Publications

Copyright notice: Clicking a link below is a request for a personal copy of the article and my delivery of a personal copy.  Any other use is prohibited. An always updated list of papers is available in my Google Scholar profile.  

Papers

23. Yan, V. X., Sana, F., & Carvalho, P. F. (2023). No Simple Solutions to Complex Problems: Cognitive Science Principles Can Guide but Not Prescribe Educational Decisions. Policy Insights from the Behavioral and Brain Sciences [Invited Submission] [link] [pdf]

22. Koedinger, K. R., Carvalho, P.F., Liu, R., & McLaughlin, E. A. (2023). An Astonishing Regularity in Student Learning Rate. Proceedings of the National Academy of Sciences, 120(13), e2221311120. [link] [pdf]

21. Carvalho, P. F., McLaughlin, E. A., & Koedinger, K. R. (2022). Varied Practice Testing Is Associated With Better Learning Outcomes in Self-Regulated Online Learning. Journal of Educational Psychology. Advance online publication. [link] [pdf]

20. Carvalho, P.F., & Goldstone, R.L. (2022). A computational model of context-dependent encodings during category learning. Cognitive Science, 46 (4), e13128. [link] [pdf]

19. Sana, F., Yan, V.X., & Carvalho, P.F. (2022). On rest-from-deliberate-practice as a mechanism for the spacing effect: Commentary on Chen et al. (2021). Educational Psychology Review. https://doi.org/10.1007/s10648-022-09663-8 [link] [pdf]

18. de Leeuw, J.R., Motz, B.A., Fyfe, E.R., Carvalho, P.F., & Goldstone, R.L. (2022) Generalizability, transferability, and the practice-to-practice gap. Behavioral and Brain Sciences, 45, E11. doi:10.1017/S0140525X21000406 [preprint]

17. Carvalho, P.F., Chen, C., & Yu, C. (2021). The distributional properties of exemplars affect category learning and generalization. Scientific Reports, 11:11263, 1-10. [link] [pdf] [data and stimuli]

16. Fyfe, E., de Leeuw, J. R., Carvalho, P. F., Goldstone, R., Sherman, J., … Motz, B. (2021). ManyClasses 1: Assessing the generalizable effect of immediate versus delayed feedback across many college classes. Advances in Methods and Practices in Psychological Science. [link] [pdf] [data, stimuli, and registration]

15. Carvalho, P.F., & Goldstone, R.L. (2021). The most efficient sequence of study depends on the type of test. Applied Cognitive Psychology, 35 (1), 82-97. [link] [pdf] [data and stimuli]

14. Carvalho. P.F., Sana, F., Yan, V. X. (2020). Self-regulated Spacing in a Massive Open Online Course is Related to Better Learning. Nature Science of Learning, 5, 2. https://doi.org/10.1038/s41539-020-0061-1 [link]

13. Motz, B.A., Carvalho, P.F., de Leeuw, J.R., & Goldstone, R.L. (2018). Embedding Experiments: Staking Causal Inference in Authentic Educational Contexts. Journal of Learning Analytics, 5(2), 47–59. http://dx.doi.org/10.18608/jla.2018.52.4. [link] [pdf]

12. Carvalho, P.F., Vales, C., Fausey, C.M., & Smith, L.B. (2018). Novel names extend for how long preschool children sample visual information. Journal of Experimental Child Psychology, 168, 1-8. [link] [pdf] [data and stimuli]

11. Motz, B.A, de Leeuw, J.R., Carvalho, P.F., Liang, K.L., & Goldstone, R.L. (2017). A Dissociation between Engagement and Learning: Enthusiastic Instructions Fail to Reliably Improve Performance on a Memory Task. PLoS ONE 12(7): e0181775, DOI: 10.1371/journal.pone.0181775  [link] [pdf] [data and stimuli]

10. Carvalho, P.F., & Goldstone, R.L (2017). The sequence of study changes what information is attended to, encoded and remembered during category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(11), 1699-1719. [link] [pdf] [data & stimuli]

09. Meagher, B.J., Carvalho, P.F., Goldstone, R.L., & Nosofsky, R.M. (2017). Organized Simultaneous Displays Facilitate Learning of Complex Natural Science Categories. Psychonomic Bulletin & Review, 24(6), 1987-1994. [link] [pdf] [data]

08. Carvalho, P.F., & Goldstone, R.L. (2017). Zebras and antelopes: category sparsity as the result of the relations between objects and within categories. Language, Cognition, and Neuroscience, 32(8) 944-946. doi: 10.1080/23273798.2016.1236978 [Commentary on Perry & Lupyan (2016) “Recognizing a zebra from its stripes and the stripes from ‘zebra’: the role of verbal labels in selecting category relevant information”] [Link] [pdf]

07. Carvalho, P.F.*, Braithwaite, D. W.*, de Leeuw, J.R., Motz, B.A., & Goldstone, R.L. (2016) An in vivo study of self-regulated study sequencing in Introductory Psychology courses, PLoS ONE 11 (3), 1-16. [Link] [pdf] [data & materials] *equal author contribution

06. Carvalho, P.F., & Goldstone, R.L. (2015). What you learn is more than what you see: What can sequencing effects tell us about inductive category learning? Frontiers in Psychology, 6(505), 1-12. [Link] [pdf] [supplemental material]

05. Carvalho, P.F., & Goldstone, R.L. (2015). The benefits of interleaved and blocked study: Different tasks benefit from different schedules of study. Psychonomic Bulletin & Review, 22, 281-288. DOI:10.3758/s13423-014-0676-4 [Link] [pdf] [supplemental material 1] [supplemental material 2] [data]

04. Brunel, L., Carvalho, P. F., & Goldstone, R.L. (2015). It does belong together: Cross-modal correspondences influence cross-modal integration during perceptual learning. Frontiers in Psychology, 6(358), 1-10. [Link] [pdf]

03. Carvalho, P.F. & Goldstone, R.L. (2014). Effects of Interleaved and Blocked Study on Delayed Test of Category Learning Generalization. Frontiers in Psychology, 5 (936), 1-10. [Link] [pdf] [data & stimuli]

02. Carvalho, P.F., & Goldstone, R.L. (2014). Putting category learning in order: category structure and temporal arrangement affect the benefit of interleaved over blocked study. Memory & Cognition, 42(3), 481-495. [Link] [pdf] [supplemental material 1] [data & stimuli]

01. Carvalho, P. F., & Albuquerque, P. B. (2012). Memory encoding of stimulus features in human perceptual learning. Journal of Cognitive Psychology, 24(6), 654-664. [Link] [pdf] [data & stimuli]

Preprints

05. Wei, Y.*, Carvalho, P.F., Stamper, J. (under review). Uncovering Name-Based Biases in Large Language Models Through Simulated Trust Game.  [link]

04. Asher, M. W., Sana., F., Koedinger, K.R., & Carvalho, P.F. (under review). Students Can Learn More Efficiently When Lectures Are Replaced with Practice Opportunities and Feedback. [link]

03. Carvalho, P.F., Sana, F. & Koedinger, K. R. (under review). Do upfront reading assignments aid learning beyond practice with feedback? [link]

02. Carvalho, P.F. & Godwin, K. (under review). Comparing generating predictions with retrieval practice as learning strategies for primary school children. [link]

01. Schuetze, B.A., Yan, V.X., & Carvalho, P.F. (under review). Capturing Session-to-Session Dynamics of Learning and Forgetting: A Test of Existing Knowledge Tracing Models. [link]

Book Chapters

05. Yan, V., Carvalho, P.F., & Sana, F. (2023). How Students' Decisions to Space Their Practice are Related to Better Learning. In Overson, C. E.,  Hakala, C. M.,  Kordonowy, L. L. & Benassi, V. A. (Eds). In their own words: What scholars want you to know about why and how to apply the science of learning in your academic setting (pp. 473-449). Society for the Teaching of Psychology. https://teachpsych.org/ebooks/itow

04. Carvalho, P. F., & Goldstone, R.L. (2019). When does interleaving practice improve learning?. In J. Dunlosky & K. Rawson (Eds). The Cambridge Handbook of Cognition and Education (pp. 411-436). Cambridge University Press. [link] [pdf]

03. Goldstone, R. L., Kersten, A., & Carvalho, P. F. (2017).  Categorization and Concepts.  In J. Wixted (Ed.) Stevens’ Handbook of Experimental Psychology and Cognitive neuroscience, Fourth Edition, Volume Three: Language & Thought (pp. 275-317). New Jersey: Wiley. [pdf]

02. Carvalho, P.F., & Goldstone, R.L. (2016). Human Perceptual Learning and Categorization. In Murphy R.A., & Honey, R.C. (Eds). The Wiley Handbook on The Cognitive Neuroscience of Learning (pp. 223-248). Chichester, West Sussex, UK: John Wiley & Sons Ltd.​ [pdf]

01. Goldstone, R. L., Kersten, A., & Carvalho, P.F. (2013). Concepts and Categorization. In Weiner, I.B, Healey, A.J., & Proctor, R.W. (Eds.) Handbook of Psychology, Volume 4, Experimental Psychology, 2nd Edition (pp. 607-630). New York, NY: Wiley. [pdf]

Peer-Reviewed Conference Proceedings

*undergraduate student  author; **graduate student author

28. Gold, G.*, Borchers, C.*, & Carvalho, P.F. (2024). Students’ Academic Performance and Goal Orientation Relate to Initial Knowledge but Not Learning Rate. Companion Proceedings 14th International Conference on Learning Analytics & Knowledge (LAK24). [link] [pdf]

27. Borchers, C.*, Carvalho, P.F., Xia, M., Liu, P., Koedinger, K.R., Aleven, V. (2023). What Makes Problem-Solving Practice Effective? Comparing Paper and AI Tutoring. In Proceedings of the Eighteenth European Conference on Technology Enhanced Learning. [link] [pdf]

26. Rachatasumrit, N.**, Carvalho, P.F., Li, S.*, Koedinger, K.R. (2023). Content Matters: A Computational Investigation into the Effectiveness of Retrieval Practice and Worked Examples. In: Wang, N., Rebolledo-Mendez, G., Matsuda, N., Santos, O.C., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2023. Lecture Notes in Computer Science(), vol 13916. Springer, Cham. [link] [pdf] **Best paper award**

25. Carvalho, P.F., Rachatasumrit, N., & Koedinger, K.R. (2022). Learning depends on knowledge: The benefits of retrieval practice vary for facts and skills. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [pdf]

24. Chine, D. R., Brentley, C., Thomas-Browne, C., Richey, J.E., Gul, A., Carvalho, P.F., Branstetter, L., & Koedinger, K.R. (2022). Educational Equity Through Combined Human-AI Personalization: A Propensity Matching Evaluation. International Conference on Artificial Intelligence in Education (pp. xx-xx). [pdf]

23. Hou, X., Carvalho, P. F., & Koedinger, K. R. (2021) Drinking Our Own Champagne: Analyzing the Impact of Learning-by-doing Resources in an E-learning Course. In Companion Proceedings of the 11th International Conference on Learning Analytics & Knowledge (LAK21). [pdf]

22. Richey, J. E., Lobczowski, N. G., Carvalho, P. F., & Koedinger, K. (2020). Comprehensive Views of Math Learners: A Case for Modeling and Supporting Non-math Factors in Adaptive Math Software. In International Conference on Artificial Intelligence in Education (pp. 460-471). Springer, Cham. [pdf]

21. Motz, B. & Carvalho, P. F. (2019). Not whether, but where: Scaling-up how we think about effects and relationships in natural educational contexts. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge (LAK19). doi: 10.13140/RG.2.2.30825.34407

20. Thaker, K.**, Carvalho, P.F., & Koedinger, K.R. (2019). Comprehension Factor Analysis: Modeling student’s reading behaviour. Proceedings of the 9th International Learning Analytics and Knowledge (LAK) Conference. [pdf]

19. Koedinger, K.R., Stamper, J., & Carvalho, P.F. (2019). Sharing and Reusing Data and Analytic Methods with LearnSphere. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge (LAK19).

Stamper, J., Carvalho, P.F., Moore, S., & Koedinger, K.R. (2019). Tigris: An Online Workflow Tool for Sharing Educational Data and Analytic Methods. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge (LAK19).

18. Chounta, I. & Carvalho. P.F. (2019). Square it up! How to model step duration when predicting student performance.  Proceedings of the 9th International Learning Analytics and Knowledge (LAK) Conference. [pdf]

17. Carvalho, P.F. (2018). Understanding the Dynamics of Learning: The Case for Studying Interactions. In T.T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 51-52). Austin, TX: Cognitive Science Society. [pdf]

16. Carvalho, P.F., Manke, K.J, & Koedinger, K.R. (2018). Not all Active Learning is Equal: Predicting and Explaining Improves Transfer Relative to Answering Practice Questions. In T.T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 1458-1463). Austin, TX: Cognitive Science Society. [pdf] [data & stimuli]

15. Carvalho, P.F., Gao, M.*, Motz, B.A., & Koedinger, K.R. (2018). Analyzing the relative learning benefits of completing required activities and optional readings in online courses. In Proceedings of the 11th International Conference on Educational Data Mining. Buffalo, NY.  [pdf]

14. Chounta, I. A., Carvalho, P.F. (2018). Will time tell? Exploring the relationship between step duration and student performance. In Kay, J. & Luckin, R. (Eds.), Rethinking Learning in the Digital Age: Making the Learning Sciences Count, 13th International Conference of the Learning Sciences (ICLS) 2018, Volume 2 (pp. 993-996). London, UK: International Society of the Learning Sciences. [pdf]

13. Carvalho, P.F., McLaughlin, E. A., & Koedinger, K.R. (2017). Is there an explicit learning bias? Students beliefs, behaviors and learning outcomes.  In G. Gunzelmann, A. Howes,, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (pp 204-209). Austin TX: Cognitive Science Society. [pdf] 

12. Carvalho, P.F. & Goldstone, R.L. (2017). The most efficient sequence of study depends on the type of test. In G. Gunzelmann, A. Howes,, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (pp 198-203). Austin TX: Cognitive Science Society. [pdf] 

11. Finch, D. D.*, Carvalho, P.F., & Goldstone, R.L. (2016). Variability in category learning: The Effect of Context Change and Item Variation on Knowledge Generalization. In A. Papafragou, D. Grodner, D. Mirman, & J.C. Trueswell (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society (pp 2327-2332). Austin TX: Cognitive Science Society. [pdf] 

10. Carvalho, P.F., Braithwaite, D. W., de Leeuw, J. R., Motz, B. A., & Goldstone, R.L. (2015). Effectiveness of Learner-Regulated Study Sequence: An in-vivo study in Introductory Psychology courses. In Noelle, D. C., Dale, R., Warlaumont, A. S., Yoshimi, J., Matlock, T., Jennings, C. D., & Maglio, P. P. (Eds.), Proceedings of the 37th Annual Meeting of the Cognitive Science Society (pp. 309-314). Austin, TX: Cognitive Science Society. [pdf]

09. Kost, A. S.*, Carvalho, P. F., Goldstone, R. L. (2015). Can You Repeat That? The Effect of Item Repetition on Interleaved and Blocked Study. In Noelle, D. C., Dale, R., Warlaumont, A. S., Yoshimi, J., Matlock, T., Jennings, C. D., & Maglio, P. P. (Eds.), Proceedings of the 37th Annual Meeting of the Cognitive Science Society (pp. 1189-1194). Austin, TX: Cognitive Science Society. [pdf]

08. Carvalho, P.F., & Goldstone, R.L (2014) Effects of interleaved and blocked study in a 24 hour delayed transfer test. [Abstract] In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 1760-1765). Austin, TX: Cognitive Science Society. [pdf]

07. Weitnauer, E., Carvalho, P.F., Goldstone, R.L., & Ritter, H. (2014). Similarity-based Ordering of Instances for Efficient Concept Learning. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 1760-1765). Austin, TX: Cognitive Science Society. [pdf]

06. Carvalho, P.F., & Goldstone, R.L. (2013). How to present exemplars of several categories? Interleave during active learning and block during passive learning. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [pdf]

05. Carvalho, P.F., Vales, C., Fausey, C. M. & Smith, L.B. (2013). An eyetracking study of children's relational thinking: The role of labels and sustained attention. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [pdf]

04. Weitnauer, E., Carvalho, P.F., Goldstone, R.L., & Ritter, H. (2013). Grouping by Similarity Helps Concept Learning. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [pdf]

03. Carvalho, P.F., & Goldstone, R.L. (2012). Category structure modulates interleaving and blocking advantage in inductive category acquisition. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 186-191), Austin, TX: Cognitive Science Society. [pdf]

02. Hendrickson, A.T., Carvalho, P.F., & Goldstone, R.L. (2012). Going to Extremes: The influence of unsupervised categories on the mental caricaturization of faces and asymmetries in perceptual discrimination. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 1662-1667), Austin, TX: Cognitive Science Society. [pdf]

01. Carvalho, P.F., & Goldstone, R.L. (2011). Sequential similarity and comparison effects in category learning. In L. Carlson, C. Hölscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. [pdf] [data & stimuli]