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Inquiry-based Learning & MOOCs: Challenges & Opportunities

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Presentation at the FutureLearn academic network at the Open University UK, Milton Keynes on June 15, 2015

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Inquiry-based Learning & MOOCs: Challenges & Opportunities

  1. 1. Inquiry-based Learning & MOOCs: Challenges & Opportunities Vitomir Kovanović School of Informatics THE UNIVERSITY of EDINBURGH v.kovanovic@ed.ac.uk @vkovanovic The Open University, UK 15 June 2015 http://goo.gl/6tPjuj
  2. 2. MOOCs: Revolution or evolution? “Disruptive Change” “Tsunami is coming” “Year of the MOOCs” 2 MOOC Hype is passing Media coverage is decreasing and is getting more productive (Kovanovic et al., 2015b)
  3. 3. MOOCs: Current progress of DE ● MOOCs were envisioned as “social-constructivism 2.0” Anderson & Dron (2010): Cognitive-Behaviorism Social Constructivism Connectivism 3 cMOOCs xMOOCs Modern DE/OL Learners do not acquire knowledge, they construct knowledge
  4. 4. MOOCs: Current progress of DE ● In some aspects, xMOOCs are even a step back in online learning ○ Step back to cognitive-behaviorist learning models ○ Step back because of practical reasons ● We need to look what we already know from distance/online learning (Kovanović et al., 2015c) 4
  5. 5. Goal: More social MOOCs ● Goal to enable for an environment in which students are able to learn together at scale ○ Online discussions should be better ■ Currently work mostly as Q/A ■ More knowledge building in discussions ○ Currently, students are having solitary experiences in MOOCs at scale ● Look at the existing models of DE/OL in MOOC context Community of Inquiry (CoI) model (Garrison, Anderson, & Archer, 1999) 5
  6. 6. Community of Inquiry (CoI) model Social presence Cognitive presence Teaching presence Educational experience 1. Affectivity 2. Interactivity 3. Group cohesion 1. Triggering event: Problem identification, sense of puzzlement 2. Exploration: Brainstorming, Idea exploration, divergence 3. Integration: Synthesis of relevant information 4. Resolution: Problem resolution, testing application 1. Design & Organization 2. Direct instruction 3. Facilitation Garrison, Anderson, and Archer (1999) 6
  7. 7. CoI instruments Quantitative coding schemes for each of the presences: ● Labour-intensive manual coding ● Requires experienced coders 34 likert items survey instrument ● 13 Teaching presence ● 9 Social presence ● 12 Cognitive presence 7
  8. 8. MOOCs: Challenges CoI (and other social-constructivist) models require a strong teacher’s presence -> up to 30-40 student cohorts (Anderson & Dron, 2010) MOOCs? ● In short, just too many students for strong teaching presence during course 8
  9. 9. How different is MOOC context? ● We evaluated CoI survey instrument ● Data from 5 MOOCs ● Exploratory Factor Analysis (EFA) of existing CoI survey instrument ● Structural Equation Model (SEM) of relationships between three presences
  10. 10. CoI EFA in MOOC context 34 Survey Items 3 Latent Factors (TP, CP & SP)
  11. 11. CoI EFA in MOOC context Resolution & application Affectivity Course design & organization 11
  12. 12. How different is MOOC context? ● Course design & organization are particularly important ● Less affective communication ● Application & resolution are not reached most of the time
  13. 13. CoI SEM in MOOC context SEM model of relationships between presences Main findings: ● Strong direct effect of TP on CP ● SP mediator between TP and CP 13
  14. 14. CoI SEM in MOOC context ● Moderately good fit (RMSEA = 0.09) ● Stronger direct effect of TP on CP ● Lesser mediating effect of SP 14 (0.52) (0.51) (0.40)
  15. 15. Summary: How much different is the MOOC context? ● Basic CoI model still holds ● In MOOCs, social presence is not developed as good as in traditional DE/OL courses. ● Teaching presence is still very important
  16. 16. Goal: More social MOOCs through Learning Analytics and Data Mining ● Build on the existing models such as CoI ● Make MOOCs “feel smaller” ● Overcome barriers for social-constructivism in MOOCs 16
  17. 17. Goal: More social MOOCs through Learning Analytics and Data Mining ● Build on the existing models such as CoI ● Make MOOCs “feel smaller” ● Overcome barriers for social-constructivism in MOOCs Automate as much as possible 17
  18. 18. Current work: automated message classification (Kovanovic et al., 2014) 18 ● Automatically classify messages in accordance with CoI coding scheme ● Faster and much cheaper use of CoI model ● Provide feedback to students and instructors in real- time ● Wider adoption of CoI model ● Better insights into CoI coding scheme
  19. 19. Current work: Profiling students by the technology use (Kovanovic et al., 2015a) 19
  20. 20. 20 Thank you
  21. 21. References I Anderson, T., & Dron, J. (2010). Three generations of distance education pedagogy. The International Review of Research in Open and Distance Learning, 12(3), 80–97. Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical Inquiry in a Text- Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2–3), 87–105. Kovanović, V., Joksimović, S., Gašević, D., & Hatala, M. (2014). Automated Content Analysis of Online Discussion Transcripts. In Proceedings of the Workshops at the LAK 2014 Conference. Indianapolis, IN. Retrieved from http: //ceur-ws.org/Vol-1137/ 21
  22. 22. References II Kovanovic, V., Gašević, D., Joksimović, S., Hatala, M., & Adesope, O. (2015a). Analytics of communities of inquiry: Effects of learning technology use on cognitive presence in asynchronous online discussions. The Internet and Higher Education, (in-press). Kovanović, V., Joksimović, S., Gašević, D., Siemens, G., & Hatala, M. (2015b). What public media reveals about MOOCs. British Journal of Educational Technology 43(3), 510-527. Kovanović, V., Joksimović, S., Skrypnyk, O., Gašević, D., Dawson, S., & Siemens, G. (2015c). The history and state of distance education. Athabasca University. 22
  23. 23. 23 Questions?

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