Handbook of Learning Analytics

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Colasante, M. (2010). Future-focused learning via online anchored discussion, connecting learners with digital artefacts, other learners, and teachers. Proceedings of the 27th Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education: Curriculum, Technology & Transformation for an Unknown Future (ASCILITE 2010), 5–8 December 2010, Sydney, Australia (pp. 211–221). ASCILITE.

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Coleman, C. A., Seaton, D. T., & Chuang, I. (2015). Probabilistic use cases: Discovering behavioral patterns for predicting certification. Proceedings of the 2nd ACM conference on Learning@Scale (L@S 2015), 14–18 March 2015, Vancouver, BC, Canada (pp. 141–148). New York: ACM. http://doi.org/10.1145/2724660.2724662

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de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2011). Attention cueing in an instructional animation: The role of presentation speed. Computers in Human Behavior, 27(1), 41–45. http://doi.org/10.1016/j.chb.2010.05.010

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Gašević, D., Mirriahi, N., & Dawson, S. (2014). Analytics of the effects of video use and instruction to support reflective learning. Proceedings of the 4th International Conference on Learning Analytics and Knowledge (LAK ʼ14), 24–28 March 2014, Indianapolis, IN, USA (pp. 123–132). New York: ACM. http://doi.org/10.1145/2567574.2567590

Giannakos, M. N. (2013). Exploring the video-based learning research: A review of the literature: Colloquium. British Journal of Educational Technology, 44(6), E191–E195. http://doi.org/10.1111/bjet.12070

Giannakos, M. N., Chorianopoulos, K., & Chrisochoides, N. (2014). Collecting and making sense of video learning analytics. Proceedings of the 2014 IEEE Frontiers in Education Conference (FIE 2014), 22–25 October 2014, Madrid, Spain. IEEE. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7044485

Giannakos, M. N., Chorianopoulos, K., & Chrisochoides, N. (2015). Making sense of video analytics: Lessons learned from clickstream interactions, attitudes, and learning outcome in a video-assisted course. The International Review of Research in Open and Distributed Learning, 16(1). http://www.irrodl.org/index.php/irrodl/article/view/1976

Giannakos, M. N., Jaccheri, L., & Krogstie, J. (2015). Exploring the relationship between video lecture usage patterns and students’ attitudes: Usage patterns on video lectures. British Journal of Educational Technology, 47(6), 1259–1275. http://doi.org/10.1111/bjet.12313

Gkonela, C., & Chorianopoulos, K. (2012). VideoSkip: Event detection in social web videos with an implicit user heuristic. Multimedia Tools and Applications, 69(2), 383–396. http://doi.org/10.1007/s11042-012-1016-1

Gonyea, R. M. (2005). Self-reported data in institutional research: Review and recommendations. New Directions for Institutional Research, 2005(127), 73–89.

Greller, W., & Drachsler, H. (2012). Translating learning into numbers: A generic framework for learning analytics. Journal of Educational Technology & Society, 15(3), 42–57.

Grigoras, R., Charvillat, V., & Douze, M. (2002). Optimizing hypervideo navigation using a Markov decision process approach. Proceedings of the 10th ACM International Conference on Multimedia (MULTIMEDIA ’02), 1–6 December 2002, Juan-les-Pins, France (pp. 39–48). New York: ACM. http://doi.org/10.1145/641007.641014

Guo, P. J., Kim, J., & Rubin, R. (2014). How video production affects student engagement: An empirical study of MOOC videos. Proceedings of the 1st ACM conference on Learning@Scale (L@S 2014), 4–5 March 2014, Atlanta, Georgia, USA (pp. 41–50). New York: ACM. http://doi.org/10.1145/2556325.2566239

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Ilioudi, C., Giannakos, M. N., & Chorianopoulos, K. (2013). Investigating differences among the commonly used video lecture styles. Proceedings of the Workshop on Analytics on Video-Based Learning (WAVe 2013), 8 April 2013, Leuven, Belgium (pp. 21–26). http://ceur-ws.org/Vol-983/WAVe2013-Proceedings.pdf

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