Adam Sales

According to our database, Adam Sales authored at least 28 papers between 2015 and 2024.

Collaborative distances:

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

2024

The Effect of Assistance on Gamers: Assessing The Impact of On-Demand Hints & Feedback Availability on Learning for Students Who Game the System.

Kirk Vanacore, Ashish Gurung, Adam Sales, Neil T. Heffernan

Proceedings of the 14th Learning Analytics and Knowledge Conference, 2024

Multiple Choice vs. Fill-In Problems: The Trade-off Between Scalability and Learning.

Ashish Gurung, Kirk Vanacore, Andrew A. McReynolds, Korinn S. Ostrow, Eamon Worden, Adam C. Sales, Neil T. Heffernan

Proceedings of the 14th Learning Analytics and Knowledge Conference, 2024

Problem-Solving Behavior and EdTech Effectiveness: A Model for Exploratory Causal Analysis.

Adam C. Sales, Kirk P. Vanacore, Hyeon-Ah Kang, Tiffany A. Whittaker

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Tools for Planning and Analyzing Randomized Controlled Trials and A/B Tests.

Adam C. Sales, Johann A. Gagnon-Bartsch, Duy M. Pham

Proceedings of the 17th International Conference on Educational Data Mining, 2024

LOOL: Towards Personalization with Flexible \& Robust Estimation of Heterogeneous Treatment Effects.

Duy M. Pham, Kirk P. Vanacore, Adam C. Sales, Johann Gagnon-Bartsch

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Boosting Precision in Educational A/B Tests Using Auxiliary Information and Design-Based Estimators.

Yanping Pei, Adam Sales, Johann Gagnon-Bartsch

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Using Publicly Available Auxiliary Data to Improve Precision of Treatment Effect Estimation in a Randomized Efficacy Trial.

Charlotte Z. Mann, Jiaying Wang, Adam Sales, Johann A. Gagnon-Bartsch

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Power Calculations for Randomized Controlled Trials with Auxiliary Observational Data.

Jaylin Lowe, Charlotte Z. Mann, Jiaying Wang, Adam Sales, Johann A. Gagnon-Bartsch

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Causal Inference in Educational Data Mining.

Anthony F. Botelho, Avery Harrison Closser, Adam C. Sales, Neil T. Heffernan, Kirk P. Vanacore

Proceedings of the 17th International Conference on Educational Data Mining, 2024

2023

A Bandit You Can Trust.

Ethan Prihar, Adam Sales, Neil T. Heffernan

Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, 2023

Benefit of Gamification for Persistent Learners: Propensity to Replay Problems Moderates Algebra-Game Effectiveness.

Kirk Vanacore, Adam Sales, Allison S. Liu, Erin Ottmar

Proceedings of the Tenth ACM Conference on Learning @ Scale, 2023

Investigating the Impact of Skill-Related Videos on Online Learning.

Ethan Prihar, Aaron Haim, Tracy Jia Shen, Adam Sales, Dongwon Lee, Xintao Wu, Neil T. Heffernan

Proceedings of the Tenth ACM Conference on Learning @ Scale, 2023

How Common are Common Wrong Answers? Crowdsourcing Remediation at Scale.

Ashish Gurung, Sami Baral, Morgan P. Lee, Adam C. Sales, Aaron Haim, Kirk P. Vanacore, Andrew A. McReynolds, Hilary Kreisberg, Cristina Heffernan, Neil T. Heffernan

Proceedings of the Tenth ACM Conference on Learning @ Scale, 2023

Effective Evaluation of Online Learning Interventions with Surrogate Measures.

Ethan Prihar, Kirk Vanacore, Adam Sales, Neil T. Heffernan

Proceedings of the 16th International Conference on Educational Data Mining, 2023

2022

Automatic Interpretable Personalized Learning.

Ethan Prihar, Aaron Haim, Adam Sales, Neil T. Heffernan

Proceedings of the L@S'22: Ninth ACM Conference on Learning @ Scale, New York City, NY, USA, June 1, 2022

Using the Open Science Framework to promote Open Science in Education Research.

Stacy T. Shaw, Adam Sales

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

Causal Inference in Educational Data Mining.

Adam Sales, Neil T. Heffernan

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

Exploring Common Trends in Online Educational Experiments.

Ethan Prihar, Manaal Syed, Korinn Ostrow, Stacy T. Shaw, Adam Sales, Neil T. Heffernan

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

More Powerful A/B Testing Using Auxiliary Data and Deep Learning.

Adam Sales, Ethan Prihar, Johann Gagnon-Bartsch, Ashish Gurung, Neil T. Heffernan

Proceedings of the Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners' and Doctoral Consortium, 2022

2021

Toward Personalizing Students' Education with Crowdsourced Tutoring.

Ethan Prihar, Thanaporn Patikorn, Anthony Botelho, Adam Sales, Neil T. Heffernan

Proceedings of the L@S'21: Eighth ACM Conference on Learning @ Scale, 2021

Estimating the Intelligent Tutor Effects on Specific Posttest Problems.

Adam Sales, Ethan Prihar, Neil T. Heffernan, John Pane

Proceedings of the 14th International Conference on Educational Data Mining, 2021

2020

The effect of teachers reassigning students to new Cognitive Tutor sections.

Adam Sales, John Pane

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

2018

Using Big Data to Sharpen Design-Based Inference in A/B Tests.

Adam Sales, Anthony Botelho, Thanaporn Patikorn, Neil T. Heffernan

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

2017

Tutorial: Principal Stratification for EDM Experiments.

Adam Sales

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

2016

A systematic analysis of the science of sandboxing.

Michael Maass, Adam Sales, Benjamin Chung, Joshua Sunshine

PeerJ Comput. Sci., 2016

Discovering 'Tough Love' Interventions Despite Dropout.

Joseph Jay Williams, Anthony Botelho, Adam Sales, Neil T. Heffernan, Charles Lang

Proceedings of the 9th International Conference on Educational Data Mining, 2016

Student Usage Predicts Treatment Effect Heterogeneity in the Cognitive Tutor Algebra I Program.

Adam Sales, Asa Wilks, John Pane

Proceedings of the 9th International Conference on Educational Data Mining, 2016

2015

Exploring Causal Mechanisms in a Randomized Effectiveness Trial of the Cognitive Tutor Algebra I Program.

Adam Sales, John Pane

Proceedings of the 8th International Conference on Educational Data Mining, 2015