Handbook of Learning Analytics

Aguiar, Everaldo, Himabindu Lakkaraju, Nasir Bhanpuri, David Miller, Ben Yuhas, and Kecia L Addison. 2015. “Who, When, and Why: A Machine Learning Approach to Prioritizing Students at Risk of Not Graduating High School on Time.” In Proceedings of the Fifth International Conference on Learning Analytics and Knowledge, 93–102. ACM.

Alhadad, Sakinah, Kimberly Arnold, Josh Baron, Ilana Bayer, Christopher Brooks, Russ R Little, Rose A Rocchio, Shady Shehata, and John Whitmer. 2015. “The Predictive Learning Analytics Revolution: Leveraging Learning Data for Student Success.” EDUCAUSE Center for Analysis; Research.

Anderson, Chris. 2008. “The End of Theory: The Data Deluge Makes the Scientific Method Obsolete.” Wired Magazine 16.07 (June). http://www.wired.com/science/discoveries/magazine/16-07/pb_theory.

Baker, Ryan S. J. d. 2007. “Modeling and Understanding Students’ Off-Task Behavior in Intelligent Tutoring Systems.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1059–68. ACM.

———. 2019. “Challenges for the Future of Educational Data Mining: The Baker Learning Analytics Prizes.” JEDM Journal of Educational Data Mining 11 (1): 1–17.

Baker, Ryan S. J. d., Albert T Corbett, Kenneth R Koedinger, and Angela Z. Wagner. 2004. “Off-Task Behavior in the Cognitive Tutor Classroom: When Students Game the System.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 383–90. ACM.

Baker, Ryan S. J. d., Sujith M Gowda, and Albert T. Corbett. 2011. “Towards Predicting Future Transfer of Learning.” In Artificial Intelligence in Education, 23–30. Lecture Notes in Computer Science. Springer Berlin Heidelberg.

Barber, Rebecca, and Mike Sharkey. 2012. “Course Correction: Using Analytics to Predict Course Success.” In Proceedings of the 2Nd International Conference on Learning Analytics and Knowledge, 259–62. LAK ’12. New York, NY, USA: ACM. https://doi.org/10.1145/2330601.2330664.

Brooks, Christopher, Craig Thompson, and Stephanie Teasley. 2015. “A Time Series Interaction Analysis Method for Building Predictive Models of Learners Using Log Data.” In Proceedings of the Fifth International Conference on Learning Analytics and Knowledge, 126–35. LAK ’15. New York, NY, USA: ACM.

D’Mello, Sidney, Scotty D Craig, Amy Witherspoon, Bethany McDaniel, and Arthur Graesser. 2007. “Automatic Detection of Learner’s Affect from Conversational Cues.” User Model. User-Adapt Interact. 18 (1): 45–80.

Doroudi, Shayan, and Emma Brunskill. 2019. “Fairer but Not Fair Enough on the Equitability of Knowledge Tracing.” In Proceedings of the 9th International Conference on Learning Analytics & Knowledge, 335–39. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3303772.3303838.

Dowell, Nia, Tristian Nixon, and Arthur C. Graesser. 2019. “Group Communication Analysis: A Computational Linguistics Approach for Detecting Sociocognitive Roles in Multiparty Interactions.” Behavior Research Methods 51: 1007–41.

Duckworth, Angela L., Christopher Peterson, Michael D Matthews, and Dennis R Kelly. 2007. “Grit: Perseverance and Passion for Long-Term Goals.” Journal of Personality and Social Psychology 92 (6): 1087.

Gardner, Josh, and Christopher Brooks. 2018. “Coenrollment Networks and Their Relationship to Grades in Undergraduate Education.” In Proceedings of the 8th International Conference on Learning Analytics and Knowledge, 295–304. LAK ’18. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3170358.3170373.

Hall, Mark, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten. 2009. “The WEKA Data Mining Software: An Update.” SIGKDD Explor. Newsl. 11 (1): 10–18. https://doi.org/10.1145/1656274.1656278.

HarvardX. 2014. “HarvardX Person-Course Academic Year 2013 De-Identified dataset, version 3.0.” Harvard Dataverse. https://doi.org/10.7910/DVN/26147.

Ho, Andrew. 2015. “Four Variations on a Theme of Data-Intensive Research in Education.” In Workshop on Data‐Intensive Research in Education, 79–82. Arlington, VA: Computing Research Association. http://archive2.cra.org/uploads/documents/events/bigdata/Workshop_Briefing_Book.pdf.

Joksimovic, Sreckp, Areti Manataki, Dragan Gasevic, Shane Dawson, Vitomir Kovanovic, and Inés Friss de Kereki. 2016. “Translating Network Position into Performance: Importance of Centrality in Different Network Configurations.” In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, 314–23. LAK ’16. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/2883851.2883928.

Koedinger, Kenneth, Sidney D’Mello, Elizabeth A McLaughlin, Zachary A Pardos, and Carolyn P Rosé. 2015. “Data Mining and Education.” Wiley Interdisciplinary Reviews: Cognitive Science 6 (4): 333–53.

Kovanovic, Vitomir, Dragan Gašević, Shane Dawson, Srećko Joksimovic, and Ryan S. J. d. Baker. 2016. “Does Time-on-Task Estimation Matter? Implications on Validity of Learning Analytics Findings.” Journal of Learning Analytics 2 (3): 81–110.

Kuzilek, Jakub, Martin Hlosta, and Zdenek Zdrahal. 2017. “Open University Learning Analytics Dataset.” Scientific Data 4: 170171.

Li, Warren, Christopher Brooks, and Florian Schaub. 2019. “The Impact of Student Opt-Out on Educational Predictive Models.” In Proceedings of the 9th International Conference on Learning Analytics & Knowledge, 411–20. LAK19. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3303772.3303809.

Lonn, Steven, and Stephanie D. Teasley. 2014. “Student Explorer: A Tool for Supporting Academic Advising at Scale.” In Proceedings of the First ACM Conference on Learning @ Scale Conference, 175–76. L@S ’14. New York, NY, USA: ACM. https://doi.org/10.1145/2556325.2567867.

Mikolov, Tomas, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Distributed Representations of Words and Phrases and Their Compositionality.

Shmueli, Galit. 2010. “To Explain or to Predict?” Stat. Sci., 289–310.

Stripling, Jack, Katherine Mangan, Nick DeSantis, Rio Fernandes, Sarah Brown, Steve Kolowich, Patricia McGuire, and Anne Hendershott. 2016. “Uproar at Mount St. Mary’s.” The Chronicle of Higher Education, March. http://chronicle.com/specialreport/Uproar-at-Mount-St-Marys/30.

Taylor, Colin, Kalyan Veeramachaneni, and Una-May O’Reilly. 2014. “Likely to Stop? Predicting Stopout in Massive Open Online Courses.”

Tempelaar, Dirk, Bart Rienties, and Quan Nguyen. 2020. “Subjective Data, Objective Data and the Role of Bias in Predictive Modelling: Lessons from a Dispositional Learning Analytics Application.” PloS One 15 (6): e0233977.

Wang, Yutao, Neil T Heffernan, and Cristina Heffernan. 2015. “Towards Better Affect Detectors: Effect of Missing Skills, Class Features and Common Wrong Answers.” In Proceedings of the Fifth International Conference on Learning Analytics and Knowledge, 31–35. ACM.

Whitehill, Jacob, Joseph Jay Williams, Glenn Lopez, Cody Austun Coleman, and Justin Reich. 2015. “Beyond Prediction: First Steps Toward Automatic Intervention in MOOC Student Stopout.” Available at SSRN 2611750.

Witten, Ian H. 2016. Weka Courses. https://weka.waikato.ac.nz/explorer.

Witten, Ian H., Eibe Frank, and Mark A. Hall. 2011. Data Mining: Practical Machine Learning Tools and Techniques. 3rd ed. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.

Xing, Wanli, Xin Chen, Jared Stein, and Michael Marcinkowski. 2016. “Temporal Predication of Dropouts in MOOCs: Reaching the Low Hanging Fruit Through Stacking Generalization.” Comput. Human Behav. 58 (May): 119–29.

Xing, Wanli, and Sean Goggins. 2015. “Learning Analytics in Outer Space: A Hidden Naïve Bayes Model for Automatic Student Off-Task Behavior Detection.” In Proceedings of the Fifth International Conference on Learning Analytics and Knowledge, 176–83. ACM.