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44.081 - Data-Driven Techniques That Complement Theoretical Study of Cognition and Learning With Technology
Sat, April 29, 2:45 to 4:15pm, Grand Hyatt San Antonio, Floor: Fourth Floor, Texas Ballroom Salon BSession Type: Symposium
Abstract
This session reviews data mining and analytics methods that model cognitive and metacognitive learning processes in the context of computer-based learning environments. Recent advancements by researchers in educational data mining and learning analytics communities have produced new methods to represent and understand learners’ efforts to monitor and enact strategies to control their learning during tasks. The aim of this session is to demonstrate methods that produce new understanding of cognition and learning in technology settings, and to share new knowledge they have produced. Additional focus is placed on the observable indicators of student learning these methods produce and time to discuss how these enable educational software to tailor instruction to learners’ specific needs will be allotted.
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Chairs
Papers
Challenges in Using Data Mining to Identify Robust Indicators of Cognitive, Affective, and Metacognitive Self-Regulatory Processes From Trace Data During Learning With Advanced Learning Technologies - Roger Azevedo, North Carolina State University; Joseph Grafsgaard, North Carolina State University; Michelle Taub, North Carolina State University; Nicholas Vincent Mudrick, North Carolina State University; Eunice Eunhee Jang, University of Toronto; Clarissa Lau, University of Toronto; Jeanne Sinclair, University of Toronto
Examining Students' Achievement Goals, Metacognitive Monitoring Behaviors, and Achievement Using Person-Centered and Data-Mining Approaches - Wonjoon Hong, University of Nevada - Las Vegas; Matthew L. Bernacki, University of Nevada - Las Vegas
Modeling Information-Seeking Behaviors During Learning From Hypermedia With nBrowser - Eric G. Poitras, University of Utah; Negar Fazeli, University of Utah
Toward Detection of Learner Distractions in a Medical Learning Environment: A Subgroup Discovery Approach - Tenzin Doleck, McGill University; Eric G. Poitras, University of Utah; Susanne P. Lajoie, McGill University