A New Competence-based Approach for Personalizing MOOCs in a Mobile Collaborative and Networked Environment

Massive Open Online Courses (MOOCs) are a disruptive new development in higher education which combines openness and scalability in a most powerful way. They have the potential to widen participation in higher education. Thus, they contribute to social inclusion, the dissemination of knowledge and pedagogical innovation and also the internationalization of higher education institutions. However, one of the critical elements for a massive open language learning experience to be successful is to empower learners and to facilitate networked learning experiences. In fact, MOOCs are designed for an undefined number of participants thus serving a high heterogeneity of profiles, with diverse learning styles and prior knowledge, and also contexts of participation and diversity of online platforms. Personalization can play a key role in this process. The iMOOC pedagogical model introduced the principle of diversity to MOOC design, allowing for a clear differentiation of learning paths and also virtual environments. In this article the authors present a proposal based on the iMOOC approach for a new framework for personalizing and adapting MOOCs designed in a collaborative, networked pedagogical approach by identifying each participant’s competence profile and prior knowledge as well as the respective mobile communication device used and to generate matching personalized learning. This paper also shows the results obtained in a laboratory environment after an experiment has been performed with a prototype of the framework. It can be observed that creating personalized learning paths is possible and the next step is to test this framework with real experimental groups.

[1]  José Bidarra,et al.  Universidade Aberta's pedagogical model for distance education: a university for the future , 2008 .

[2]  Nishikant Sonwalkar,et al.  The First Adaptive MOOC: A Case Study on Pedagogy Framework and Scalable Cloud Architecture—Part I , 2013 .

[3]  George Siemens,et al.  The MOOC model for digital practice , 2010 .

[4]  Alfredo Garro,et al.  X-Learn: An XML-Based, Multi-agent System for Supporting "User-Device" Adaptive E-learning , 2003, CoopIS/DOA/ODBASE.

[5]  Albert Sangrà,et al.  MOOC Design Principles. A Pedagogical Approach from the Learner"s Perspective , 2013 .

[6]  Marco Ronchetti,et al.  A general architecture to support mobility in learning , 2004, IEEE International Conference on Advanced Learning Technologies, 2004. Proceedings..

[7]  Eva García,et al.  Comparing the performance of evolutionary algorithms for permutation constraint satisfaction , 2011, GECCO '11.

[8]  Max M. North,et al.  To Adapt MOOCs, or Not? That Is No Longer the Question. , 2014 .

[9]  Francis Brouns,et al.  A networked learning framework for effective MOOC design: the ECO project approach , 2014 .

[10]  José Mota,et al.  Innovation and openness through MOOCs: Universidade Aberta's pedagogical model for non formal online courses , 2013 .

[11]  George Siemens,et al.  Courses : Innovation in Education ? , 2013 .

[12]  Antonio Garc,et al.  EVOLUTIONARY ALGORITHMS TO SOLVE LOOSELY CONSTRAINED PERMUT-CSPS: A PRACTITIONERS APPROACH , 2012 .

[13]  Carlos Delgado Kloos,et al.  Proposal for a Conceptual Framework for Educators to Describe and Design MOOCs , 2014, J. Univers. Comput. Sci..

[14]  Greg McVerry,et al.  The CCK08 MOOC – Connectivism course, 1/4 way – Dave’s Educational Blog , 2018 .

[15]  Zahir Tari,et al.  On the Move to Meaningful Internet Systems. OTM 2018 Conferences , 2018, Lecture Notes in Computer Science.

[16]  Hélène Fournier,et al.  The value of learning analytics to networked learning on a personal learning environment , 2011, LAK.

[17]  J. Daniel,et al.  Making Sense of MOOCs : Musings in a Maze of Myth , Paradox and Possibility Author : , 2013 .

[18]  David George Glance,et al.  The pedagogical foundations of massive open online courses , 2013, First Monday.

[19]  Carlos Delgado Kloos,et al.  Adapting an Awareness Tool for Massive Courses: the Case of ClassON , 2014, J. Univers. Comput. Sci..

[20]  Eva García,et al.  An empirical study on m-learning adaptation: Learning performance and learning contexts , 2015, Comput. Educ..

[21]  António Teixeira,et al.  3 A Proposal for the Methodological Design of Collaborative Language MOOCs , 2014 .

[22]  Audrey Watters Top Ed-Tech Trends of 2015? , 2015 .

[23]  Antonio García Cabot,et al.  Adapting learning content to user competences, context and mobile device using a multi-agent system: case studies , 2014 .

[24]  Fatos Xhafa,et al.  A Review on Massive E-Learning (MOOC) Design, Delivery and Assessment , 2013, 2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing.

[25]  Olga C. Santos,et al.  Extending web-based educational systems with personalised support through User Centred Designed recommendations along the e-learning life cycle , 2014, Sci. Comput. Program..