- Browse
Search
Program Calendar
Browse By Day
Browse By Time
Browse By Person
Browse By Room
Browse By Unit
Browse By Session Type
- Information Menu
Search Tips
Visiting Washington, D.C.
- Navigation and Settings Menu
Personal Schedule
Sign In
- Social Media Menu
Facebook
X (Twitter)
Self-Regulated Learning Analytics: Aligning Data and Their Treatment to the Assumptions of Theory
Sat, April 9, 4:05 to 5:35pm, Convention Center, Floor: Level One, Room 101Session Type: Structured Poster Session
Abstract
This session will bring together SRL researchers with learning scientists who do not necessarily consider themselves “self-regulated learning researchers,” but who excel at investigating cognitive, metacognitive, motivational, or affective learning processes by using rich, unobtrusive, automated data collection or advanced analytic methods (e.g., data mining, learning analytics). Connecting these two research communities can encourage collaborations that 1) provide a useful theoretical lens to guide the inquiry undertaken by learning technologists and data scientists, and 2) introduce the SRL research community to methods of data collection and analysis that are not commonly encountered in the SRL literature, yet in the field but that are more appropriately aligned to the assumptions of models than the approaches most often employed in SRL research.
Sub Unit
Chair
Papers
nStudy Traces of Process and Content in Self-Regulated Learning - Philip H. Winne, Simon Fraser University; John Cale Nesbit, Simon Fraser University; Zahia Marzouk, Simon Fraser University; Mladen Rakovic, Simon Fraser University; Ilana Ram, Simon Fraser University; Donya Samadi, Simon Fraser University; Jason Stewart, Simon Fraser University; Kenny Teng, Simon Fraser University; Derra Truscott, Simon Fraser University; Joviat Vytasek, Simon Fraser University; Sonya Woloshen, Simon Fraser University
Aligning Log-File and Facial Expression Data to Validate Assumptions Linking Self-Regulated Learning, Metacognitive Monitoring, and Emotions During Learning - Michelle Taub, North Carolina State University; Roger Azevedo, North Carolina State University; Seth A. Martin, North Carolina State University; Garrett C. Millar, North Carolina State University; Franz Wortha, Technische Universitaet Dresden
Active Learning in a Massive Open Online Course: Intentions, Self-Regulation, and the Trajectory of Utilization - Eric N. Wiebe, North Carolina State University; Isaac Benjamin Thompson, North Carolina State University
Coherence Analysis for Identifying Self-Regulated Learning Profiles and Changes Over Time - Gautam Biswas, Vanderbilt University; John Kinnebrew, Vanderbilt University; James Segedy, Vanderbilt University
Using Data Mining to Identify Common Behavior Patterns in Computer-Assisted Math Learning - Erica Marti; Matthew L. Bernacki, University of Nevada - Las Vegas; Kira Albers, University of Nevada - Las Vegas; John Kinnebrew, Vanderbilt University; Vincent Aleven, Carnegie Mellon University; Timothy James Nokes-Malach, University of Pittsburgh
Tracing Students' Learning Behaviors in Large Face-to-Face Lecture Courses and Their Relations to Achievement - Matthew L. Bernacki, University of Nevada - Las Vegas; P. Merlin Uesbeck, University of Nevada - Las Vegas; Nancy Webb, University of Nevada - Las Vegas; Kyle B Bowen, University of Nevada - Las Vegas; Lucie Vosicka, University of Nevada, Las Vegas; Nicholas Diana, Carnegie Mellon University
Motivational Design of Support for Learning Effective Problem-Selection Strategies in an Intelligent Tutoring System - Yanjin Long, University of Pittsburgh; Vincent Aleven, Carnegie Mellon University
Beyond Tutor Logs: Exploring Multiple Streams of Data to Identify Self-Regulated Learning - John Stamper, Carnegie Mellon University; Ran Lui, Carnegie Mellon University; Jodi Davenport, WestEd; Bruce Sherin, Northwestern University; Danielle S. McNamara, Arizona State University
New Literacies, New Challenges: Modeling Self-Regulated Learning and Epistemic Cognition Using Think-Aloud Protocol Data - Jeff A. Greene, University of North Carolina - Chapel Hill; Dana Z Copeland; Victor M Deekens, University of North Carolina - Chapel Hill; Seung Yu, University of North Carolina