2017
Kizilcec, R. F., Saltarelli, A. J., Reich, J., & Cohen, G. L. (2017). Closing global achievement gaps in MOOCs. Science 355(6322), 251-252.
Kizilcec, R. F., Perez-Sanagustin, M., & Maldonado, J. J. (2017). Self-Regulated Learning Strategies Predict Learner Behavior and Goal Attainment in Massive Open Online Courses. Computers & Education, 104, 19-33.
Kizilcec, R. F., Davis, G. M., & Cohen, G. L. (2017). Towards equal opportunities in MOOCs: Reducing gender & social-class achievement gaps in China with a value relevance affirmation. In Proceedings of the Fourth ACM Conference on Learning at Scale, L@S 2017. Cambridge, MA.
Davis, D., Jivet, I., Kizilcec, R. F., Chen, G., Hauff, C., & Houben, G.-J. (2017). Follow the Successful Crowd: Facilitating Social Comparison Raises MOOC Completion Rates. In Proceedings of the 7th International Conference on Learning Analytics and Knowledge (LAK).
Kizilcec, R. F. & Brooks, C. (in press). Diverse Big Data and Randomized Field Experiments in Massive Open Online Courses: Opportunities for Advancing Learning Research. In G. Siemens & C. Lang (Eds.), Handbook on Learning Analytics & Educational Data Mining.
Johanes, P. (2017). Epistemic cognition: A promising and necessary construct for enriching large-scale online learning analysis. In Proceedings of the Fourth ACM Conference on Learning at Scale, L@S 2017. Cambridge, MA.
2016
Eckles, D., Kizilcec, R. F., & Bakshy, E. (2016). Estimating peer effects in networks with peer encouragement designs. Proceedings of the National Academy of Sciences (PNAS), 113(27), 7316-7322. (Supporting Information)
Johanes, P., & Lagerstrom, L. (2016, June). Online Videos: What Every Instructor Should Know. In Proceedings of the123rd American Society for Engineering Education (ASEE) Annual Conference and Exposition, New Orleans, Louisiana. 10.18260/p.25832. | Best Paper in the Computers in Education Division.
Kizilcec, R. F., Perez-Sanagustin, M., & Maldonado, J. J. (2016). Recommending Self-Regulated Learning Strategies Does Not Improve Performance in a MOOC. In Proceedings of the Third ACM Conference on Learning at Scale, L@S 2016. Edinburgh, UK.
Li, J., Kizilcec, R. F., Bailenson, J. N., & Ju, W. (2016). Social Robots and Virtual Agents as Lecturers for Video Instruction. Computers in Human Behavior, 55(B), 1222-1230.
2015
Veletsianos, G., Collier, A. and Schneider, E. (2015), Digging deeper into learners' experiences in MOOCs: Participation in social networks outside of MOOCs, notetaking and contexts surrounding content consumption. British Journal of Educational Technology. 46: 570–587.
Kizilcec, R. F., Bailenson, J.N., & Gomez, C. J. (2015). The Instructor’s Face in Video Instruction: Evidence from Two Large-Scale Field Studies. Journal of Educational Psychology, 107(3), 724-739.
Kizilcec, R. F. & Schneider, E. (2015). Motivation as a Lens to Understand Online Learners. ACM Transactions on Computer-Human Interaction (TOCHI), 22(2).
Kizilcec, R. F., & Halawa, S. A. (2015). Attrition and Achievement Gaps in Online Learning. In Proceedings of the Second ACM Conference on Learning at Scale, L@S 2015, March 14-15, 2015, Vancouver, Canada.
Lagerstrom, L., Johanes, P., & Ponsukcharoen, U. (2015). The myth of the six-minute rule: student engagement with online videos. In Proceedings of the 122nd American Society for Engineering Education (ASEE) Annual Conference and Exposition,Seattle, Washington.
2014
Thille, C., Schneider, D. E., Kizilcec, R. F., Piech, C., Halawa, S. A., & Greene, D. K. (2014). The Future of Data–Enriched Assessment. Research & Practice in Assessment, 9(2), 5-16.
Grover, S., Pea, R., and Cooper, S. (2014). Promoting Active Learning & Leveraging Dashboards for Curriculum Assessment in an OpenEdX Introductory CS Course for Middle School. In Proceedings of 1st Conference on Learning at Scale, L@S 2014. Atlanta, GA.
Huang, J., Dasgupta, A., Ghosh, A., Manning, J., Sanders, M. (2014). Superposter behavior in MOOC forums. In Proceedings of ACM’s Learning @ Scale (L@S 2014), Atlanta GA.
Nguyen, A., Piech, C., Huang, J, Guibas, L.J. (2014). Codewebs: Scalable Homework Search for Massive Open Online Programming Courses. In Proceedings of the 23rd International World Wide Web Conference (WWW 2014), Seoul, Korea.
Williams, J. J., Kovacs, G., Walker, C., Maldonado, S. G., & Lombrozo, T. (2014). Learning Online Via Prompts to Explain. In Extended Abstracts of ACM CHI 2014. New York, NY: Association for Computing Machinery.
Halawa, S., Greene, D., Mitchell, J. (2014). Dropout Prediction in MOOCs using Learner Activity Features. Proceedings of the Second European MOOCs Stakeholders Summit, EMOOCs’14. Lausanne, Switzerland. | Selected to appear in a special edition of PAU Education. (paper, slides)
Kizilcec, R. F. (2014). Reducing Non-Response Bias with Survey Reweighting: Applications for Online Learning Researchers. Proceedings of the First ACM Conference on Learning at Scale, L@S’14, March 4-5, 2014, Atlanta, GA.
Schneider, E. & Kizilcec, R. F. (2014). “Why did you enroll in this course?” Developing a Standardized Survey Question for Reasons to Enroll. Proceedings of the First ACM Conference on Learning at Scale, L@S’14, March 4-5, 2014, Atlanta, GA.
Kizilcec, R. F., Papadopoulos, K., & Sritanyaratana, L. (2014). Showing Face in Video Instruction: Effects on Information Retention, Visual Attention, and Affect. Proceedings of the SIGCHI conference on human factors in computing systems, CHI’14. Toronto, Canada: ACM.
Kizilcec, R. F., Schneider, E., Cohen, G., & McFarland, D. (2014). Encouraging Forum Participation in Online Courses with Collectivist, Individualist, and Neutral Motivational Framings. Proceedings of the Second European MOOCs Stakeholders Summit, EMOOCs’14. Lausanne, Switzerland. | Selected to appear in a special edition of PAU Education.
Williams, J.J., Kizilcec, R.F., Russell, D. M., & Klemmer, S. R. (2014). Learning Innovation at Scale. Proceedings of the SIGCHI conference on human factors in computing systems, CHI’14. Toronto, Canada: ACM.
2013
Dede, C., Grimson, E., Pea, R., et al., (2013, May). New Technology-based Models for Postsecondary Learning: Conceptual Frameworks and Research Agendas, Report of a National Science Foundation-Sponsored Computing Research Association Workshop held at MIT on January 9-11, 2013. (pdf)
Huang, J. Piech, C. Nguyen, A., & Guibas, L. (2013). Syntactic and Functional Variability of a Million Code Submissions in a Machine Learning MOOC. Paper presented at the MOOCshop Workshop, International Conference on Artificial Intelligence in Education, Memphis, TN. (pdf)
Kizilcec, R. (2013). Collaborative Learning in Geographically Distributed and In-person Groups. Paper presented at the MOOCshop Workshop, International Conference on Artificial Intelligence in Education, Memphis, TN. (pdf)
Piech, C., Huang, J., Chen, Z., Do, C., Ng, A., & Koller, D. (2013). Tuned Models of Peer Assessment in MOOCs. Paper presented at the International Conference on Educational Data Mining, Memphis, TN. (pdf)
Schneider, B., & Pea, R. (2013, November). Real-time Mutual Gaze Perception Enhances Collaborative Learning and Collaboration Quality. International Journal of Computer-Supported Collaborative Learning, 8(4), 375-397 (First published online October 4, 2013). (pdf)
Schneider, B., & Pea, R. (2013, June). Using Eye-Tracking Technology to Support Visual Coordination in Collaborative Problem-Solving Groups. In Rummel, N., Kapur, M., Nathan, M., & Puntambekar, S. (Eds.) (2013). To See the World and a Grain of Sand: Learning across Levels of Space, Time, and Scale: CSCL 2013 Conference Proceedings Volume 1 — Full Papers & Symposia, pp. 406-413, University of Wisconsin, Madison. (pdf)
Schneider, B., Abu-El-Haija, S., Reesman, J., & Pea, R. (2013). Toward Collaboration Sensing: Applying Network Analysis Techniques to Collaborative Eye-tracking Data. ACM International Conference on Learning Analytics, LAK ’13 (pp. 107-111). Leuven, Belgium: ACM. (pdf) Best Paper Award.
Schneider, E. (2013). Welcome to the Moocspace: A Proposed Taxonomy for Massive Open Online Courses. Paper presented at the MOOCshop Workshop, International Conference on Artificial Intelligence in Education, Memphis, TN. (pdf)
Williams, B. (2013). Roll Call: Taking a Census of MOOC Students. Paper presented at the MOOCshop Workshop, International Conference on Artificial Intelligence in Education, Memphis, TN. (pdf)
Williams, J.J. & Williams, B. A. (2013). Using Interventions to Improve Online Learning. Paper presented as a poster at the Data Driven Education Workshop at the Conference on Neural Information Processing Systems.
Williams, J. J., Renkl, A., Koedinger, K., Stamper, J. (2013). Online Education: A Unique Opportunity for Cognitive Scientists to Integrate Research and Practice. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society, 113-114. Austin, TX: Cognitive Science Society. (pdf)
Williams, J.J. (2013). Improving Learning in MOOCs by Applying Cognitive Science. Paper presented at the MOOCshop Workshop, International Conference on Artificial Intelligence in Education, Memphis, TN. (pdf)
Williams, J.J., Paunesku, D., Haley, B., & Sohl-Dickstein, J. (2013). Measurably Increasing Motivation in MOOCs. Talk presented at the MOOCshop Workshop, International Conference on Artificial Intelligence in Education, Memphis, TN.
Grover, S., Franz, P., Schneider, E. and Pea, R. (2013) The MOOC as Distributed Intelligence: Dimensions of a Framework for the Design and Evaluation of MOOCs. In Proceedings of the 10th International Conference on Computer Supported Collaborative Learning (Madison, WI, June 16-19). (pdf)
R. Kizilcec, C. Piech, E. Schneider. (2013) Deconstructing Disengagement: Analyzing Learner Subpopulations in Massive Open Online Courses, Proc. 3rd Int’l Conference on Learning Analytics and Knowledge (LAK ’13), Leuven, Belgium, April, 2013. (pdf) (LAK’13 Slides)
