Editorial: Augmenting Learning Analytics with Multimodal Sensory Data
DOI:
https://doi.org/10.18608/jla.2016.32.10Abstract
The goal of Learning Analytics is to understand and improve learning. However, learning does not always occur through or mediated by a technological system that can collect digital traces. To be able to study learning in non-technology centered environments, several signals, such as video and audio, should be captured, processed and analyzed to produce traces of the actions and interactions of the actors of the learning process. The use and integration of the different modalities present in those signals is known as Multimodal Learning Analytics. This editorial presents a brief introduction to this new variation of Learning Analytics and summarizes the four representative articles included in this special issue. The editorial closes with a small discussion about the current opportunities and challenges in multimodal learning analytics.
References
Blikstein, P., Worsley, M., Piech, C., Gibbons, A., Sahami, M., Cooper, S., & Koller, D. (2013). Programming Pluralism: Using Learning Analytics to Detect Patterns in Novices' Learning of Computer Programming. International Journal of the Learning Sciences Special Issue on Learning Analytics.
Domínguez, F., Chiluiza, K., Echeverria, V., & Ochoa, X. (2015). Multimodal selfies: Designing a multimodal recording device for students in traditional classrooms. In Proceedings of the 2015 ACM on International Conference on Multimodal Interaction (pp. 567-574). ACM.
Freedman, D. H. (2010). Why scientific studies are so often wrong: The streetlight effect. Discover Magazine, 26.
Grafsgaard, J. F. (2014). Multimodal affect modeling in task-oriented tutorial dialogue. North Carolina State University.
Grafsgaard, J., Wiggins, J., Boyer, K. E., Wiebe, E., & Lester, J. (2014). Predicting learning and affect from multimodal data streams in task-oriented tutorial dialogue. In Educational Data Mining 2014.
Morency, L. Oviatt, S., Scherer, S. Weibel, N. & Worsley, M. (2013). ICMI 2013 Grand Challenge Workshop on Multimodal Learning Analytics. In Proceedings of the 15th ACM international conference on Multimodal Interaction (ICMI '13). ACM, New York, NY, USA. pp. 373-378.
Ochoa, X., Chiluiza, K., Méndez, G., Luzardo, G., Guamán, B., & Castells, J. (2013). Expertise estimation based on simple multimodal features. In Proceedings of the 15th ACM on International conference on multimodal interaction (pp. 583–590). ACM.
Ochoa, X., Worsley, M., Weibel, N., & Oviatt, S. (2016). Multimodal learning analytics data challenges. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (LAK '16). ACM, New York, NY, USA, 498-499. DOI=http://dx.doi.org/10.1145/2883851.2883913
Ochoa, X., Worsley, M., Chiluiza, K., & Luz, S. (2014). MLA'14: Third Multimodal Learning Analytics Workshop and Grand Challenges. In Proceedings of the 16th International Conference on Multimodal Interaction. pp. 531-532. ACM.
Oviatt, S. & Cohen, A. (2013) Written and multimodal representations as predictors of expertise and problem-solving success in mathematics. In Proceedings of the 15th ACM on International conference on multimodal interaction (ICMI '13). ACM, New York, NY, USA, 599-606. DOI=http://dx.doi.org/10.1145/2522848.2533793
Scherer, S., Worsley, M. & Morency, L.P. (2012). 1st international workshop on multimodal learning analytics: extended abstract. In Proceedings of the 14th ACM international conference on Multimodal interaction (ICMI '12). ACM, New York, NY, USA, 609-610. DOI=http://dx.doi.org/10.1145/2388676.2388803
Schneider, B., Wallace, J., Blikstein, P., & Pea, R. (2013). Preparing for future learning with a tangible user interface: the case of neuroscience. Learning Technologies, IEEE Transactions on, 6(2), 117–129
Worsley, M. (2014). Multimodal Learning Analytics as a Tool for Bridging Learning Theory and Complex Learning Behaviors. In Proceedings of the 2014 International Conference on Multimodal Interaction. ACM, New York, NY, USA. pp 1-4
Worsley, M., Abrahamson, D., Blikstein, P, Grover, S., Schneider, B., Tissenbaum, M. (2016) Situating Multimodal Learning Analytics. In Proceedings of the 2016 International Conference of the Learning Sciences (ICLS). pp. 1346 - 1349.
Worsley, M., Abrahamson, D., Blikstein, P., Grover, S., Schneider, B., & Tissenbaum, M. (2016). Situating multimodal learning analytics. In C.-K. Looi, J. L. Polman, U. Cress, & P. Reimann (Eds.), "Transforming learning, empowering learners," Proceedings of the International Conference of the Learning Sciences (ICLS 2016) (Vol. 2, pp. 1346-1349). Singapore: International Society of the Learning Sciences.
Worsley, M. & Blikstein, P. (2013) Towards the development of multimodal action based assessment. In Proceedings of the Third International Conference on Learning Analytics and Knowledge (LAK '13), Dan Suthers, Katrien Verbert, Erik Duval, and Xavier Ochoa (Eds.). ACM, New York, NY, USA, 94-101. DOI=http://dx.doi.org/10.1145/2460296.2460315
Worsley, M. & Blikstein, P. (2015) Leveraging multimodal learning analytics to differentiate student learning strategies. In Proceedings of the Fifth International Conference on Learning Analytics And Knowledge (LAK '15). ACM, New York, NY, USA, 360-367. DOI=10.1145/2723576.2723624 http://doi.acm.org/10.1145/2723576.2723624
Worsley, M, Chiluiza, K., Grafsgaard, J., & Ochoa, X., (2015). 2015 Multimodal Learning and Analytics Grand Challenge. In Proceedings of the 2015 International Conference on Multimodal Interaction. ACM, New York, USA. pp. 525-529.
Worsley, M. Scherer, S., Morency, L.P., & Blikstein, P. (2015). Exploring Behavior Representation for Learning Analytics. In Proceedings of the 2015 International Conference on Multimodal Interaction. ACM, New York, USA. pp. 251-258.
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