| 2025 | CogSci | Training Methods in Categorization: A Comparison of Classification and Observation on Rule Adoption and Rule Consistency. | Yu-Wei Chang, Michael L. Kalish, Daniel Corral |
| 2025 | CogSci | The Role of Insight and Analytic Learning During Concept Acquisition. | Maci DelFavero, Daniel Corral |
| 2025 | CogSci | Classification Versus Observation through Within- and Between-Category Comparison. | Rachel Lynn Perri, Michael L. Kalish, Daniel Corral |
| 2024 | CogSci | Towards a Unified Model Describing Multiple Tasks: Extending the Retrieving Effectively from Memory Model to Categorization. | Sinem Aytac, Yu-Wei Chang, Michael L. Kalish, Daniel Corral |
| 2024 | CogSci | Extending the Locally Bayesian Learning Model to Exemplar-Based Categorization with Continuous Features. | Yu-Wei Chang, Sinem Aytac, Cindy G. Mendoza Gonzalez, Michael L. Kalish, Daniel Corral |
| 2023 | CogSci | The Effects of Causal Structure on Causal Attribution Judgements. | Judith L. Burkle, Micah B. Goldwater, Daniel Corral |
| 2022 | CogSci | The Effects of Reflective Reasoning on Philosophical Dilemmas. | William T. Ervin, Daniel Corral |
| 2022 | CogSci | Testing the testing effect with featural and relational categories. | Enoch Sumakpoyaa, Daniel Corral |
| 2018 | CogSci | When being wrong makes you right: Incorrect examples improve complex concept learning. | Daniel Corral, Shana Carpenter, Samara Clingan-Siverly |
| 2017 | CogSci | Learning Relational Concepts through Unitary versus Compositional Representations. | Daniel Corral, Matt Jones |
| 2012 | CogSci | Learning of Relational Categories as a Function of Higher-Order Structure. | Daniel Corral, Matt Jones |