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Learning Analytics and student feedback
The document discusses learning analytics, defined as the measurement and analysis of data to enhance learning environments. It highlights early research, interdisciplinary methodologies, and formative assessments' importance in predicting academic outcomes. Key projects and findings, such as the 'Signals' project that improves student performance through real-time feedback, are also presented.
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Learning Analytics and student feedback
- 1. Learning Analytics andStudent Feedback Professor Denise Whitelock The Open University, Walton Hall, Milton Keynes MK7 6AA, UK [email protected]
- 2. Learning Analytics andStudent Feedback • What is Learning Analytics? • Origins • Early work • Learning Analytics and Assessment DMW UOC May 2013
- 3. Definition “Learning Analytics areconcerned with the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs”. Reference SoLAR, Open Learning Analytics: An Integrated & Modularised Platform, White Paper, Society for Learning Analytics Research, 2011. DMW UOC May 2013
- 4. Interdisciplinary Research • ComputerSciences • Learning Sciences • AIED • Data Mining specialists DMW UOC May 2013
- 5. Middle Space • 3rd LAKConference • Learning explicit • New analytic methods • Computational • Representational • Statistical • Visualisation DMW UOC May 2013
- 6. Can LAK holdtogether for long? • Challenges • Different methodologies • Different theories • Different predjucies • Agreement on topics 3rd LAK 2013 • Visualisation, social network analysis, communication and collaboration, discourse analytics, predictive analytics, sequence analytics, assessment After Suthers & Verbert (2013) DMW UOC May 2013
- 7. Political and economicdrivers • Educause Review (2007) • Academic Analytics, Campbell & Oblinger (2007) • Large data and stats = predictive modelling • Improve number of graduates in US • US finding now with school exam data • Hand code • M.L. • Apply whote set • Make predictions DMW UOC May 2013
- 8. Formative Research towardsseparate field • Open Learner models (Bull & Kay, 2007) • Social Network analysis (De Laat et al, 2007) • Networks Adapting Pedagogical Practice (SNAPP), (Dawson et al, 2010) • Visualisation of large data sets, Honeycomb (van Ham et al, 2009) • Gephi: open source tool (Bastian et al, 2009) • Signals (Arnold, 2010) DMW UOC May 2013
- 9. Signals: Flagship Project •Moves data from VLE • Combines with prediction models • Real time red/amber/green traffic lights • Pilot study (Arnold, 2010) showed • Students sought help earlier • 12% more B/C grades • 14% less D/F grades DMW UOC May 2013
- 10. Formative Assessment andLearning Analytics (1) Tempelaar et al, 2013 • 1st year Math & Stats undergraduates, Maastricht • Reason text book • Online questions • Practice and performance tests • 92% higher practice pass • 51% lower practice pass DMW UOC May 2013
- 11. Formative Assessment andLearning Analytics (2) Important for SAFeSEA? • Learning styles (Vermunt, 1996) • Self regulation for deep learning • Practice for stepwise learning • Motivation and engagement wheel (Martin, 2007) • Learning emotions • Pekrun’s control-value theory of learning emotions DMW UOC May 2013
- 12. Performance of videolectures • Findings from Mirriahi & Dawson (2013) • Correlations between quizzes and lectures • Shows misalignment between Assessment and Teaching materials? DMW UOC May 2013
- 13. HOU2LEARN • PLE fromHellenic Open University • Social network analysis and final grades • Online collaboration is not a predictor for final grade • Koulocheri & Xenos, 2013 DMW UOC May 2013
- 14. OpenEssayist: SAFeSEA Webapplication for summarisation-based formative feedback DMW UOC May 2013
- 15. Key words andphrases visualized in the essay context. Sentences in light-grey (green) background are key sentences as extracted by the EssayAnalyser (the number at the start of the sentence indicates its key-ness ranking); bigrams are indicated in bold (red) and boxed. DMW UOC May 2013
- 16. The structural elementsof the essay can be used jointly with the key word extraction to highlight relevant information within specific parts of the essay, here the introduction (and the assignment question) DMW UOC May 2013
- 17. Key words andphrases as separate lists DMW UOC May 2013
- 18. Dispersion of keywords across the essay http://www.open.ac.uk/iet/main/research-scholarship/research-projec DMW UOC May 2013
- 19. Can we findways of using graph visualization techniques on the key words and key sentences, to make them helpful and meaningful to students? DMW UOC May 2013
- 20. Final Thoughts • Instantmachine feedback not prevalent • Artificial Intelligence analysis to tutors leading to Wizard of Oz responses (Shaffer, 2013) • Just in time feedback is the ultimate goal DMW UOC May 2013
- 21. References (1) Arnold, K.E.(2010). Signals: applying academic analytics, Educause Quarterly, 33(1), p10. http://www.educause.edu/ero/article/signals-applying-academic-analytics (Accessed 30 April 2013) Bastien, M., Heymann, S. & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. Paper presented at the International AAAI Conference on Weblogs and Social Media. Bull, S & Kay, J. (2007). Student models that invite the learner in: the SMILI:-) open learner modelling framework, International Journal of Artificial Intelligence in Education, 17(2). Campbell, J.P. & Oblinger, D.G. (2007). Academic Analytics, Educause. Dawson, S., Bakharia, A. & Heathcote, E. (2010). Snapp: Realising the affordances of real-time SNA within networked learning environments. Paper presented at The 7th International Conference on Networked Learning, Aalborg, Denmark (3-4 May).DMW UOC May 2013
- 22. References (2) De Laat,M., Lally, V., Lipponen, L. & Simons, R.-J. (2007). Investigating patterns of interaction in networked learning and computer-supported collaborative learning: a role for social network analysis. International Journal of Computer Supported Collaborative Learning, 2, pp.87-103. Koulocheri, E. & Xenos, M. (2013). Considering Formal Assessment in Learning Analytics within a PLE: The HOU2LEARN Case. Paper presented at The International Learning Analytics & Knowledge (LAK) Conference, Leuven, Belgium, (8-12 April 2013) © 2013 ACM 978-1-4503-1785-6/13/04 Martin, A.J. (2007). Examining a multidimensional model of student motivation and engagement using a construct validation approach. British Journal of Educational Psychology, 77, 413-440. DMW UOC May 2013
- 23. References (3) Mirriahi, N.& Dawson, S. (2013) The pairing of lecture recording data with assessment scores: A method of discovering pedagogical impact. Paper presented at The International Learning Analytics & Knowledge (LAK) Conference, Leuven, Belgium, (8-12 April 2013) © 2013 ACM 978-1-4503-1785-6/13/04 Pekrun, R. (2006). The control-value theory of achievement emotions: assumptions, corollaries and implications for educational research and practice. Educational Psychology Review, 18, 315-34. SoLAR, Open Learning Analytics: An Integrated & Modularised Platform, White Paper, Society for Learning Analytics Research, 2011. Suthers, D. & Verbert, K. (2013) Learning Analytics as a “Middle Space”. Paper presented at The International Learning Analytics & Knowledge (LAK) Conference, Leuven, Belgium, (8-12 April 2013) © 2013 ACM 978-1-4503-1785-6/13/04 DMW UOC May 2013
- 24. References (4) Tempelaar, D.T.,Cuypers, H., van de Vrie, E., Heck, A. & van der Kooij, H. (2013). Formative Assessment and Learning Analytics. Paper presented at The International Learning Analytics & Knowledge (LAK) Conference, Leuven, Belgium, (8-12 April 2013) © 2013 ACM 978-1-4503-1785-6/13/04 Van Ham, F., Schulz, H.-J. & Dimicco, J.M. (2009). Honeycomb: visual analysis of large scale social networks, Ifip International Federation for Information Processing, 429-442. Van Labeke, N., Whitelock, D., Field, D., Pulman, S. & Richardson, J. (2013) ‘OpenEssayist: Extractive Summarisation & Formative Assessment of Free-Text Essays’. Workshop on Discourse-Centric Learning Analytics, 3rd Conference on Learning Analytics and Knowledge (LAK 2013), Leuven, Belgium Vermunt, J.D. (1996). Leerstijlen en sturen van leerprocessen in het Hoger Onderwijs. Amsterdam/Lisse: Swets & Zeitlinger. DMW UOC May 2013