Phillip Grimaldi

According to our database, Phillip Grimaldi authored at least 10 papers between 2017 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

Estimating the causal effects of Khan Academy Map Accelerator across demographic subgroups.

Phillip Grimaldi, Kodi Weatherholtz, Kelli Millwood Hill

Proceedings of the 15th International Conference on Educational Data Mining, 2022

2020

Workshop Proposal: Educational A/B Testing at Scale.

Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Burr Settles, Phillip Grimaldi, Derek Lomas

Proceedings of the L@S'20: Seventh ACM Conference on Learning @ Scale, 2020

qDKT: Question-centric Deep Knowledge Tracing.

Shashank Sonkar, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk

Proceedings of the 13th International Conference on Educational Data Mining, 2020

Inferring Student Comprehension from Highlighting Patterns in Digital Textbooks: An Exploration in an Authentic Learning Platform.

David Y. J. Kim, Adam Winchell, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk, Michael Mozer

Proceedings of the Second International Workshop on Intelligent Textbooks 2020 co-located with 21st International Conference on Artificial Intelligence in Education (AIED 2020), 2020

2019

A Meta-Learning Augmented Bidirectional Transformer Model for Automatic Short Answer Grading.

Zichao Wang, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk

Proceedings of the 12th International Conference on Educational Data Mining, 2019

2018

QG-net: a data-driven question generation model for educational content.

Zichao Wang, Andrew S. Lan, Weili Nie, Andrew E. Waters, Phillip J. Grimaldi, Richard G. Baraniuk

Proceedings of the Fifth Annual ACM Conference on Learning at Scale, 2018

Textbook annotations as an early predictor of student learning.

Adam Winchell, Michael Mozer, Andrew S. Lan, Phillip Grimaldi, Harold Pashler

Proceedings of the 11th International Conference on Educational Data Mining, 2018

2017

Short-Answer Responses to STEM Exercises: Measuring Response Validity and Its Impact on Learning.

Andrew E. Waters, Phillip Grimaldi, Andrew S. Lan, Richard G. Baraniuk

Proceedings of the 10th International Conference on Educational Data Mining, 2017

A Latent Factor Model For Instructor Content Preference Analysis.

Jack Z. Wang, Andrew S. Lan, Phillip Grimaldi, Richard G. Baraniuk

Proceedings of the 10th International Conference on Educational Data Mining, 2017

Data-Mining Textual Responses to Uncover Misconception Patterns.

Joshua J. Michalenko, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk

Proceedings of the 10th International Conference on Educational Data Mining, 2017