, and try-again feedback (Dempsey, Driscoll and Swindell, 1993). Given that this is a core rationale for feedback in instructional settings, corrective feedback should be incorporated into most instructor feedback responses. A second category of feedback is motivational, which is learner focused, and provides positive reinforcement for quality performance as well as assist the learner in continuing effort despite challenges and setbacks. Motivation impacts the depth and enthusiasm with which learners perform learning tasks, and high instructor (or peer) motivation is positively correlated with highperceived learning and superior perceived learning application (Lim & Morris, 2009). A third category is

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Niyi Awofeso and Moyosola Bamidele technology feedback. As Mory (2004) posits: “there is ever-increasing need to consider how new technologies change and impact feedback, its forms, and its dynamic potential for use in instructional settings” (p. 777). The use of Backboard and Moodle platforms have significantly improved technology-mediated feedback. Online feedback using these platforms is currently presented with grades and learning materials, thus placing them 'in context' and providing a direct connection, making it easier for learners to understand the assessment processes course instructors go through to arrive at a grade. Technology also enables the use of Feedback Wizard, which provides feedback responses from a bank of pre-populated comments, which may then be refined by course instructors with more personalized comments, when applicable (Hepplestone et al, 2010). Over the past two decades, online learning has evolved from an instructor-centred to a student-centred paradigm; instructionist and constructivist models underpin these paradigms respectively (Schell and Janicki, 2012). This paradigm shift necessitates greater prominence of instructor feedback in providing guideposts, mentoring and coaching learners, and designing assessments which by themselves provide feedback on learning milestones. Race (2011) discusses the use of feedback in facilitating (online) learning by segmenting feedback categories of conscious competence – where learners know that they have performed well in an assignment and feedback is geared towards taking ownership of their success; conscious incompetence – where feedback is focused on helping learners to become better at things they already know they can't yet do; unconscious incompetence – using timely and constructive feedback to help learners find out much more about what they didn't yet know that they couldn't yet do; unconscious competence – tactful feedback may be utilised to move unconscious competencies towards the conscious level, invariably leading to increased motivation and selfesteem for the learner. He discussed occasional trade-offs between feedback types and learning efficiency. For example, although one-to-one face-to-face feedback provides a high learning pay-off, it is not efficient in terms of instructor’s time, especially in courses with large enrolments. Conversely, one-to-many communication and automated feedback using an answer bank for frequently asked questions may be efficient, but does not usually foster high levels of learning. A conceptual framework for appraising learnings perceptions and approaches to learning is shown in Figure 1 (Tudor and Penlington, 2009):

Figure 1: Learning context, student perceptions and approaches to learning The framework shows that feedback is one of the important influences on learner perception and ultimately on their approach to learning. Understanding how learners perceive their learning contexts at university is as vital as understanding how these perceptions influence students’ approaches to their studies. Entwistle (2008, p4) emphasized that “high quality learning depends not just on pass or completion rates, but on the nature of the knowledge, skills and conceptual understanding that students have acquired during their degree course”. In this study, we explore the perceptions of 66 online undergraduate and postgraduate public health learners at Hamdan Bin Mohammed Smart University to feedback provided by an Instructor over two semesters, as well as the process of efficient learner feedback. Our two research questions were: ƒ

Is efficient instructor feedback positively associated with learners’ perceived learning in, and satisfaction with, technology-mediated learning programs at university level?

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Niyi Awofeso and Moyosola Bamidele ƒ

How can the evaluations of learners’ perceptions of instructor feedback processes be utilized in improving the quality and other attributes of instructor feedback as well as learners’ approaches to learning?

2. Materials and methods Hamdan Bin Mohammed Smart University is the first online university in the Middle East and North African region. The university is equipped with the latest Moodle online learning platform, and was recently an ‘Extraordinary Contribution Award’ by Ellucian, a global leader in providing innovative technology solutions for higher education institutions. The study participants comprised 66 (89%) out of 74 participants who were invited to participate in any anonymous and voluntary/optional instructor feedback survey of eight courses taught by the same instructor between August 2014 and September 2015. The survey was conducted online using Moodle’s Virtual Learning Environment. The survey instrument used was the Likert Scale feedback assessment template developed by Getzlaf et al (2009). It comprised 20 questions, which seek to ascertain learners’ perspectives of the content and process of efficient instructor feedback. A one-parameter Item Response Theory model was utilized, commonly known as the Rasch Model, using Winsteps software (Linacre and Wright, 2000). Winsteps implements the Andrich “rating scale” model with the Joint Maximum Likelihood Estimation method, also known as UCON, which does not assume a person distribution and is flexible with missing data (Wright & Masters, 1982). The Rasch model used in Winsteps for ܲ this analysis is the polytomous “Rating Scale” model with the equation: Log ௡௜௝൘ܲ = ‫ܤ‬௡ െ  ‫ܦ‬௜ െ  ‫ܨ‬௝ , where ௡௜ሺ௝ିଵሻ ܲ௡௜௝ probability that person n encountering item i is observed in category j, ‫ܤ‬௡ is the “ability” or rater-severity measure of person n, ‫ܦ‬௜ is the difficulty-to-endorse measure of item i, and ‫ܨ‬௝ is the “calibration” measure of category j relative to category ܲ௡௜௝ ‫ܤ‬௡ ‫ܦ‬௜ ‫ܨ‬௝ (j-1) (Linacre, 2004). Throughout the analysis, several results were produced. A statistical summary table is generated to show the fit indices of student and item. There are two types of fit indices i.e. the mean square (MNSQ) and standardized fit statistics (ZSTD). The acceptable range of weighted MNSQ for a Likert scale item is from 0.6 to 1.4 (Smith, E., Jr. 2000). The acceptable range also holds true by following the general rule of mean ± standard deviation. The acceptable range weighted ZSTD values is between -2 and 2, whereas the optimum unweighted ZSTD for student is below 5. Fit statistics of items and students were checked at first and misfit items or students should be excluded from further analyses due to the violation of model assumption or redundancy (Linacre, 2000).

3. Results Findings show that on average, about 73% of the undergraduate and postgraduate of students responded Mostly Agree or Completely Agree to the evaluation questions, indicating that the majority of respondents were satisfied with the process and content of feedback provided by the instructor. The category measures the evaluations increased as the categories increased (see appendix 1). Table 1: Rasch analysis of learners survey responses INPUT: 66 PERSON 20 ITEM REPORTED: 66 PERSON 20 ITEM 6 CATS MINISTEP 3.74.0 -------------------------------------------------------------------------------SUMMARY OF 46 MEASURED (NON-EXTREME) PERSON ------------------------------------------------------------------------------| TOTAL MODEL INFIT OUTFIT | | SCORE COUNT MEASURE ERROR MNSQ ZSTD MNSQ ZSTD | |-----------------------------------------------------------------------------| | MEAN 101.6 20.0 2.38 .39 .98 -.1 1.00 .0 | | S.D. 11.5 .0 1.50 .16 .43 1.2 .46 1.2 | | MAX. 119.0 20.0 5.89 1.02 2.16 2.6 2.34 2.9 | | MIN. 65.0 20.0 -.48 .21 .33 -2.5 .36 -2.3 | |-----------------------------------------------------------------------------| | REAL RMSE .45 TRUE SD 1.44 SEPARATION 3.21 PERSON RELIABILITY .91 | |MODEL RMSE .43 TRUE SD 1.44 SEPARATION 3.38 PERSON RELIABILITY .92 | | S.E. OF PERSON MEAN = .22 | ------------------------------------------------------------------------------MAXIMUM EXTREME SCORE: 20 PERSON

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Niyi Awofeso and Moyosola Bamidele

SUMMARY OF 66 MEASURED (EXTREME AND NON-EXTREME) PERSON ------------------------------------------------------------------------------| TOTAL MODEL INFIT OUTFIT | | SCORE COUNT MEASURE ERROR MNSQ ZSTD MNSQ ZSTD | |-----------------------------------------------------------------------------| | MEAN 107.2 20.0 3.82 .83 | | S.D. 12.8 .0 2.52 .68 | | MAX. 120.0 20.0 7.13 1.83 | | MIN. 65.0 20.0 -.48 .21 .33 -2.5 .36 -2.3 | |-----------------------------------------------------------------------------| | REAL RMSE 1.08 TRUE SD 2.28 SEPARATION 2.12 PERSON RELIABILITY .82 | |MODEL RMSE 1.07 TRUE SD 2.28 SEPARATION 2.13 PERSON RELIABILITY .82 | | S.E. OF PERSON MEAN = .31 | ------------------------------------------------------------------------------PERSON RAW SCORE-TO-MEASURE CORRELATION = .93 CRONBACH ALPHA (KR-20) PERSON RAW SCORE "TEST" RELIABILITY = .96 SUMMARY OF 20 MEASURED (NON-EXTREME) ITEM ------------------------------------------------------------------------------| TOTAL MODEL INFIT OUTFIT | | SCORE COUNT MEASURE ERROR MNSQ ZSTD MNSQ ZSTD | |-----------------------------------------------------------------------------| | MEAN 353.7 66.0 .00 .23 1.02 .1 1.00 -.1 | | S.D. 10.2 .0 .51 .02 .31 1.3 .28 1.0 | | MAX. 372.0 66.0 .92 .27 1.86 2.9 1.66 1.6 | | MIN. 333.0 66.0 -1.06 .19 .38 -3.2 .36 -3.0 | |-----------------------------------------------------------------------------| | REAL RMSE .24 TRUE SD .45 SEPARATION 1.84 ITEM RELIABILITY .77 | |MODEL RMSE .23 TRUE SD .46 SEPARATION 2.01 ITEM RELIABILITY .80 | | S.E. OF ITEM MEAN = .12 | -------------------------------------------------------------------------------

Table 1 provides an overview of the reliability estimates. The real separation reliability is highlighted above and is comparable to a Cronbach’s alpha estimate. Here, “real” indicates that the estimated standard errors of measurement have been adjusted for any misfit encountered in the data. The real person reliability of 0.82 suggests that the scale discriminates well between the persons. The real item separation reliability of 0.77 suggests that the questions are reliable in measuring the proper item. INFIT and OUTFIT ZSTD statistics are also reported in Table 2. OUTFIT ZSTDs are the standardized unweighted item and person fit statistics. These estimates are sensitive to unexpected rare extremes. INFIT ZSTDs are standardized information-weighted item and person fit statistics. These estimates are sensitive to irregular inlying patterns. When the data fit the model, these statistics are approximately t-statistics. For this setting, the approximate t-statistics would have a mean of 0 and standard deviation of 1. Here (highlighted), the mean is close to 0 in both cases; however the standard deviation is high suggesting that there are some items that misfit and there is more variability in the fit of the students than expected (Wright and Masters, 1982). Table 2 presents a summary of the individual item statistics. Values less than –2 are considered to be ‘muted’, meaning redundancy or error trends exist; values greater than 2 are considered to be ‘noisy, an indication of unexpected or inconsistent irregularities (Linacre, 2000). Highlighted items above are 3 and 11. Figure 2 documents item difficulties on right side of the mapping. Item difficulty is a measure of the difficulty of endorsement for an item. An item placed above another item is said to be more difficult to endorse then the lower item. Person difficulty, found on the left side of the mapping, is a measure of the individual’s level of agreement with the items. A person higher on the chart would find an item easier to endorse, or more likely to agree with the item, than a person who was placed lower on the figure. In figure 2, each “#” represents one postgraduate and “.” represents one undergraduate student and the mean of these students ability, or level of agreeableness for the students is found on the left side of the figures and is denoted with an “M”. The mean of the item difficulties, or difficulty to endorse, is also denoted with an “M” and is located on the right side of the figures. For the student efficient instructor feedback evaluation, the mean for the students is much higher than the mean of the items. This agrees with the previous finding that overall, most students agreed or strongly with

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Niyi Awofeso and Moyosola Bamidele the items, i.e. that the process and content of instructor feedback was at least adequate to enhance their learning. Table 2: Infit-Outfit measures

Figure 2: Variable mapping for student perception on efficient instructor feedback.

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Niyi Awofeso and Moyosola Bamidele

4. Discussion and conclusion Efficient instructor feedback plays a crucial role in enhancing learners’ academic achievement, in part though justification of grade derivation, identifying and acknowledging learners’ commendable scholarly initiatives, outlining steps for improvement of academic work, and developing in learners the capability to monitor, regulate and evaluate their learning (Nichol, 2010). Effective feedback should be efficient so that learners can benefit individually and collectively in a timely manner, and instructors can manage the feedback activities using smart technology-mediated and writing tools without being over-burdened. The feedback instrument utilised in this study comprehensively addresses the diverse objectives of instructor feedback and therefore addresses common reasons why many learners find instructor feedback unsatisfactory, such as whether and how the feedback is related to their mark, and what they might do to improve. If instructors agree with the objectives of the feedback process contained in our study instrument prior to commencement of a course or discussion forum activity, it might mitigate most of the challenges experienced by instructors, such as the time-consuming nature of individualized feedback. Course instructors benefit from timely feedback by being able to adjust the teaching approach to learners comments and concerns. To the best of our knowledge, ours is the first study to examine students’ perception of instructor feedback in the Middle East and North Africa region. Studies which have investigated the determinants of students’ perceived learning outcomes and satisfaction in university online education in other regions with advanced elearning systems have consistently rated timely, comprehensive and motivational instructor feedback highly in the list of self-reported facilitators of in-depth learning (Eom,Wen and Ashill, 2006; Eason, 2003). The quality and coverage of instructor feedback covered by this survey is huge, and it is impractical to assume that course instructors will view the objectives of instructor feedback through this lens. It is therefore important that universities who expect instructor feedback to meet these diverse objectives undertake seminars on instructor feedback and other student-instructor interaction variables during staff orientation, in addition to enhancing the competencies of instructors to craft learning activities that promote interaction with the content, the instructor and the learners in the class (Sher, 2009). A noteworthy limitation of this study is the small sample size of 66 participants, although this represented 89% of the 74 invited participants enrolled in courses taught by the same instructor during the review period. In addition, there was no open-ended section for learners to describe their perspectives about the content and process of effective instructor feedback. However, we believe that Getzlaf et al’s (2009) meticulously constructed 20 Likert-scale questions possessed adequate depth and coverage for our study. Convincing online academic staff to expose themselves to learner’s scrutiny in relation to students’ perceptions about diverse aspects of their feedback is a difficult task, but an essential one in order to consistently improve the effectiveness of online learning beyond what currently obtains in the traditional classroom learning format (Nguyen, 2015). Our study’s noteworthy contributions to the literature on instructor feedback includes the successful use of a comprehensive feedback instrument in a blended learning environment for undergraduate and postgraduate public health degree programs, as well as providing a platform for learners and course instructors to develop a shared understanding of the objectives of efficient instructor feedback. The frustration expressed by some learners that instructor feedback is generally cryptic, and by some instructors that time-consuming feedback is not being used to good effect, if at all, by learners (Bailey 2009) may be addressed by being explicit about the details of feedback processes, ensuring that feedback activities accord with the 20 stated objectives of instructor feedback, letting learners understand why they are getting individualized or group feedback, and how their learning can benefit from their reflecting, and acting, on feedback (Scott, 2008).

Appendix 1: Descriptive statistics Average interitem covariance: .3985204 Number of items in the scale: 20 Scale reliability coefficient: 0.9587

Level | Freq. Percent Cum. --------------+----------------------------------Undergraduate | 44 66.67 66.67 Postgraduate | 22 33.33 100.00

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Niyi Awofeso and Moyosola Bamidele --------------+----------------------------------Total | 66 100.00

|Q1 - Motivated me to continue in the course Level | Slightly Mostly Ag Completel | Total --------------+---------------------------------+---------Undergraduate | 4 17 23 | 44 | 57.14 80.95 60.53 | 66.67 --------------+---------------------------------+---------Postgraduate | 3 4 15 | 22 | 42.86 19.05 39.47 | 33.33 --------------+---------------------------------+---------Total | 7 21 38 | 66 | 100.00 100.00 100.00 | 100.00

| Q2 - Encouraged me to interact with my inst Level | Mostly Di Slightly Slightly Mostly Ag Completel | Total --------------+-------------------------------------------------------+---------Undergraduate | 0 1 4 17 22 | 44 | 0.00 2.27 9.09 38.64 50.00 | 100.00 --------------+-------------------------------------------------------+---------Postgraduate | 1 0 1 5 15 | 22 | 4.55 0.00 4.55 22.73 68.18 | 100.00 --------------+-------------------------------------------------------+---------Total | 1 1 5 22 37 | 66 | 1.52 1.52 7.58 33.33 56.06 | 100.00

|Q3 - Stimulated me to reflect on what ihave Level | Slightly Mostly Ag Completel | Total --------------+---------------------------------+---------Undergraduate | 4 20 20 | 44 | 9.09 45.45 45.45 | 100.00 --------------+---------------------------------+---------Postgraduate | 3 6 13 | 22 | 13.64 27.27 59.09 | 100.00 --------------+---------------------------------+---------Total | 7 26 33 | 66 | 10.61 39.39 50.00 | 100.00

| Q 4 - Has been provided frequently through Level | Mostly Di Slightly Slightly Mostly Ag Completel | Total --------------+-------------------------------------------------------+---------Undergraduate | 1 0 4 20 19 | 44 | 2.27 0.00 9.09 45.45 43.18 | 100.00 --------------+-------------------------------------------------------+----------

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Niyi Awofeso and Moyosola Bamidele Postgraduate | 0 1 2 3 16 | 22 | 0.00 4.55 9.09 13.64 72.73 | 100.00 --------------+-------------------------------------------------------+---------Total | 1 1 6 23 35 | 66 | 1.52 1.52 9.09 34.85 53.03 | 100.00

| Q5 - Challenged me to think indepth about t Level | Slightly Slightly Mostly Ag Completel | Total --------------+--------------------------------------------+---------Undergraduate | 1 5 11 27 | 44 | 2.27 11.36 25.00 61.36 | 100.00 --------------+--------------------------------------------+---------Postgraduate | 0 0 6 16 | 22 | 0.00 0.00 27.27 72.73 | 100.00 --------------+--------------------------------------------+---------Total | 1 5 17 43 | 66 | 1.52 7.58 25.76 65.15 | 100.00

| Q6 - Helped me evaluate my progress in the c Level | Mostly Di Slightly Slightly Mostly Ag Completel | Total --------------+-------------------------------------------------------+---------Undergraduate | 0 1 8 12 23 | 44 | 0.00 2.27 18.18 27.27 52.27 | 100.00 --------------+-------------------------------------------------------+---------Postgraduate | 1 0 2 3 16 | 22 | 4.55 0.00 9.09 13.64 72.73 | 100.00 --------------+-------------------------------------------------------+---------Total | 1 1 10 15 39 | 66 | 1.52 1.52 15.15 22.73 59.09 | 100.00

| Q7 - Promoted my active involvement in lea Level | Slightly Slightly Mostly Ag Completel | Total --------------+--------------------------------------------+---------Undergraduate | 1 7 16 20 | 44 | 2.27 15.91 36.36 45.45 | 100.00 --------------+--------------------------------------------+---------Postgraduate | 0 3 7 12 | 22 | 0.00 13.64 31.82 54.55 | 100.00 --------------+--------------------------------------------+---------Total | 1 10 23 32 | 66 | 1.52 15.15 34.85 48.48 | 100.00

| Q8 - Helped me to build new knowledge about Level | Slightly Slightly Mostly Ag Completel | Total --------------+--------------------------------------------+---------Undergraduate | 1 3 15 25 | 44 | 2.27 6.82 34.09 56.82 | 100.00 --------------+--------------------------------------------+---------Postgraduate | 0 2 1 19 | 22

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Niyi Awofeso and Moyosola Bamidele | 0.00 9.09 4.55 86.36 | 100.00 --------------+--------------------------------------------+---------Total | 1 5 16 44 | 66 | 1.52 7.58 24.24 66.67 | 100.00

| Q9 - Supported my self directed learning Level | Mostly Di Slightly Slightly Mostly Ag Completel | Total --------------+-------------------------------------------------------+---------Undergraduate | 1 2 7 13 21 | 44 | 2.27 4.55 15.91 29.55 47.73 | 100.00 --------------+-------------------------------------------------------+---------Postgraduate | 0 0 0 9 13 | 22 | 0.00 0.00 0.00 40.91 59.09 | 100.00 --------------+-------------------------------------------------------+---------Total | 1 2 7 22 34 | 66 | 1.52 3.03 10.61 33.33 51.52 | 100.00

| Q10 - Stimulated further learning about th Level | Mostly Di Slightly Slightly Mostly Ag Completel | Total --------------+-------------------------------------------------------+---------Undergraduate | 1 1 4 15 23 | 44 | 2.27 2.27 9.09 34.09 52.27 | 100.00 --------------+-------------------------------------------------------+---------Postgraduate | 0 0 2 4 16 | 22 | 0.00 0.00 9.09 18.18 72.73 | 100.00 --------------+-------------------------------------------------------+---------Total | 1 1 6 19 39 | 66 | 1.52 1.52 9.09 28.79 59.09 | 100.00

| Q11 - Been provided in a timely manner Level | Slightly Slightly Mostly Ag Completel | Total --------------+--------------------------------------------+---------Undergraduate | 0 2 10 32 | 44 | 0.00 4.55 22.73 72.73 | 100.00 --------------+--------------------------------------------+---------Postgraduate | 2 1 2 17 | 22 | 9.09 4.55 9.09 77.27 | 100.00 --------------+--------------------------------------------+---------Total | 2 3 12 49 | 66 | 3.03 4.55 18.18 74.24 | 100.00

| Q12 - Stimulated me to reflect on what is til Level | Slightly Slightly Mostly Ag Completel | Total --------------+--------------------------------------------+---------Undergraduate | 1 10 13 20 | 44 | 2.27 22.73 29.55 45.45 | 100.00 --------------+--------------------------------------------+---------Postgraduate | 1 4 4 13 | 22 | 4.55 18.18 18.18 59.09 | 100.00 --------------+--------------------------------------------+----------

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Niyi Awofeso and Moyosola Bamidele Total | 2 14 17 33 | 66 | 3.03 21.21 25.76 50.00 | 100.00

| Q13 - Provided in an encouraging manner Level | Completel Slightly Slightly Mostly Ag Completel | Total --------------+-------------------------------------------------------+---------Undergraduate | 0 1 8 15 20 | 44 | 0.00 2.27 18.18 34.09 45.45 | 100.00 --------------+-------------------------------------------------------+---------Postgraduate | 1 0 1 5 15 | 22 | 4.55 0.00 4.55 22.73 68.18 | 100.00 --------------+-------------------------------------------------------+---------Total | 1 1 9 20 35 | 66 | 1.52 1.52 13.64 30.30 53.03 | 100.00

| Q14 - Helped me identify my strengths Level | Mostly Di Slightly Slightly Mostly Ag Completel | Total --------------+-------------------------------------------------------+---------Undergraduate | 0 4 10 10 20 | 44 | 0.00 9.09 22.73 22.73 45.45 | 100.00 --------------+-------------------------------------------------------+---------Postgraduate | 1 2 3 5 11 | 22 | 4.55 9.09 13.64 22.73 50.00 | 100.00 --------------+-------------------------------------------------------+---------Total | 1 6 13 15 31 | 66 | 1.52 9.09 19.70 22.73 46.97 | 100.00

| Q15 - Helped me identify areas of needed imp Level | Mostly Di Slightly Slightly Mostly Ag Completel | Total --------------+-------------------------------------------------------+---------Undergraduate | 1 2 11 11 19 | 44 | 2.27 4.55 25.00 25.00 43.18 | 100.00 --------------+-------------------------------------------------------+---------Postgraduate | 1 0 2 8 11 | 22 | 4.55 0.00 9.09 36.36 50.00 | 100.00 --------------+-------------------------------------------------------+---------Total | 2 2 13 19 30 | 66 | 3.03 3.03 19.70 28.79 45.45 | 100.00

| Q16 - Increased my level of knowledge about Level | Slightly Slightly Mostly Ag Completel | Total --------------+--------------------------------------------+---------Undergraduate | 1 4 13 26 | 44 | 2.27 9.09 29.55 59.09 | 100.00 --------------+--------------------------------------------+----------

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Niyi Awofeso and Moyosola Bamidele Postgraduate | 0 2 6 14 | 22 | 0.00 9.09 27.27 63.64 | 100.00 --------------+--------------------------------------------+---------Total | 1 6 19 40 | 66 | 1.52 9.09 28.79 60.61 | 100.00

| Q17 - Provided direction of the learning pr Level | Mostly Di Slightly Mostly Ag Completel | Total --------------+--------------------------------------------+---------Undergraduate | 2 4 15 23 | 44 | 4.55 9.09 34.09 52.27 | 100.00 --------------+--------------------------------------------+---------Postgraduate | 0 2 6 14 | 22 | 0.00 9.09 27.27 63.64 | 100.00 --------------+--------------------------------------------+---------Total | 2 6 21 37 | 66 | 3.03 9.09 31.82 56.06 | 100.00

| Q18 - Built my confidence Level | Completel Mostly Di Slightly Slightly Mostly Ag Completel | Total --------------+------------------------------------------------------------------+---------Undergraduate | 0 0 1 9 12 22 | 44 | 0.00 0.00 2.27 20.45 27.27 50.00 | 100.00 --------------+------------------------------------------------------------------+---------Postgraduate | 1 1 0 2 5 13 | 22 | 4.55 4.55 0.00 9.09 22.73 59.09 | 100.00 --------------+------------------------------------------------------------------+---------Total | 1 1 1 11 17 35 | 66 | 1.52 1.52 1.52 16.67 25.76 53.03 | 100.00

| Q19 - Been individualized to my performanc Level | Mostly Di Slightly Slightly Mostly Ag Completel | Total --------------+-------------------------------------------------------+---------Undergraduate | 1 2 12 7 22 | 44 | 2.27 4.55 27.27 15.91 50.00 | 100.00 --------------+-------------------------------------------------------+---------Postgraduate | 1 0 2 9 10 | 22 | 4.55 0.00 9.09 40.91 45.45 | 100.00 --------------+-------------------------------------------------------+---------Total | 2 2 14 16 32 | 66 | 3.03 3.03 21.21 24.24 48.48 | 100.00

| Q20 - Included both positive comments and c Level | Slightly Slightly Mostly Ag Completel | Total --------------+--------------------------------------------+----------

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Niyi Awofeso and Moyosola Bamidele Undergraduate | 2 6 8 28 | 44 | 4.55 13.64 18.18 63.64 | 100.00 --------------+--------------------------------------------+---------Postgraduate | 0 1 4 17 | 22 | 0.00 4.55 18.18 77.27 | 100.00 --------------+--------------------------------------------+---------Total | 2 7 12 45 | 66 | 3.03 10.61 18.18 68.18 | 100.00

References Allen, I. E. & Seaman, J. (2011). Going the Distance: Online Education in the United States, 2011. Babson Survey Research Group, Boston. Bailey, R. (2009). Undergraduate students’ perceptions of the role and utility of written assessment feedback. Journal of Learning Development in Higher Education. Issue 1, February 2009. Retrieved on 15 January 2016 from http://www.aldinhe.ac.uk/ojs/index.php?journal=jldhe&page=article&op=view&path%5B%5D=29&path%5B%5D=13 Dempsey, J. V., Driscoll, M. P., and Swindell, L. K. (1993). Text-based feedback. In J. V. Dempsey & G. C. Sales (Eds.), Interactive instruction and feedback (pp. 21-54), Educational Technology Publications, Englewood Cliffs, N.J. Easton, S.S. (2003). Clarifying the instructor's role in online distance learning. Communication Education, 52(2), 87-105. Eon, S. B., Wen, H. J., and Ashill, N. (2006). The determinants of students’ perceived learning outcomes and satisfaction in university online education: an empirical investigation. Decision Sciences Journal of Innovative Education, 4, 215-235. Entwistle N. Taking stock: teaching and learning research in higher education. Paper presented at the Ontario international symposium on teaching and learning in higher education, May 2008. Retrieved on 11 December 2015 from: http://www.research.ed.ac.uk/portal/files/14426330/ENTWISTLE_Taking_Stock.pdf Getztlaf, B., Perry, B., Toffner, G., Lamarche, K., and Edwards, M. (2009). Effective Instructor Feedback: Perceptions of Online Graduate Students. Journal of Educators Online, 6(2). Retrieved on 2 December 2015 from: http://webcache.googleusercontent.com/search?q=cache:ZUFzmrHMo0QJ:www.thejeo.com/Archives/Volume6Num ber2/GetzlafetalPaper.pdf+&cd=1&hl=en&ct=clnk&gl=au Hepplestone, S., Parkin, H., Irwin, B., Holden, G., and Thorpe, L. (2010). Using technology to help students engage with their feedback – technology, feedback, action! A short report. Sheffield Hallam University, Sheffield. Linacre, J.M. and Wright, B.D. (2000). A user’s guide to WINSTEPS: Rasch Model Computer Program. Chicago: MESA Press. Lim, D. H., and Morris M. L. (2009). Learner and instructional factors influencing learning outcomes within a blended learning environment. Educational Technology & Society, 12 (4), 282–293. Mory, E. H. (2004). Feedback research revisited. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology: A project for the Association for Educational Communications and Technology (Second ed., pp. 745-783), Lawrence Erlbaum Associates, Mahwah, New Jersey. Nguyen, T. (2015). The effectiveness of online learning: beyond no significant difference and future horizons. MERLOT Journal of Online Learning and Teaching, 11, 309-319. Nicol, D. (2010). From monologue to dialogue: improving written feedback processes in mass higher education. Assessment and Evaluation in Higher Education 35(5), 501–517. Race, P. (2002) Using feedback to help students to learn. The higher education academy, UK. Retrieved on 13 December from; http://wap.rdg.ac.uk/web/FILES/EngageinFeedback/Race_using_feedback_to_help_students_learn.pdf. Sales, G. C. (1993). Adapted and adaptive feedback in technology-based instruction. In J. V. Dempsey & G. C. Sales (Eds.), Interactive instruction and feedback (pp. 159-175), Educational Technology Publications, Englewood Cliffs, N.J. Schell, G. P. and Janicki T. J. (2013). Online Course Pedagogy and the Constructivist Learning Model. Journal of the Southern Association for Information Systems, 1, 26-36. Scott, S. (2008). Improving Student satisfaction with Feedback: Report on a Project Undertaken in the Faculties of Arts & Social Sciences and of Law at UNSW. Retrieved on 15 January 2016 from https://teaching.unsw.edu.au/sites/default/files/upload-files/scottreport.pdf Shannon, C. E. and Weaver, W. (1964). The Mathematical Theory of Communication. University of Illinois Press, Illinois. Sher, A. (2009). Assessing the relationship of student-instructor and student-student interaction to student learning and satisfaction in web-based online learning environment. Journal of Interactive Online Learning, 8, 102-120. Smith, E., Jr. (2000). Rasch Measurement Models. Paper presented at An Introduction to Rasch Measurement: Theory and Applications, Chicago. Suen, H. (2014). Peer assessment for massive open online courses (MOOCs). The International Review of Research in Open and Distributed Learning, 15(3). Retrieved on 13 December 2015 from http://www.irrodl.org/index.php/irrodl/article/view/1680/2904 Tudor, J., and Penlington, R. (2009). Perceptions and their influences on approaches to learning. The Higher Education Academy Engineering Subject Centre, UK. Wright, B. D., & Masters, G. N. (1982). Rating scale analysis. Chicago, IL: MESA Press.

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Dilemmas Facing Universities in Implementing Online Learning Programmes Mammed Bagher and Aileen Sibbald Edinburgh Napier University, UK [email protected] [email protected] Abstract: Recent advancements in communication technology, coupled with the popularity of social media platforms, have enabled educational providers to open up access to education to a wider community of students. Whilst technology provides opportunities it also poses a competitive threat, as traditional universities are now faced with strong competition for students from Universities across the globe as well as private sector providers. In 2010, there were 113 HE and FE providers in the UK, offering more than 1,500 online/ distance learning courses, most of them keen to expand their provision (White, et. al., 2010). In 2012, the Business School at Edinburgh Napier University (the University featured in this research) entered into this already established market place, with the aim of being recognised internationally as a leading provider of online education. This research explores the tensions between the academic and the organisation during a process of organisational change. Specifically, the implementation and delivery of a sustainable online learning strategy within a UK University environment which traditionally focused on physical face to face on-campus education. In addition, the paper aims to further develop the ongoing study of change management within the University sector by seeking to identify the main strengths and limitations of implementing online education. The paper concludes with an identification of the core elements to be considered when measuring the success of implementation and the delivery phase of online education. Keywords: online education, virtual learning environment (VLE), change management, sustainability

1. Introduction Globalisation and advancements in communication technology have created a new platform for distance learning education. While this brings challenges for the planning, delivery and quality assurance of education within an online learning environment, it also provides opportunities to enhance the student experience. As worldwide demand for higher education continues to grow, stimulated by economic growth, the changing economic needs of developing economies, and the growth of the consumer class worldwide, web assisted technology provides educational providers with the tools to access this market place (Boys & Ford, 2007). Universities in the UK operate within a rapidly changing environment involving pressures on public expenditure, uncertainty over international student fee income arising from changes to immigration policy, increasing international competition for students, and growing expectations of ourselves and our students in relation to the student experience. Universities need to adapt their learning models to address these pressures, and changes are required to enable Universities to compete in increasingly competitive domestic and international markets, within which high quality learning resources are freely available online, on demand, and at no cost such as MOOCs. In the last few decades a myriad of terms have been used to describe learning in an online environment, such as e-learning, web-assisted learning, networked learning and virtual learning. There are, however, common characteristics of online learning: physical distance between the student and the academic (Tutor), and the use of technology to access learning materials, engage with academic tutors and other students, and provide support to students. This research uses the definition of online learning suggested by Ally (2007): “The use of the Internet to access learning materials; to interact with the content, Instructor and other learners; and to obtain support during the learning process, in order to acquire knowledge, to construct personal meaning, and to grow from the learning experience” (2007, p7). Online learning aims to engage students as a group of virtual learners who may be geographically dispersed, providing them with a unique and culturally diverse learning experience. Software applications such as Moodle and WebEx are utilised to provide a platform to encourage students to engage in their learning process and further help them to build community and trust.

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Mammed Bagher and Aileen Sibbald Historically, the act of gaining knowledge through learning and education has focused on traditional, face to face on-campus interaction, although the concept of distance learning is nothing new (e.g. The UK Open University). However, contemporary advancements in Information Technology have created an opportunity to foster a new paradigm, where for the first time mass global education can take place at a distance, with immediate access to learning materials, breaking down geographical barriers and supporting the re-establishment of social interaction. This new approach to distance teaching and learning, utilising web assisted technology, demands a revised methodology. Moser (2007) suggests that an appropriate framework must be put in place to enable staff to use educational technology, if the University’s strategy is to promote its use. This paper aims to explore the changes which are necessary to support the successful implementation of online distance education within a UK University.

2. Literature review 2.1 Context Recent advancements in communication technology, coupled with the popularity of social media platforms, have enabled educational providers to open up access to education to a wider community of students. Whilst technology provides opportunities, it is also poses a competitive threat as traditional universities are now faced with strong competition for students from Universities across the globe as well as private sector providers. This reinforces the need for Universities to overcome possible complacency and take advantage of the opportunities being presented – ‘otherwise there is a threat of being left behind’ (O’Neill, Singh & O’Donghue 2004; Volery & Lord 2000). In 2010, there were 113 HE and FE providers in the UK, offering more than 1,500 online/distance learning courses, most of which were keen to expand their provision (White, et. al., 2010). In 2012, the University featured in this research entered into this already established market place, with the aim of being recognised internationally as a leading provider of online education.

2.2 Online learning As noted by Ciussi & Freitas, “e-Learning is now fully part of our learning environment and no longer an add-on to traditional pedagogies. It is integrated in the way we live, work and teach. However, there is a potential tension in the manner that this has been launched into Institutions in relation to online distance learning courses” (2012, piii). Cubric, Lilley & Clarke claim that in traditional UK institutions these have been, “bolted onto long established practices without clear institutional understanding of the need for a distinct studentcentred distance learning pedagogy” (2012, p107). To this end they highlight the need for Institutions to have a “clearer vision to enable the delivery of the benefits and scalability which technology seems to promise”. This notion by definition questions the appropriateness of the current structure of UK Higher Education Institutions which are geared to deliver education on a face-to-face basis. Hence the need for institutions to adapt a more hybrid model in which they can accommodate both traditional and online distance education. This hybrid model must have the capabilities to deliver a high quality learning experience for students, maintain academic standards and quality of awards in line with UK Quality Assurance Agency (QAA) benchmarks, and protect and enhance the brand and reputation of the institution. Furthermore, it must facilitate the development of students to acquire the skills which will enable them to transfer their knowledge into practice. This notion is reinforced by Mayes & de Freitas, who argue that “the role of technology may be primarily to get remote learners into a position to learn as favourably as though they were campus based, rather than offering a new learning method” (2013, p 17). This highlights the fundamental importance of making sure that “both campus based and distance learning needs to be within the same theoretical constructs” (ibid, p17). According to Hiltz and Turoff “current evolutionary changes in educational technology and pedagogy will be seen, 50 years from now, as revolutionary changes in the nature of higher education as a process and as an institution” (2005, p60). They consider that “we are in the process of moving from face-to-face courses to online and hybrid courses using digital technologies….”, and further suggest that “online learning would infiltrate and change the nature of traditional face to face delivery” (ibid, p60).

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Mammed Bagher and Aileen Sibbald Hall, et. al., (2012) interprets these changes as the merging of formal and informal learning. Leadbeater further suggests that “Schools and Universities should become more like hubs of learning, within the community, capable of extending this into the community, more learning needs to be done at home, in offices and kitchens, in the contexts of where knowledge is deployed to solve problems and add value to people’s lives” (2000, p112). Puzziferro & Shelton note that “online education has forever transformed Higher Education, and we are learning that quality is really about flexibility and the ability to adapt to the changing demands of learners, the new promises of technology, and the new competitive landscape of Higher Education (HE). If HE is to remain competitive we must focus and redesign our paradigms, as well as design business processes that integrate with quality assurance models"(2008, p 135). Further, "in order to compete in the online HE market we need to get relevant high quality product to market quicker. In a market where students expect fast service, consistency and quality, a more streamlined production approach is now required" (ibid, p120).

2.3 Change within organisational paradigms Change is an integral part of everyday life and is the only thing which is certain to happen; change is the only constant thing in life, and according to Darwin (1859) the adaptability to change determines a ‘species’ fate’. There are a variety of approaches which an organisation can choose in order to implement change, and for the purpose of this research change is introduced by providing a range of definitions and explanations. Senior & Swailes (2010) suggest that models of change can be divided predominantly into hard and soft systems. The hard systems approach originates from the field of project management, with industrial origins. The model consists of description, options and implementation phases, with a main objective of problem solving. According to Senior & Swailes (2010), the hard system model of change can be applied where there is no need to consider human emotions and where there is an emphasis on the technical complexity of the task. The hard approach is a rigorous and systematic way of determining objectives or goals for change. This particular approach implies that all measurement techniques, and the decision-making process, are clear, and is very much concerned with the content and context of change. In practice, this approach means that an organisation initially describes the current situation, the objectives for change, and the performance measures to be used in detail. The so called soft system approach is more appropriate for situations that affect an organisation and its internal departments, and it requires support and buy-in from top management, through collective ownership. The soft approach deals not only with the context and content of change but also with the process. This particular approach is based on the notion of interpreting organisations as a community where the decision making process is not limited to senior management. The soft system model focuses on people as the main deliverers of change, with particular emphasis on their values, beliefs and culture, combined with their developmental needs. Further, it aims to develop the organisation by placing emphasis on developing the people involved within the organisation. In addition, organisational change falls into two types – strategic and operational. Strategic change is considered as a long-term broad set of plans which are organisation-wide. Senior & Swaile’s interpretation of “classic thinking” suggests that “strategic change assumes that the planning process rely on the ability to join-up causes and effects” and to this end this model “underpins the top-down approach to strategy analysis and implementation” (2010, p51). Operational change relates to the achievement of aims and objectives of the plans set out within the strategic framework. This is closely linked to ‘operational strategies’, interpreted by Johnson & Scholes as being “concerned with how the component parts of an organisation deliver effectively the corporate and business level strategies in terms of resources, processes and people” (2002, p.12). It can be argued that the hard approach does provide a useful way to manage organisational change where operational change activities are measureable. This approach to change may work well when implementing new technology or initiatives. For broader changes, however, the soft approach takes into account people’s emotions and cultures, and in turn may have a more sustainable effect, as change is not imposed on people; they are engaged and convinced through a well-communicated vision of change.

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Mammed Bagher and Aileen Sibbald Whether a hard or soft system approach for change is chosen, the common denominator is the actual management and sustainability of that change. In addition, the approach needs to fit the context within which the organisation is operating.

3. Methodology This research was designed to explore the tensions between ‘the Academic’ and ‘the Organisation’ during a process of organisational change. Specifically, during the implementation and delivery of a sustainable online learning strategy within a UK University that traditionally focused on physical, face to face, on-campus education. A phenomenological approach was selected to explore the way in which academics experienced social phenomena in their world (Saunders, et al, 2012), and to seek to identify perceptions, perspectives and understandings of a situation. Given the subjective nature of the research, as academics will have different interpretations of the same situation, a mixed methods approach of a qualitative survey followed by individual interviews was selected, to provide the opportunity for richer data collection, analysis and interpretation (Bryman & Bell, 2001). Further, using a qualitative approach enabled engagement with participants to understand behaviours, by focusing on ‘why’ rather than ‘what’ behaviours occur (McBride & Schostak, 1995). A purposive sampling process was used to select participants in a strategic way, in order that those sampled had relevant knowledge relating to the research questions (Bryman & Bell, 2011). Data was collected by means of a questionnaire from academics from one Faculty in a UK University, who were closely involved in the development of online programmes. The questionnaire sought the views of academics in four key areas: their understanding of Online Learning; their attitude to the development of online programme delivery; the University strategy for taking forward this development; and the sustainability of the approach being taken. Although questionnaires are a convenient method of gathering primary data, there is potential to lose the personal views and considerations, which is an important element of this research. Therefore the questionnaires were followed up by individual interviews, in order to provide an opportunity to probe initial answers and obtain a richer source of comments, as well as providing participants with assurance as to how the data was going to be used. The limitations of this research in terms of the sample size and the use of a qualitative approach are recognised, in particular the potential for the findings to be influenced by the researchers’ presence and objectivity, and its limited capacity for generalisation across a wider population (McBride & Schostak, 1995). However, the objective of the research was to explore tensions which existed, with a view to identifying areas which required further work to ensure the successful implementation of a University’s strategy for online education.

4. Research findings and analysis Previous research in the University (Bagher, Marek & Sibbald, 2007), explored staff attitudes to the implementation of web-assisted learning within the traditional face to face educational environment of a UK University. With the extension of web-assisted learning into distance education, the objective of this paper is to ascertain the views of the academic staff within the same University to the progression from web-assisted learning to fully online distance education. The analysis of the findings is based on the significance of the answers in relation to the dilemmas facing academics implementing online learning programmes. Questionnaires were issued to 90 academic staff, and a total of 38 responded (42%). The response rate was acceptable as it was sufficient to establish a number of common factors.

4.1 Online learning The initial question sought to determine whether there was a common understanding amongst the academic staff within the University as to what online learning means. The survey found that respondents expressed similar views to that proposed by Ally (2007). They considered it to be “Learning without face to face contact, providing students with the opportunity to study for a qualification at a time and place which meets their individual needs via a virtual learning environment”. There was also a growing recognition that online delivery enables education to reach out to a wider learning community, by removing an access barrier, although some respondents were “sceptical that this was for economic rather than andragogical reasons and a bolt onto

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Mammed Bagher and Aileen Sibbald established practices”. This view was also expressed by Lentell, who describes the situation in traditional UK institutions where online learning has been “bolted onto long established practices without clear institutional understanding of the need for a distinct student-centred distance learning pedagogy. If it is to deliver efficiently the benefits and scalability which technology seems to promise, a clearer vision is needed” (2012, p107). The respondents recognised the desire and demand by online students for flexibility in the way education is delivered, which online learning can offer. The majority of respondents accepted that the move into online learning was the way forward. One respondent indicated their preference for face to face contact, but recognised “it is the way forward to reach many learners all over the world, so we have to embrace it”. However, respondents expressed caution that “such developments must be supported by adequate resourcing and training in the development of online materials, online learning and student support”. As one respondent noted, it “works if invested in properly”. In addition, one respondent expressed the view that online learning was “not an economical way to increase student numbers; the nature of such study means that online learners seek more support on an individual basis than traditional face to face education”.

4.2 Staff attitudes The findings highlighted a significant change of attitudes towards the move into online learning from external, university and personal perspectives. One respondent was of the opinion that this was “a good and pioneering move”; another stressed that the University should “keep going, it is very exciting that we are doing this! And it is the future!” and another noted that online education is “getting more and more popular but we need to get better at it”. Respondents also expressed caution and that such a move requires “more resources” and “we need training and support”. Abrahams (2010) highlights a number of barriers to technology adoption: perception; resistance to change; technological support; financial support; infrastructure; knowledge/ information; and technophobia. This is supported by Rogers (2003), Butler and Sellborn (2002). This notion of barriers is reflected by the respondents who highlighted the need for additional training and development in order to acquire the necessary skills to facilitate the implementation and delivery of online programmes. Comments from respondents also included: “my frustration comes from my own lack of confidence [knowledge] with ICT”; “perhaps support amongst module leaders and the ability to share best practices would be more helpful than formal training”; “need academic experts to tell us about best practice and latest innovation, more evidence based guidance required”; “finding time to attend training sessions difficult”. According to Eckel & Kazar “people think differently” and the process of “getting people to adopt new mind-sets is a cognitive and intellectual process spurred by a set of activities that can be intentionally designed to leave behind old ideas, assumptions and mental models” (2003, p73). This reinforces the notion that to achieve this, there is a need for organisations to provide the environment for individuals to develop new ‘mind sets’.

4.3 Institutional strategy The University’s development of online programmes was partly a result of the need to enter an alternative educational market in order to fill a gap caused by a reduction in overseas non-EU student enrolments. This reduction was mainly due to the UK Border Agency’s revised non-EU student entry requirements, which included the removal of post-study stay. Whilst academic staff recognised the rationale behind the move, one respondent felt that the approach taken by the University to the development restricted their academic freedom. The majority of respondents highlighted that for this move into online education to be successful, it is necessary to develop a strategy for online education at an institutional level, and this should be supported by the necessary resources to design and develop specific online learning materials. As one respondent advised “to get this right we need spend time reviewing online provision and have the necessary time and resources to offer an appropriate distant learning experience”. These responses support the view of Puzziferro & Shelton that “integration of online education into the institutional strategic planning and goal setting process is critical to achieving the level of quality need to

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Mammed Bagher and Aileen Sibbald compete in the competitive industry of online education” (2008, p120 ). Furthermore, they are in agreement with Greenberg who points out that “universities are indeed businesses, and if they are to compete in the evergrowing competitive online higher education market, they need to take a hard look at their culture and practices” (ibid, p120); a perspective reinforced by the findings of this study, with respondents stating that “the systems and processes are not fit for the purpose of online education” and as such they “need to be revised across the board”.

4.4 Sustainability All respondents acknowledged that the move into online education is one of the key determinants to the “successful delivery of the University’s overall Strategy”. However, the majority of respondents highlighted the “need for adequate resources for initial training and ongoing development”. They also expressed the “importance of developing learning materials which are interactive, relevant, engaging and academically challenging”. The above factors reinforce the need for investment in appropriate technology, coupled with supporting administrative infrastructure, to ensure a quality student experience that is, albeit from a distance, comparable to that delivered on campus. This view is supported by the findings of Puzziferro & Shelton who note that in order to meet the demand for online education, institutions need to put in place a “a sustainable ‘business model’ for online course development that offers a scalable production process that is the foundation for quality, efficiency and productivity for the entire institution” (2008, p119). Respondents were concerned over the perceived lack of appropriate human resources to meet the strategic objectives, both at academic and support staff level. Respondent comments included: “careful consideration must be given to an appropriate model to ensure adequate levels of staff are in place in order to sustain growth in student numbers”; “online learning should not be seen as a cheap option, and business processes should integrate with quality”. Respondents also highlighted that in order for the delivery of online materials to be sustainable they (academics) “must have the appropriate knowledge and skills”, and “all related academic team members need to be actively engaged with online delivery”. Additionally, a need was identified for “relevant training in various aspects of online development and delivery at appropriate times which academics could attend”. One respondent suggested that “more informal training in the form of peer support would be more appropriate” and “debriefs for online programmes using workshops for development would be helfpul”.

4.5 Student experience There was a myriad of responses to the question on potential benefits of utilising online learning assets on other modes of deliveries such as face to face, blended distance learning and Transnational Education. A number of respondents saw benefit in the “materials being an additional resource for these modes, affording students the time to reflect on the topic”. A number of respondents suggested that online learning “enhances flexibility and provides alternative methodologies that may suit the students learning style, rate of learning and engagement issues” and “my thinking has developed as a result of reviewing and updating my online materials”. Few respondents perceived that there would be no benefit to student experience.

5. Conclusions and reflections The focus of this paper was to explore the tensions which exist between ‘the Organisation’ and ‘the Academic’ during the implementation and delivery of a sustainable strategy for online education, and to identify areas for action. The findings highlighted that academics recognised that there were benefits in the shift into online education. Nonetheless, they expressed the fundamental requirement that a clear and focused strategy for online education be developed by the University, to ensure successful implementation.

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Mammed Bagher and Aileen Sibbald Furthermore, the paper established the need for careful planning and guidance in order to manage and sustain the change process. In addition, appropriate and timely training and development support must be in place, and this needs to be matched by adequate levels of technical and administrative support. The research further highlighted the importance of creating the necessary environment in order to enable change to take place effectively. The findings identified a number of key areas which need to be addressed in order to ensure the successful move into online education. These include: ƒ

The need to embed online education into normal academic activity.

ƒ

The importance of ensuring that the online student experience is comparable with that of face-to-face students.

ƒ

University systems and processes must be capable of supporting the requirements of the mode of delivery.

ƒ

Clear and concise information must be provided to students, explaining what and how the institution will deliver the online education.

The dilemmas facing the University and its academics is not unique to this institution. To this end, lessons learned from this study may be helpful to other educational establishments that are embarking on their journey into online education. Having identified the tensions and possible barriers at university level, the next phase of this research is to examine the views of past and current students to identify the limitations and strengths of online education from the student perspective.

References Abrahams, David, A. (2010) ‘Technology Adoption in Higher Education: A framework for identifying and prioritising issues and barriers to adoption of Instructional Technology’, Journal of Applied Research in Higher Education, Vol 2, Iss2, pp34-49 Ally, M. (2007) ‘Foundations of Educational Theory for Online Learning’ in The Theory & Practice of Online Learning 2008, 2nd edn. Editor Anderson, T. AU Press: Athabaca University Bagher, M., Marek, S., & Sibbald, A. M. (2007) ‘Transition to Web assisted learning: influences on academic staff engagement’, Edinburgh: Napier University, School of Accounting & Economics Beetham, H. & Sharpe, R. (2013) eds. Mayes, T. & de Freitas, S. “Chapter 1: Technology-Enhanced Learning – the role of theory”, Rethinking Pedagogy for a Digital Age: Designing for 21st Century Learning, Routledge: Oxon Boys, J. & Ford, P. (2007) eds. The e-Revolution and Post-Compulsory Education: using e-business models to deliver quality education, Routledge: London Bryman, A. and Bell, E. (2011) Business Research Methods, Oxford University Press: Oxford Burnes, B. (2004) Managing Change, Pearson Education Limited: Harlow Butler, D. L. & Sellborn M. (2002) ‘Barriers to adopting technology for teaching and learning’, Educause Quarterly, Vol 25, No 2, pp 22-28 Ciussi, M. & Freitas, E. G. (2012) eds. Leading issues in e-Learning Research, Academic Publishing International: Reading Collis, B. & Moonen, J. (2001) Flexible Learning in a digital world, Kogan Page Limited: London Cubric, M., Lilley, M. & Clark, K. (2012) ‘An Evaluation of Online Distance Learning Programmes Through the Lens of Student’s Expectations’, The Proceedings of the 11th European Conference on e-Learning, Academic Publishing International: Reading Darwin, C. (1859) The Origin of Species, Bantam Dell: New York (republished June 1999) Eckel, P. & Kazar, A. (2003) Taking the reins: Institutional transformation in Higher Education, Westport CT: Praeger Greenberg, M. (2004) A University is not a Business (and other Fantasies), Educause Review Vol 39, No2, pp 10-16 Hall, M., Nix, I. & Baker, K. (2012) ‘Why bother?” Learner perceptions of digital literacy skills development - learning design implications’, in ECEL Proceedings of the 11th European Conference on eLearning, Academic Publishing International: Reading Hiltz, S.R, & Turoff, M (2005) ‘Education Goes Digital: The Evolution of Online Learning and the Revolution in Higher Education’, Communications of the ACM, October 2005 Vol 48, No10, pp59-642 Johnson, G. & Scholes, K. (2002) Exploring Corporate Strategy – Text and Cases 6th edn, Pearson Education Ltd: Harlow Lentell, H (2012) ‘Distance learning in British Universities: is it possible?’, Journal of Open and Distance Learning Vol 27, No 1, pp 23-26 McBride, R. & Schostak, J. (1995) “Chapter 2: Qualitative Versus Quantitative Research”, [online], Available: http://www.enquirylearning.net/ELU/Issues/Research/Res1Ch2.html Miller, D. (1990) The Icarus Paradox, Harper Business: New York Moser, F. Z. (2007) ‘Faculty Adoption of Educational Technology’ Educause Quarterly Vol 30, No 1, pp 66-69

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Mammed Bagher and Aileen Sibbald O’Neill, K,. Singh, G. & O’Donghue, J (2004) ‘Implementing eLearning Programmes for Higher Education: A Review of the Literature’, Journal of Information Technology Education, Vol 3, 2004 pp 313-323 Peters, T. J. & Waterman, R. H. (1982) In Search of Excellence, Harper & Row: New York Puzziferro, M. & Shelton, K. (2008) ‘A model for developing high-quality online courses: Integrating a systems approach with learning theory’, Journal of Asynchronous Learning Networks, Vol 12, Issue 3-4 pp119-136 Saunders, M.K., Lewis, P. & Thornhill, A. (2012), Research Methods for Business Students 2nd edn, Pearson Education Ltd: Harlow Senior, B. & Swailes, S. (2010) Organizational Change 4th edn, Pearson Education Ltd: Harlow Volery, T. & Lord, D. (2000) ‘Critical success factors in online education’, The International Journal of Education Management, Vol 14, No 5, pp 216 – 223 White, D, Warren, N, Faughnan, S & Manton M ( 2010) Study of UK Online Learning, Report to HEFCE by the Department for Continuing Education, University of Oxford :Available at http://www.hefce.ac.uk/pubs/rereports/Year/2010/ukonlinelearning/Title,92247,en.html

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ICT Tools Usage’s Effectiveness by Communities of Practice in Promoting Knowledge Management Innovation Kay Bandlow and Sheryl Buckley University of South Africa, Pretoria, South Africa [email protected] [email protected] Abstract: We live in a globalised world where knowledge is obtainable on the internet at the press of a button. As a result of this globalisation and ease of access to knowledge on the internet, knowledge economies have emerged in some parts of the world. In these economies, organisations have become aware that is it not enough to merely compete with one another on the basis of financial strength; and that knowledge is the new competitive advantage and differentiator. Knowledge management is the key to power, because it is a significant factor for the strategic survival of organisations. Furthermore, knowledge management is identified as a framework for creating organisational strategy, structures and processes so that it can use what an organisation knows to learn and create economic and social value for itself and its stakeholders. The purpose of this study was to investigate how effective Communities of Practice (CoP) use ICT tools when promoting innovation in knowledge management by looking at a specific ICT tool, Knowbie, and a specific CoP, which in this case was a software development team of a mining company. To meet this purpose, the study purposed three research questions. One of the findings to these questions is that the team does not know if the use of Knowbie is effective in promoting innovation in the way that knowledge is managed in the company. A further finding is that they do not use Knowbie. The study concluded that since the specific CoP does not use the specific ICT tool the effectiveness of its use in promoting innovation in the way that knowledge is managed cannot be determined. Keywords: communities of practice, knowledge management, mining company, software development team, ICT tools

1. Introduction and purpose of the study The saying ‘knowledge is power’ is attributed to Sir Francis Bacon, an English Philosopher (Garcia, 2001: 110). It means that when you gain knowledge you gain power. We live in a globalised world where knowledge is obtainable on the internet at the press of a button. As a result of globalisation and ease of access to knowledge via the Internet, knowledge economies have emerged in some parts of the world (Omotayo, 2015: 1). In these economies, organisations have come to realise that is it not enough to merely compete with one another on the basis of financial strength; and that knowledge is the new competitive advantage and differentiator (Omotayo, 2015: 1). Not only is knowledge power, but the management of it is the key to this power, because it is a significant factor for the strategic survival of an organisation (Omotayo, 2015: 2). Furthermore, knowledge management is identified as a framework for formulating the strategy, structures and processes of an organisation so that it can use what it knows to learn and create economic and social value for itself and its stakeholders (Omotayo, 2015: 2). The main ingredient to understanding the successes and failures of the management of knowledge in organisations is the identification of resources that allow organisations to become aware of knowledge, and create, transform and distribute knowledge (Omotayo, 2015: 2). Organisations that effectively manage and transfer their knowledge are more innovative, productive and perform better than their competitors (Omotayo, 2015: 2). The significance of knowledge management is no longer restricted to knowledge intensive firms in hi-tech industries, but to all sectors of an economy, for example education, banking, telecommunications and mining. The purpose of this study was to investigate how effective the use of ICT tools by Communities of Practice (CoP) is in promoting innovation in knowledge management by looking at a specific ICT tool and a specific CoP.

2. Research questions To fulfil the purpose stated above, the study proposed the following research questions:

2.1 How effective is the use of Knowbie, an ICT tool, by the software development team, a community of practice (CoP), of a mining company in stimulating innovation in the way knowledge is managed? Related to this question are the following sub-questions:

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Kay Bandlow and Sheryl Buckley 2.1.1 What are the software development team’s beliefs regarding the following: ƒ

Knowbie

ƒ

the benefits and disadvantages of being a Knowbie member

2.1.2 How frequently Knowbie is used in the organisation by the indicated software development team

3. Literature review Knowledge management can be conducted in two ways: CoPs and ICT tools. This section discusses these two ways.

3.1 CoPs More organisations are increasingly employing CoPs to take advantage of knowledge as one of the key success factors of operating in the global economy and to increase the knowledge base and experiences of its employees (Daele, Deschryver, Gorga, and Kunzel, 2007: 2). In order to manage the knowledge of CoPs, it is important to determine the needs of the various CoPs (Daele et al, 2007: 4). Daele et al (2007:4) identified two needs during a project they conducted. Firstly, the CoP members need to define what each of them wants to learn; and what the collective group wants to learn (Daele et al., 2007: 4). Secondly, members of the CoP need to participate in regular and rich collaborations, because the learning will be more efficient if the interactions are richer and wellsupported (Daele et al, 2007: 4). These two needs are related to the commitment of the CoP members (Daele et al, 2007: 4). If a member states and clarifies what his or her goals of learning are in relation to that of the group; and if the interaction in the member’s CoP leads him/ her to achieving his/her stated goal, then he/she would in future be more willing to become involved in the CoP’s activities (Daele et al., 2007: 4). A further need relates to the resources that the CoP members produced (Daele et al., 2007: 4). In order to manage learning through social interactions, the members of the CoP produce and re-use resources, such as technological tools for maintaining the tacit knowledge or organisational tools of the members to perform activities that guide them to share their knowhow (Daele et al., 2007: 4). These tools can support each member’s learning in the CoP (Daele et al., 2007: 4). Michaelides, Tickle and Morton (2010: 925) assert that a member’s participation in social networks, for example, Facebook, is the outcome of increased social interaction, whereas in CoPs, constant motivation is required for consistent member engagement. In order for CoPs to be successful, these groups need to be structured around motivated members who are willing to take part in the group(s) they belong to, thereby creating a higher commitment to the community (Michaelides et al., 2010: 924). The role moderators, play in a CoP is significant because they can present thought-provoking arguments or articles to members in order to inspire debate and encourage participation (Michaelides et al., 2010 925). When selecting a moderator one should consider factors such as time proactively spent on engaging in CoPs, volunteering, blogging and interacting with other members (Michaelides et al., 2010: 925). Training and advice to moderators should be provided in order to assist them in managing their community group effectively (Michaelides et al., 2010: 925). Having a moderator as part of the community allows for an increased level of enthusiasm (Michaelides et al., 2010: 925). Therefore, a further requirement for CoPs to be successful is the need for the regular monitoring of issues and changes in the developing needs of their members, thus making the role of moderator even more significant (Michaelides et al., 2010: 925).

3.2 ICT tools Rashid, Wang, and Hashim (2011: 227) are of the opinion that the influence of social networks has been underestimated in recent years; and that they play a significant role in an organisational context . Organisations are able to better advance their relationship in various departments for the purpose of maximising profits and providing efficient customer service by using these networks (Rashid et al., 2011: 227). The apparent usefulness and perceived ease of use of technology are related to extrinsic and intrinsic motivation (Soo, 2006: 184). This connection gives rise to the likelihood that technology may influence the motivation of employees to share their knowledge (Soo, 2006:184). Given the everyday use of technology in the organisation,

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Kay Bandlow and Sheryl Buckley this is an important issue to consider (Soo, 2006: 184). The quality of a tool which is easy to use is a significant aspect of technology for employees, since they work under tight pressures (Soo, 2006: 189). If a tool is not intuitive, it will be ignored (Soo, 2006: 189). At the opposite end of the spectrum is the usefulness of a tool (Soo, 2006: 189). Although usefulness is important, it is not as important as ease of use Soo, 2006: 189). If a technology is useful, but difficult to use, the users will reject it (Soo, 2006: 189). Another key aspect of technology for employees who share their knowledge is the accessibility of experts and information in the organisation (Soo, 2006: 189). Technology enables employees to recognise and communicate faster with the desired experts (Soo, 2006: 188). In organisations today, employees are experts in the areas in which they work, but many of them may not be reachable or approachable for some reason (Soo, 2006: 188). While research has highlighted the possibility of electronic mail, bulletin boards, databases and document repositories to give employees access to the explicit knowledge of experts, the opposite is also true (Soo, 2006: 202). Technology also gives experts a superior ability to distribute their knowledge to those employees who desire it (Soo, 2006: 202). This ability is invaluable for the productivity of the expert, since the convenience and the distant reach of technology is motivating (Soo, 2006: 202). The accessibility operates in both directions: technology gives employees access to the knowledge of experts with unrivalled ease and speed, but technology is more important to experts who are trying to share their knowledge (Soo, 2006: 202). In light of the time constraints, employees who are subject to ease of use and the speed of technology are highly valued (Soo, 2006: 202). The extended reach and speed of technology allows experts to achieve their goal of sharing their knowledge more efficiently than was previously possible (Soo, 2006: 202). The ability to swiftly and easily share knowledge facilitates the provision of it to a knowledge base even though the exercise of entering the knowledge might be perceived to be a repetitive chore (Soo, 2006: 202).

4. Research method As mentioned in section 1, the goal of this study was to investigate how effective the use of ICT tools by CoPs are in promoting innovation in knowledge management by looking at a specific ICT tool, Knowbie, which is used by employees in a group of mining companies to communicate, collaborate, create and share knowledge as well as by looking at a specific CoP – the software development team in one of the mining companies in this group of companies.

4.1 Protocols For privacy purposes, the actual name of the ICT tool under investigation was changed to Knowbie, while the name of the company the tool belongs to, to Company X and the subjects of the study to Participant 1, 2 and so forth. After providing a brief explanation of the purpose of the study on the said tool and team, permission was obtained from the Communications Manager and the software development team manager to conduct the study. Permission was also obtained from the team after an explanation on the purpose of the study was also provided to them.

4.2 Data generation methods The research strategy that was employed was a case study since it enables one to focus and study one instance of an object in detail: a company, department, ICT tool. (Oates, 2006: 140). It also allows for a range of methods to generate data, such as interviewing and observation to name but a few (Oates, 2006: 140). The data generation method that was used to answer the research questions set out in section 2 above comprised a semistructured interview, a questionnaire, a study of the existing information that had been shared on Knowbie; and the Knowbie application. 4.2.1 Semi-structured interview A semi-structured interview was selected, because the researcher wanted to obtain background knowledge on the tool mentioned above. Due to the difficulty in securing the availability of the two employees who were part of the original roll out of Knowbie to conduct a face-to-face interview, two semi-structured interview questionnaires were emailed to them instead. The one employee’s role in Knowbie was to ensure the tool’s accessibility to staff and the other employee played the role of administrator. Of the two interview questionnaires that were sent to these two participants, only one was returned.

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Kay Bandlow and Sheryl Buckley The semi-structured interview questionnaire contained 18 questions that were divided into two sections. Section A contained structured questions that elicited specific information on the participants, such as the industry they work in; the company they work for; their job titles; age and nationality and Section B contained background questions on Knowbie. 4.2.2 Questionnaire A questionnaire was selected because it was an efficient way of collecting data from the team, due to time constraints. The team consisted of eight members. Seven questionnaires were e-mailed to the team and six of them were completed and returned. The questionnaire had 53 questions that were divided into four sections. Section A contained structured questions that elicited specific information about the participants, such as the industry they work in; the company they work for; their job titles; age and nationality. Sections B to C contained the main and sub research questions that elicited information about Knowbie; their beliefs about Knowbie; how often they use specific ICT tools; and their use of Knowbie and Section D contained open ended questions about Knowbie. 4.2.3 Observation The researcher was an employee of Company X and one of the software development team members. This gave her the opportunity to observe and interact with the tool mentioned above; and to study the information shared on it.

4.3 Data analysis The data was analysed on a Spreadsheet. The responses from the questionnaires were grouped according to the following categories: beliefs, ICT tools frequency of use and Knowbie’s effectiveness.

5. Findings After conducting the research using the data generation methods above, the following findings emerged:

5.1 Finding(s) of the main research question 5.1.1 How effective is the use of Knowbie, by the software development team, in promoting innovation in the way that knowledge is managed? One of the results of the study was that the team does not know if the use of Knowbie is effective in promoting innovation in the way that knowledge is managed in the company

5.2 Findings of the two sub research questions 5.2.1 What are the software development team’s beliefs regarding the following: ƒ

Knowbie

ƒ

the benefits and disadvantages of being a Knowbie member

(a) Knowbie Furthermore, when queried on their beliefs about Knowbie, the team responded as follows: they do not believe that Knowbie is a useful tool that could help them with their job; it does not increase their productivity; the guidelines for the tool are clear and understandable; the tool is easy to use; work or learning on the job is made interesting when using the tool; they enjoy working with the tool; their colleagues are helpful in supporting them to use the tool; and the tool gives them access to experts and information within the company. (b) Benefits and disadvantages of being a Knowbie member When the team was asked what they believe the benefits and disadvantages are of being Knowbie members, it was discovered that some team members do not know what the advantages and disadvantages are since they

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Kay Bandlow and Sheryl Buckley do not use the tool. Others cited not knowing the group members of the other companies and not having an interest in using the tool as disadvantages. 5.2.2 How frequently is Knowbie used in the organisation by the indicated software development team? Compared to other ICT tools like Facebook and Outlook, to name but a few, a further finding was that the team never uses Knowbie.

5.3 Linking the findings to the literature on CoPs and ICT tools For knowledge management to be successful through using a CoP, such as the software development team, the literature review section above states that a CoP team must comprise of motivated members who are willing to participate in the community they belong to, since this will ensure a high level of commitment and knowledge sharing (Michaelides et al., 2010: 924). In addition, a further requirement to ensure the success of CoPs is the need for the regular monitoring of problems and changing for the growing needs of CoP members; thus, making the moderator role in a CoP a must (Michaelides et al., 2010: 925). A final requirement is member commitment (Daele et al., 2007: 4). Motivation, having a monitoring agent; and the commitment of members, are found to be lacking in the software development team. Furthermore, to effectively manage and enable the sharing of knowledge through ICT tools such as Knowbie, the literature emphasises usefulness, ease of use and accessibility to experts and information in the organisation as key success factors (Soo, 2006: 202). It was found that the team does not believe that Knowbie possesses these factors.

6. Conclusion We live in a globalised world where knowledge is obtainable via the internet at the press of a button. Organisations have come to realise that is it not enough to merely compete on the foundation of their financial strength and that knowledge is the new competitive advantage and differentiator. Companies that effectively manage and share their knowledge are more innovate, productive and perform better. The purpose of this study was to investigate how effective the use of ICT tools by Communities of Practice (CoP) is in promoting innovation in knowledge management by looking at a specific ICT tool, Knowbie, and a specific CoP, the software development team of a mining company. To achieve this goal the study proposed three research questions. One of the findings to these questions was that the team does not know if the use of Knowbie is effective in promoting innovation in the way that knowledge is managed in the company. Furthermore, compared to other ICT tools, like Facebook and Outlook it was also found that the team does not use Knowbie. Since the findings state that the team does not know if the use of Knowbie is effective in promoting innovation in the way that knowledge is managed in the company and since their perceptions of the tool are mainly negative coupled with the fact that they do not use it, this study concluded that the lack of use of this specific ICT tool by the specific CoP in question, does not enable one to determine if its use is effective in promoting innovation in the way that knowledge is managed in Company X.

References Daele, A., Deschryver, N., Gorga, D., and Kunzel, M. (2007) Managing knowledge within communities of practice: analysing needs and developing services. eLearning Papers, no.5. ISSN 1887-1542. Garcia, J.M.R. (2001) Scientia Potestas est. Knowledge is Power: Francis Bacon to Michel Foucault. Neohelicon, 28(2001): 109-121. Michaelides, R., Tickle, M., and Morton, S.C. (2010) Online communities of practice for innovation and knowledge transfer: a case study in the U.K. Proceedings of the 2010 IEEE ICMIT. Oates, B.J. (2006) Researching Information Systems and Computing. London: Sage Publications Ltd. Omotayo, F.O. (2015) Knowledge Management as an important tool in Organisational Management: A Review of Literature. Library Philosophy and Practice (e-journal). Paper 1238. Rashid, A., Wang, W.Y.C, and Hashim, K.G. (2011) Social networks and its impact on knowledge management. 2011 IEEE International Conference on Control System, Computing and Engineering. Soo, K. (2006) Why workers share or do not share knowledge: a case study. Doctor of Philosophy. Indiana University. Ann Arbor.

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Invisible Pedagogy: Developing Learners’ Self-Responsibility in Digital Environments Through Problem-Based Learning Wendy Barber1 and Sherry King2 1Faculty of Education, University of Ontario Institute of Technology, Oshawa, Ontario, Canada 2Faculty of Pre-Health Studies., Confederation College, Thunder Bay, Ontario, Canada [email protected] [email protected] Abstract: Universities and institutions of higher education are facing economic pressures to sustain large classes, while simultaneously maintaining the quality of the online learning experience for students. Digital learning environments require significant pedagogical shifts on the part of the teacher and the learner. This paper is a qualitative examination of the nature of teaching and learning in the digital age, and the significant changes facing both teachers and learners in the 21C. The authors describe key features of quality distance learning that were exhibited during 12 weeks of a synchronous undergraduate course held in Adobe Connect. The central research questions are 1. How can problem-based learning pedagogy enable instructors to form smaller cohesive groups of students that take greater responsibility for their own learning? 2. What strategies can be used to develop communities of practice and inquiry in these smaller student groupings? and 3. How can a network of students in a large virtual class create the level of social capital that is required to build and maintain the relationships that are a necessary condition for a high quality learning experience? The research is grounded in literature through the work of Cousins and Bissar (2012), Kaufman (2013), Badge, Saunders and Cann (2012), Flavin (2012) and McNeill, Gosper and Xu (2012). These authors examine how teachers and learners adapt to the digital age. Within the context of this online environment, the traditional roles of teacher and learner became reciprocal and symbiotic. The pace of information flow and knowledge mobilization in 21C learning environments mean that instructors no longer act as top down experts. Rather, they become facilitators, guides, collaborators and learners themselves, thus making traditional pedagogy virtually invisible. The authors further chronicle how a community of practice and inquiry was created and sustained while significant social capital was developed. The paper describes how problem-based learning was used to create small independent student groupings and articulates the strategies used to develop and sustain this community of practice. The authors conclude by arguing that increased levels of student engagement and the development of social capital in the learning community result in significant changes to quality online pedagogy. Keywords: online pedagogy, problem-based learning

1. Introduction: It is clear that learners in the 21C exist in a world that continually reinvents itself. Thus, a key skill for online learners becomes “learning how to learn in a digital world”. The development of new knowledge outpaces our ability to keep up with content, and one need only acknowledge that our first action when investigating a new phenomenon or problem is “to google it”. We may seek out further assistance or expertise from others, but our initial reaction is to use the technology to find the answers for ourselves. Not only have we invented a new verb to describe this self-directed learning process, but this, in itself, demonstrates that 21C learners are in the driver’s seat. Graduating to a new world that is evolving constantly, these learners require different and broader competencies than what have been considered learning outcomes in traditional teacher-centred pedagogy. Several authors have re-defined the essential skills required of the 21C learner. Many of these authors concur that these skills include the development of creativity, self-motivation, innovation, problem-solving and collaboration skills (McNeill, Gosper & Xu, 2012; Voogt, Erstad, Dede & Mishra, 2013; Kaufman, 2013). These are also skills that are developed by students in a problem-based learning context. According to Savin-Baden (2007) there are significant characteristics of PBL that include: Complex real world situations that have no one ‘right’ answer are the organizing focus for learning. Students work in teams to confront the problem, to identify learning gaps, and to develop viable solutions. Students gain new information through self-directed learning. Staff act as facilitators Problems lead to the development of clinical problem-solving capabilities. (Savin-Badin, 2007)

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Wendy Barber and Sherry King In a PBL learning environment, the focus is on student-centred and collaborative learning, moving beyond cooperative learning to an environment where critical feedback and challenge between peers and instructor are essential. Shifts in teacher-learner roles occur, students take ownership of the learning, become involved in the assessment process, and define their own course of learning. Thus, there is a perception that the pedagogy becomes virtually invisible. This approach to teaching and learning is one avenue to better prepare students for the situations that await them beyond the walls of post-secondary education. Although universities have not traditionally been in the position of preparing students for specific work roles in the economy, financial and other pressures are continually pressing for institutions of higher education to prepare students for the “real world of work”. Due to the fact that the world is in a continual state of flux, it becomes almost impossible for universities to predict which content is key for students to learn. This is especially so due to the fact that over the course of an undergraduate’s four years in school the jobs for which they apply at the end may not yet exist. Thus, it becomes incumbent upon university instructors to shift their pedagogy, put students at the centre of the learning experience and provide opportunities, situations and experiences to develop the kinds of broad competencies that are required for the 21C economy. Although it has not been the historical purview of universities to provide society with workers, the 21C economic situation of colleges and universities requires them to market themselves as institutions from which students will graduate prepared and ready to enter the workforce. In response to this, an interesting set of parameters has been proposed by the Conference Board of Canada Employability Skills 2000+ (Conference Board of Canada, 2000). These 21C skills include (a) Fundamental Skills (the ability to communicate, manage information, think and solve problems, and use numbers), (b) Teamwork Skills (the ability to work with others and participate in projects and tasks), and (c) Personal Management Skills (the ability to learn continuously, demonstrate positive attitudes and behaviors, be responsible, be adaptable and work safely). These align clearly with some of the elements that surround a problem-based learning pedagogy, one which essentially puts students at the centre of the process and renders the instructor perceptually “invisible”.

1.1 Methodology This research was conducted using qualitative case study methodology (Merriam (1998). Participants in the study were two groups of 30 students taking a synchronous undergraduate class in a fully online environment. The instructor was an Assistant Professor in the Faculty of Education. Classes met once per week using video conferencing through Adobe Connect. Students completed a Likert style questionnaire pre and post course to indicate their level of comfort, engagement and competence in an online community, as well as their selfreported level of their ability to be self-directed learners and take responsibility for their own learning. Further to this, a focus group for each of the two groups was convened in Adobe connect after the course had completed to discuss each of the three research questions. 1. How did a PBL structure help/not help students to take greater responsibility for their learning as a member of a small group? 2. What strategies did students or the instructor use to develop communities of practice and inquiry? And 3. How did the network of students create or develop/not develop greater social capital in the online class. The researchers analyzed and coded the data to identify key themes that emerged through the class recordings, focus groups, and questionnaire results.

2. Data collection Ethical review was passed (Research Ethics Board # 14-029) and informed consent of participants was obtained. Data were collected via recordings of classes in Adobe connect, including both formal and informal chat rooms for review. Recordings of classes were kept on a secure server located at the university. Students were asked to maintain weekly comments in Blackboard chat rooms and use this as a journal format to record their observations about their online community. Anecdotal information from focus groups was recorded and kept on a secure server. Observations of external professional learning communities created by the students in Linked In and Facebook were obtained. Table 1: Elements of invisible pedagogy: the role of teacher and student in PBL vs traditional university lecture environments Pedagogy in PBL Student-centred Real world situations

Pedagogy in Traditional Lecture Teacher-centred Theoretical situations

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Wendy Barber and Sherry King Pedagogy in PBL Collaborative work Co-constructed solutions Multiple outcomes

Pedagogy in Traditional Lecture Individual work Individual solutions One correct outcome

Assessment in PBL Uses real world tasks often assessed in groups Collaborative assessment Students involved in assessment criteria Many possible solutions are correct Assessment embedded formatively throughout the learning process

Assessment in Traditional Lecture Theoretical concepts individually tested Individual assessment Teacher develops assessment criteria One or few possible solutions are correct Assessment is summative at the end of a course or unit

Community in PBL Community-based learning Inquiry-based learning allows students to drive learning outcomes Students take ownership of learning by selecting problems Learning is dynamic and ongoing Community extends beyond course parameters through digital means Social Capital is at a high level Student Engagement at a high level and depends on peer interaction and teacher as facilitator

Community in Traditional Lecture Individual learning Teacher sets learning outcomes Teacher retains power by setting the problems to be solved Learning is contained within course outcomes Any group work is contained within confines of the course Social Capital is not connected to learning Student Engagement depends on teacher as leader

3. Key Themes Problem Based Pedagogy: Student responses to the PBL environment were overwhelmingly positive, however two general trends occurred based on student demographics. For those undergraduates who had recently left a secondary school environment that was based on traditional pedagogy, they found the problem based strategies frustrating. Having not been empowered to be self-directed or to be involved in guiding their own learning, many wanted to be told what to do, how to go about it and what the results should look like. By contrast, mature students (who were working full time and pursuing their undergraduate degree online part time) found the constructivist and social elements of PBL very engaging. As adult learners, they responded very well to the independence, autonomy, and self-direction of the assignments. In addition, having had work experience, this may have prepared them better to work as part of a collaborative team, to contribute their own strengths, accept others’ input, and demonstrate a willingness to work as a team. Mature students tended to demonstrate more of the Conference Board of Canada (2000) skills already in place, and this may have been why they embraced PBL readily, as it mirrored what they experienced in their own professional world of work. Role of the Teacher: Invisible pedagogy does not mean the teacher is absent, nor does it imply that the pedagogy is simple. In fact, done well, it can be more challenging, more artful, more creative and widely diverse. The instructor must step out of his/her traditional role and become the disruptor, creating situations and experiences that both challenge, inspire, support students while providing critical feedback throughout the process. This is what Flavin (2012) refers to as “disruptive technologies” (p. 103). He states that “when digital technologies are brought into the classroom setting, the lecturer may have to relinquish some of their authority, thus impacting on the ‘rules’ and ‘division of labour’ nodes in order to enable enhanced learning” (Flavin, 2012, p. 104). Cochrane (2012) identifies this unique sharing of the digital learning environment as one of the critical success factors in mobile learning. He states that features of a successful virtual learning environment include Pedagogical integration of technology into the course and assessment, lecturer modelling of the pedagogical use of the tools, creating a supportive learning community, and creating sustained interaction that explicitly scaffolds the development of ontological shifts that is the reconceptualization of what it means to teach and learn within social constructivist paradigms, both for the lecturers and the students. (Cochrane, 2012, p. 125) Further to this, “invisible teachers”, in fact, must be willing to step out of the way; they must demonstrate an ongoing aptitude to embrace new technologies as they develop, in order to help students, not from a position at centre stage, but quietly from the background, empowering students to choose and develop the 21C skills

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Wendy Barber and Sherry King they need. Teachers themselves “need to acquire 21st century competencies as well as become competent in supporting 21st century learning” (Voogt, Erstad, Dede & Mishra, 2013, p.408). Online Community: Lin and Lee (2006) state that “the online community can be defined as a social relationship aggregation, facilitated by internet-based technology, in which users communicate and build personal relationships”(p. 480). Wenger and Synder (2000) believe that “online communities facilitate virtual collaboration among community members with the potential of transforming the activities of off-line into an online context” (in Lin & Lee, 2000, p. 480). While this social element of online learning remains a predominant challenge to educators, effective online pedagogy relies on how skilled the instructor is at developing and sustaining a sense of belonging to the digital community. By combining problem-based learning and a strong sense of community, educators can become adept at helping students become independent autonomous learners who are capable of solving the complex problems facing 21C learners. Instead of taking the power role normally assumed by the teacher, instructors become equal members of the community, bringing unique strengths and learning needs themselves. In this way, instructors blend into the community, become one with the background. By appearing to be on a level field with students, the teacher’s role in the community disappears, and reappears as something completely different – as facilitator, lurker, guide and co-learner. Development of Social Capital: Kearney et al (2012) attest that learning “is a situated social endeavor” (p. 1). Students in these classes invested a great deal of time in developing social networks within the course, many indicated that they also created a Linked In or Facebook group to supplement their contact with peers, following Twitter feeds on their mobile devices outside of scheduled class time. Kearney et al (2012) reiterate that “this socio-cultural view of learning takes into consideration both technical characteristics as well as social and personal learning processes” (p. 2). LittleJohn, Beetham and McGill (2012) agree that the social elements of learning are being embraced by students, and that “learners are responding to the new technical and social opportunities with little help from the formal education system” (p. 551). Student responses in the anecdotal focus groups indicated that they felt safe to take risks, ask questions and go to peers for support and present seminars with confidence. Many attributed this to the PBL climate of the course, and the expectation that a community of mutual respect had been developed. Within this relationship-based community, it became the norm to challenge, ask critical questions, provide feedback and respond to it constructively. As a result, the level of engagement, motivation and the quality of products generated by students increased. Development of 21C Skills: As McNeill, Gosper and Xu (2012) state, “universities increasingly acknowledge the value of skills such as problem solving, critical thinking and creativity, yet the curriculum needs to be designed to support and scaffold development of these skills. 92012, p. 283). They go on to state that “academics who were likely to introduce the development of student creativity in their curriculum found that confidence emerged as a key characteristic” (2012, p. 284) Students in this PBL class demonstrated skills in collaboration, the ability to come to a variety of workable and diverse solutions, and they also acknowledged that each member of the community, while possessing different skills, had an important and valuable place in the group. These are critical skills for anyone working in the knowledge economy. LittleJohn, Beetham and McGill (2012) indicate that the nature of the workplace has changed, and digital forms of information are changing the meaning of what it means to work. They state that these changes are being exacerbated by three factors First, workplaces are being transformed such that production and practice are increasingly knowledge driven. Second, work problems are becoming more complex and third, people are regularly and repeatedly transitioning into new roles and careers, necessitating life-long learning. (2012, p.547) Students in this study were often mature adults who had changed careers several times, and during the focus groups it was mentioned several times that the PBL approach to learning enabled them to contextualize their learning to their workplace, as well as develop the confidence and competence to use digital tools to solve workrelated problems. Student Self-Responsibility: During the course of the twelve weeks students built a considerable amount of what they determined to call “social capital”. This networking and ability to create and sustain relationships within the learning community was a key feature in helping students take more responsibility for their own learning. An interesting feature that emerged was that students also felt an element of responsibility to the community, to come to class prepared, to engage in discussions, to prepare thought-provoking seminars and case study presentations. Self-responsibility did not mean “going it alone”, and as the course progressed

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Wendy Barber and Sherry King students indicated that because of the community they had built they felt safer to ask questions, take risks and help one another. What evolved was not only an improvement in student self-responsibility, but a redefinition of it. Being self-directed also meant a reliance on others for critical feedback, discussion and challenge, as well as being prepared to provide reciprocal feedback for peers to enable their learning and development.

4. Discussion This paper examines three primary research questions: 1. How can problem-based learning pedagogy enable instructors to form smaller cohesive groups of students that take greater responsibility for their own learning? 2. What strategies can be used to develop communities of practice and inquiry in these smaller student groupings? and 3. How can a network of students in a large virtual class create the level of social capital that is required to build and maintain the relationships that are a necessary condition for a high quality learning experience? To answer question one, it is clear from the surveys and comments of students and the observations of the instructor that PBL pedagogy can work effectively to enable instructors to step out of the way, to empower students in smaller groups to take ownership of the learning. While the research began asking the question of how individuals can take greater self-responsibility, it became apparent that the PBL process also means individuals feel a greater responsibility to their community of inquiry. Students commented that they felt the seminars each week were improving, that each member of the group felt a certain obligation to their peers to be well prepared and deliver an engaging and thought provoking seminar or case study. Thus, it is only by allowing students more control, that the instructor can take on large classes effectively. By investing up front and modelling a PBL structure, smaller groups of students can grow into the autonomy required to develop successful pods within a large class. Responses to question two involve strategies to build online communities. In this case, the initial use of Digital Moments, a community building strategy in the first few classes means that individuals share in an Adobe connect video pod a photo or visual image that shows the community a bit about themselves, their learning backgrounds, reasons for taking the course, age and stage of career, and their personal goals and learning outcomes. In this way, the instructor can see more readily how to create diverse groups, can identify the students having greater experience with PBL, and those that may need greater support. In addition, it appears important that students connect outside of class time, using social media, Twitter, Facebook or LinkedIn. This occurred around the third week of the twelve week course. This phase appears to be important in order for students to invest more of themselves in the course, since they become more accountable to one another and thereby own the learning experience more fully. Finally, how can a network of students in a large virtual class create the level of social capital that is required to build and maintain the relationships that are a necessary condition for a high quality learning experience? Many of the students in this class were simultaneously taking classes with other instructors who were not using a full PBL pedagogical model. Often they commented that the level of social capital in this class was far superior to courses where they did not connect to others. Several students said they had taken full courses and “not even known anyone’s names”, whereas it became a norm in this class for students to know one another. It was not, in fact, necessary for all students to connect or get along with everyone, but respect for diversity was a key factor. By sharing personal backgrounds (work, family, weekly challenges) the students gravitated to those with whom they felt they had commonalities. At the same time they worked collaboratively in diverse groups, often commenting that this diversity was an important feature in helping them to think critically outside of their own sociocultural perspective and to see with one another’s “lenses”. Overall, several key themes emerged through this learning environment that ultimately wove together to create increased levels of student self-responsibility. The primary aspect included a focus on a problem-based pedagogy which clearly put students at the centre of the learning process. Second, there were significant changes in the roles of the teacher-learner, requiring the instructor to step into the background and have less of a “top down expert” presence. Third, it became critical that there was the development of an online community of learners that broadened to the larger digital world beyond the class. Using social media and mobile devices, students stayed connected beyond traditional class time. This then resulted in a significant level of social capital and networking, which increased student engagement, commitment, accountability to peers and improved the

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Wendy Barber and Sherry King quality of assignments they produced. Finally, the interdependent combination of all these themes created an environment in which students could develop 21C skills that they needed to be successful in a digital workplace.

5. Conclusion This paper has provided a qualitative analysis of one case study in problem based learning, where the pedagogy of PBL helps undergraduate students develop greater self-responsibility for the learning process. The authors have argued that a significant outcome of PBL is also the enhancement of what many have termed 21C skills. This is what Littlejohn, Beetham and McGill (2011) refer to as “the capabilities required to thrive in and beyond education, in an age when digital forms of information and communication predominate” (p. 547). Kaufman concurs that “school is not simply about tests and ‘checking boxes’ of topics and assignments. Rather, schools today should have a mission of developing students as individuals and igniting their creativity” (2013, p. 79). Voogt et al (2013) also attest that it is generally agreed upon that “collaboration, communication, digital literacy, citizenship, problem-solving, critical thinking, creativity and productivity are essential for living in and contributing to our present societies” (p. 404). Universities and other institutions of higher education have a moral and social obligation to prepare big thinkers for the needs of the 21C. Despite the fact that these colleges and universities are undergoing severe economic cutbacks, surely it is still incumbent upon them to provide education that is relevant, forward thinking and that empowers students to become contributing members of society. While financial pressures may require universities to hold very large classes with one instructor, PBL can be used as a pedagogical strategy to empower students in smaller learning pods. In this way we maintain or enrich the quality of learning by placing it in the hands of the community of students. The problems of the 21C are complex, multi-dimensional and diverse, situated in different geographies, economies and cultures. People living and working in these environments must continually use digital technologies to learn, relearn and come to collaborative solutions. Problem-based pedagogy can be one aspect of higher education that can prepare students for what they will experience in this new world. It prepares them to take responsibility for their own learning as well as contribute to the learning of their colleagues, a skill that they will need as they continually change careers and roles in the workplace. As educators, we must step out of the way, facilitate PBL environments and experiences that help students to leap forward while we, as instructors, simultaneously move quietly into the background. Universities will still need professors, but maybe it’s time we begin making their pedagogy invisible.

References: Badge, J., Saunders, N. & Cann, A. (2012). Beyond marks: new tools to visualize student engagement via social networks. Research in Learning Technology, 20(16283). doi: 10.3402rlt.v2010/16283 Cochrane, T. (2012). Secrets of m-learning failures: confronting reality. Research in Learning Technology, ALT-C Conference Proceedings, http://dx.doi.org/10.3402/rlts2010.19186 Conference Board of Canada (2000) A Report on Employability Skills 2000+ http://www.conferenceboard.ca/topics/education/learning-tools/employability-skills.aspx Cousins, S. & Bissar, D. (2012). Adapting to the digital age: a narrative approach. Research in Learning Technology, 20(18976), 1-13. Flavin, M. (2012). Disruptive technologies in higher education. Research in Learning Technology, ALT-C 2012 Conference Proceedings. http://dx.doi.org/10.3402/rlt.v2010.19184 Kaufman, K. (2013). 21 Ways to 21st century skills: why students need them and ideas for practical implementation. Kappa Delta Pi Record, 49(2), 78-83. doi: 10.1080/00228958.2013.786594 Kearney. M., Schuk, S., Burden, K. & Aubusson, P. (2012). Viewing mobile learning from a pedagogical perspective. Research in Learning Technology, 20(14406). doi: 10.3402/rlt.v2010.14406 Lin, H. & Lee, G. (2006). Determinants of success for online communities: an empirical study. Behavior and Information Technology, 25(6), 479-488. Littlejohn, A., Beetham, H. & McGill, L. (2012). Learning at the digital frontier: a review of digital literacies in theory and practice. Journal of Computer Assisted Learning, 28, 547-556. doi: 10.1111/j.1365-2729.2011.00474.x McNeill, M., Gosper, M. & Xu, J. (2012). Assessment choices to target higher order learning outcomes: the power of academic empowerment. Research and Learning Technology, 20(17595) doi: 10.3402/rlt.v2010.17595 Merriam, S. (1998). Qualitative Research and Case Study Applications in Education. San Francisco, CA: Jossey-Bass. Savin-Baden, Maggi. "Challenging models and perspectives of problem-based learning." Management of change: Implementation of problem-based and project-based learning in engineering (2007): 9-30. Voogt, J., Erstad, O., Dede, C. & Mishra, P. (2013). Challenges to learning and schooling in the digital networked world of the 21st century. Journal of Computer Assisted Learning, 29, 403-413. doi: 10.1111/jcal.12029

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Engagement in Online Asynchronous Discussions: Roles of Students' Interests and Preferences Kevin Chan, Simon Lai, Hildie Leung and Kelvin Wan Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong [email protected] [email protected] [email protected] [email protected] Abstract: Asynchronous discussion is considered an effective and pervasive tool for engaging students to learn in an online or blended environment. Quality of asynchronous discussions in online learning platform has been suggested to associate with various design and learners characteristics, such as forum design in terms of embeddedness with background knowledge, social presence in group, type of discussion topics relating to higher-order thinking, cognitive strategies for eliciting discussion (e.g. debate, role-play), discussion group size, and intrinsic motivation to engage in asynchronous discussions. Design and facilitation in asynchronous discussions constitute two major determinants in the success of interaction among students in a discussion forum setting. Regarding issues pertaining to the design of asynchronous discussions, relatedness to real-life problems, rubrics and guidelines for discussion participation, and students' choice, are key components for conceptualizing effective construction of knowledge through discussion. While empirical evidence on effectiveness of asynchronous discussion in online learning suggested that choice and intrinsic motivation are critical to students' interaction and performance in discussion, the extent to which students' choices would moderate their effort and performance in participating discussions has received little attention and empirical investigation. The current study aims to explore role of students' interest and choice in asynchronous discussion in predicting their engagement and performance in the discussion process. With students’ choice operationalized as their self-indicated preference for discussion topic, we examine the following research hypotheses: 1) Students' self-indicated preference for a specific topic among an array of topics available for asynchronous discussions would be associated with quantitative performance in the discussion process, in terms of the frequency of posts; and 2) Students' self-indicated preference for a specific topic among an array of topics available for asynchronous discussions would be associated with qualitative performance in the discussion process, in terms of the higher-order thinking artefacts exhibited in their posts. These research questions were tested with an observational design study with 707 students in a large undergraduate introductory psychology course in Hong Kong. Participating students engaged in a 3-week asynchronous discussion towards summative assessment via a centralized learning management system (LMS). Discussion behaviors were extracted from the LMS, while learning outcomes attainment was coded according to the structure of observed learning outcomes (SOLO) taxonomy. Students’ volition to participate, operationalized as their indicated preference for a specific topic out of an array of 8 available topics on the subject matter, correlated with their effort and performances in the discussion in terms of post frequencies, post length, and learning outcomes with reference to the SOLO taxonomy. Findings suggested that students’ indicated preferences to commit to their discussion topics influenced their participation in the discussion in terms of both posting behaviors and level of learning outcomes. Impact on current findings for understanding students’ autonomy and commitment in asynchronous discussion should be contextualized in a constructivist-learning environment. Keywords: asynchronous discussions, blended learning, students’ engagement, learning management system (LMS), constructivism

1. Background Effectiveness of an discussion forum in blended learning setting for asynchronous discussions is influenced numerous factors in its design prior to commencement of discussion and facilitation during discussion. Design and facilitation in asynchronous discussions constitute two major determinants in the success of interaction among students in a discussion forum setting. Regarding issues pertaining to the design of asynchronous discussions, Rovai (2007) reviewed and suggested that relatedness to real-life problems, rubrics and guidelines for discussion participation, and students' choice, are key components for conceptualizing effective construction of knowledge through discussion. In addition, forum design and embeddedness with background knowledge required for discussion moderate the quantity and quality of interaction in asynchronous discussions (Gao and Putnam, 2009). An interesting and intellectually stimulating question is necessary for initiating a vibrant discussion. Type of discussion topics for eliciting higher-order thinking is critical to participation in asynchronous discussions (Kim and Bateman, 2010). Debate and role-play strategies have been reported to be highly associated with

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Kevin Chan et al. exploration and integration phases in asynchronous discussions (Darabi et al., 2011). A moderate group size for students to feel comfortable for discussion is also crucial in a forum for effective learning. Large group size has been suggested to deter students from engaging in high-level interaction (Kim, 2013). Even a well-designed forum could yield different learning experiences among students with individual differences towards the common learning task. Students tend to exhibit more engagement in asynchronous discussions when they are motivated. In particular, intrinsic motivation to asynchronous discussion has been suggested as a critical factor to interactions in discussion participation (Martin Timothy and Jason, 2016). Motivated students tend to establish social presence in asynchronous discussions, such as self projection and group identification, that moderates the quality and engagement in discussions within groups (Caspi and Blau, 2008). Willingness to join in collaborative learning is critical to initiate interactions in asynchronous discussions (Bromme et al., 2005). However, students’ willingness to participate and their efficacy about conversing on a particular discussion topic, in terms of the extent they exhibited engagement and effort on the discussion, has been suggested to be contingent upon their own perceived capabilities (Xie, 2013). In a structured asynchronous discussion environment (Salter and Conneely, 2015) in which students engage in a pre-defined debate question, students who “owns” the argument, in terms of their familiarity and interest on the discussion topic, could be a catalyst for their willingness to join and make effort in their discussions. With a design of pre-defined and finite number of topics for asynchronous discussion, leveraging students with their choices to pick from the finite set of topics could facilitate students’ perceived engagement with the topic and thus enhance their motivation in the learning process. The current study aims to explore the role of students' interest and choice in asynchronous discussion in predicting their engagement and performance in the discussion process. With students’ choice operationalized as their self-indicated preference for discussion topic, we examine the following research hypotheses: 1) Students' self-indicated preference for a specific topic among an array of topics available for asynchronous discussions would be associated with quantitative performance in the discussion process, in terms of the frequency of posts; and 2) Students' self-indicated preference for a specific topic among an array of topics available for asynchronous discussions would be associated with qualitative performance in the discussion process, in terms of the higher-order thinking artefacts exhibited in their posts.

2. Methods 2.1 Participants From a 4-year undergraduate university in Hong Kong, a total of 707 students from three sessions of a large introductory level psychology class were included in this study. The majority (90%) of this enrolment were 1st year students, followed 2nd year students (6.5%), 3rd year students (2.4%), and 4th year students (1.1%).

2.2 The asynchronous discussion task Towards the end of a 13-week curriculum, students engaged in a mandatory 3-week asynchronous discussion towards 20% of their overall summative assessment. The asynchronous discussions were hosted on Blackboard 9.1, a centralized learning management system (LMS) that is accessible exclusively to the participating students & their host institution. On this discussion assignment, students were required to deliberate on one out of 8 distinct topics across different sub-disciplines in psychology (e.g. cognitive psychology, neuropsychology, personality) towards application to real-life problems. A sample discussion topic would be “To what extent is preference towards Anime / Comic / Game (ACG) being influenced by one's personality?”. During the 3-week discussion forum assignment period, students were advised to make an effort to post at least 4 replies to the original questions or replies by other students pertinent to the topic on hand. Prior to the commencement of discussion, all participating students were prescribed with a guideline documenting appropriate etiquette in conducting the forum discussion and rubric on discussion assessment based on the Structured Observed Learning Outcomes taxonomy (SOLO) (Biggs and Collis, 1982, Kember et al., 2004). One week prior to the commencement of the discussion assignment, students in all three sessions were invited to indicate their self preference to their own discussion topics by indicating their preferred topics out of the prescribed topics array in a survey on the LMS. Based on their indicated preferences, students indicating their

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Kevin Chan et al. interest in any of the eight topics formed groups of eight members to commence their discussions. Those who did not indicate their preferences were randomly assigned to one of the prescribed discussion topics and formed similar groups (n=8) for discussions. The topic selection exercise did not contribute to any marks on students’ summative assessment in this subject.

2.3 Students’ performance and discussion behaviors in asynchronous discussions Each student was assessed with an individual scores for their participation in forum discussion. Adopted from work by Chan (Chan et al., 2002) on applying SOLO taxonomy in local higher education context, a 5-level taxonomy of learning outcome was adopted for students’ assessment in this study. Students’ depth and complexity in their discussions were classified into five ascending levels: prestructural, unistructural, multistructural, relational, and extended abstract (Biggs and Collis, 1982). Attainment in each level was separated by a 4-point increment, adding up to a maximum of 20 points. Actual scores were normalized to a 100-point scale for convenient interpretation. Statuses of students having indicated their preferred discussion topics or not were extracted from the LMS and coded into a dichotomous variable (i.e. Preferred topic indicated Vs No Preferred Topic Indicated). Number of forum posts, word count on all posts, and timestamp of posts were extracted from the LMS records of the participating sessions. Discrete counts of forum posts and number of words in posts were imported directly into the analysis as scale variables. Hours before deadline – the differences between time of 1 st post and deadlines in hours, was calculated with timestamps of students’ 1st post in the forum (e.g. October 28, 2015 22:00), the extent to which they first initiated and exhibited their effort on the discussion, and their respective deadlines for completion in each of the three sessions (e.g. November 19, 2015 23:59). Associations between research variables were analyzed with a Kendall-tau nonparametric correlation of forum behaviors and learning outcome variables. Forum behavior variables included topic self-preferences, number of forum posts, word length of forum posts, and time of 1 st post in terms of hours ahead of the deadline. Learning outcome variables included SOLO-based students’ discussion marks out of 100, as well as overall assessment of students in the subject out of a maximum marks of 100. All statistical analyses were conducted using the SPSS Version 22 software (IBM Statistics, 2014).

3. Results The majority of participating students (530 out of 707, 75%) indicated their preferences on discussion topics. On average they contributed 4.37 posts in their discussion with 958 words in their posts. The mean hours before deadline at which students started their 1st post was 158 hours, equivalent to 6 to 7 days ahead of the deadline for graded discussions. Regarding students’ performances, the average and normalized SOLO-based forum mark was 70.8 while the average overall assessment mark was 69.2. Table 1 presents descriptive of the forum behaviors and learning outcomes variables. Table 1: Descriptive of the forum behaviors and learning outcomes variables Variable

n

Mean (S.D.)

Self-indicated preference on topic in Forum Discussion

707

0.75, (0.43)

Number of Posts in Forum Discussion

707

4.37, (1.53)

Word Count Total in Forum Discussion

692

957.49, (523.58)

Hours before deadline

692

158.75, (128.64)

Forum Score Normalized to 100

707

70.8, (16.03)

Overall Assessment Score Normalized to 100

707

69.21, (10.36)

Kendall-tau correlations between the study variables provided evidence in support of both hypotheses 1 & 2 about the effect of students’ self-indicated preferences on learning behaviors and learning outcomes. Students’ self-indicated preference on discussion topics was positively correlated with all forum behaviors, including number of posts (r = .155), word count total (r = .096), and hours before deadline (r = .162). Indication of preference was also correlated with both learning outcomes variables in normalized discussion forum scores (r = .163) and overall assessment scores (r = .186). All correlation coefficients reported reached statistical significance with an alpha level of p < 0.01.

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Kevin Chan et al. Table 2: Kendall’s tau correlation coefficients of study variables Variable

Self-indicated preference on topic in Forum Discussion

Self-indicated preference on topic in Forum Discussion

Number of Posts in Forum Discussion

Word Count Total in Forum Discussion

Hours before deadline

Forum Score Normalized to 100

Overall Assessment Score Normalized to 100

.155**

.096**

.162**

.163**

.186**

.486**

.192**

.312**

.288**

.132**

.219**

.270**

.124**

.221**

Number of Posts in Forum Discussion Word Count Total in Forum Discussion Hours before deadline Forum Score Normalized to 100

.375**

Overall Assessment Score Normalized to 100 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).

4. Discussion The role of self-indicated preferences on learning task resonated with various psychological mechanisms underlying students' behaviors in an asynchronous discussion context, namely their motivation, self-regulation, and goal orientation, as proposed in the seminal work by Corno & Kanfer on the role of volition on learning (Corno and Kanfer, 1993). Findings suggested that students’ indicated preferences to commit to their discussion topics influenced their participation in the discussion in terms of both posting behaviors and level of learning outcomes. Given students were required to contribute 4 posts in the structured forum only, students with selfindicated preference exhibited higher engagement in terms of the additional posts on the topic and a significantly earlier head start on discussing their selected topics. The observed elevation in behavioral engagement in online learning task possibly correlated with positive emotions (Xu et al., 2013) at the beginning of the forum discussion, which was sustained throughout the learning process. In terms of students’ prospect to engage in online discussions, the observed increased engagement in the selfindicated preference group could be a subsequent manifestation of higher performance expectancy in terms of the utility of learning about a psychological concept and its application beyond fulfillment of curricular requirement as students were more likely to start a discussion out of their genuine interest in the topic. As outlined in Unified Theory of Acceptance and Use of Technology (UTAUT) (Dwivedi et al., 2011, Venkatesh et al., 2003), performance expectancy about how an online learning task and environment, the degree to which a tool brings benefits to its users, significantly influences students’ online learning (Xie and Ke, 2011, Chan et al., 2015). Aligning with contemporary conceptualization of motivation, self-indicated preference on discussion topic could be interpreted as a proxy of intrinsic motivation (Ryan and Deci, 2000) where students participated in the topic selection process with no apparent gain of extrinsic reward but responded to their need for autonomy in the learning process. The effect of topic preference illustrated in the present study corroborated with two key aspects of constructivism in blended learning (Fosnot and Perry, 2005, Al-Huneidi and Schreurs, 2013) in personalization and responsibility. By selecting an interested topic in asynchronous discussion, these students have carved themselves with a personalized learning environment in which they discuss, research, and argue on a topic of their genuine interest. With such predisposed intrinsic motivation, they are more likely to assume more responsibilities in engaging in this learning task, as reflected in the early head start when compared with their counterparts who did not pick their own topics.

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5. Conclusion The present study offers empirical evidence to the role of autonomy through asking students to select their topic of interest for asynchronous discussion in a blended learning context. Results supported the hypotheses that students with self-indicated preferences were more likely to exhibit higher level of engagement in the learning task, as well as better learning outcomes. Findings from this study calls for further research on delineating the role of students’ autonomy on various motivational constructs (Xie and Ke, 2011, Martin Timothy and Jason, 2016) and impact on blended learning designs (Rovai, 2007, Kim and Bateman, 2010, Gao and Putnam, 2009).

References Al-Huneidi, A. & Schreurs, J. (2013). Constructivism Based Blended Learning in Higher Education. In: Lytras, M., Ruan, D., Tennyson, R., Ordonez De Pablos, P., García Peñalvo, F. & Rusu, L. (eds.) Information Systems, E-learning, and Knowledge Management Research. Springer Berlin Heidelberg. Biggs, J. B. & Collis, K. F. (1982). Evaluating the quality of learning: The SOLO taxonomy (Structure of the Observed Learning Outcome), New York, Academic Press. Bromme, R., Hesse, F. & Spada, H. (2005). Barriers, Biases and Opportunities of Communication and Cooperation with Computers: Introduction and Overview. In: Bromme, R., Hesse, F. & Spada, H. (eds.) Barriers and Biases in ComputerMediated Knowledge Communication. Springer US. Caspi, A. & Blau, I. (2008). "Social presence in online discussion groups: testing three conceptions and their relations to perceived learning". Social Psychology of Education, 11, pp.323-346. Chan, C. C., Tsui, M. S., Chan, M. Y. C. & Hong, J. H. (2002). "Applying the Structure of the Observed Learning Outcomes (SOLO) Taxonomy on Student's Learning Outcomes: An empirical study". Assessment & Evaluation in Higher Education, 27, pp.511-528. Chan, K., Cheung, G., Brown, I. & Luk, G. W.-T. (2015). "Synthesizing technology adoption and learners’ approaches towards active learning in higher education". Electronic Journal of e-Learning, 13, pp.431-440. Corno, L. & Kanfer, R. (1993). "Chapter 7: The Role of Volition in Learning and Performance". Review of Research in Education, 19, pp.301-341. Darabi, A., Arrastia, M. C., Nelson, D. W., Cornille, T. & Liang, X. (2011). "Cognitive presence in asynchronous online learning: a comparison of four discussion strategies". Journal of Computer Assisted Learning, 27, pp.216-227. Dwivedi, Y. K., Rana, N. P., Chen, H. & Williams, M. D. (2011). A Meta-analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT). Governance and Sustainability in Information Systems. Managing the Transfer and Diffusion of IT. Springer. Fosnot, C. T. & Perry, R. S. (2005). Constructivism: A psychological theory of learning. In: Fosnot, C. T. & Perry, R. S. (eds.) Constructivism: Theory, perspectives, and practice. 2nd ed. New York: Teachers College Press. Gao, F. & Putnam, R. T. (2009). "Using Research on Learning from Text to Inform Online Discussion". Journal of Educational Computing Research, 41, pp.1-37. Ibm Statistics 2014. Statistical Package for the Social Sciences (SPSS). 22 ed. Chicago, Illinois: IBM Statistics,. Kember, D., Biggs, J. & Leung, D. Y. P. (2004). "Examining the multidimensionality of approaches to learning through the development of a revised version of the Learning Process Questionnaire". British Journal of Educational Psychology, 74, pp.261-279. Kim, H. K. & Bateman, B. (2010). "Student Participation Patterns in Online Discussion: Incorporating Constructivist Discussion into Online Courses". International Journal on E-Learning, 9, pp.79-98. Kim, J. (2013). "Influence of group size on students' participation in online discussion forums". Computers & Education, 62, pp.123-129. Martin Timothy, H. & Jason, E. M. (2016). Intrinsic and Extrinsic Motivation within the Context of Modern Education. In: Railean, E., Walker, G. & Jackson, L. (eds.) Handbook of Research on Applied Learning Theory and Design in Modern Education. Hershey, PA, USA: IGI Global. Rovai, A. P. (2007). "Facilitating online discussions effectively". The Internet and Higher Education, 10, pp.77-88. Ryan, R. M. & Deci, E. L. (2000). "Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions". Contemporary Educational Psychology, 25, pp.54-67. Salter, N. P. & Conneely, M. R. (2015). "Structured and unstructured discussion forums as tools for student engagement". Computers in Human Behavior, 46, pp.18-25. Venkatesh, V., Morris, M. G., Gordon, B. D. & Davis, F. D. (2003). "User Acceptance of Information Technology: Toward a Unified View". MIS Quarterly, 27, pp.425-478. Xie, K. (2013). "What do the numbers say? The influence of motivation and peer feedback on students’ behaviour in online discussions". British Journal of Educational Technology, 44, pp.288-301. Xie, K. & Ke, F. (2011). "The role of students' motivation in peer-moderated asynchronous online discussions". British Journal of Educational Technology, 42, pp.916-930. Xu, J., Du, J. & Fan, X. (2013). "Individual and group-level factors for students' emotion management in online collaborative groupwork". The Internet and Higher Education, 19, pp.1-9.

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Exploring the Experiences of Learners in a Large Scale Distance Language Learning Program Offered in Countries Across Latin America Paula Charbonneau-Gowdy Universidad Andres Bello, Chile [email protected] Abstract: Large-scale online learning programs such as MOOCs are being increasingly seen as a beacon of hope for educational and social development, especially in evolving countries. While research points to some disturbing results of such programs, for example disturbingly high rates of attrition, emerging changes to some of these large-scale programs are offering interesting solutions. This paper reports on a case study that examined how participants engaged in a 10-week pilot distant learning program that was intended to provide access to English language training to over 500 individuals working in the context of a network of private higher education institutions in countries across Latin America. Informed by numerical data collected from an end-of-course survey and an in-depth questionnaire, a virtual ethnographic approach was adopted to explore how the distant learning courses influenced both learning and the various groups of learners. Drawing on sociocultural learning theory and using a descriptive, thematic-based coding approach to the data analysis, the study revealed salient differences in various participants’ experiences. Findings indicated that small group tutorials supported by a robust, low-cost videoconferencing technology that complimented an asynchronous shared language activity platform offered critical opportunities for community building, social networking and meaning-making. Yet the evidence also strongly suggests that exploiting these opportunities depended on a) institutional support, b) the varying degrees of cultural capital that learners brought to the distant learning program and c) the level of investment of teachers to actively promote agency and identity construction through inter-learner activity. While it appears possible for such large-scale, well-designed distant programs to meet educational challenges, we argue that addressing deeply-rooted contextual issues and the investment of teachers to promote agency and learner-learner interactivity must be of prime concern in order for a majority, rather than a minority of learners, to work towards achieving their potentials and goals. Keywords: MOOCs, videoconferencing, social learning, investment, distant language education

1. Introduction The current increase in the number of open and distant education (ODE) courses supported by a plethora of 21st century social media technologies seems to be on a trajectory that defies waning. This unprecedented growth is not surprising given the push of institutions to reduce costs and the pull of an ever-expanding international market for accessible higher education. While it may appear that the switch to this new paradigm for learning is a win-win scenario for stakeholders in education on both pull and push sides, current studies that are critically examining these large-scale ODE courses, including MOOCS, are grappling with several unanswered questions: the productive or disruptive nature of these educational innovations (de Langen &van den Bosch, 2013; Marginson, 2012); their sustainability as a business model (Kalman, 2014); their disturbingly high attrition rates (Fini, 2009, Baggaley, 2014); the need for learner support and guidance and the most effective ways to provide it (see Bates, 2014 for a summary of this discussion). More recent authors extoll the value of these innovations based on the nature of social technologies to promote lifelong learning (Dron & Anderson, 2016) and networked learning. By networked learning, we refer to individuals having the opportunity to engage with others and yet remain at the centre of their own social worlds (Rainie & Wellman; 2012), i.e. having the freedom to control place, time and direction of those worlds. Some supporters of these new forms of organized learning see them as a means to circumvent institutions and their restrictive practices (Macintosh, McGreal & Taylor, 2011). Opposing views (Bustillos, 2013) question whether the pedagogical underpinnings of this distance courseware are anything but the infamous university lecture “turned into a sitcom” (Bogost, 2013). In response to these contradictions, Siemens (2012), an originator of one of the first massive open online courses, adopts the stance that like any human constructed tool these one-to-many or many-to-many massive open systems can be viewed as opportunities for centralizing standardized instruction to unprecedented numbers or an opportunity for selfdirected learning and interaction with others. His emerging theory of connectivisim is seeking to explain the potential opportunity that new technologies provide to link with others for learning. Siemens’ (2008) connectivisim hypothesis suggests that connections are more powerful than states of knowing. Like social constructivism perspectives of learning that have prevailed over the last 20 years in many educational settings, connectivism explains learning as a social meaning-making activity rather than a knowledge-transfer

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Paula Charbonneau-Gowdy one and places the spotlight on individuals and their relationships to others, including within digital spaces. Both theories draw from Vygotsky’s (1978) social activity theories of learning that explain the essential value of others in raising our current knowledge to new levels, i.e. cognition. These theories clearly underline the critical need for studies that examine the nature of learners’ relationships and their learning experiences in emerging social media-supported ODE systems. The results of such studies cannot only add to the philosophical debates over the merits and/or shortcomings but also highlight exemplary practices to educators in view of the revolutionary direction that technology is taking in higher education. This paper serves to add to the dialogue around largescale distance learning by describing the lived experiences of a group of learners in an online, networked language-learning environment from their perspectives. It aims to uncover how the value and sustained nature of their learning experiences was influenced by the various levels of investment of their institutions, teachers and other learners in supporting their agency and interaction.

2. Literature review Early research on learners’ experiences in distance learning sites since large-scale ODE courses first appeared in 2008, received a paucity of attention in the literature. Liyanagunawardena et al. (2012) in reviewing the publications on these courseware systems in a broad range of leading ODE journals and selected academic data bases uncovered 45 publications and of these only 9 focus on learner participation and their experiences, 3 from the same lead author (Kop, 2011; Kop et al. 2011, Kop & Carroll, 2012). More recently, in a 2014 issue of Distance Education Journal devoted entirely to MOOC’s, two out of the ten articles focus on learner’s participation in such sites (Andersen & Ponti, 2014; Li et al. 2014). Findings from a series of surveys and qualitative tools employed as part of Kop et al.’s (2011) research data collection process highlight the difference between consuming behaviour and active participation in these programs. Active participators regularly produced digital artifacts and interacted with others. Results showed that these latter behaviours were conducive to positive learning outcomes, participants’ reflection, creativity and cognitive stimulation (p.82). Yet, the active engagers numbered on average only 40-60 of the 1,641 registered in the course. Their findings also clearly acknowledge that engagement by both peer participants and their facilitators in online interaction was an essential part of many for the value they took in terms of learning from the course. Andersen & Ponti (2014) investigated the opportunities and challenges in users’ co-creation of tasks in an ODE course. Through the lens of a sociocultural perspective of learning, they unveil the complexities of a participatory approach to learning in these kinds of courses and the uneven experiences that various learners perceive based on their levels of experience in the subject area and the power relations that exist between users and organizers of the programs. Online Interaction The importance and benefits of online interaction to learning outcomes in distance learning in general have been well documented. Baker (2011) has shown that active interactions online serve teaching goals, allow group construction of knowledge, hone learners’ communication skills, have important social benefits and lead to social connections. Cormier (2010), the originator of the first MOOC course distinguishes between two kinds of online interaction: networking and clustering. While networking is about reaching and striking up a relationship with someone you have never met before, clustering is about making long-term efforts to extend that relationship for mutual benefit and continued collaborative knowledge construction (Scholl, 2012). Wenger’s construct of situated practice (1998) has helped many involved in online learning to explain that when learners interact online through the process of sharing information and experiences or as Cormier (2010) advises, seeking out and commenting on others ideas, they learn from each other and develop both professionally and personally. Yet while the value of these interactions has been well accepted, the road to achieving them has been less well defined. In the field of language education in which this study took place, Norton (2015) explains that an individual learner’s openness or reluctance to engage in learning-generating activities is connected to the identities that they mediate in the learning situation and in addition to the value they place on the cultural capital to be gained in engaging in the interactive activity. Since the use of the target language in authentic interactions is an essential part of improving in the language, learners’ levels of engagement has a high stakes value to linguistic development. In other words, consuming as opposed to engaged behaviours on the part of online language learners, have serious drawbacks to learning and improvement.

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Paula Charbonneau-Gowdy Identity, Agency and Investment Norton’s (2013) poststructuralist views of learning are underpinned with the notion of investment rather than motivation. Kramsch (2013) explains Norton’s views thus: “Unlike motivation, investment carries connotations of hopes of returns and benefits; it accentuates the role of agency and identity in engaging with the task at hand, in accumulating economic and symbolic capital, in having stakes in the endeavor and in persevering in that endeavor” (p. 155). Norton’s views are based on the assumption that each of us has multiple subjective identities, in other words ways in which we see ourselves in relation to others, and those that are assigned to us by others as we interact and lead our lives. Our identities are rooted in our selfhood in our sense of being human and gendered as well as influenced by our personal and cultural histories. Social identities importantly are dynamic and subject to change both intentionally and unconsciously. Tied closely to identity is agency or the “sociocultural mediated capacity to act” (Ahearn (2001, p. 112). Agency is especially significant in our understanding of educational contexts. Wertsch, Tulviste, and Hagström (1993, p. 337) explain that agency is “frequently a property of dyads and other small groups rather than individuals”. In successful educational contexts, including online ones, individual identities are shaped and learner agency is exploited. Returning then to investment, we see that the degree to which learners invest in opportunities for learning, i.e.to change, are often dictated by the agency they assume or are offered in learning situations and in a large part to the options they have in such contexts for mediating empowered identities. These understandings we believe can help to explain the various responses in the collaborative-dynamic paradigms that participants in online programs, particularly large-scale ODE contexts, find themselves. These understandings help to frame our research, which explores the learner experiences in large scale English as a foreign language distancelearning program offered in the context of a network of private higher education institutions in Latin America. In conducting this study, we sought to respond to strong interest being expressed in the literature for studies in education across a broad range of disciplines for an understanding of the nature of learner participation in online social spaces (Andersen & Ponti, 2014; Scott, et al. 2016). The questions that helped to guide our inquiry were: What is the nature of this group of participants’ experiences in a networked online learning EFL program? What influence did these experiences have on their investment in the online opportunities and in their learning, if at all?

3. Methodology 3.1 Context Across the globe, many countries, such as those in Latin America are pinning their hopes on advancement on increased opportunities to education that technology is providing. This study examined the experiences of learners in a distance-learning program that was offered to individuals employed in higher education institutions in several countries in Latin America. Like many enterprises worldwide, the network of private educational institutions has realized that the ability of their employees to communicate in English is paramount to the recognition by both academics and potential foreign students as accredited places to work and study, as well as vital for global inter-institutional collaboration. The Network had been offering professional distance courses for several years, The 10-week pilot course was the first time the Network Office offered an English language program to all institutions in Latin America. The pilot program was set in place in late 2015 as an opportunity to a cross-section of faculty and staff in institutions in Brazil, Peru, Costa Rica, Mexico, Honduras and Chile. The twenty-four teachers for the program were geographically dispersed within and outside Latin America. Over five hundred employees originally registered for the pilot program, four hundred and eighty-six initially took part. Participants were given written placement tests and divided up into small groups of 8-10 according to language levels. Each group was assigned a tutor who then was responsible for meeting the group at least once per week in a ZOOM videoconferencing virtual classroom to facilitate dialogue and speaking practice. The tutor also oversaw the work done by members of the group between virtual meetings on a community-based platform. The materials for the platform were pre-established (Connected General English Programs) and gave opportunities for the participants to practice their various linguistic skills in activities involving speaking, writing, listening and reading in English. Active participation and inter-learner feedback was expected on this platform. Assessment included regular unit tests and multiple-choice formative mid-term and final tests. Marks for the formal tests were automatically graded and scored by SCORM-compliant LMS tools. Administrators reported a pass rate of 40% for the 353 participants who took the final test.

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3.2 Data collection Data for the study included: a survey sent out to 423 participants, a follow-up questionnaire as well as interviews from volunteer participants, field notes and document analysis. Surveys The end-of-course survey, containing 8 items, based on Level 1 assessment satisfaction indicators was developed by the administrators of the program and solicited both numbers-based and qualitative data. A month after the course ended a follow-up questionnaire containing 30 items developed by the researcher was circulated to all participants. Both the survey and questionnaire were made available on Survey Monkey in English, Spanish, and Portuguese and required approximately 15 and 35 minutes respectively to complete. Two hundred and sixteen participants responded to the survey, forty-eight individuals to the questionnaire. Case Study Interviews In order to unveil a focused view of the experiences of the online program, all participants were invited to participate in either group or individual video conferencing ZOOM-supported interviews, depending on their schedules. Twenty-four participants representative of Brazil, Peru, Chile Honduras, Costa Rica and Mexico chose to be interviewed. The interviews were conducted by the researcher and lasted from 40 minutes to an hour in length. The interviews were based on semi–structured and open-ended questions about participants’ experiences and self reports on their learning progress. All interviews were video recorded and selective parts transcribed providing approximately 8 hours of video recording data and 25 pages of written notes. Field Notes Documents and online materials relating to the program were examined closely for their pedagogical underpinnings. Meetings were held with administrators for added information regarding organization, background, feedback and drivers of the pilot.

3.3 Analysis A descriptive analysis of the survey and questionnaire data was used to uncover general information about the experiences of the participants in the online program. Qualitative analysis was performed for the interview data, which was coded using a bottom-up scheme and focusing on the most salient themes.

4. Findings and discussion Among the survey items that measured satisfaction with the online program, two in particular stood out in response to our research questions: a) the low level of satisfaction with the opportunities to interact in the SocialLearn Platform and Zoom Live video conferencing site (see Table 1) and b) the low rate of satisfaction on the part of one particular institution as compared with others in the program with regard to technology (Table 2). In Table 1, satisfaction with opportunities to interact in the SocialLearn and Zoom classroom received median scores of 68% and 72% respectively, significantly less than other features of the Program. In Table 2, survey results indicated that institution 10 gave a score of 62% for satisfaction with the technology, a clearly lower score compared to the other 13 institutions. These results were cross-referenced with the questionnaire data set where only 43% of respondents indicated they could actively interact with others in the writing-based SocialLearn Platform and 63% in the ZOOM classroom. Yet both of these settings were designed and intended to engage learners with learners. In terms of accessing these sites, 47% collectively had reservations with the ease of using the various technologies features in the Program. The questionnaire did not provide a breakdown by institution but the interview data in the next section sheds further light on this phenomenon. While the survey and questionnaire provide an overall view of the nature of the learning experiences of participants in the Program, two themes that emerged from the analysis of the interviews provided further understanding about these experiences: Interacting with peers, and Investing in sustained learning. Given the limitations of space in this report and the descriptive characteristic of qualitative research, we limit the support of our findings to the analysis of representative excerpts drawn from the interview data. Social cultural theory

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Paula Charbonneau-Gowdy and investment is used as an analytical framework when explaining the significance of these excerpts and in highlighting different aspects of the data. Table 1: Satisfaction with features of the distance program

Table 2: Institutional levels of satisfaction with technology

When unraveling the two central themes that emerged from the data sets, we report on two different kinds of experiences that surfaced for each theme. Although the experiences may appear here to be diametrically opposed and contradictory, our analysis revealed a much more blurred reality. Our aim in teasing apart these themes while providing the results of this analysis is to highlight the main influences that were present in the context of this online distance-learning program that led to the more or less encouraging findings. Interacting with Peers From a sociocultural perspective, social interaction is key to learning and the prime reason to learn online with others is the opportunity it presents for creating such possibilities. The two online sites that offered an occasion for participants to interact and engage with others were the Zoom video web conferencing room and the Social Learn Platform. Zoom classes It [the Zoom classes] is a great opportunity to talk with many people online. (Ricardo, Interview, Jan. 13) The classes were very exciting. The teacher was talking to each of us trying to give us a time for speaking and sharing experiences. (Carlos, Interview Jan. 14) Ricardo and Carlos (pseudonyms), quoted above, considered the ZOOM virtual meeting rooms as a valuable opportunity to increase the extent of their social community and to share the cultural capital, ie. their particular knowledge and experiences, that each of these individuals brought to those meetings. We understand from Carlos’ comment that the teacher played an instrumental role in providing a space for each learner to highlight their individual differences and in so doing empowered their identities, i.e. their sense of themselves as individual learners. Simon affirmed the positive environment that his teacher created in the Zoom sessions: “I felt it was not strict like going to school. It’s very friendly, very familiar so it felt like you were having conversations with someone you knew not some stranger (Interview Jan. 20). Simon’s words are significant as they underline the potential of these virtual sites to create a new pedagogy, one that Simon’s tutor obviously seized that breaks

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Paula Charbonneau-Gowdy with traditional institution-based approaches. Also, the conversations that Ricardo, Carlos and Simon report on were conducted in a language, English, that in and of itself has powerful cultural significance. These technologysupported occasions suggested an added value in that they provided an opportunity to potentially increase their economic and symbolic capital (Darvin & Norton, 2015), an important consideration for many in these Latin American countries. Indeed, other participants spoke of how vital learning English and networking was to their future advancement in their work, as Ricardo alludes to in his comment above. A further vivid example of this potential for making connections can be found in Liticia’s remark: “In this group [her small working group assigned to her in the program] we had a student who was very powerful. And in this you can raise your network in L. [name of the larger network of institutions]. While Ricardo, Carlos and others spoke with great excitement about these opportunities to interact and meet others in the Zoom classes, other participants recognized them more as sources of fear and shame. In the following excerpt, Liticia remarked on the experiences of others she saw in the Zoom sessions. She comments: In the Zoom classes, people have different levels of participation. I don’t know if it is different levels [English language levels], different personalities or when relating to these new tools..in front of the camera people are sometimes shy…when you have people who are maybe older maybe you get shy, you don’t know how to use the microphone or the camera or you are worried about how you look. (Interview, Jan 13) Liticia’s comments reveal the many ways that the learners in the virtual classroom could be marginalized by the affordances of the technology and/or their own sense of themselves, their learner identities, based on age or their language learning level. Indeed, 55% of questionnaire respondents indicated that there were issues of equality of linguistic level within their online groups. Such marginalization speaks to the unequal power structures that exist in any learning community and that can prevent learners from seizing valuable opportunities to co-construct knowledge with others. At the same time, we understand from Liticia’s comments that her own experiences with her classmates were not ideal in that all those who participated with her were not actively interacting and engaging with others. Due to this less than ideal situation in Liticia’s particular Zoom classroom, it appears that many of the participants lost the opportunity to build their economic and social power that comes with learning English (Norton, 2013). It is not surprising then, as reported above, that the results of the survey indicated that satisfaction with opportunities for interaction in the Zoom classes were not ideal for one third of the participants. The LearnSocial Platform As indicated in Table 1, the LearnSocial Platform, which was intended by program designers and administrators to provide a second site for facilitating learners to interact with others, was not well regarded according to the survey data. In analyzing the data from interviews for reasons for this lack of satisfaction, the impersonal nature of these writing-based spaces and the lack of interaction that participants encountered especially with peers were frequently cited. Martin’s comment below represents the opinions of others when speaking about this writing-based site: The platform really didn’t encourage the human part. It was a little cold when interacting with someone. I think that it is something of a habit. Since it was our first time I had problems interacting with other students… not the teacher. With the teacher, it was very easy but with other students it was difficult. (Interview, Jan. 11) Martin reasons that the limited interaction from peers is rooted in “habit”. We understand from his words, that the traditional education systems in which many participants have been exposed, have not prepared him or his classmates for the kinds of interactivity and peer learning that affordances of social-networked technologies can offer. Instead, he and many other participants reported that he used the LearnSocial Platform as a space to do individual work and to seek feedback from the tutor. The author’s own work in this area (Charbonneau-Gowdy, 2014) while discussing the challenges educators face in having students engage with each other online, has questioned the kinds of pedagogies, both materials and teaching approaches, that program designers set up in such scenarios. In many of these situations, she argues, learners are faced with obstacles rather than incentives to interact with others online. The majority of responses to the survey and questionnaire provided evidence of the shortcomings of the LearnSocial site in terms of encouraging interaction. The reasons cited were bandwidth problems, technical

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Paula Charbonneau-Gowdy glitches with materials and working in the site, or lack of support when these issues arose. As Table 2 above indicates these technical problems were institutional specific. It is also significant we believe that the participants from the institution that rated technology significantly lower than others also gave the lowest of all ratings to satisfaction with the Platform and Zoom sites for supporting interaction, at 55% & 62% respectively. Indeed technical issues along with the nature of the Platform’s pre-established materials, proved to be a deterrent for many to attempt to engage with others. Instead a majority interviewed reported that they chose to do no more than what was necessary in the Platform to ‘pass’ the course. For those that persevered, many reported feedback came only from tutors or there was none at all. In other words, their interaction opportunities in the LearnSocial Platfom were almost negligible and tutors chose to interact with learners directly rather than encourage learner-learner interaction in these sites. Martin’s perceptive comment that “The platform really didn’t encourage the human part “mirrors the research in technology based on Lave & Wenger’s (1991) Community of Practice and the importance of community building in these sites (Rovai, 2002, Nicol et al. 2002). Such studies demonstrate the essential component of learner input in the generation of online materials and the support of a learner-centred teaching approach that promotes the building of a meaning-making community among members. Based on the data that emerged from the various data sets both seemed lacking generally in the LearnSocial Platform. Investing in sustained learning Zoom classes In the first time, I had some doubts you see for the time because it was at 10:00 o’clock in the night. But really it was once a week to stay with the rest of the group and that was great to meet the other ones and to have, how you say, ‘alimentaçión’ [feedback] of the teacher. (Patricia, Interview Jan 13) In her own words, Patricia comments on how she appreciated the feedback from others. The hour of her Zoom meetings were late in the evening and although inconvenient, she continued to attend because of the value she placed on meeting others and receiving feedback from the teacher. These occasions for adding to her social and material resources fueled her sustained interest in the course and investment in learning. Others talked about how the Zoom classes helped build relationships beyond the classroom. For example, Mauricio (Interview Jan. 22) related how his teacher had formed a Facebook group from the beginning and how he and his classmates used this shared site to continue conversations that had started in the Zoom classroom. He explained how it was the teacher who would draw them into such interesting subjects about their own countries, cultures, work and personal interests that his classmates would be curious and would want to exchange further on these topics, often two to three times a week in Facebook. It is significant to mention that since the course has ended Mauricio has resurrected a practice he had started and left 10 years ago of connecting regularly with people from countries all over the world to speak and practice his English, and this despite his self-proclaimed extreme shyness in speaking English. Through the lens of Norton’s (2013) construct of investment, we understand that Mauricio’s online tutor provided occasions for agency in the virtual classroom to Mauricio and his classmates by taking cues from their professional and personal interests and making room for learner-centred discussion. These occasions for developing agency led to Mauricio and his classmates constructing more empowered identities as learners and to their adopting self-directed behaviours outside the classroom as well as to long-term investment in learning. These behaviours reflect Cormier’s (2010) construct of clustering and its advantages, as explained above. The LearnSocial Platform Several participants who reported being too shy or shameful to speak in the Zoom classroom or who had technical and/or bandwidth issues for which they were unable to have resolved by administrators, resorted to the LearnSocial Platform as a means to increase their language capabilities. Natalia was one example. She commented about her experiences in the Zoom classroom: “I have shame because other people know more.” A busy director of a very large team in Brazil with little time she saw the Zoom sessions as “I waste my time” and only attended two of the ten classes offered. Yet, she regularly spent many hours of her limited time in the LearnSocial Platform completing all the activities and sending them to her tutor for correction and comment. Several others reported doing the same, working around busy professional and personal schedules to faithfully

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Paula Charbonneau-Gowdy do what was required on the Platform. Indeed, analyzing the survey data results indicated a split in those who saw the LearnSocial Platform as a valuable tool and those who did not. Feelings of pride on the part of the participants who did persevere in the Platform rather than in Zoom were evident when they expressed how they had completed all of the exercises and passed the course. Yet, despite the investment made in learning in the Platform, it is essential to point out that in interviews with the native English researcher, most of this particular group of participants often chose to speak in their native language through an interpreter rather than in English and/or apologized repeatedly for their low level of English and marginalized feelings when speaking. In other words, the return on their investment in the LearnSocial Platform appeared questionable in terms of adding to their social and economic capital. While many of these individuals felt pleased with their efforts, the feelings of security they received from working alone or with the tutor seemed to deny them access to the funds of knowledge they required when participating in authentic use of English.

5. Conclusion and implications It was clearly evident from the various data sets that participants appreciated the opportunity offered by their employer to learn English online instead of in a traditional learning context. The majority reported that they felt that they had made progress in many of their language skills. Analysis from three data sets – the interviews, survey and questionnaire all indicated that the majority of participants expressed a desire for further program offerings. In terms of language progress, multiple-choice test results, limited in scope, are able to provide only measurements of passive skills, not the active ones needed for authentic communication. Yet, the data clearly revealed that select groups of learners did report obvious increased fluency as compared to their abilities prior to the onset of the program. A limitation of the study is that these self-reports were not investigated in terms of the teachers’ feedback or a deeper analysis of extensive video data available from the online ZOOM classes. Importantly, testimonies of increased confidence, active investment and evidence of self-directedness of those who had dynamic experiences in the Zoom classes are enlightening. They are enlightening because these results strongly suggest that appropriate uses of technology combined with effective learning and teaching approaches offer opportunities for quality and sustained learning despite the challenges in MOOC-style distance programs. Yet it is clear from the findings that some participants lacked the opportunities necessary for building the kinds of self-directed and empowered learner identities research has shown lead to optimal sustained learning. Our data clearly indicate that the reasons for these unfavorable conditions were in part due to a lack of institutional support – both in terms of technical infrastructure and importantly in valuing the time participants needed to actively engage in the course. The results also unraveled issues rooted in the experience and practices of the tutors who either lacked the facility to create conditions for the more marginalized language learners to develop agency, particularly in the live Zoom classroom, or alternatively, did not succeed in encouraging more peer support in the group. There were indeed many stellar teachers in the group of tutors, yet other more traditional ones were evident as well. In response to the practices of the latter, many of the participants relied instead on more conventional tools available in the LearnSocial Platform where they reported they felt more in control of their learning, but where they worked alone or solely with the tutor and used only their passive skills in English. There was strong support in the data that demonstrated that these more marginalized participants by missing out on an opportunity for peer learning, also failed to construct more powerful identities that would allow them the confidence in using the language in authentic situations. In a recent 2017 call for papers, the editors of a leading distance learning journal Open and Distributed Learning claimed that: “A key strategic shift in the focus of education is evident, from a core-knowledge oriented education to a collaborative-dynamic evolving paradigm. It seems that we are at a crossroads where the traditional, classroom-based model of higher education has to be critically enriched with technology enabled, added-value components.” (n.p). The Network administrators responsible for designing the large-scale distant learning project program reported on in this study, evidently has hearkened this call. Indeed we believe they are unique trailblazers in education, especially in Latin America. Through combining powerful emerging technology tools that provide added value opportunities for creating networks for interactive learning, they have created a space for empowering identity construction and greater investment in learning and professional development in the context of a large-scale distance-learning program in countries that have much to gain from such opportunities. The results of this study clearly indicate that institutional support and 21st century teaching practices combined with materials that actively encourage and foster agency and interactive practices in these spaces, are critical for the advantages of these tools to be exploited and for sustained effective learning practices to prevail.

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Teachers’ Knowledge and Technology Acceptance: A Study on the Adoption of Clickers George Cheung, Kevin Chan, Ian Brown and Kelvin Wan Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong [email protected] [email protected] [email protected] [email protected] Abstract: Teacher acceptance is the key for the successful implementation of a new technology in education settings. While the Unified Theory of Acceptance and Use of Technology (UTAUT) offers a well-validated solution in explaining the behavioral intention of adopting an emerging technology, there are research gaps in understanding the determinants of the components in the model. Extending the previous model and applying it in the context of adoption of student response system (a.k.a. clickers), the current study explored the underlying factors that influence the core components of UTAUT— effort expectancy, performance expectancy, social influence, and facilitating conditions. In particular, the study examined the impact of teachers’ knowledge on the evaluation of those components. Incorporating the concepts of Technological Pedagogical Content Knowledge (TPACK), the study attempted to investigate the association of teachers’ knowledge and the major components in UTAUT. Fifty two teachers from 7 faculties at the Hong Kong Polytechnic University participated in our teacher survey between May and July 2015. Pearson’s correlation analysis reveals that technological knowledge was positively correlated with effort expectancy (p