Richard Scruggs

Publication Activity (10 Years)

Years Active: 2018-2022
Publications (10 Years): 11

Top Topics

Computational Thinking

Erroneous Examples

Top Venues

Comput. Hum. Behav.

EDM (Workshops)

Publications

Shamya Karumbaiah, Jiayi Zhang, Ryan Baker, Richard Scruggs, Whitney L. Cade, Margaret Clements, Shuqiong Lin
Using Neural Network-Based Knowledge Tracing for a Learning System with Unreliable Skill Tags. EDM (2022)
Richard Scruggs, Jalal Nouri, Torkel Klingberg
Using Knowledge Tracing to Predict Students' Performance in Cognitive Training and Math. AIED (2) (2022)
Elizabeth Rowe, Ma. Victoria Almeda, Jodi Asbell-Clarke, Richard Scruggs, Ryan Baker, Erin Bardar, Santiago Gasca
puzzle gameplay. Comput. Hum. Behav. 120 (2021)
Rohini Das, Jiayi Zhang, Ryan S. Baker, Richard Scruggs
A New Interpretation of Knowledge Tracing Models' Predictive Performance in Terms of the Cold Start Problem. EDM (Workshops) (2021)
J. Elizabeth Richey, Jiayi Zhang, Rohini Das, Juan Miguel L. Andres-Bray, Richard Scruggs, Michael Mogessie Ashenafi, Ryan S. Baker, Bruce M. McLaren
Gaming and Confrustion Explain Learning Advantages for a Math Digital Learning Game. AIED (1) (2021)
Jiayi Zhang, Rohini Das, Ryan S. Baker, Richard Scruggs
The Cold Start Problem and Interpretation of Knowledge Tracing Models' Predictive Performance. EDM (2021)
Jodi Asbell-Clarke, Elizabeth Rowe, Mia Victoria Almeda, Teon Edwards, Erin Bardar, Santiago Gasca, Ryan S. Baker, Richard Scruggs
. Comput. Hum. Behav. 115 (2021)
J. Elizabeth Richey, Juan Miguel L. Andres-Bray, Michael Mogessie Ashenafi, Richard Scruggs, Juliana Ma. Alexandra L. Andres, Jon Star, Ryan S. Baker, Bruce M. McLaren
More confusion and frustration, better learning: The impact of erroneous examples. Comput. Educ. 139 (2019)
Richard Scruggs, Ryan S. Baker, Bruce M. McLaren
Extending Deep Knowledge Tracing: Inferring Interpretable Knowledge and Predicting Post-System Performance. CoRR (2019)
J. Elizabeth Richey, Bruce M. McLaren, Miguel Andres-Bray, Michael Mogessie Ashenafi, Richard Scruggs, Ryan S. Baker, Jon Star
Confrustion in Learning from Erroneous Examples: Does Type of Prompted Self-explanation Make a Difference? AIED (1) (2019)
Elizabeth Rowe, Jodi Asbell-Clarke, Ryan Shaun Baker, Santiago Gasca, Erin Bardar, Richard Scruggs
Labeling Implicit Computational Thinking in Pizza Pass Gameplay. CHI Extended Abstracts (2018)