2014 04 03 (educon2014) emadrid uam towards a collaborative pedagogical model in moocs


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2014 04 03
towards a collaborative pedagogical model in moocs

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2014 04 03 (educon2014) emadrid uam towards a collaborative pedagogical model in moocs

  1. 1. Towards a Collaborative Pedagogical Model in MOOCs *Iván Claros, **Leovy Echeverría, *Antonio Garmendía, *Ruth Cobos *{ivan.claros, antonio.garmendia, ruth.cobos}@uam.es, ** leovy.echeverria@estudiante.uam.es Department of Computer Science Universidad Autónoma de Madrid Madrid, Spain
  2. 2. Outline • Motivation ▫ Massive Open Online Courses (MOOCs) ▫ Collaborative Learning • Two Collaborative Learning Approaches ▫ Social Media Learning System ▫ Teaching Assistant System • Discussion ▫ Are possible massive collaborative learning experiences? • Conclusion and Future Work
  3. 3. What we Know about MOOCs • Massive Open Online Course ▫ Distributed shared space for learning ▫ Large-scale feedback and interaction ▫ Open and Online: free and universal access ▫ But have rules: at the end is a Course • Examples ▫ Coursera (https://www.coursera.org/) ▫ Udacity (http://www.udacity.com/) ▫ edX (https://www.edx.org/) ▫ Miríada X (http://miriadax.net/)
  4. 4. What we Know about MOOCs • Stephen Downes (2011) ▫ xMOOCs (Coursera, edX)  Formal (traditional)  Structured  Centralized discussion forum support ▫ cMOOCs (CCK-Style)  Distributed  Chaotic  Learners create and share artefacts  Often blog, forum or personal space
  5. 5. What we Know about MOOCs • Multiple services ▫ Centralized: forums, mails ▫ Decentralized: social media (blogs, social networks, …) • Content ▫ Fragmented - distributed resources - Sharing ▫ Format - short video (Multimedia) lectures • Learners ▫ Foster Autonomous, Self-regulated ▫ Peer-learning ▫ Knowledge is generative • Assessments ▫ Quiz, test, creation artefact, peer-commented ▫ Learning analytics
  6. 6. What we don’t Know about MOOCs • MOOC requires a flexible pedagogical model based on a high interaction and self-motivation. ▫ The collaborative learning approach seems to be the answer, or at least a starting point.  What happens with a massive collaboration? • Social Media (Web 2.0) ▫ Wikis, Blogs, Microblogs, Videoblogs, and others. ▫ Such platforms allow communication and social interaction  Is this enough for supporting a collaborative learning experience in a MOOC context?
  7. 7. Two Collaborative Learning Approaches • Social Media Learning System (Claros & Cobos, 2013) ▫ High support to social interaction processes around the composition of interactive multimedia learning objects. • Teaching Assistant System (Echeverría & Cobos, 2013) ▫ Extends a LMS (Moodle) to support a collaborative instructional model, helping the design of collaborative learning scenarios and assessment processes.
  8. 8. Social Media Learning System • Theoretical base ▫ Active Learning (Bonwell and Eison, 1991) ▫ Multimedia Learning (Mayer, 2002) • Services ▫ Social Media environment (Facebook + Youtube) ▫ Tagging ▫ Comments ▫ Rates ▫ Resource Management
  9. 9. Social Media Learning System Analysis Synthesis Composition Consume Searching Creating Evaluating Playing Structured Resources And Concepts Shared Database Interactive Multimedia Learning Script Feedback and Interactivity
  10. 10. Social Media Learning System • Monitoring Process ▫ Three types of interfaces  Summary: view embedded with basic reports  Exportation : formats such as VNA (for Social Network Analysis), ARFF (for datamining) and CVS (for standard analysis).  Analysis: views embedded with metrics and indicators about collaborative processes. For instances, Sociographs.
  11. 11. Summary
  12. 12. Exportation
  13. 13. Analysis Size: proportional with total of comments Red: in-degree bigger than out-degree Blue: out-degree bigger than in-degree
  14. 14. Social Media Learning System • Assessment Process ▫ Traditional Learning outcome assessment complemented by three perspectives:  Individualistic: individual accountability.  Cooperative: contribution to community.  Social Acceptation: peer-assessment measured by interactions derived from his actions.
  15. 15. Teaching Assistant System • Theoretical base ▫ A collaborative instructional model based on the Group Investigation method (Sharan & Sharan, 1994) • Four interconnected elements ▫ Topics ▫ Collaborative learning scenarios ▫ Activities ▫ Assessments • Two workspaces ▫ Instructor’s ▫ Student’s
  16. 16. Teaching Assistant System • Instructor’s Workspace ▫ The Task Manager ▫ The Assessment Manager ▫ The Report Manager • Student’s workspace ▫ The Assessment Manager ▫ The Report Manager
  17. 17. Teaching Assistant System • Monitoring Process ▫ Feedback about the students’ progress in their learning process. ▫ The Report Manager tool embedded in this assistant contains an algorithm that monitors the students’ interactions ▫ Two types of accomplishment rules  Number of activities .  Deadline of activities.
  18. 18. Teaching Assistant System • Assessment Process ▫ Two type of assessment: the collaborative learning process and the collaborative learning product assessment. ▫ Assessment criteria in each collaborative learning scenario:  Max/Min grades  Penalty Period.
  19. 19. Technological features • Standard Web technologies: HTML5, JS, CSS. • Social Media Learning System ▫ Integration with social networks Facebook and Youtube. REST and Open services. • Teaching Assistant System ▫ Moodle Modules Extensions.
  20. 20. Discussion • A collaborative learning activity requires several conditions, for instances: ▫ A common goal (Dillenbourg, 1999) ▫ Positive interdependence (Johnson & Johnson, 1999) ▫ Coordination and Communication (Gutwin & Greenberg, 2004) ▫ Individual accountability (Slavin, 1996) ▫ Awareness (Janssen et. al, 2007)
  21. 21. Discussion • Peer-assessment is a scalable assessment strategy, however implicit mechanisms are required, for instance through interaction analysis. • Teachers ▫ Cannot control all the processes ▫ Facilitator in learning processes ▫ He/she needs assistance to facilitate design, monitoring and assessment processes
  22. 22. Conclusions • This paper has presented two collaborative learning approaches: the first one supported by social media services, and the second one supported by the LMS Moodle. • This work has presented the main strategies related with the design, assessment and monitoring processes for both approaches. • Both students and teachers require new services. • As future work, the environments that support the proposed approaches would be integrated to MOOCs.
  23. 23. References • I. Claros, and R. Cobos, "Social Media Learning: an Approach for Composition of Multimedia Interactive Object in a Collaborative Learning Environment". In Proceedings of the 17th IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD 2013), 2013. • L. Echeverría, R. Cobos and M. Morales, Designing and Evaluating Collaborative Learning Scenarios in Moodle LMS Courses. In Cooperative Design, Visualization, and Engineering. Springer Berlin Heidelberg, 2013, pages 61–66. • Y. Sharan and S. Sharan "Group investigation in the cooperative classroom". In S. Sharan (Ed.) Handbook of Cooperative Learning Methods. Greenwook Press, 1994. • P. Dillenbourg, What do you mean by collaborative learning?. Collaborative-learning: Cognitive and computational approaches, 1999, 1-19. • D. W. Johnson, and R. T. Johnson, An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 2009, 38(5), 365. • C. Gutwin, and S. Greenberg, The importance of awareness for team cognition in distributed collaboration. In E. Salas & S. M. Fiore (Eds.), Team cognition: Understanding the factors that drive 455 processes and performance, 2004, pp. 177–201. • R. E. Slavin, Research on cooperative learning and achievement: What we know, what we need to know. Contemporary Educational Psychology, 1996, 21(1), pp. 43–69. • J. Janssen, G. Erkens, G. Kanselaar, and J. Jaspers, Visualization of participation: Does it contribute 465 to successful computer-supported collaborative learning? Computers & Education, 2007, 49(4), pp. 1037–1065.
  24. 24. Towards a Collaborative Pedagogical Model in MOOCs *Iván Claros, **Leovy Echeverría, *Antonio Garmendía, *Ruth Cobos *{ivan.claros, antonio.garmendia, ruth.cobos}@uam.es, ** leovy.echeverria@estudiante.uam.es Department of Computer Science Universidad Autónoma de Madrid Madrid, Spain