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ORCIDAdam Sales
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- affiliation: Worcester Polytechnic Institute, MA, USA
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2020 – today
- 2024
[c20]Kirk Vanacore
, Ashish Gurung, Adam Sales, Neil T. Heffernan:
The Effect of Assistance on Gamers: Assessing The Impact of On-Demand Hints & Feedback Availability on Learning for Students Who Game the System. LAK 2024: 462-472- [c19]Ashish Gurung, Kirk Vanacore, Andrew A. McReynolds, Korinn S. Ostrow, Eamon Worden, Adam C. Sales, Neil T. Heffernan:
Multiple Choice vs. Fill-In Problems: The Trade-off Between Scalability and Learning. LAK 2024: 507-517 - 2023
- [c18]Ethan Prihar, Kirk Vanacore, Adam Sales, Neil T. Heffernan:
Effective Evaluation of Online Learning Interventions with Surrogate Measures. EDM 2023 - [c17]Ethan Prihar, Aaron Haim, Tracy Jia Shen, Adam Sales, Dongwon Lee, Xintao Wu, Neil T. Heffernan:
Investigating the Impact of Skill-Related Videos on Online Learning. L@S 2023: 4-13 - [c16]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:
How Common are Common Wrong Answers? Crowdsourcing Remediation at Scale. L@S 2023: 70-80 - [c15]Kirk Vanacore, Adam Sales, Allison S. Liu, Erin Ottmar:
Benefit of Gamification for Persistent Learners: Propensity to Replay Problems Moderates Algebra-Game Effectiveness. L@S 2023: 164-173 - [c14]Ethan Prihar, Adam Sales, Neil T. Heffernan:
A Bandit You Can Trust. UMAP 2023: 106-115 - 2022
- [c13]Adam Sales, Ethan Prihar, Johann Gagnon-Bartsch, Ashish Gurung, Neil T. Heffernan:
More Powerful A/B Testing Using Auxiliary Data and Deep Learning. AIED (2) 2022: 524-527 - [c12]Ethan Prihar, Manaal Syed, Korinn Ostrow, Stacy T. Shaw, Adam Sales, Neil T. Heffernan:
Exploring Common Trends in Online Educational Experiments. EDM 2022 - [c11]Adam Sales, Neil T. Heffernan:
Causal Inference in Educational Data Mining. EDM 2022 - [c10]Stacy T. Shaw, Adam Sales:
Using the Open Science Framework to promote Open Science in Education Research. EDM 2022 - [c9]Ethan Prihar, Aaron Haim, Adam Sales, Neil T. Heffernan:
Automatic Interpretable Personalized Learning. L@S 2022: 1-11 - 2021
- [c8]Adam Sales, Ethan Prihar, Neil T. Heffernan, John Pane:
Estimating the Intelligent Tutor Effects on Specific Posttest Problems. EDM 2021 - [c7]Ethan Prihar, Thanaporn Patikorn, Anthony Botelho, Adam Sales, Neil T. Heffernan:
Toward Personalizing Students' Education with Crowdsourced Tutoring. L@S 2021: 37-45 - 2020
- [c6]Adam Sales, John Pane:
The effect of teachers reassigning students to new Cognitive Tutor sections. EDM 2020
2010 – 2019
- 2018
- [c5]Adam Sales, Anthony Botelho, Thanaporn Patikorn, Neil T. Heffernan:
Using Big Data to Sharpen Design-Based Inference in A/B Tests. EDM 2018 - 2017
- [c4]Adam Sales:
Tutorial: Principal Stratification for EDM Experiments. EDM 2017 - 2016
- [j1]Michael Maass, Adam Sales, Benjamin Chung, Joshua Sunshine:
A systematic analysis of the science of sandboxing. PeerJ Comput. Sci. 2: e43 (2016) - [c3]Adam Sales, Asa Wilks, John Pane:
Student Usage Predicts Treatment Effect Heterogeneity in the Cognitive Tutor Algebra I Program. EDM 2016: 207-214 - [c2]Joseph Jay Williams, Anthony Botelho, Adam Sales, Neil T. Heffernan, Charles Lang:
Discovering 'Tough Love' Interventions Despite Dropout. EDM 2016: 650-651 - 2015
- [c1]Adam Sales, John Pane:
Exploring Causal Mechanisms in a Randomized Effectiveness Trial of the Cognitive Tutor Algebra I Program. EDM 2015: 504-507
Coauthor Index
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