VLDB 2026 Research / reviewers in the wild / expert
Megan Wiedbusch
dblp:243/3782 · also Megan D. Wiedbusch
· DBLP profile ↗
9ranked-venue papers
4as first author
6since 2021 · last 2025
0000-0002-4619-1709ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 8 · 3 first-author · 6 since 2021Human-computer interaction and ubiquitous computing · 6 · 2 first-author · 4 since 2021Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Balancing Emotional and Motivational Self-Regulatory Processes During Complex Learning with Intelligent Tutoring Systems
Annamarie Brosnihan, Megan Wiedbusch, Cameron Marano, Maral Karimi, Matthew Moreno, Tara Delgado, Oscar Tidwell, Roger Azevedo |
AIED (2) | 2 |
| 2025 | Examining the Influence of Students' Personality on Self-regulatory Behaviors and Learning Outcomes During Complex Learning with MetaTutor
Cameron Marano, Megan Wiedbusch, Annamarie Brosnihan, Matthew Moreno, Milla Sherman, Maral Karimi, Tara Delgado, Roger Azevedo |
AIED (5) | 2 |
| 2022 | Pedagogical Agent Support and Its Relationship to Learners' Self-regulated Learning Strategy Use with an Intelligent Tutoring System
Daryn A. Dever, Nathan A. Sonnenfeld, Megan Wiedbusch, Roger Azevedo |
AIED (1) | 3 |
| 2022 | Clustering Learner's Metacognitive Judgment Accuracy and Bias to Explore Learning with AIEd Systems
Megan Wiedbusch, Nathan A. Sonnenfeld, Daryn A. Dever, Roger Azevedo |
AIED (1) | 1 |
| 2022 | Enhancing Learner Models for Pedagogical Agent Scaffolding of Self-Regulated Learning
Daryn A. Dever, Megan Wiedbusch, Roger Azevedo |
ICCE | 2 |
| 2022 | Pedagogical Companions to Support Teachers' Interpretation of Students' Engagement from Multimodal Learning Analytics Dashboards
Megan Wiedbusch, Nathan A. Sonnenfeld |
ICCE | 1 |
| 2020 | Can a Composite Metacognitive Judgment Accuracy Score Successfully Capture Performance Variance during Multimedia Learning?
Megan Wiedbusch, Roger Azevedo |
CogSci | 1 |
| 2020 | Modeling Metacomprehension Monitoring Accuracy with Eye Gaze on Informational Content in a Multimedia Learning EnvironmentabstractMultimedia learning environments support learners in developing self-regulated learning (SRL) strategies. However, capturing these strategies and cognitive processes can be difficult for researchers because cognition is often inferred, not directly measured. This study sought to model self-reported metacognitive judgments using eye-tracking from 60 undergraduate students as they learned about biological systems with MetaTutorIVH, a multimedia learning environment. We found that participants’ gaze behaviors were different between the perceived relevance of the instructional content provided regardless of the actual content relevance. Additionally, we fit a cumulative link mixed effects ordinal regression model to explain reported metacognitive judgments based on content fixations, relevance, and presentation type. Main effects were found for all variables and several interactions between both fixations and content relevance as well as content fixations and presentation type. Surprisingly, accurate metacognitive judgments did not explain performance. Implication for multimedia learning environment design are discussed. Megan Wiedbusch, Roger Azevedo |
ETRA | 1 |
| 2019 | Learners' Gaze Behaviors and Metacognitive Judgments with an Agent-Based Multimedia Environment
Daryn A. Dever, Megan Wiedbusch, Roger Azevedo |
AIED (2) | 2 |