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Learning Analytics: A short introduction Learning Analytics & Machine Learning March 25, 2014 #LAK14

Learning Analytics: A short introduction

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Learning Analytics: A short introduction. Learning Analytics & Machine Learning March 25, 2014 #LAK14. - PowerPoint PPT Presentation

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Page 1: Learning  Analytics:  A short introduction

Learning Analytics: A short introduction

Learning Analytics & Machine LearningMarch 25, 2014

#LAK14

Page 2: Learning  Analytics:  A short introduction

Learning analytics is the measurement, collection, analysis, and reporting of data about learners and their contexts, for the purposes of understanding and optimizing learning and the environments in which it occurs.

LAK11 Conference

Page 3: Learning  Analytics:  A short introduction

Analytics is the process of developing actionable insights through problem definition and the application of statistical models and analysis against existing and/or simulated future data

Cooper, 2012

Page 4: Learning  Analytics:  A short introduction

Historical influences

Page 5: Learning  Analytics:  A short introduction

1. Citation analysis

Garfield, 1955Page et al., 1999

Page 6: Learning  Analytics:  A short introduction

2. Social network analysis

Milgram, 1967Granovetter, 1973Wellman, 1999Haythornthwaite, 2002

Page 7: Learning  Analytics:  A short introduction

3. User modeling

Rich, 1979Fischer, 2001 (HCI)

Page 8: Learning  Analytics:  A short introduction

4. Education/cognitive models

Anderson et al., 1995

Page 9: Learning  Analytics:  A short introduction

5. Tutors (intelligent)

Burns, 1989Anderson et al., 1995

Page 10: Learning  Analytics:  A short introduction

6. Knowledge discovery in databases

Fayyad, 1996

Page 11: Learning  Analytics:  A short introduction

7. Adaptive hypermedia

Brusilovsky, 2001

Page 12: Learning  Analytics:  A short introduction

8. Digital learning

Elearning/online learningMOOCs

Page 13: Learning  Analytics:  A short introduction

Related

Business intelligenceAcademic analytics

Page 14: Learning  Analytics:  A short introduction

Technique: Baker and Yacef (2009) five primary areas of analysis: - Prediction- Clustering- Relationship mining- Distillation of data for human

judgment- Discovery with models

Page 15: Learning  Analytics:  A short introduction

Application: Bienkowski, Feng, and Means (2012) five areas of LA/EDM application:- Modeling user knowledge, behavior, and experience- Creating profiles of users- Modeling knowledge domains- Trend analysis- Personalization and adaptation

Page 16: Learning  Analytics:  A short introduction

Why ML?Two main areas of promise for LA:

NeuroscienceML

(wearable (ambient) computing)

Page 17: Learning  Analytics:  A short introduction

https://tekri.athabascau.ca/analytics/ Cooper, A. (2012a). What is analytics? Definitions and essential characteristics. JISC CETIS Analytics Series, 1(5). Retrieved on March 10, 2013 from http://publications.cetis.ac.uk/wp-content/uploads/2012/11/What-is-Analytics-Vol1-No-5.pdfGarfield, E. (1955). Citation indexes for Science: A new dimension in documentation through association of ideas. Science, 122(3159), 108-111. Page, L., Brin, S., Motwani, R., & Winograd, T. (1999). The PageRank Citation Ranking: Bringing Order to the Web. Technical Report. Stanford InfoLab. Retrieved on March 10 from http://ilpubs.stanford.edu:8090/422/Milgram, S. (1967) ‘The small world problem.’ Psychology Today 2, 60-67.Granovetter, M. (1973) ‘The strength of weak ties.’ American Journal of Sociology, 78(6), 1360-1380.Wellman, B. (1999) Networks in the global village: life in contemporary communities. Boulder: Westview PressHaythornthwaite, C. (2002) ‘Strong, weak, and latent ties and the impact of new media.’ The Information Society 18, 285-401Rich, E. (1979). User modeling via stereotypes. Cognitive Science 3, 329-354.Fischer, G. (2001). User Modeling in Human-Computer Interactions. User Modeling and User-Adapted Interaction, 11, 65-86. Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995). Cognitive tutors: Lessons learned. The Journal of the Learning Sciences, 4(2), 167-207. Burns, H. L. (1989). Foundations of intelligent tutoring systems: An introduction. In Richardson, J. J., & Polson, M. C. (Eds.), Proceedings of the Air Force Forum for Intelligent Tutoring Systems. Retrieved on March 10, 2013 from http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA207096#page=16 Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. American Association for Artificial Intelligence, 17(30), 37-54.Brusilovsky, P. (2001). Adaptive hypermedia: From intelligent tutoring systems to web-based education. User Modeling and User-Adapted Interaction, 11(1-2), 87-110.Baker, R. S. J.d., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data Mining, 1(1). http://www.educationaldatamining.org/JEDM/images/articles/vol1/issue1/JEDMVol1Issue1_BakerYacef.pdfBienkowski, M., Feng, M., & Means, B. (2012). Enhancing teaching and learning through educational data mining and learning analytics. U.S. Department of Education. Retrieved on March 10, 2013 from http://www.ed.gov/edblogs/technology/files/2012/03/edm-la-brief.pdf