Getting lost in MOOCs – Identifying Key Learners to ...

Getting lost in MOOCs – Identifying Key Learners to Ease (Open) Online Education Stephan Schl¨ ogl MCI Management Center Innsbruck Dept. Management, Communication & IT Innsbruck, Austria [email protected] Peter J. Mirski MCI Management Center Innsbruck Dept. Management, Communication & IT Innsbruck, Austria [email protected] Reinhard C. Bernsteiner MCI Management Center Innsbruck Dept. Management, Communication & IT Innsbruck, Austria [email protected]

Abstract The market of Internet-based education is constantly growing. More and more universities offer free lectures, attracting students from all over the world to engage in online learning activities. While this trend may generally be seen as a boost expanding the educational outreach, it also bears a number of deficiencies. In particular, we face the challenge of loosing the inter-personal layer, which typically eases the learning in small(er) study settings. In this paper we therefore argue that ‘key learners’, i.e. course participants that offer important skills (e.g. technically savvy students, critical thinkers, and creatives), may help to close this gap by potentially taking on mentorship roles. However, in order to identify these participants we require better integrated learning solutions.

Author Keywords Online Education, MOOC, Integrated Learning Solutions Paste the appropriate copyright statement here. ACM now supports three different copyright statements: • ACM copyright: ACM holds the copyright on the work. This is the historical approach. • License: The author(s) retain copyright, but ACM receives an exclusive publication license. • Open Access: The author(s) wish to pay for the work to be open access. The additional fee must be paid to ACM. This text field is large enough to hold the appropriate release statement assuming it is single spaced.

ACM Classification Keywords K.3.1 [Computer Uses in Education]: Collaborative Learning; K.3.1 [Computer Uses in Education]: Distance Learning.

General Terms Human Factors

Introduction

Problem Space

Recently we have seen dramatic changes in the online education landscape. Although Internet-based learning has been around for more than a decade, access was usually limited to those who were able to cover costly tuition fees. The big turning point came in 2011 when Stanford University started offering three computer science courses online, and most notably free of charge1 . More than 400.000 students signed up and with that opened the educational chapter of Massive Open Online Courses (MOOC). Today many of the leading universities in the U.S., and increasingly also in Europe and Asia, offer free learning material, usually provided in the form of courses and lectures hosted at one of the various open learning platforms (e.g. Coursera2 , Udacity3 ). In this way students not only have access to lecture slides, notes and exercises, from often highly esteemed professors, but are also given the chance to freely engage in an interactive learning experience with peers from all over the world. Sometimes these courses are even used as a compulsory extension to existing in-class lectures, permitting educators to focus more intensively on those aspects of learning that require face-to-face contact (e.g. direct tutoring and personal feedback) [?]. Given this trend we would therefore argue, that MOOCs, and other types of Internet-based learning, can on the one hand be seen as a great chance to bridge the educational gap, and on the other hand as a precious instrument to improve existing in-class education. However, we also see a number of challenges that need to be overcome if we want to create a more established model of (open) online education; most notably of which is the lack of inter-personal contact, which often plays an important role for successful knowledge transfer.

When using an online platform students are usually able to engage in their learning experience whenever and wherever they are. This flexibility with respect to time and place may be seen as the most important advantage of Internet-based education. However, it could also be considered as its biggest challenge, as without adhering to a strict schedule students often face the problem of interacting with one another. Hence, if we want to improve online learning in general and large-scale learning (as it is depicted by MOOCs) in particular, we first should look at principles of knowledge transfer and how it can be achieved.

1 http://online.stanford.edu/ 2 https://www.coursera.org/ 3 https://www.udacity.com/

From the literature [?] we can see that any type of learning, whether it is carried out online or in the more traditional face-to-face form, deals with the challenge of effectively passing knowledge from a ‘knowledge holder’ to a ‘knowledge seeker’. This transfer may be achieved in various ways, ranging from classical approaches where a learner acquires knowledge directly from an educator, to more interactive procedure such as aligning new knowledge with already existing experiences, or creating knowledge through conceptualization, contextualization and reflection. Using such a general understanding of the knowledge acquisition process we may further distinguish between self-directed learning and learning through social or socio-technical interaction. Sfard [?] emphasizes this distinction by separating people’s engagement with learning in two different metaphors: 1) pure knowledge acquisition; and 2) participation. The knowledge acquisition method reflects the formal setting in which students learn directly from an educator without engaging in additional community discourse. The participation method, on the other hand, promotes knowledge expansion through discussion and reflection. From an

online learning perspective this second method seems particularly important, as due to the number of students potentially involved in an online course, direct interaction with an educator (i.e. a professor or teaching assistant) is often impossible. This furthermore leads to the often underestimated role of university lecturers and professors being not only educators but also important mentors and motivators. Limited physical interaction, as it is the case in online education, can be seen as a critical threat to this master-student relationship.

Vision Given the above described problem space we believe that interactive and ‘involved’ learning may not only require advanced learning management systems and tools like Moodle4 , Sakai5 or Blackboard6 , but also a better understanding of the social norms related to the exchange of information. For example, communities of practice and the way they exchange information may serve as an inspiration for future peer-to-peer learning solutions [?]. The connectivist theory, which dismisses the classical educator-learner model and instead focuses on the distribution of knowledge through engagement with peers, already offers an adequate theoretical framework for community-based learning [?]. What is missing, however, are concepts and best practices which both technologically and pedagogically facilitate interactivity and knowledge exchange between students. Along theses lines Kop [?] has highlighted three important challenges that need to be tackled: 1) the aspect of self-directed learning where a student needs to be given the possibility to autonomously engage in the aggregation, relation, creation and sharing of content; 2) the aspect of presence as a key factor for 4 https://moodle.org/ 5 https://sakaiproject.org/ 6 http://www.blackboard.com/

motivation (i.e. actively taking part in a study group helps to achieve regularity and consequently supports the learning progress) and as a basis for knowledge exchange (i.e. the more peers one has to interact with the more reflection is possible); and 3) the aspect of critical literacy, which describes the need for course participants that posses critical thinking and innovation abilities as well as the necessary technological skills to support this process through self-created and adequately structured content. In particular the third point, which essentially focuses on ‘key learners’, may be seen as a core requirement for future learning solutions. That is, usually it is rather unlikely that all course participants have the required technological skills as well as the creativity that leads to a perfect learning experience. However, if we can identify those participants that have the ability to trigger critical thinking and reflection in others, we will be able to increase the overall motivation and at the same time improve the knowledge transfer within the course. We are especially thinking of ‘learning facilitators’, ‘critical thinkers’, ‘data integrators’ and ‘practitioners’ who would, when put in the right context, fertilize interdisciplinary thinking and reflection, and consequently may take on a certain mentoring role. We therefore believe that the key to future learning solutions lies in offering ways of identifying these ‘key learners’ and integrating them into the ongoing learning process.

Potential Solution Based on the here described vision our proposed solution for future online learning is that of a heterogeneous landscape of different tools and technologies embedded into an overarching pedagogical concept – a concept that better integrates educators, critical students (i.e. ‘enablers’) and the university’s information system.

Taking into account the tremendous pace with which new technologies are developed, we furthermore believe that universities need to work intensively on integration aspects, so that their learning solutions more and more become the center piece of their course landscape, increasingly blurring the border between in-class and online education. For example, while today’s MOOCs offer access to a wide range of knowledge holders (i.e. course participants) in different fields and with various levels of expertise, it is still difficult to identify these peers in order to better orchestrate the overall learning experience. Deeper integrated learning solutions can help pin-point theses ‘key learners’, so that it is possible to analyze their contributions and consequently optimize a course’s discussions and information exchange. Finally, we believe that this focus on course participants as an integral aspect of (open) online learning should also be taken into account when it comes to matters of accreditation. Given the fact that learning at a university level does involve more than understanding, remembering and analyzing, we believe that the quality assurance of courses should not be restricted to the assessment of curricula. Rather, the full transfer of knowledge that leads to deep understanding and the creation of new knowledge built on rich discussions, should be considered as the main quality measurement. Moreover, we would suggest that the underpinning pedagogy may be seen as an additional evaluation criteria, extending the content perspective of an online course by a socio-technical factor that evaluates knowledge transfer.

Current and Future Work At MCI Management Center Innsbruck we have already started implementing the above described vision. So far our main focus was on the system integration aspect,

where the interaction between students, educators (i.e. professors, lecturers, teaching assistants) and administrative university personnel has been optimized by integrating all the data and necessary processes into a central software system. In a next step we will now explore solutions for the identification of ‘key learners’ and their potential role as motivators and mentors. A full-fledged online degree program, whose development is currently in progress, should provide us with an optimal framework for testing and implementing these ideas.

References [1] Argote, L., and Ingram, P. Knowledge transfer: A basis for competitive advantage in firms. Organizational Behavior and Human Decision Processes 82, 1 (2000), 150–169. [2] Fox, A. From moocs to spocs: Supplementing the classroom experience with small private online courses. Communications of the ACM 56, 12 (2013). [3] Kop, A., and Hill, A. Connctivism: Learning theory of the future or vestige of the past. The International Review of Research in Open and Distance Learning 9, 3 (2008). [4] Kop, R. The challenges to connectivist learning on open online networks: Learning experiences during a massive open online course. International Review in Open and Distance Learning 12, 3 (2011), 19–38. [5] Sfard, A. On two metaphors for learning and the dangers of choosing just one. Educational Researcher 27, 2 (1998), 4–13. [6] Wenger, E. Communities of Practice: Learning, Meaning, and Identity. Cambridge University Press, 1998.

Stephan Schl¨ ogl is assistant professor at MCI Management Center Innsbruck. He holds an MSc in Human-Computer Interaction from University College London and a PhD in Computer Science from Trinity College Dublin. His post-doctoral research was conducted at Institute Mines-T´el´ecom, T´el´ecom ParisTech. Stephan’s main research interest lies in the area of Human-Computer Interaction and Interaction Design. Furthermore he investigates aspects of Computer Supported Cooperative Work, and Information and Knowledge Management. As an MCI faculty member Stephan is also involved in teaching activities. He holds courses in User Experience, Software Engineering, Business Intelligence and Artificial Intelligence. Stephan is actively involved in the expansion of the online learning solutions at MCI, testing new concepts and potential ideas for knowledge transfer. Peter J. Mirski is professor and authorized officer at MCI Management Center Innsbruck. He is director of the academic department “Management, Communication & IT” as well as the central university management service“IT & Learning Solution”. Peter holds his degrees in management (electives in business informatics) from Leopold-Franzens University of Innsbruck. He teaches classes in the field of Business Informatics, Project

Management, eLearning, Research Management and Design Thinking. Peter is also founding CEO of the Trans IT Transfer Center University Innsbruck PLC as well as the PDAgroup GmbH. He has led several national and international research and development projects and is an active member in various regional, national and international boards such as the official eLearning association of Austria (founding member), the regional IT-Cluster board, or the SAP University Alliances. Reinhard C. Bernsteiner is professor at MCI Management Center Innsbruck. He holds degrees in Business Administration and Computer Science from Johannes Kepler University Linz. He also attended postgraduate studies at the Technical University of Vienna where he is still a graduate faculty member. His main research activities focus on technologies that support collaborative work. Furthermore he is interested in Information Engineering and Information Management, in particular investigating new media and tools for Knowledge Management and Decision Making. He teaches in different degree programs within the MCI as well as in other universities. Before returning to the academic world, Reinhard has also worked in industry, where he gained experience in a number of national and international projects.