Learning Technologies

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Workshop Proceedings

Learning Technologies 26 March 2014, University of Hull, Hull The Higher Education Academy STEM (Computing) / Department of Computer Science, University of Hull Edited by Deryn Graham and Neil Gordon

Workshop Proceedings

Learning Technologies 26 March 2014, University of Hull, Hull The Higher Education Academy STEM (Computing) / Department of Computer Science, University of Hull Edited by Deryn Graham and Neil Gordon

ISBN 978-1-907207-48-8


We are pleased to present in this volume the position papers for the second Higher Education Academy (HEA) STEM (Computing) Learning Technologies Workshop 2014. Collectively, they cover a range of interesting research and informed opinion. The success of a workshop of this nature is dependent upon the calibre of the submissions and the participants, which have both been exceptionally high. We wish to both welcome and thank the contributors to this workshop. In addition, we wish to extend our thanks to the workshop committee and referees. In particular, we wish to thank Mark Ratcliffe and Karen Fraser of the Higher Education Academy (HEA), STEM (Computing), for continuing assistance and support in making this workshop possible.

Workshop Chairs Neil Gordon and Deryn Graham

Workshop Committee/Referees Members of the Department of Computer Science, University of Hull: Neil Gordon. University of Greenwich: Deryn Graham.

This workshop was funded by the HEA. Templates were also provided by the HEA. 1


Keynote Introduction to the HEA, Learning Technologies and WebPA. Karen Fraser, The Higher Education Academy; Neil Gordon, University of Hull; Deryn Graham, University of Greenwich 3 Papers Personalised Learning Environments. Robert Costello and Nigel Shaw, University of Hull 4 Mixing Social into the Blend: The impact of Social Learning on Learning Technologies. Mike Brayshaw and Neil Gordon, University of Hull 12 Using program source control to motivate student learning. Simon Grey, University of Hull 21

A Pedagogically Motivated Guided Inquiry Based Tutor For C#. Adele Butterfield and Mike Brayshaw, University of Hull 33

Introduction to WebPA and the WebPA Special Interest Group Report. Neil Gordon, University of Hull 53 Launch Of The New WebPA Help Support. Melanie King, Loughborough University





Neil Gordon

Deryn Graham

The Higher Education Academy, STEM, Academic Development, York, YO10 5BR, UK [email protected]

Department of Computer Science, University of Hull, Hull, HU6 7RX, UK [email protected]

Faculty of Business, University of Greenwich, London, SE10 9LS, UK [email protected]

Abstract This keynote introduces the second HEA STEM (Computing) Workshop on Learning Technologies. It describes the Higher Education Academy (HEA), the workshop and the WebPA at Hull. Beginning with an introduction to the work of the HEA, a brief history of the evolution of this workshop on Learning Technologies is given, and its relationship to the WebPA Special Interest Group at Hull. Keywords Higher Education Academy, Learning Technologies, WebPA.

References Graham D. (2013a). Learning Technologies, Keynote. Proceedings of the Learning Technologies Workshop 2013, University of Greenwich/Higher Education Academy STEM (Computing), University of Greenwich, th London, 6 June 2013, p.3. Graham D. (2013). Redeploying the Transnational Framework for E-Learning Technologies as a Tool for Evaluation. Journal of E-Learning and Digital Media (ELEA). Vol. 10, No. 1, March 2013, pp. 111-123. Graham D. (2011). Findings from the “e-Teaching and Learning Workshop (2006 – 2011). Proceedings of the th 12 Annual Conference of the Subject Centre for Information and Computer Sciences, Higher Education Academy, University of Ulster, 23-25 August 2011, pp. 51-59. Graham D. (2010). Development of a Transnational Framework for e-Learning Technologies. In Cases on Technological Adaptability and Transnational Learning: Issues and Challenges, Siran Mukerji and Purnendu Tripathi (Editors), IGI Global Publishers, Chapter 10, pp. 187-201.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. © 2013 The Higher Education Academy


Personalised Learning Environments Robert Costello

Nigel Shaw

The Graduate School University of Hull United Kingdom

The Graduate School University of Hull United Kingdom

[email protected]

[email protected]

Abstract Traditional, on-line e-learning theories, are contextually driven and influenced largely by learning management systems (LMS’s) through the use of technology. These conformities and standardizations have led away from personalisation and learner-centricity to a LMS, where the student is only the consumer (instructor-centred) and not a Prosumer. The concept of e-learning was to allow a student to have a high degree of learner self-direction and personalisation within the learning process. The rapid development of technologies within the field of “Web 2.0” is encouraging the development of new educational strategies to support self-regulated learning in higher education contexts, through the use of personal learning environments (PLE) and the application of Heutagogy. This paper will explore the multiple communication and creative formats that social media can offer postgraduate students within the higher education sector for supporting learning opportunities within a PLE. It will explore different types of andragogical theory, how to integrate new Web 2.0 technologies into delivery of programs and what supporting mechanisms will be required. Keywords Personalised, E-learning, Pedagogical, Andragogical, Heutagogy.

1. Introduction Traditional e-learning environments establish a framework that enables contact between student and the curriculum lead tutor. E-Learning is a tool that uses web-based platform technology to provide training and development in the education sector. According to Derouin et al., (2005) “elearning is a powerful tool for delivering the many and varied instructional technologies and methods”, and can be used to “present online lectures, through the use of live stream audio and video technology” (Page 921). Van Raaij & Schepers (2008) agree with Sampson & Karagiannidis (2002) and Derouin et al., (2005) about e-learning being a powerful tool for the teacher; and suggest that a “VLE is a web-based communications platform, that allows students, without limitation of time and place, to access different learning tools” (Page 840). Sun et al., (2008) indicates that even though e-learning allows students to


study at their own pace, 24 hours a day, there are still limitations associated with this technology. According to Sun et al., (2008) these can be categorized as the following: (1) Learners’ satisfaction, dimension, interest and attitudes, (2) Educational tools available within the environment (3) Educational content, curriculum and choice of learning theory (4) Tutor or learner-centricity led Liaw (2008) suggests that there are other factors that might contribute to learners’ dissatisfaction with e-learning that are to do with an “absence of a learning atmosphere”, “e-learning lacks interpersonal and direct interaction among students and teachers”, and sometimes the design of the educational curriculum is not carefully thought out (Liaw 2008, Sun et al., 2008). According to Kozaris (2010), e-learning tries to create the direct opposite of what (Liaw 2008, Sun et al., 2008) indicated as “absence of a learning atmosphere”. Kozaris (2010) indicates that on-line learning tries to deliver “many enhancements to the teaching and learning experience; the largest impact occurs when the technology enables social and collaborative interaction where an individual person, students, or parties build actively their understanding” As indicated by Sampson & Karagiannidis (2002), Coats et al., (2005) and Kozaris (2010) e-learning environments are tailored around the Learning Management Systems (LMS) that provide the technology infrastructure through which the educational materials can be delivered. Sclater (2008) suggests that current Learning Management Systems like that of Blackboard, Moodle and Ebridge, are controlling the educational creativity of the individuals. It is this feature that has led away from personalisation and learner-centricity to a standard LMS, where the student is only the consumer (instructor-centred) and not a Prosumer. Sampson & Karagiannidis (2002) suggests that personalisation shifts away from the traditional LMS methods and focuses on the flexibility of learning materials, customizing and adapting content to suit individual learners, incorporating a wealth of rich media through a learner-centric environment. Personalised learning “should not be restricted by time, place or any other barriers, and should be tailored to the continuously modified individual’s learner’s requirements, abilities, preferences, background knowledge, interests, skills, etc…” (Sampson and Karagiannidis 2002, Page 2). McLoughlin and Lee (2010) agree with Sampson & Karagiannidis (2002), that personalisation within e-learning is important and indicates that there is a growing shift within education that is allowing the learner to take more autonomy in their own learning, through the use of social media, and webbased platforms like that of wikis, Eduwiki, Twitter, Skype, YouTube, www.Slideshare.net, etc. According to Sant (2013) EduWiki is used to “support innovative, active, low-cost activities for learners, promoting subject skills”.


2. Personal Learning Environments Personal Learning Environments (PLEs) are designed for the learner to use a variety of media platforms to engage in curriculum activities. Sclater (2008) suggests that by using PLEs within learning activities, individuals can embrace learner centricity through a multitude of on-line tools, like Twitter, Facebook, Bebo, Skype, etc.). Nussbaumer et al., (2012) suggest that PLEs provide individuals with the opportunity to build and develop their own choice of educational activity, through the use of web-based technologies, for example: face to face interaction using Skype; Twitter, to share and communicate questions with other students on the course or globally; YouTube and SlideShare.net for Self-Regulated Learning (SRL), Facebook, to communicate discussion and engage within collaborative development challenges. Nicol and Macfarlane-Dick, (2006) suggest that students who use SRL, automatically engage in thinking, motivation and accommodate their behaviour to the learning activity. “In practice, self-regulation is manifested in the active monitoring and regulation of a number of different learning processes, e.g. the setting of, and orientation towards, learning goals; the strategies used to achieve goals; the management of resources; the effort exerted; reactions to external feedback; the products produced.” (Nicol and Macfarlane-Dick, 2006, Page 1). According to Petrovic et al., (2012) studies have shown that social network tools like that of Facebook can encourage collaborative development activities, critical thinking and problem solving opportunities. The use of Facebook within education enables the individuals/groups to: “Create a shared group for educational purposes ‘Open, Closed, Secret’ Notes, Events Calendar, Photos, Messages and Notifications, real time chat, and Mobile support. Another useful educational tool to be used within PLEs is that of Twitter. Skiba (2008) suggests that Twitter is used “to communicate, to ask questions, to ask for directions, support, advice, and to validate open-ended interpretations or ideas by discussing with others” (Skiba 2008, Page 2). The benefit of using twitter within HE, especially at postgraduate level, is to create a virtual classroom community in which teams can form, to promote and develop a variety of skills, including networking, team building and critical thinking. It enables students to keep a personal record of progress on line “record their cognitive trails” and this will enable them to submit work for their reflective dairies. The lecturer can send out questions relating to a variety of topics within modules to encourage extra-curricular activities, to which the groups will have to respond out of hours, within an


informal/formal setting, allowing them to engage in discussions, reflect ideas, and share conceptual thoughts (collaboration). However, limitations of these approaches can be: students being easily distracted from other web 2.0 applications and usages; lack of educational structure (tasks not being clearly thought out and designed by the course lecturer); privacy of thought and intellectual property; lack of support or willingness to engage with conversations 24/7. The application of social learning theories to the use of Twitter would enable students to engage and learn from one another within an informal/formal collaborative environment. Within Higher Education, Twitter can be used to “Knowledge Probe” and interrogate technical principles. Skiba (2008) suggests that “Twitter can be used to facilitate active, interactive and reflective learning”. The use of Twitter will enable students to develop “metacognition, forcing users to be brief and to the point” enabling them to work on descriptive and communication skills. Nussbaumer et al., (2012) agrees with Skiba (2008) about supporting and encouraging students to engage in metacognition development through PLEs. According to Nussbaumer et al., (2012) PLEs will enable individuals to build and develop their planning, monitoring their own learning paths through reflection The use of PLEs within an informal learning situation, while using web-based platforms can create a customised learning environment, tailored to a variety of learners needs. This can support interoperability through multimedia, open standards, and reusability’s of curriculum materials. The issues raised by PLEs are: Assessments (fluencies, accuracy, literacies); Feedback (teacher: online to groups, peer support informal times), time: social-connectability. According to Meyer et al., (2009) the use of PLEs within web-platforms within education can provide valuable evidence to support formative assessment. Black and Wiliam (2009) suggest that Formative Assessment Theory enables students to work together to accomplish group tasks and create contributions from different communities. According to Ajjan and Hartshorne (2008) the use of social networking within Higher Education has been shown to improve student’s learning, through interactive curriculum designs, collaborative development, and peer review exercises. As mentioned by Blaschke (2012) andragogical theories have been extensively used on-line to reinforce distance learning to improve competencies and capabilities of the individual. Blaschke (2012) suggests that the tutor uses andragogical learning theories to support and develop the


learner’s capability to become more self-directed in his or her learning. “The instructor shows learners how to find information, relates information to the learner experience, and places a focus on problem-solving within real-world situations” Blaschke (2012) indicates that SRL, through the use of an andragogical learning approach, may not be adequate to challenge the individual through the use of modern web-based platforms and a new holistic approach is needed. Kirkwood (2010), Cochran et al., (2012) and Blaschke (2012) suggest that one approach that could be used is Heutagogy.

3. Heutagogy According to Bhoyrub (2010), Kirkwood (2010) and Blaschke (2012), Heutagogy refers to the personal learning experience of an individual within a constantly changing environment. Blaschke (2012) suggests that Heutagogy “can be viewed as progression from pedagogy to andragogy to heutagogy, with learners likewise progressing in maturity and autonomy” (Page 2). Within Heutgogy, the learner helps to steer the direction of the learning curriculum, designing and developing the map of learning, and assessment through reflection. Bhoyrub (2010) suggests that heutagogy enables the learner to engage and learn from other peoples’ responses to “unpredictable need, frequently when faced with the limits of their current knowledge or capabilities”. It is this unpredictable learning approach where the learner has to readjust his or her own learning that makes this amenable to use with web-based technologies. This type of approach supports self-regulated learning and incorporates a more holistic learner-centric model, which will, according to (Bhoyrub 2010), improve “individual capabilities in terms of knowledge, skills and values” and develop “expertise, linking theory to practice”. According to Kirkwood (2010), using heutagogy within social media to deliver curriculum, can overcome the boundaries that the traditional LMS, one-size fits all approach, suffers from.

4. Heutagogy in Practice The Graduate School has applied a variety of web-based applications to support postgraduates through the 2012 and 2013 Easter and Summer Schools. In particular the modules of ‘The Effective and Successful Researcher’, ‘Project Managing Your Research Degree’ and ‘Practical Entrepreneurship’, which involved the use of: YouTube, Facebook, GVRE (ebridge), Prezi, and Skype to enable students to maximise their learning experience. Some ideas and content were developed from Vitae’s experiential learning materials. The use of Heutagogy has enable students to engage in self-regulated learning through questions being placed on Facebook and YouTube. The lecturer would load up a series of images to the Facebook account, please see fig 1 “Facebook in Action” and allow the students to engage in a series of questions associated with the slides.


However, due to the nature of Heutagogy, this is where the curriculum can change, due to what the student learner wants to learn. Given that project management is such a large area, topics within it can be explored and curriculum changed due to the direction lead by student requests. Minimum curriculum must be covered to enable credits to be achieved as part of the PGTS. Students were encourage by the lecturer to use YouTube to record personal views about the topics associated with project management, to enable others to share and contribute in selfregulated learning. Resources from this task enabled marking to be collated through reflective accounts. Skype and mobile devices were heavily used throughout the week long course at the Graduate School to encourage interactive and collaborative development, while working on group tasks.

Figure 1 “Facebook in Action”

5. Quality module evaluation Using the end of course evaluation forms, it can be shown that 46% (18n) of the students from the 2013 cohort found that this approach to learning was intellectually stimulating, while 38% had no opinion and15% disagreed with the whole idea. However, extracting the results from the 2012 data set, 57% (21n) of students found that using a more student led educational experience was more beneficial to their learning needs; 19% agreed with this, 14% of students had not opinion at all relating to the methods used within the classroom and 10% disagreed and wanted a completely lecturer led curriculum based module. The feedback shows that this approach can assist individuals to engage in self-regulated learning, while supporting a more holistic learning approach through web-base media. We found that adding flexibility to the curriculum can improve the students’ overall learning experience.

6. Conclusion This research indicates that the application of Heutagogy at postgraduate level can be beneficial. However, the numbers involved in the study, the class size of (18) and (21) over the 2012 and 2013


year period, limits the robustness of conclusions that can be drawn. More research is needed, including more Question and Answer sessions, through Twitter or new technologies, to see if results match those found so far.

7. References: Ajjan, H., and Hartshorne R., (2008) “Investigating faculty decisions to adopt web 2.0 technologies: Theory and empirical tests” The Internet and Higher Education, Volume 11, Issue 2, 2008, Pages 71-80 Bhoyrub, J., Hurley, J., Neilson, R. G., Ramsay, M., and Smith, M., (2010). “Heutagogy: An alternative practice based learning approach”. Nurse Education in Practice, Volume 10, Issue 6, November 2010, Pages 322-226 Black, P., and Wiliam, D., (2009). “Developing the theory of formative assessment” Educ Assc Eval Acc (2009) 21:5-31. DOI 10.1007/s11092-008-9068-5 Blaschke, M. L., (2012) “Heutagogy and Lifelong Learning: A Review of Heutagogical Practice and SelfDetermined Learning”. The International Review of Research in Open and Distance learning, Vol 13, No 1 ISSN: 1492-3831 Coats, H., James, R., and Baldwin G., (2005). “A Critical Examination of the Effects of Learning Management System on University Teaching and Learning”, Tertiary Education and Management 11: 19-36, 2005, Springer Cochran, T., Antonczak, L., Gordon, A., Sissions, H., and Withell, A., (2012). “Heutagogy and Mobile Social Media: Post Web 2.0 Pedagogy” ascilite (2012) Future Challenges | Sustainable futures 25-28 November 2012, New Zealand Derouin, E. R., Fritzsche A. B., and Salas, E., (2005). E-Learning in Organisations, Journal of Management 2005 31: 920 DOI: 10.1177/0149206305279815 th

Grosseck, G., and Holotescu (2008). Can we use twitter for education activities? The 4 International Scientific Conference, eLearning and Software for Education. Bucharest, April 17-18, eLSe 2008 Henter, R., and Unianu, M, E., (2012) Metacognition in On-line Foreign Language Learning http://www.icvl.eu/2012/disc/icvl/documente/pdf/met/ICVL_ModelsAndMethodologies_paper13.pdf Kirkwood, K., (2010) “The SNAP Platform: social networking for academic purposes” Campus-Wide Information Systems Vol. 27 No. 3, 2010, pp. 118-126 Kozaris, A, I., (2010) “Platforms for e-learning, ABCs of Teaching Analytical Science”. Analytical and Bioanalytical Chemistry, Springer-Verlag 2010. 10.1007/s00216-010-3587-x Liaw, S-S., (2008) “Investigating students' perceived satisfaction, behavioral intention, and effectiveness of elearning: A case study of the Blackboard system”. Computers & Education Volume 51, Issue 2, September 2008, Pages 864–873 McLoughlin, C., and Lee, W. J. M., (2010) “Personalised and self regulated learning in Web 2.0 era: International exemplars of innovative pedagogy using social software” Australasian Journal of Educational Technology 2010,26(1), 28-43. Meyer, E., Abrami C. P., Wade A. C., Aslan, O., and Deault, L., (2009) “Improving literacy and metacognition with electronic portfolios: Teaching and learning with ePearl” http://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=1006&context=coe_dean Nussbaumer, A., Kravcik, M., and Albert, D., (2012) “Supporting Self-Reection in Personal Learning Environments Through User Feedback”. Vol, 872. http://ceur-ws.org/Vol-872/pale2012_paper_7.pdf Sampson, D., and Karagiannidis, C., (2002) Personalised Learning: Educational, Technological and Standardisation Perspective Interactive Educational Multimedia, Number 4 (April 2002), pp. 24-39


Sant, T., (2013) EduWiki (accessed 27 January 2014).




Skiba, J. D, (2008) “Can you post a Nugget of Knowledge in 140 Characters or Less? Emerging Technologies Center, Nursing Education 2.0: Twitter & Tweets”. Nursing Education Perspectives 2008 Vol.29 No.2 Pages 110-112 Sun, P-C., Tsai, J, R., Finger G., Chen, Y-Y., and Yeh, D., (2008) “What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction”. Computers & Education 50 (2008) 1183-1202 Petrovic, N., Petrovic D., and Jeremic, V., (2012) “Possible Educational Use of Facebook in High Environmental Education” (2012) ICICTE 2012 Proceedings 355 http://www.icicte.org/Proceedings2012/Papers/09-1-Petrovic.pdf Van Raaij, M, E., and Schepers, L. J. J., (2008) “The acceptance and use of a virtual learning environment in China”. Computers & Educations 50 (2008) 838-852. Webster, R., (2013) “Metacognition and the Autonomous Learner: Student Reflections on Cognitive Profiles and Learning Environment Development”. http://citeseerx.ist.psu.edu/viewdoc/download?doi=

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. © 2013 The Higher Education Academy


Mixing Social into the Blend: the Impact of Social Learning on Learning Technologies. Mike Brayshaw

Neil Gordon

Department of Computer Science, University of Hull, Hull, HU6 7RX, UK [email protected];

Department of Computer Science, University of Hull, Hull, HU6 7RX, UK [email protected]

Abstract The success of school and university based learning has been built on the social context within which the learning takes place. In this paper we consider this learning in the context of 21 st century technologies, where social interaction and presence can be dually in the virtual world as well as in the physical world. Technology can offer new flexible approaches to learning, opening up more opportunities and choice for learners in the where, when and how they learn – making learning truly flexible. The variety of interactions between students becomes something which can happen in a variety of ways, which may complement – as with blended learning - or replace traditional learning exchanges. This raises questions about how teaching and learning are delivered and managed, and how they may be assessed. Social media is a particular challenge – students’ preferences differ, some wanting to utilise their social presence in their formal learning, others want to keep it separate. For institutions and staff, the issues around personal and institutional identities make the decision to use social technologies a challenging one. Massive Open Online Courses (MOOCS) offer another approach – for some commentators a disruptive one –to university education, and raise challenges about how universities develop their own campus and online offerings in this developing virtual marketplace. Keywords Social Learning; Blended Learning; Flexible Pedagogy.



Going to school or University was always a social event. The importance of the social aspect of learning has been noted before, particularly the use of the appropriate scaffolding that this interaction may bring about (Vygotsky, 1934; Bruner, 1961, 1966; Wood, et al., 1976). So what has changed and how have learning technologies brought this about? We now have new ways of being social and this has major pedagogic impacts. The development of the Internet, Web 2.0, and ubicomp (Brush, 2014) have led us to consider how we deliver “what, which, and how” in a blended fashion, where the blend reflects that we have now multiple options about the way in which we deliver material (Allen, 2007). Of importance here is the new affordances of social technologies and how they support peer-to-peer interactions. They offer the opportunity to overcome teacherstudent contradictions (Freire, 1970) or classic Computer Mediated Communication hang-ups like synchronous versus asynchronous communication. Most people do not think of their phone as a computer, rather they consider the phone as a social communication device. Given that we live online, the question is how can we effectively learn online? Virtual campuses are not new 12

(Eisenstadt et al, 1996), but early implementations are typically a metaphorical veneer on existing practice. This paper will look at how social media can be used to deliver core University teaching that would of old constituted lectures, seminars, and tutorial as well as key linked social events – it is not always what you went to see as who you missed it with. The role of Webinars, MOOCS and Virtual and Augmented Reality will be discussed and we reflect on how they change the educational mix. Social aspects of being at a University will also be addressed. Indeed in Social Computing we are not shackled to any Newtonian Reality; the context in which we choose to interact and learn can be one that we imagine to best scaffold our personal learning.


Flexible and Blended Learning

Flexible learning (Higher Education Academy, 2013) focusses on providing learners with choice – sometimes considered in terms of the 3 dimensions of flexibility; the how, where and when to learn. Such choices can be enhanced and supported with technology (Gordon, 2014), with opportunities to allow for blended learning (Ceretta et al, 2002), which considers the use of computer based learning technologies alongside formal instruction. As noted above, computers are now becoming ubiquitous, with many users not considering their mobile, tablet, television or games console as a computer; however, in terms of eLearning these are all manifestations of computers within everyday life. In terms of blended learning, a student may attend classes and other more traditional activities, which are complemented by computer based support such as interactive learning objects, computer based simulations and computer aided assessment. This may include lecture capture and replay, or other support to replace some elements of the original teaching, or to give extra flexibility by enabling students to learn in different ways. The opportunities here can include supporting different learning styles, allowing choice in the place and/or time of study, as well as the more pedagogic focus of what the learning actually involves in terms of the learning style and content. The choices afforded by technology become more challenging when issues of assessment are considered. Allowing some choices – such as where to take an assessment, can be considered as placing the robustness of the outcome at risk e.g. how to verify the identity of the individual taking the assessment. Allowing selection in the form of assessment can also cause difficulties when it comes to ensuring the comparability and equivalence of different assessments – in what way is an oral presentation equivalent to a report, and how to these really compare to a closed book exam? Another aspect of assessment may be choosing whether to work individually or in a group – which places extra complications around the recognition of work and the allocation of marks. Such choices can require culture change by the individual teachers as well as by institutions and their systems.


Assessment in a social context

With the internet generally, and social media in particular – whether promoted and required within a course, or utilised by students to supplement institutional tools and systems – the opportunity for cooperation between students is sometimes encouraged and is certainly more available and supported than hitherto. However, the borderline between cooperation and collaboration, and the transition to unfair means remains a challenge when it comes to assessment.


Peer assessment – that is the marking of one student’s piece of work by another student – is one way to manage scalable marking solutions. However, such approaches open up issues around the training and capacity of the (student) markers. Such approaches can encourage student to student dialogue around work, but the difficulties of validating the marking may dissuade teachers from using it. Team based projects are another way to encourage interaction, and to utilise the strengths of social media. However, team based activity can be problematic when it comes to assessment. The issue becomes how to apportion marks, how to validate marks, and how to deal with appeals and complaints. 3.1 Groupware and Web 2.0 for team projects Groupware – that is Internet technologies to support group and team work – offer tools that can assist individuals in carrying out group activity. Equally, a number of Web 2.0 technologies – such as Wiki and Blogs – offer mechanisms that can support cooperative working. The benefit of such tools from an assessment perspective is that they provide author and date stamping of work, so giving some audit trail of who did what, and when. This can aid in assigning marks based on apparent contribution; however, such analysis can be time consuming and would miss any non-recorded interactions, such as utilising other private social media, or even face-to-face interaction. One solution to this is to put the onus on the allocation of marks back onto the students themselves, as considered in the next section. 3.2 Assigning Marks e.g. WebPA As noted in the previous section, assigning marks is non-trivial. One approach to deal with this is for the teaching staff to mark the overall product that a team produce, and then to use a weighting to allocate a proportion of that mark to the individual team members, based on some judgement of the relative contributions. Such a judgement could come from reviewing the audit information on a team site, from interviewing – in person or virtually – the team and/or its individual members, or by offering the opportunity for the individual team members to record their perspective on the relative contribution of the team members. This last approach is one supported by a number of web tools, in particular by WebPA (2008) which allows students to provide a rating of team members’ contributions, which are then used to generate a weighting to allocate an individual mark. Whilst WebPA is typically used in traditional campus based teaching, the approach and tool itself would be equally applicable to an entirely virtual teaching environment. Of course, any auditable data available – such as activity logs – can be used to validate the weightings that come from the student judgements (Gordon, 2010).


Social Media and Education

Social Media is at the very heart of our modern interaction with each other. The thought of being off-line or unable to connect with those that we want to – despite the often vast distances that this involves – is an anathema in the modern ages. It is common for Universities now to use Social Media in their advertising (e.g. https://www.facebook.com/UniversityOfHull), as method of communicating with their alumni (e.g. Twitter #HullAlumni orhttps://www.facebook.com/yorkalumniassoc) and for the existing students organisations and


societies to communicate (e.g. https://www.facebook.com/Hullstudent). As a follow on to this now we will now look at how this technology impacts in an educational context. 4.1 Changing the Location of Learning The internet and WWW have changed how Universities can disseminate their material and interact on an educational basis with their students. This can be in terms of making slides/notes available, as virtual notice boards or messaging systems, YouTube Video Lectures, direct mailing to cohorts or targeted students, as well as, as previously noted, carrying out assessment and marking. It is easy to see how Facebook and Google+ can be used in a similar fashion as providers of information and download facilities or to post homework. What is more of interest is the social interaction affordances they offer. An early attempt at a Virtual Campus was the Virtual Summer School (Eisenstadt et al, 1996). It used WWW and forum style synchronous and asynchronous interaction to provide the infrastructure backbone. However, two weeks before the course was set to run, in order to familiarise people with the new equipment and facilitate interaction they were required to meet in a Virtual Bar using a standard chat facility and virtual drinks (virtual for some – actual local drinks for others) with social sessions taking place between 8pm and 9pm (GMT). Conversations on dogs and cats and other subjects were entered into. This continued through the fortnight of the summer school culminating with a virtual disco on the last night. The students were perceived to carry on using this social world throughout the Summer School and for academic as well as personal, non-academic conversations. Another bold attempt to change location is to move to a new world altogether. The Department of Information Systems at the University of Sheffield has developed a Second Life (http://secondlife.com/) island. Second Life is a parallel reality where you can live through your own invented avatar and trade in money and real estate in an analogous manner to a conventional experience. Communication is via real world metaphors in this virtual world. Information Islands in this world are focuses of activity. Infolit iSchool is a (University of Sheffield) island that promotes Information Literacy and Inquiry-based learning (http://secondlife.com/destination/infolit-ischool). The educational activity is quite literally moved to a second place. The problem with this metaphor is that considerable extra baggage has to be engaged with before any learning takes place. That students might not be predisposed to entering into this fantasy is also an issue. One of the major changes to location over the last few years has been the growth of MOOCS (Massively Open Online Courses). Many major Universities now offer access to online materials and assessment. They offer access to famous Universities at very affordable prices. Anyone from around the world can take these courses and thus their uptake in less-affluent countries is one of their major claims. Proponents would argue that the change of location allows the world to educate itself and re-adjust social imbalance. For example Stanford University’s AI course has 160 000 enrolled with 23 000 students completing the course and getting an appropriate achievement certificate. If you consider an average University Lecturer starting teaching at 25 years old, with a class of 200 students a year, in a whole career they are not going to teach that number of successful students. This represents a massive shift towards virtual locations of learning but it is not without its downside as we shall discuss.


Another aspect of change of location is mobile learning. MOOCs don’t care where you are. Ubicom means that we can interact with virtual universities wherever in the world we find ourselves and at whatever time we choose. Given the development of Unicom delivery devices the co-location of student and university campus is loosened even further. The constraint now is more one of bandwidth and appropriate receiving device like a Pad or console. The location of class is similarly altered. It is no longer necessary to co-located with fellow students to interact with them in the same way as the teacher does not have to be physically present. This is also true for people with similar interests or those that pursue similar causes. Google+ Communities allow those with common interests and subject matters to form subject interest groups. In a classroom setting this can be used as a basis for group work and sharing of resources 4.2 Changing the Educational Paradigm Employed Mixing Social into the Blend is all about how to use Social Media in the fundamental philosophies of teaching. As discussed earlier Blended learning aims to exploit different approaches as most applicable to the current learning context. To do this the flexibility and liveliness of the approach naturally lends itself to the endeavour. Indeed the lack of inertia that new media brings to the mix means that swapping between approaches is easy. Classic chalk and talk can readily be updated to multi-media presentation for example via YouTube, Picasa, Facebook, and Google+. Didactic blends can have a similar treatment by the associative interactive techniques which we will deal with in the next section. 4.3 Changing the Type of Interaction Mixing Social into the Blend means that we can look at how the types of interaction, in an education context, can change. Sharing resources using Googledocs, YouTube, and Picasa is an exciting new way of interacting. Fordham, and Goddard, (2013) present two case studies using Facebook to provide students with information, to encourage them to communicate, and organise their activities and share the results of their research. They note how Facebook Timeline can help teach a curriculum, provide a platform for homework and revision, host debates, provide for peer mentoring and tutoring, allow sharing of ideas, videos, and resources, and the setting up supporting groups. In Twitter use of hashtags for rapid response and research is a similar resource. The importance of choice of #hashtag in Twitter is a critical issue. Tweeting provides for a rapid response although the limited in characters (140) may limit what can be expressed and effect necessary dialog. Follow up Fridays provide reviews about who to follow next. This can lead to the development of Twitter strategies; for example do you decide to follow those with a large following? A Twitter backchannel (Bruff 2011) or parallel conversation can be developed alongside physical teaching to encourage reflection on and meta-discussion of existing lectures or seminars, so that questions raised in any mode of delivery could be dealt with using this channel Crowdsource is another emerging type of interaction in social media that learning technologies can exploit. It allows for multiple views to be solicited by asking the folk out there on the net for their views. The idea is that if you ask for a wide range of opinions and knowledge you will be in a more


informed situation on which to base our subsequent actions. A real-time stream of discussion via can be implemented by a particular #hashtag. In interactions there is always the issue about who you are talking to. In a physical co-located work you can sense the actual presence of your correspondent and from that extrapolate some personal details. This is not so online. People typically have multiple identities e.g. a work/school/university email and private ones like GoogleMail , Hotmail, or their ISP provider based email. This is compounded by new identities on Facebook and Twitter. This may indeed be a feature so that one can have one identity or many identities depending upon what role that you wish to play in a Learning Technology based pedagogic interaction. Another enhancement social learning can bring to learning technology is to build a learning community (e.g. Holton, 2013). In a community mutual help and support can be encouraged, knowledge and resource shared, tips passed on, and learning made a sociable experience. Distance Learning can often be a very lonely thing to do (e.g. Willems, 2007), particularly when there is just you in the house or housemates are all asleep. Communities can help to overcome this by bringing people together, talking to each other, maybe at antisocial times, whilst sharing common goals like studying a course. Further Interaction in Learning Technologies can be provided by the use of a news stream that provides up to date information for absorption and comment. Live debates on social events and current zeitgeists can be entered into which can greatly add to a pedagogical dialog. Foreign language news streams can further add to this debate and enlarge the syllabus. Blogging is a Learning Technology that provides yet another new type of learning possibility. Although intended as biographical logs they can be used to provide commentaries on education courses and as a focus for repositories of education resources (e.g. robmiles.com) Real time education policy can also be updated e.g. via Twitter timelines which give us access to the latest thoughts of Government Policy makers Whilst not strictly Social Events Webcasts/Webinars can form part of a new Online Interaction that fit in with Social User of Computers for Learning.




Who is really out there listening

One of the big problems with using social media is understanding who we are broadcasting to. Even with email people frequently confuse reply with reply to all. Likewise people often only mean to send a message to a local group “I’m playing squash this lunchtime” and end up sending it to the entire University. For a University this is not catastrophic – however if you post on the internet this is to the whole world and it is (maybe) a permanent event. The effects can be far reaching (BBC, 2011). What can be thought of as private conversation, when broadcast in public can have far reaching consequences. Google+ provides additional levels of privacy, selectable at each session which may help militate against some of these problems.


Google+ Hangouts allows limited number of people to talk and video conference. That it is a Hangout is a constraint on who is going to be present and thus who can hear your comments. Even so the need to be candid in such an open forum still remains. 5.2 Is “being a friend” the right thing for student and teacher? The world of social media is a very flat one without the rigid hierarchy traditionally associated with schools and universities. This can be a good thing. It can encourage open discussion and knowledge sharing. Conversely meeting your first professor can also be a positive experience. Respect for learning can aid learning itself. The views of a neophyte may not be the best ones that that individual will subsequently have. A downside to social media is that it has to be used responsibly and professionally. In 2011 Vasagar and Williams (2012) noted that one in ten school teachers accused of misconduct in the UK and reported to the General Teaching Council for England had used social media, chat rooms, and email contact to forge inappropriate relationships with their pupils. 5.3 To the Future One key driver in the field of virtual universities is MOOCs and the vast uptake of this learning technology may be one of the most important of the contemporary age. Major Universities around the world are investing in this route as a way forward, but do they solve all of our problems? The enrolment rates may be impressive, yet to call a course successful with only a 14% completion rate would be considered a disaster in convention chalk and talk circles. Indeed one wonders how many of those taking the course already had a degree and thus had additional experience which helped them in their studies. That they provide little hand holding is a problem. We have reported elsewhere about the need to provide guidance in education provision (Butterfield and Brayshaw, 2014). One of the opportunities for Learning Technologies in the future is how they can provide not just the education media but the associated interaction and contact to guide and best inform students in their study. With the increased growth in bandwidth and the massive expansion of power of the computers that we wear, how long will the text based social tools that we use today reamin dominant? Whilst students can see they own learning, reciprocity, and instinctive thinking, what can you say in 140 characters and in an open and public forum (Rich and Miah, 2013). Given all this online social interaction, it is ironic in that we do it often with no one physically around. In Alone Together, Sherry Turtle (Turtle, 2010) reflects on how we now rely on the technology for our social needs rather than meet up in a real space. Often here we are using Learning Technology Interaction in the place of traditional classrooms and face to face. It is a reflection of changing times, and our own norms of communication that we choose to do so. As times change, we change, and in a wireless age, how we interact with learning technologies and each other also changes.




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Using program source control to motivate student learning

Simon Grey Department of Computer Science, University of Hull, Hull, HU6 7RX, UK [email protected]

Abstract This paper will consider how source control systems can provide a learning technology to measure and potentially encourage learner’s engagement. Video games seem to have found a successful formula for fuelling player engagement and commitment to often quite arduous tasks. This paper begins with an examination of how games motivate players to engage, and examines how we might emulate that in learning and teaching. This leads to concepts of Self-Determination Theory as a theory of human motivation, as well as the conditions required to achieve flow – a state of complete engagement and focus on an activity. A case study using information from source control logs from laboratory tasks will then be used to illustrate as an innovative method to measure student engagement with lab activities across a module, closing the feedback loop between student and lecturer. Preliminary results of an ongoing study are presented of students’ engagement and activity whilst undertaking learning and testing tasks during self-directed learning activities using source control log data generated by those activities. Finally, future work is given consideration particularly to the types of activities that are measured. By splitting flexible, self-directed activities into threshold concepts, and then into a variety of learning, re-enforcement or testing activities, it may be possible to increase student motivation and gain insight into comprehension of threshold concepts. Keywords Technology Enhanced Learning; Gamification; Motivation



Getting students to engage in learning is an ongoing problem, whereas well designed games are incredibly engaging for the players who interact with them. The overall goal of this research is to use technology to develop a scalable system to enhance learning through increased motivation and engagement, using games design principles as an inspiration. As part of this goal, this paper presents the use of source control logs as a method of measuring student engagement with work in order to close the feedback loop between students and teachers.


Games and Engagement

This section draws inspiration from games. It considers what a game is and why we play games and why we find them so compelling. It looks at fields such as serious games; games based learning that have a primary aim other than fun. Finally towards the end of the section a technique adopted in a wide number of contexts called gamification is discussed. 21

One view of children playing games can be seen in the following quote: “They become like blinking lizards, motionless, absorbed, only the twitching of their hands showing they are still conscious. These machines teach them nothing. They stimulate no ratiocination, discovery or feat of memory — though some of them may cunningly pretend to be educational.” (Johnson 2006) This seems to be a typical view amongst the critics of video games. There are plenty of arguments to the contrary. Modern video games are hard, time consuming work, requiring the order of tens to hundreds of hours of attention. Regardless of whether the work performed is of any value, McGonigal claims that video games are not an easy option; citing philosopher Bernard Suits eloquent description of playing a game as “the voluntary attempt to overcome unnecessary obstacles” (McGonigal 2012) It is proposed that the key word in this description is “voluntary”, which implies freedom of choice to pursue one of several options, or none at all. This leads to the question, what is it that motivates gamers to invest so much time and effort into performing hard work, or any work at all? 2.1 What are games and why do we play them? McGonigal (2012) presents games as having four defining traits; a goal, rules, a feedback system and voluntary participation. Under this definition it is argued that any higher education can be considered to be a game, as they incorporate all four of the elements McGonigal has identified. Not all games are good games though, and as such it seems appropriate that the people who design the higher education may learn something from the teachings of those who actively research what makes a good game and what makes a bad one. Whilst the potential advantages and disadvantages of video games are still a matter for debate. One thing that is widely agreed upon is that good, well designed video games can be incredibly engaging. The question is why, how and what can be learned from games, and how can those lessons be applied to learning and teaching? For a long time games were seen as a niche, and as a result the industry has a habit of constantly trying to be taken more seriously. This is perhaps where the term “gamer” comes from, as opposed to “player” which is deemed to seem trivial or childlike. Play is often substituted in language to mean explore, experiment or learn (Brown and Vaughn 2009). When exploring new ideas with the expectation of learning something from the outcome an individual might describe what they are doing as “playing with an idea”. The freedom of experimentation embodied within this playful nature inspire is synonymous with creativity. This section will present a series of examples of learning from games Learning can be the result of a carefully targeted design specifically with the objective of learning and teaching (Where in the World is Carmen Sandiego), or it can be an accidental result of an engaging process (Civilisation 2014; Sim City 2014; Transport Tycoon 2014). It can be framed in a traditional academic learning environment, or in a wider context, with the goal of providing simulated training (serious games) or changing behaviour (games 4 change 2014). Koster makes a bold claim that “Fun is just another word for learning” and that games are ultimately teachers (Koster 2010). Through his work on the function of play in culture Huizinga (Huizinga 1971) highlights that play is a fundamental part of human culture, with an important role to play. Interestingly, Huizinga points out


the origin of the word ‘school’ “Meaning originally ‘leisure’ it has now acquired precisely the opposite sense of systemic work and training” (Huizinga 1971). Whilst answering the question “why do we play?” Lazarro identifies four keys to different keys to fun (Lazzaro 2004) she termed Hard Fun, Easy Fun, Serious Fun and People Fun. Each type of fun requires different conditions, and elicits different emotions, yet all can be termed as being “Fun”. Game designer Chris Crawford claims that “the fundamental motivation for all game playing is to learn” (Crawford 2011), claiming that the purpose of games was to learn about the game domain, solve the problems and beat the challenges it presents by developing the required skills to do so. 2.2 Serious Games and Game Based Learning Squire describes the accurate historical, cultural and geographical knowledge he acquired inadvertently through playing Sid Meier’s perpetual simulation game “Pirates!” (Squire 2011). More recently, the modern adventure game series Assassin’s Creed is set during the same time and place as significant historical events. Other games that have been credited with this “inadvertent” domain based learning effect include titles such as Civilisation (2014), Transport Tycoon (2014) and Sim City (2014). These are typically games in which success requires strategic planning and systemic thinking. Whilst these are examples of games that can teach something about the domain in which they are set, it seems that they were created as commercial ventures, and were not specifically created with learning in mind. Rather they happened upon the potential of games to teach something almost as a by-product of playing. These are examples of game based learning. Other games have been created specifically with the aim of providing opportunities of learning, or with the aim of creating lasting behavioural change. Perhaps the most famous example in terms of its reputation and success is “Where in the world is Carmen Santiago?” which was released in 1983 (Carmen Santiago 2014). Unfortunately commercial genre of games labelled “edutainment” seems to be more associated with poorly designed, poorly executed games (Goldstein 2014). It is proposed that this is largely due to a combination of poor game design, poor understanding of learning and teaching and lack of funding in comparison to mainstream games. That doesn’t mean that there isn’t a place for game based learning, but many games make the mistake of taking a good game and trying to retrofit some learning activity. For edutainment to be successful the primary goal, the learning outcomes must be central to the design. A generally more successful application of games for learning is the field of serious games (Burden and Slater 2008). Often serious games take the form of training simulations. Serious games are widely used in the military, where funding is less of an issue. As well as games for training, military simulation games are also created for propaganda purposes (Chacksfield 2009). The Games for Change movement is also worthy of a mention. Games for change (2014) is a global organisation founded in 2004 with the primary goal of facilitating “the creation and distribution of social impact games that serve as critical tools in humanitarian and educational efforts”. This represents a recent, significant and active body in this field of research.



This section considers human motivation. It begins with a description of the differences between extrinsic and intrinsic motivators. Following that a theory of motivation that focuses on intrinsic motivation, called self-determination theory is discussed. Next the concept of flow as the


psychology of optimum experience is introduced, highlighting the need for good feedback in order to achieve flow. Finally, some mechanisms used to measure motivation and engagement are touched upon. 3.1 Extrinsic and Intrinsic Motivators Behaviourism as a model of motivation is built around extrinsic motivators. Extrinsic motivators are motivators that come from outside of the task. A rat has no interest in pulling a lever; it is only interested in the food that follows. Extrinsic motivators work well for mundane tasks; however, for cognitive tasks they can have a negative effect, particularly if the subject performing the task already holds some intrinsic motivation in that task. Pink lists seven negative effects of extrinsic motivation:

Figure 1 Pink's Criticism of Extrinsic Motivators (Pink 2011)

Pink (Pink 2011), Kohn (Kohn) and Werbach (Werbach and Hunter 2012) cite numerous studies in which the negative effects of extrinsic motivators have been recorded. Pink expands that for mundane tasks extrinsic motivators are a good technique, but for any cognitive task they can have a detrimental effect. Instead, it is better for cognitive tasks if there are intrinsic motivators. These motivators come from the task itself, and from the need fulfilment that the task itself can offer. The theory of intrinsic motivation is best embodied by Self Determination Theory, which will be explained in the following section. In describing a “Motivational Continuum” Werbach (Werbach and Hunter 2012) notes that there is not a black and white divide between intrinsic and extrinsic motivators. Werbach gives the example of online role playing games, which can be played alone or as part of a guild. He notes that certain mundane tasks such as collecting items will be performed as part of a group that would not be performed alone. “the users need for relatedness dramatically changes the perceived nature of the motivation” (Werbach and Hunter 2012) Malone et al identified that a focus in educational research on cognitive learning processes have left a comparative void in the area of motivating learning and creating motivating learning environments (Malone 1981; Malone and Lepper 1987). In an effort to fill this perceived void Malone et al attempted to create conditions for learning that rejected extrinsic motivators and embrace intrinsic motivators through engaging with fantasy, challenge and curiosity. John Keller’s ARCS model of motivation (Keller 1987) offers an interesting avenue for further reading. The ARCS model spans several facets of motivation, including both extrinsic and intrinsic motivation by incorporating components of attention, relevance, confidence and satisfaction. The ARCS model also includes a system that can be used to design learning and teaching resources in a motivating way. 24

3.2 Self Determination Theory Particularly applicable to games; Self Determination Theory is a theory of motivation in which participants of a task are motivated by the task itself. It includes the motivation to fulfil three needs; the need for competence in the task, the need for autonomy and the need for relatedness (Ryan 1982; Ryan and Deci 2000; Ryan, Rigby et al. 2006; Rigby and Ryan 2010). Competence (or mastery (Pink 2011)) refers to the feeling that you are good (or at least improving your skills) for a particular task. Autonomy refers to the feeling that you are in control of your actions, and that they are a result of meaningful choices that you have made. Relatedness (or purpose (Pink 2011)) refers to the need to be socially connected to others, and that you are important to those people. These three needs can be categorized as intrinsic motivators, which are inseparable from the task at hand, as opposed to extrinsic motivators, such as points, badges, money or marks. Facilitating intrinsic motivation is of particular importance in education. Ryan and Deci state that “intrinsic motivation results in high-quality learning and creativity” (Ryan and Deci 2000), Cognitive Evaluation Theory (CET) is also worthy of consideration, and is considered a sub-theory for Self Determination Theory (Ryan and Deci 2000). CET places an emphasis on the need for autonomy alongside competence feedback, hypothesising that competence feedback will have no positive affect intrinsic motivation unless it is accompanied by a feeling of autonomy. 3.3 Flow Flow is the work of psychologist Mihaly Csikszentmihalyi who described his studies into the concept of happiness as the psychology of optimal experience (Csikszentmihalyi 1990). The concept of flow describes a state of complete engagement, when a person faces a challenge is well matched to their skill that pushes them towards the limits of their ability. In the world of sports this concept is often described as being “in the zone”. That concept is illustrated in the figure below.

Figure 2 Visualisation of Flow

Figure 2 Visualisation of Flow shows a graph of challenge against skill level for a person carrying out some task, highlighting their emotions as their skill level changes with respect to the level of challenge they are facing. Flow is a valuable concept in games. In an effort to create better games some game designers have latched on to this concept. Although it is unclear whether he was talking specifically about flow, it is


claimed that Nintendo’s legendary game designer Shigeru Miyamoto described directing players into a flow state in a rare interview (2009), describing how it is important to keep the player in a flow channel, enabling them to improve their skills, and to feel mastery. Games designer and founder of ThatGameCompany, Jenova Chen, based his doctoral thesis on the concept of flow in games, and since has made several successful games based around the concept of flow (Chen 2007). These examples of game designers in pursuit of the flow state are indicative of the importance of the concept. In particular, Miyamoto’s description of the need to follow failure with the opportunity for the player to regain control and further improve their skills has parallels with both selfdetermination theory (through feelings of competence) (Ryan and Deci 2000; Ryan, Rigby et al. 2006; Rigby and Ryan 2010) and flexible personalized learning (Gordon 2013). Csikszentmihalyi states that in order to achieve flow “goals are usually clear, and feedback immediate” (Csikszentmihalyi 1990). Feedback is a vital concept both in games as well as learning and teaching. The following section describes feedback mechanism used in games. 3.4 Feedback Mechanisms We know that feedback is important in both education and in games. It is proposed that one reason games are so compelling is their ability to give immediate, focused, individual feedback. Good games are able to do this through a well- designed automated, scalable system. Rigby and Ryan break feedback in games down into three categories. These are granular competence feedback, sustained competence feedback and cumulative competence feedback (Rigby and Ryan 2010). Granular competence feedback is immediate and direct feedback reinforcing the player has done something correctly. Sustained competence feedback comes in the form of multipliers giving the player a feeling of being “in the zone”, and linking back to the concept of flow. Cumulative competence feedback is a persistent recognition of the achievements to date. This technique is particularly prevalent in role playing games such as World of Warcraft (2014) in which player characters accumulate experience, increase character levels and gain new skills as they play. 3.5 Measuring Engagement and Motivation Some institutions require student attendance to be monitored for some aspect of their courses. This is one - albeit crude - mechanism to measure engagement. There are far more sophisticated and comprehensive metrics that can be used to assess engagement. The question remains how do we model, or place a value on engagement? Zichermann and Cunningham identify five metrics for measuring engagement with online business applications (Zichermann and Cunningham 2011). Whilst the ideal proportions will differ depending on the nature of the online business the metrics used are recency, frequency, duration, virality and ratings. One method of measuring motivation is the Intrinsic Motivation Inventory (Ryan, Mims et al. 1983) which describes a questionnaire that assesses competence, effort, value, pressure, autonomy and enjoyment in a given activity. According to selfdeterminationtheory.org (2014) a seventh dimension of relatedness has also been added, but not validated. This section considers a case study of a module utilising source control. The use of source control is a valuable professional skill for any programmer. It is of particular value when learning new concepts because it eliminates the risk associated with experimentation when programming.


Knowing that any previous version is easily available means that there is less impact if a student were to break their code, permitting and promoting freedom to experiment (and learn). Submitting working code to a repository allows the freedom to investigate new concepts safe in the knowledge that a complete, synchronised set of working files is easily retrievable. As noted above, some institutions require that students’ attendance is monitored. One method of monitoring a student’s engagement involves an automated lab based sign in system to track lab attendance within modules, coupled with penalties for non-attendance in the form of an email, followed by more significant sanctions for persistent failure to engage. As described in section 3.1 Extrinsic and Intrinsic Motivators such extrinsic punishments can encourage cheating. That is, signing into a lab and not completing, or even attempting the work allocated. It is proposed that mere attendance in a lab and engagement with a module are not the same thing. It is also proposed that it is entirely possible for a motivated student to engage with a module without attending any lab sessions. The lab work for the module has been structured with a series of “check points”. As the students work through the labs they are instructed to check their work in to version control whenever they make significant progress. By examining data and log messages committed to source control it is possible to measure engagement with individual tasks set within a lab in a more flexible way, instead of insisting that they work during scheduled lab times. This allows students the flexibility, autonomy and self-direction to work at a time that is best suited to them. The check points are described with a designated log message. It is hoped that this gives the student the opportunity to reflect on the work that they have just completed. Additionally, this approach can close the feedback loop providing lecturers with a form of feedback from their students. Valuable information can be gathered by looking at the SVN log about student’s progress both individually and as a group. For example, by looking at SVN data from a lab sequence of five labs a lecturer may be able to learn that half the students are only halfway through the second lab, or that the majority of students spent longer than expected to complete a particular task within the sequence. A long time between commits could indicate that the student is having difficulty, or that the task involves a more significant amount of work, or that the student has become distracted. Analysis of any patterns of check in times outside of labs could give insight into the way students work outside of labs.


Preliminary Results

Over a five week period, from a cohort of sixty three students the total cumulative student engagement with source control is in the region of 1600 interactions. This is in comparison to the usual mechanism of measuring lab attendance, which has recorded only around 300 interactions in the same time period. Initial analysis presented here focuses on the student engagement over time, commits per student and collective student work patterns within and outside of labs. Lab sessions formally begin at 11:15am on a Monday and end at 13:05am. For the purpose of separating the data into lab data and non-lab data


Total Commits Per Day Number of Commmits

400 350 300 250

200 150 100 50 0


Figure 3 Chart of Total Daily Commits Over Five Weeks

The chart shown in Figure 3 shows the number of commits on each day. Unsurprisingly it shows that students were using source control most on lab days. It also shows a general drop in engagement over time, but also a “swell” of activity before and after each lab. This might suggest that to keep student engaged it may be better to have two one hour labs spread out through the week, instead of one two hour one.

Figure 4 Number of Commits per Student Over Five Weeks

The chart shown in Figure 4 shows the total number of commits and the number of students who have made those commits. This is an indication of how far through the lab process each student is after five weeks. A student who is completely up to date with all labs should have around 90 commits. This shows that it is likely that the vast majority of students are trailing behind with the lab work. It also shows that any data presented later may be skewed by the activity of a few students. The activity of the 4 most active students is approximately the same as the activity of the 25 least active students.


Commits During Labs 80

Number of Commits


60 50 40 30 20

10 13:50
























Figure 5 Time of Commits During Lab Sessions

The graph in Figure 5 gives an indication of how students spend their time during labs. Labs formally start at 11:15 and finish abruptly at 13:05 when another lab class takes over the lab space. Figure 5 shows that some students start the lab early, and possibly would continue for longer if they were not displaced by another lab class. There seems to be a normal distribution developing. This suggests that students are active for some time during the lab, but that they arrive late or leave early. This may be partially due to the lab taking place around lunch time. It would be interesting to see how this compares with labs that take place at different times of the day.

Commits Per Day (excluding labs) 180

Number of Commits

160 140 120

100 80 60 40

20 0 Friday





Wednesday Thursday


Figure 6 Number of Commits per Day (excluding lab sessions)

Figure 6 shows the number of commits per day during the week. For this data, the two hours during lab sessions, and an hour either side have been removed from the data set. Again, like in Figure 3 Chart of Total Daily Commits over Five Weeks we can see increased engagement centred around the day of the labs.


Figure 7 Number of Commits per Hour (excluding lab sessions)

Finally Figure 7 shows student engagement patterns. Again commits that were made during lab sessions, or an hour either side of the lab session have been removed from the data set. There is perhaps some influence of the labs in a peak around the lab time. However, this cannot be entirely due to lab sessions between 9:00 AM and 10:00 AM, and cannot explain the increased activity from 10:00 AM to midday as all these commits have been removed. Students seem to work more in the afternoon and evening. It looks like there may be two peaks at 4:00 PM and 8:00 PM, or perhaps a normal distribution developing centred around 6:00 PM, but with something creating an additional trough at the centre of the distribution. Perhaps students break to eat at that time. It would be interesting to do further analysis on this data to see what the impact of individual students, and their work patterns are.


Future work

Future work will include analysing the data from different perspectives, and developing tools to efficiently and quickly analyse this data. Crucially, comparisons should be made between SVN log data, student attendance data and student results to look for patterns and correlation. Currently there is no distinction made between the cognitive requirements of the tasks assigned to students. The next step to better understanding of the data gathered from SVN is to categorise these tasks using some criteria. One potential scheme for categorization is to identify the type of task based on whether the task involves new concepts, or reinforces old concepts, or is designed to test understanding, as well as overall difficulty. Such a categorization scheme should be developed with reference to pedagogical theory.



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Mike Brayshaw

Department of Computer Science, University of Hull, Hull, HU6 7RX, UK [email protected]

Department of Computer Science, University of Hull, Hull, HU6 7RX, UK [email protected]

Abstract This paper describes a Guided Inquiry Based Tutoring System to teach programming, in this case for the language C#. The paper introduces a pedagogically motivated tutoring system that looks at the influential first twenty hours of the learning experience for neophyte computer scientists. In this critical window we aim to combine modern Software Engineering techniques and thinking with Web 2.0/Semantic Web Content Management. We will first discuss content control and educational underpinning, synergizing ideas from Inquiry Based Learning and Guided Discovery Learning. From this we will develop a model about how to realize this within a programming context. Through a series of prototypes we will then demonstrate a working tutorial system. An important feature of this system is that it works within the context of .NET so that the tutorial is located within the context of a modern and popular programming environment. This has the advantage of avoiding the distractions of a separate tutorial system and allowing the users to program and learn within a single context. Following a detailed evaluation study and corresponding modifications we reflect on lessons learned and offer suggestions for future work. Keywords Architectures for educational technology systems, interactive learning environments, pedagogical issues, evaluation of CAL systems



The paper aims to revisit and reflect on educational pedagogy and to comment on how we should teach computer programming. Much in the current Zeitgeist are ideas of teaching from a student’s perspective so that they learn within their own individual, neophyte centric, special experience. The work presented here touches upon Inquiry Based Learning (Vygotsky, 1934; Bruner, 1961; CILASS, 2009) and revisits Guided Discovery Based Learning (Elsom-Cook, 1984, 1990a & b). Here we describe the making of a C# tutorial, with the aim to teach the first 20 hours of programming. As learning to programme is a non-trivial and sometimes traumatic task, it is natural that we should seek special help and support. Consequently we contend that an online tutorial can enhance the experience by providing powerful interaction and more directed guidance than using a book. In the manner described here the tutorial is controlled by its students; hence it is the goal to ensure the tutorial provides a personalized learning experience. The evolution of this work is demonstrated via a series of rolling prototypes. We start with an investigation into C# features, since this will have an important bearing on our overall thinking. We review existing C# tutorials and reflect upon established Learning Philosophies and Learning Management Systems. The Evolutionary Software development lifecycle model (in the


spirit of Gild and Finzi, 1988; Gilb, 2005) was employed and led to the development of an informed selection of working prototypes. From the beginning, evaluation of the final deliverable was of concern. We determined to carry out the evaluation using Undergraduate Computer Science learners and contextualise material and feedback in this light. This however raised pragmatic issues of study size, data gathering, and establishing a shared vocabulary with the student user. As a result the work reported here uses Heuristic Evaluation (Nielsen (1990), Nielsen and Mack (1994), Squires and Preece (1999), Nielsen, (2005), Benson et al, (2001)). Learning how to program for the first time can be an extremely daunting experience (du Boulay et al, 1981). Many students fail to get to grips with key concepts and numerous common misconceptions are introduced (e.g. Soloway and Ehrlich, 1984; Fung et al, 1990). This has led to extensive efforts to provide support in terms of written text, video media, and software (e.g. Eisenstadt and Brayshaw, 1987). In the latter vein, this C# programming tutorial’s main aim is to try and ease the transition of a novice towards understanding the basics of programming and being able to apply these ideas effectively, plus providing the associated backup for those who would guide them in their learning voyage. C# was chosen as a modern platform with advanced support features in order to revisit many of the ideas and problems that the above research had first surfaced, but in a modern context.



There are numerous tutoring systems already in place such as Computer Based Tutorials which consist of online support. Historical developments include Intelligent Tutors such as Anderson’s Lisp Tutor (Anderson et al, 1984) which introduced many of the common issues that tutors of today still have to face. Management System such as Learning Activity Management Systems (LAMS) (Dalziel, 2003), Reusable E-Learning Object Authoring and Delivery (Reload) (Beauvoir et al, 2004) and WebCT (Goldberg, 1997) are also relevant and considered below. Having a control mechanism in the tutorial is beneficial and will be a major focus of the pedagogy that underpins the system. 2.1 Features of C# The work reported here focusses on contemporary software developments; hence the choice of language and tools. The further work section will clearly locate the work within the context of Semantic Web Development and future Communication Models. To develop this contemporary software development context: “Around 1997, Microsoft started a project internally known as Lightning” (Dorman, 2007) which evolved to a "clean-room implementation of Java” (Dorman, ibid) called C#”. Microsoft started development of the .NET Framework in the late 1990’s with the code name "Next Generation Windows Services [NGWS]" (Reddy, 2009). The .NET Framework contains common libraries for Windows Forms and XML document manipulation capabilities with program language support including C++, Visual Basic, JScript, COBOL, Perl, C#, Python, and Smalltalk (XML UK, 2008). Intellisense (Ferracchiati, 2008) a built in feature of C# - provides suggestions on variables and functions to use along with their parameter lists. This reduces the keyboard input, as interactive documentation for the active scope appears dynamically. This feature spots common misconceptions and makes suggestions on how to


overcome them. It even provides line numbers where it believes a mistake has been made. C# includes facilities similar to SQL and may be used to discover the details of anonymous types and make suggestions such as: from, while, in, etc. Linq to XML is particularly powerful, removing the need for individual class definitions. This has been used extensively to simplify the software. There is also a help facility in C# on a wide range of topic areas from basic to advanced. The tutorial presented here aims to integrate with and supplement these features. 2.2 Tutoring Systems Background research focused on gaining an insight into other tutorials, the control mechanisms of the tutorials and the associated learning philosophies. This has in turn had a significant impact in the way the tutorial has been designed and developed. There are numerous examples of Computer Based Tutorials online, a good example is Joe Grips Tutorial which is an “animated interactive tutorial” (Interactive Words & Pictures, 2008). This tutor is notable as it talks to the student explaining in detail about the programming code and then visually highlights the screen to relate to what is being said. As it runs through the tutorial it asks the student to carry out the programming task, providing the student with a hands-on learning experience. This tutor doesn’t require any previous knowledge of programming. Although this tutor is good it does however require the student to listen to what is being said and view the screen. There is no way of seeing how the student has progressed through the tutor system. There is very little text within the tutor and it would require notes to be taken for reference use in the future. Different students learn at different rates (e.g. Eysenck, 1994; Cline, 2002); however, this tutor forces the student to go through the tutorial step by step, which could prove frustrating to the more able user. This lack of personalisation is an issue that we will address. Ideally it should be possible to track and monitor the progress of the student, at least through answered questions and results recorded. Additionally here we will teach in the Windows environment to allow students to utilize the built in capabilities of auto completion (Ferracchiati, 2008; Teitelman and Masinter, 1981). Another example of a CBT is Soft Steel Solutions C# tutorial (Boyce et al, 2008). This tutorial is essentially an ebook on the internet, which clearly shows the C# fundamental principles. It is notable due to the ease of navigation from each lesson and the lessons can be viewed in any order. However, there is a large amount of text shown on one page - this may put the student off continuing with the tutorial. Another essentially hypertext system is Sharpertutorials C# Tutor (Trott, 2008). These tutorials do not provide any hands on programming experience or any form of interactivity. In contrast to our approach where we seek to provide the student with some form of practical programming exercises, with supporting explanations. Devhood C# Tutorial (Chiu et al, 2001) is an example of a CBT. This C# tutorial is essentially an indexed document, containing exercises and source code and allowing easy navigation. However students must be familiar with a programming language already, as the code displayed isn’t explained in a lot of detail. The tutor described here focuses more on running the code and seeing what happens. A further web based C# tutorial is The C# Station Tutorial (Mayo, 2009). The tutorial is broken down into 23 lessons where a link to an associated html or source code file is clickable for each lesson. The lessons contain information, source code and the ability to click a button to run the code. Also there are links to other lessons from the first lesson, which makes navigation between


lessons very easy. This tutorial starts teaching from the command line before moving into the C# environment. This mix between explanation texts, programming code and to click a button to run the executable code has plus points for a beginner. Our C# tutor likewise provides a mix of programming code, and explanatory text to cater for all abilities. The CBT C# tutorial for beginners by Lloyd Galador (Dupont, 2009) is comprised of four tutorials, one after the other on the site. There isn’t any navigation but the tutorial only consists of one page so it is not too hard to move up and down. The tutorial works on the command line and requires the student to enter in code and run the newly created program. This tutorial is essentially a set of programming exercises that requires the student to effectively copy and paste code into Notepad then run it via the command line. The language that is used on the tutorial is extremely motivational for example “Wouah, 25 lines! That's a program!” (Dupont, 2009) this will encourage the students and build confidence. It is important that our C# tutorial uses positive, motivational language to make it user friendly and build confidence. This positive inspiration is in the spirit the The Little Lisper (Friedman and Felleisen, 1987). An interesting online tutorial is by learners paradise.com (Singh, 2008), where a personal tutor will teach the student programming through the use of voice chat, a white board shared in real time between the tutor and the student and remote administration used for practical demonstrations on the students PC. This method of tutorial is unique compared to the others on offer over the internet. The tutor and the student can be anywhere in the world but still able to carry out lessons and get immediate feedback. However the tutor and student have to be available at the same time to conduct a lesson as the communication model is synchronous. When looking at the feedback on this tutorial the following was said about one of the online tutors, as being “excellent at detecting when you do not fully comprehend a concept and comes up with many excellent exercises/examples to help achieve clarity” (Singh, 2008). Another student gave the following feedback about the same tutor: “his teaching is excellent, be prepared for surprised tests while taking his class and I think that's an excellent way to learn” [Singh, 2008]. From this we also incorporate some form of testing or questioning as a way of assessing the application of learning. Although this system is well regarded, it still has a manual element as its core; for scale reasons and availability we here would wish to explore a route to an automated pedagogue. Clearly a related area to our background here are Intelligent Tutoring Systems (e.g. Sleeman and Brown, 1983; Wenger, 1987; Ong and Ramachandran, 2003). The provision of an intelligent agent to control the tuition and the design of an effective user model (Self, 1974; Winkels, 1990) are significant, but we believe yet to be achieved goals. The purpose of the reported research is to pursue an alternative path within a new modern context: the individualisation of learning is explored but from a different starting point, with a focus on semantic net and inquiry based pedagogic approach to frame the problem. So far we have reviewed existing software and internet based approaches. From the point of view of a traditional model what we are trying to do in a pedagogic model is to concern ourselves about the nature of the pedagogic intervention, the so called what, when, and how. Classical approaches to learning are by instruction, e.g. Guided Learning (Anderson and Reiser, 1985, in our context) illustrates this where we can clearly identify the roles of teacher and student. At other times we can use classic Socratic dialogues where misconceptions on the part of the learner and their faulty models can be diagnosed and corrected. A critical notion is that of teacher and pupil, where the 36

pupil has to acquire the knowledge from the teacher via direct instruction. It also assumes that the pupils’ knowledge is a subset, albeit buggy, of the teacher’s knowledge which may not be the case (Freire, 1970; Moyse and Elsom-Cook, 1990). An alternate strand of educational research is one where we focus on the student as the centrepoint of our studies. Inquiry based learning is where you learn in your own space and explore your own zone of experience (Vygotsky, 1934: Boyle, 2004; Brew, 2006). It is very pragmatic because it guides and manages the student during their own learning discovery process, in an open and flexible way. Furthermore, in the context of teaching computer science it builds upon what is already a very familiar and established learning activity (Gordon and Brayshaw, 2008, 2009). Embracing this method of control and learning philosophy as a kernel philosophy here links inherently to how we choose to teach in computer science. Leading from this notion as learning to program being an exploratory experience this work revisits (Papert, 1980), who believed in play learning, where it is possible to get children to play in their own space, constructing new knowledge. It also follows (Elsom-Cook, 1990) who developed Papert’s idea into guided discovery; this is where the teacher recommends challenges, and the learner tries to find solutions using the guidance given. In his original work (Elsom-Cook, 1984) MATILDA worked in the domain of teaching LISP programming. The domain here is the same although the language, tools, environment and use of Internet technologies and the Semantic Web are different. The target of this work is likewise University undergraduate students --- this is reflected in the nature of the guidance proposed. The students are free to explore and learn through discovery rather than what is rote presented to them. The student learns via construction in their own zone, a teacher is a guide to individualised learning, not an instructor per se, and topic and method of learning is determined by the learner, not the teacher. As Freire (1970) points out learning can be a two way process, the teacher teaches the student and the student teaches the teacher. A clearly related learning philosophy is Inquiry Based Learning (IBL/EBL). In this the student is able to do what they want, essentially building their own learning packages ((Gordon and Brayshaw, 2008, 2009; Wen and Brayshaw, 2007; Wen, 2008), but will be guided/ advised to follow certain paths through the system, through the use of recommendations displayed on the screen. In the research presented here we aim to follow both in the spirit of both philosophies. True Guided Discovery aimed to use AI to provide the guiding mechanism, the core of the system being some type of intelligent agency that sought to customise and optimize the learning experience. As such they clearly belonged in the camp of Intelligent Tutoring Systems and embraced the problems that they faced. An alternate approach was to try and make the interface so transparent in function that no further coaching was required (e.g. Eisenstadt and Brayshaw, 1987; 1990). The locust of control was entirely with the student and the virtual machine was so transparent that no further assistance was required. However this had the overhead of learning a second visual virtual machine (Mullholland, 1995). There clearly is still a debate on whether this overall overhead is justifiable. The growth of Semantic Web technologies and advanced communications technologies that have resulted in a revisitation of the above philosophy to see if a third way, combining the two was possible. What has changed is the ability to create on the fly material, delivered via multimedia, and in an interactive way. The work presented here is a first pass look at the new affordances offered. 37

A number of e-learning systems offer functionality relevant to this work. Learning Activity Management Systems (LAMS) (Dalziel, 2003) allows for the design and management of learning resources. LAMS has features such as chat rooms, notice boards, Q&A surveys, multiple choice, surveys, voting, monitoring facilities and forums. This system allows the teacher to monitor the students’ learning and provides teachers with the ability to write sequences between learning tasks. A set of learning designs are provided which allows for ease of creation of educational resources. However LAMS does not allow learners to follow their own learning paths to meet their own requirements. Reusable E-learning Object Authoring and Delivery (RELOAD) provides the ability to make, distribute and re-use learning objects (Beauvoir et al, 2004). It presents the authors preferred units, the relationship between units in a learning content package and each units name, identifier, description, and the standard the unit is built on. Users can use any resource off the internet and put it into the RELOAD system such as pictures, webpage’s etc. These resources are then put together in a particular order chosen by the user within their learning content. They are known as learning units and are made and controlled based on metadata technology (Beauvoir et al, 2004). The learning units are not flexible and are web delivered documents, thus making it difficult for learners or teachers to create individualized learning programs. The last Management system considered here is WebCT (Goldberg, 1997) which provides extensive designing and management capabilities, thus meeting user requirements. WebCT allows for the teacher to customize their course by choosing from the available resources. The resources consist of chat rooms, discussion boards, calendars, online assessments with time limitations, and tracking of learner performance through dedicated learner storage and presentation of their work. The learner follows linear pre-designed paths created by the teachers. The rational for the paths is derived from the teacher as opposed to the paradigm being part of the tool. This will inhibit the learner’s flexibility to learn as they require. In line with our comments about semantic web development the work presented here embraces learning management systems in this new web context. Intelligent Personalisation of Web Services has been investigated elsewhere (Wen and Brayshaw, 2007, Wen et al, 2012; Li, Zhu, and Zhu, 2007; Zhu, Ip, Fok, and Cao, 2007; Wen 2008; Nganji et al, 2011; 2012). As previously noted, Inquiry Based Learning is where the student constructs new concepts and skills by the process of their own investigation. Thus the locust of control remains very much with the student. The work presented here is very much within that philosophy, but is augmented with a Passive Guiding Tutoring template. It thus invokes ideas from Guided Discovery Learning (GDL) with the context of IBL, providing a first pass at combining a student led IBL with a Semantic Web GDL philosophy, and offering important contributions in its own right. 2.3 Introduction/Questions/Answers and Tutorials In order to obtain a vanilla flavoured curriculum the following books were sampled; Visual C# 2005 How to Program (Deitel and Deitel, 2006), The C# programming language (Hejlsberg et al, 2006) and Beginning Visual C# 2005 (Watson et al, 2006), Rob Mile’s C# Book (Miles, 2008), other syllabi were also taken of note (Anderson ibid; Eisenstadt and Brayshaw, ibid). As a consequence it was decided to take the first 20hrs of programming from Introduction to Programming at Hull University (Miles, 2008) for the guidance of what topics should be included and in what order.


The software was evolved using a system of iterative prototypes, firstly using a functional review and laterally with human critics. Prototype 5 is the main prototype, heuristic evaluation was carried out on this prototype, initially by 2 PhD students and then by 5 computer science university lecturers. From the feedback given, prototype 6 was developed. Prototype 7 was evaluated by one of the original evaluators, and 3 new evaluators, and led to prototype 8, with significant changes in the software as discussed later in this paper.


Exploiting the Semantic Web for Tutorial Design

This work is within the context of the Semantic Web and Provision of Web services therein. It thus allows us to revisit previous thinking in the area of guided discovery learning and inquiry based learning, but within this new richer framework. It is our contention here that enquiry is made more powerful within the context of a modern software development environment with associated aids, in addition to a semantic web context to enable a guided learning philosophy. XML is adopted as the core knowledge representation. This system aims to be a complete solution in the spirit of a LMS (Learning Management System (Goldberg, ibid)), thus it will have two essential modus operandi, one for the teacher who needs to manage, monitor, or control the learning experience and that for the student for whom the tutorial is principally designed. A key part of the C# tutorial are XML files, which consist of Admin, Questions and TutorSize. It is done as an XML file so it can be easily adapted using a text editor, external to the program. This allows for easy modification of the program content and makes it possible for the teacher to add questions easily into the associated file if needs be. In this manner the control of the tutorial is extensible. Questions can be split into Sections. This is helpful since each Section has an Introduction and an End of Section Tutorial. Associated with each Question there is feedback. These considerations led to the design of the Questions.XML file. There is also a need to Log on and record the student Answers to a question. This led to the design of the Admin.XML file. The UID element provides a unique id similar to the primary key in a Database. An element called REFERENCE was added to the file Admin.XML to record the student Answers to a question. In addition a Section id, Question id and Question Title are stored. The file is compressed to ensure that it cannot be modified with a text editor. The software employs a GZipStream, that is data read or written to a FileStream is additionally compressed by employing the GZipStream (Watson K et al, 2006). The XML file TutorSize.XML allows the control of the Height and Width of the Tutor Forms. This is developed and shown in prototype 5 Guided Discovery Learning 1.2 Questions Ver. 2 The key to the organisation of the system is Linq (prototype 4 and 5 onwards). The use of the .Descendents method means all the XML elements of a given name may be accessed irrespective of the presence of other XML elements assuming that the XML Document is valid. This means the software is robust in the presence of modification to the XML document (which was the subject of continual enhancements when progressing from one prototype to another).



The C# Tutor

The following is an outline of the software in prototype 5 which was sent for Alpha, Beta and Final Stage Heuristic Evaluation. This prototype in addition to teaching a student also allows for management of the students learning, both are demonstrated in the next few sections. We will begin by describing basic management functions before moving onto a student centric perspective. We start with the generic login.

The key words of particular significance are put in bold so they stand out.

Figure 1: Teacher/Student Initial Screen

On starting, users get the message in figure 1. It makes the point that students can follow their choice of journey if they should so wish but passive guidance, in the way of the Recommendation Tab is available if they should so choose to use it. This is in the spirit of our IBL/GDL hybrid philosophy. The user will either be a Student or Teacher and will need to enter in there logon id and associated password and then press the logon button. A lot of logon systems are designed in a similar manner for example Hotmail. Figure 2: Logon Screen Same for Student and Teacher.

Note currently user Teacher 1 is being used to log on. Each student can have a different login and their associated results are recoded and can be viewed by the teacher and used as the basis of subsequent guidance. This feature may provide a significant area for future work as discussed later. 4.1 Teacher Walk Through Following on from above, we first provide a Teachers’ view from an overall management perspective. They will see the following:


This is a DataGridView of the current students and their passwords.

The buttons shown allow for the administration of the Students accounts

Figure 3: Initial Teacher/Admin Screen showing individual student accounts and associated options.

At the top of screen on (Figure 3) is a display of the current students with management functions shown below. A teacher may Students results by as follows: Listview of Students The Selected Student is marked in red to clearly show the selection that has been made.

Summary of overall results for the student

Break down of Student Results per question, showing if they have not been answered or answered correct/incorrect. Figure 4: Fine grained teacher‘s view, allows monitoring of individual learners’ performance

Figure 4 shows a list of the students which are displayed in the top section. On selecting a student from this display, the selected student is displayed in Red. The overall results for the selected student are displayed in the middle of the display. A more detailed breakdown of the selected student’s answers is given at the bottom of the screen. Using this the teacher is able to monitor and guide the individual students. This is our first pass through this territory. We aim in the future to build upon this in two ways, one is to use AI to personalise Semantic Web material (Wen 2008), the other is to facilitate direct guidance through CMC means and addition Semantic web and visual mediums (Nganji et al 2011). 4.2 Student Walk Through Now let us shift to the learners’ perspective. The Student initially views Figure 1 and then logs in using the same screen shown in Figure 2. The Student is then automatically put in to the recommendation tab (Figure 5) after the Select Section or Select Question is clicked on.


The Recommendation Tab gives a list of step by step navigation suggestions to the Student so they are given some guidance on how to use the tutorial. At the same time they are also free to navigate through the tutorial as they please. As a default, learners work left-to-right across the tabs to complete each learning activity, but this is a guide and users can actually wander at will. A checkbox is shown at the bottom of the tab which needs to be unchecked if the student doesn’t wish to view the recommendations.

Figure 5: Recommendation Tab which implements a passive guidance way of working in the spirit of GDL.

Below is a table of Sections from which an individual learning unit can be selected. Each Section is represented by a colour, which is shown as a banner along the top of the rest of the tabs. This is to help the Student through the use of recognition of the section and associated colour at a glance. For a student to select a section they will need to click on the associated section area. On the left hand side is the difficulty level of the section, recall that this from perspective to the users, they being novices.

Figure 6: An example of an introductory topic screen.

Figure 7 shows us the contents of a typical tutorial screen. All adopted a typical layout for consistency as illustrated below: The colour coded banner to represent a selected section The Section Introduction text has all the programming code written in the colour blue and in a different font to make it clear to read and stand out to the Student. Important information is put in red to make them stand out to the student.

Figure 7: Section Introduction for the section Main to Types.


Figure 8 shows a table representation of questions for a particular section, from which any question can be selected, in any order.

The left had side shows which questions have not been answered, or where attempted if the students answer was correct or incorrect.

This is followed by the question number and the question title. Anywhere in the row can be clicked to select the required question. Figure 8: Question Selection Menu

Figure 9 shows a question that has been selected. To answer a question that hasn’t already been answered the check box would need to be checked if the code successfully compiles or runs otherwise the user is to leave the checkbox blank and click on the answer button. See the evaluation section for the efficacy of this approach. This is the checkbox that needs either a check in it or not depending on what the student believes is the correct answer. Next to the checkbox is an answer button to submit the answer. This is not shown in Figure 13 as the question has already been answered and the outcome of the answer in this case is correct.

This is the associated output from the code above it. Figure 9: Answering and Question Feedback

Figure 10 is of the feedback given on a selected question that has been answered, in this case correctly.


This shows if the student has answered the question; if they have it will show the answer that has been given by the student. This shows what the correct answer is to the question This is where the advice and feedback on the question is given, informing the student of common misconceptions if they have answered it incorrectly. Figure 10 A screen snapshot of the Feedback Tab

Figure 11 is of an End of Section tutorial where a programming exercise is set and should be carried out in C#. This is similar to typical textbooks which contain exercises at the ends of the chapters. Clearly when programming in the large it is not possible to work out the intended semantics of such unsupervised coding. It is therefore not possible to provide further tutoring on these larger projects.

The top part of the tutorial shows what the program written by the student should include. This is an example of some code that could be adapted to include the examples above it.

Figure 11 End of Section Tutorial tab



We first present our evaluation methodology. We then go on to discuss what we learned from it and the repercussions it had for the C# Tutor and the development of subsequent versions. 5.1 Evaluating the Prototype 5 Using Heuristic Evaluation After consideration of the various options we decided to use heuristic evaluation as the method to evaluate the outcomes of the project. Squire and Preece (1999) discuss why it is suitable for assessing learning and usability for educational software. Here it proved to be a fast and effective tool to use and resulted in many changes to the system. The subjects chosen for the main experiment were all experienced deliverers of this type of material at this level; they were thus suitable experts. To use undergraduate students was considered but because of the neophytic nature of their knowledge and vocabulary available to them, we would not gain such deep insights


as using experts. The study thus benefitted from evaluators with many years’ experience with these problems and material. Prototype 5 is the main prototype, Heuristic Evaluation was carried out on this prototype, initially (Beta Testing) with 2 PhD students and then (main test, part one) by 5 university lecturers experienced at teaching introductory programming classes. From the feedback given, prototype 6 was developed. The Heuristic Evaluation led to significant updates in the software. This led to the completion of prototype 6. This version was then sent out to the same 7 evaluators. Their feedback pointed out some fundamental issues which needed to be dealt with, and updates were carried out promptly leading to the completion of prototype 7. This prototype was sent to 5 of the evaluators who had already been sent the previous versions and a new external evaluator who also has had at least 5 years’ experience of teaching introductory programming. One of the evaluators had already commented on prototype 5, had already looked at 6 and when commenting on 7 was glad that the problems they had noted had been resolved in prototype 7. That evaluator along with 3 of the evaluators who had not previously commented on the software provided their feedback. From their feedback a considerable amount of further updates were carried out: specifically relating to the details of the instructions and wording, control mechanisms and feedback, and to the visual coding of the tutorial. Eighteen specific points were identified. In addition the programming experience of the experts also resulted in 10 changes to the actual learning material to improve the technical content. 5.2 Key changes in prototype 8 as a Result of the Heuristic Evaluation As a result of 5.1, significant changes to the overall appearance of the tutor were suggested. We give a couple of example to illustrate the major modifications. The banner shown on the screen shot below is where the self-explanatory commentary (recommendations=guidance) of what to do on this tab is displayed. It is the same on every tab in the tutorial for both the student and the teacher

Figure 12. Prototype 8

The prototype illustrated in figure 12 featured major changes to overall user navigation and how it presented feedback as illustrated above. The moved location of the answering mechanism and the changed program correct/incorrect answering mechanism are illustrated. Additionally the updated text changes dynamically according to the question. 45

For the first end of section tutorial Figure 13 explains how to use the C# .NET environment, and it’s built in capabilities, followed by the programming tutorial. This is important as it makes it clear to the student how to get started and where to do the programming, overcoming an issue an evaluator found.

Figure 13. Revised feedback as a result of evaluation.

A significant reported problem was that of overall navigation. As a result important visual changes were made and the logical control also adjusted. Given the open Inquiry Based nature of the system there is clearly an interesting interplay between freedom and not knowing what to do next. Further changes included when a question is selected the Question and Feedback appears to emphasise the link between the two. This was done to overcome problems experienced with navigation by the evaluators. The evaluators made it clear that students don’t always read instructions, thus the recommendation tab wasn’t consistently being read causing the evaluators problems with navigation. This clearly is an issue for GDL when students do not use the advice when given, though less so for more inquiry based learners. To overcome this each recommendation point was also placed on each tab, so it was clear to the user at each stage of the program what is recommended as the next step of action. The evaluators that read the recommendations found it to be confusing to apply as the tabs kept changing names to correspond with the section and question that had been selected, making the recommendations difficult to follow. To overcome this problem the tabs were given fixed names and the corresponding name was placed in the recommendations. As noted earlier, prototype 6 received particular feedback from one reviewer who had already carried out the initial evaluation. Their feedback led to Prototype 7 as further updates were required. When a section is picked it throws them in to the Section Introduction and when a question is picked it throws them in to the Question tab, increasing tutorial rigidity and control at the cost of cutting freedom on inquiry. The result is to show a visible effect of making a selection thus more intuitive for the student during navigation. It still allows the learner to view any question or section so learning at their own pace and order is still possible. A label on the question tab was


added which clearly states: Program output/ Comment please see below, this makes it clearer to the student the meaning of the question being asked. Prototype 8 was created after the feedback was given on prototype 7 from 3 new evaluators and an evaluator who looked at prototype 7. This led to changes in the software concerning both layout and more importantly control as how to best enable inquiry based digestion of the material.



There have been considerable lessons learnt throughout the duration of the work reported here. This has been reflected in the software. From the initial outset of the project to reaching prototype 8 a significant journey has been undertaken. Early software development was initially due to an investigation into the affordances of C# and the development of a traditional controlled system in the spirit of CBL. As research continued and deepened it led to a freer system which uses advice to guide students through the tutorial. The evaluation used in the tutorial led to significant updates and proved that a greater degree of guidance and the importance of being clear, precise and consistent throughout the tutorial are vital for understanding and navigation of students. It is now clear on reflection that it is essential to strike the correct balance between a system which is heavily controlled and which restricts the student’s movement through the system, to that of a system which is free and allows the student to follow any path. The latter can leave the student feeling lost and overwhelmed whereas the former can cause the student to feel restricted. Prototype 8 has to an extent a combination of freedom and control. The freedom in the tutorial is that any path can be followed and the control can be seen as the guidance given in the form of recommendations and that when a selection is made the consequence of a selection is to put the student into the tab displaying that selection. This proves to be the optimum solution from the prototypes tried and evaluated as navigation is clear but the tutorial is not restrictive, essentially the fundamentals of Inquiry Based Learning (Gordon and Brayshaw, 2008, 2009) and a restricted form of Guided Discovery. This prototype significantly demonstrates the benefits of such an approach. The tutorial adds to the current debate over which teaching method and learning philosophy to employ. The subject matter caters for all ability levels and allows the sections in the tutorial to be carried out in any order thus meeting the needs of each student. Through the end of section tutorials the student is given the opportunity to get some hands on programming experience. They are asked to carry out the tutorials in the .NET C# windows environment so they can benefit from Intellisense. They learn within the environment they may use professionally should they go on to be professional programs thus providing a cradle to grave solution. The tutorial allows students and teachers to log in a secure way thus meeting the aim set out and providing valuable unique records of individual experiences, allowing the teachers to track and monitor the progress of students through the questions being answered and the results being recorded. The teacher is also able to add new students, delete students, reset student’s answers and change a student’s passwords thus meeting this aim and providing the tutorial with some of the capabilities of a LMS. It was noted earlier about the partial success of the Guidance provided in the tutorial as surfaced in the evaluation and although this was partly mitigated against and might be improved with alternative heuristics. This would still provide essentially canned and less flexible guidance then provided in an


ITS Guided Discovery system (Elsom-Cook, 1990b). Its integration with Intellisense, XML, and the knowledge-base of the Semantic Web make it more than just a Branching CAL approach. However, we have noted elsewhere (Wen and Brayshaw, 2007; Nganji et al, 2011) about using the semantic web and intelligence content handling to produce personalised services. An obvious way forward is to look to combine intelligent guide agencies in a manner which would provide intelligent ElsomCook style Guides or Agents (e.g. Zhu et al, 2007) within the overall context of an Inquiry based learning philosophy and approach. Doing so within the context of new communication technologies afforded by the web presents new interaction experiences for our neophyte programmers. With a website synchronous and asynchronous communication can be utilised. Synchronous feedback could consist of IRC’s and asynchronous alternatives could be via bulletin boards or white boards. Open Source possibilities could be looked at to maximise potential uptake. Also some further functionality (e.g. Singh, 2008) could be incorporated such as voice chat and white boards in real time. All this to be populated by Real Learners and Artificial Guides.



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Introduction to WebPA and the WebPA Special Interest Group Report Neil Gordon Department of Computer Science, University of Hull, Hull, HU6 7RX, UK [email protected]

Abstract A Special Interest Group meeting of the international WebPA was held within the more general Learning Technologies workshop. This began with an overview of peer assessment of team work using WebPA, and finished with a more general WebPA meeting about issue around the immediate and future development of WebPA. Keywords Peer assessment; group work; WebPA. A brief Introduction to WebPA Team and group work are recognised as valuable skills, for employability. However, such group work creates some complexities with assessment, one of the biggest challenges being how to assign individual marks when teams submit an overall deliverable or deliverables. One solution is peer and self-assessment, where students indicate the relative contribution through marking and grading criteria. WebPA offers a web based solution, where assessments can be created, and students can submit the views on their own, and their team-mates, relative contributions to the activity. The student teams submit their work for marking by the tutor, and WebPA then uses the student scores to produce a weighting factor for each student in the team, which is applied to the tutor mark to produce individual marks for the students. For details of using WebPA, see Gordon (2010). More information about WebPA, including download and installation it is available at the link under WebPA (2014), with information on the LTI Connector – enabling direct linking to Virtual Learning Environments (WebPA LTI connector, 2014). For notes from the WebPA SiG meeting itself, see the SiG (2014) reference below.

References Gordon N. (2010) Group working and peer assessment — using WebPA to encourage student engagement and participation. Innovation in Teaching and Learning in Information and Computer Sciences 9(1), 20-31. SIG (2014) WebPA Special Interest Group, Available http://www.webpaproject.com/?q=node/487 (Accessed 9 April 2014) WebPA (2014) WebPA Project site (and download of WebPA version 2.0) Available http://www.webpaproject.com (Accessed 9 April 2014)


WebPA LTI connector (2014) Available http://www.spvsoftwareproducts.com/php/webpa-lti/ (Accessed 9 April 2014)

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Melanie King

Matt Mould

Dan Towns

Loughborough University [email protected]

Loughborough University [email protected]

Loughborough University [email protected]

Abstract The WebPA Special Interest Group at Learning Technologies 2014 saw the launch of the new and updated WebPA help and support material.


The Department of Computer Science University of Hull Cottingham Road Hull, HU6 7RX www.hull.ac.uk/dcs

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9 April 2014