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

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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Summary

12. Exportation

13. Analysis
Size: proportional with
total of comments
Red: in-degree bigger
than out-degree
Blue: out-degree bigger
than in-degree

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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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