Schroeder, N. L., & Cenkci, A. T. (2018). Spatial contiguity and spatial split-attention effects in multimedia learning environments: A meta-analysis. Educational Psychology Review, 30, 679–701.
Ginns, P. (2005). Meta-analysis of the modality effect. Learning and Instruction, 15(4), 313–331.
Prior knowledge
Hattie, J. (2009). Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. Routledge.
Ausubel, D. P. (1968). Educational Psychology: A Cognitive View. Holt, Rinehart & Winston.
Simonsmeier, B. A., Flaig, M., Deiglmayr, A., Schalk, L., & Schneider, M. (2021). Domain-specific prior knowledge and learning: A meta-analysis. Educational Psychologist, 57(1), 31–54.
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5(2), 121–152.
The YouTube aha moment and media effects
Clark, R. E. (1983). Reconsidering research on learning from media. Review of Educational Research, 53(4), 445–459.
Russell, T. L. (1999). The No Significant Difference Phenomenon. North Carolina State University.
Noetel, M., Griffith, S., Delaney, O., Sanders, T., Parker, P., del Pozo Cruz, B., & Lonsdale, C. (2021). Video improves learning in higher education: A systematic review. Review of Educational Research, 91(2), 204–236.
Deslauriers, L., McCarty, L. S., Miller, K., Callaghan, K., & Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences, 116(39), 19251–19257.
Kounios, J., & Beeman, M. (2014). The cognitive neuroscience of insight. Annual Review of Psychology, 65, 71–93.
Retrieval practice and testing effect
Roediger, H. L., III, & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255.
Rowland, C. A. (2014). The effect of testing versus restudy on retention: A meta-analytic review. Psychological Bulletin, 140(6), 1432–1463.
Adesope, O. O., Trevisan, D. A., & Sundararajan, N. (2017). Rethinking the use of tests: A meta-analysis of practice testing. Review of Educational Research, 87(3), 659–701.
Karpicke, J. D., & Blunt, J. R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331(6018), 772–775.
Agarwal, P. K., Nunes, L. D., & Blunt, J. R. (2021). Retrieval practice consistently benefits student learning: A systematic review of applied research in school classrooms. Educational Psychology Review, 33, 1409–1453.
Pan, S. C., & Rickard, T. C. (2018). Transfer of test-enhanced learning: Meta-analytic review and synthesis. Psychological Bulletin, 144(7), 710–756.
Spacing and distributed practice
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354–380.
Cepeda, N. J., Vul, E., Rohrer, D., Wixted, J. T., & Pashler, H. (2008). Spacing effects in learning: A temporal ridgeline of optimal retention. Psychological Science, 19(11), 1095–1102.
Interleaving
Brunmair, M., & Richter, T. (2019). Similarity matters: A meta-analysis of interleaved learning and its moderators. Psychological Bulletin, 145(11), 1029–1052.
Pan, S. C., Tajran, J., Lovelett, J., Osuna, J., & Rickard, T. C. (2019). Does interleaved practice enhance foreign language learning? The effects of training schedule on Spanish verb conjugation skills. Journal of Educational Psychology, 111(7), 1172–1188.
Study strategies review
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58.
Desirable difficulties
Bjork, R. A. (1994). Memory and metamemory considerations in the training of human beings. In J. Metcalfe & A. Shimamura (Eds.), Metacognition: Knowing About Knowing (pp. 185–205). MIT Press.
Bjork, E. L., & Bjork, R. A. (2011). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. In M. A. Gernsbacher et al. (Eds.), Psychology and the Real World (pp. 56–64). Worth.
Soderstrom, N. C., & Bjork, R. A. (2015). Learning versus performance: An integrative review. Perspectives on Psychological Science, 10(2), 176–199.
Koriat, A., & Bjork, R. A. (2005). Illusions of competence in monitoring one’s knowledge during study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(2), 187–194.
Karpicke, J. D., & Roediger, H. L., III (2008). The critical importance of retrieval for learning. Science, 319(5865), 966–968.
Productive failure
Sinha, T., & Kapur, M. (2021). When problem solving followed by instruction works: Evidence for productive failure. Review of Educational Research, 91(4), 823–861.
Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for future learning: The hidden efficiency of encouraging original student production in statistics instruction. Cognition and Instruction, 22(2), 129–184.
Expertise reversal effect
Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors, 40(1), 1–17.
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38(1), 23–31.
Tetzlaff, L., Peters, L., & Simonsmeier, B. A. (2025). The expertise reversal effect: A meta-analysis. Educational Psychology Review, 37.
Interactive simulations
Finkelstein, N. D., Adams, W. K., Keller, C. J., Kohl, P. B., Perkins, K. K., Podolefsky, N. S., Reid, S., & LeMaster, R. (2005). When learning about the real world is better done virtually: A study of substituting computer simulations for laboratory equipment. Physical Review Special Topics — Physics Education Research, 1, 010103.
Wieman, C. E., Adams, W. K., & Perkins, K. K. (2008). PhET: Simulations that enhance learning. Science, 322(5902), 682–683.
Adams, W. K. (2009). Student engagement and learning with PhET interactive simulations. In Il Nuovo Cimento C, 33, 21–32.
Podolefsky, N. S., Moore, E. B., & Perkins, K. K. (2014). Implicit scaffolding in interactive simulations: Design strategies to support multiple educational goals. Working paper, University of Colorado Boulder.
Usmeldi (2026). Meta-analysis of PhET interactive simulations on student learning outcomes. (Aggregation of 47 effect sizes, 20 studies, N = 4,563.)
Worked examples and adaptive fading
Renkl, A., Atkinson, R. K., Maier, U. H., & Staley, R. (2002). From example study to problem solving: Smooth transitions help learning. Journal of Experimental Education, 70(4), 293–315.
Analogies
Gentner, D., & Gentner, D. R. (1983). Flowing waters or teeming crowds: Mental models of electricity. In D. Gentner & A. L. Stevens (Eds.), Mental Models (pp. 99–129). Lawrence Erlbaum.
Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7(2), 155–170.
Clement, J. (1993). Using bridging analogies and anchoring intuitions to deal with students’ preconceptions in physics. Journal of Research in Science Teaching, 30(10), 1241–1257.
Spiro, R. J., Feltovich, P. J., Coulson, R. L., & Anderson, D. K. (1989). Multiple analogies for complex concepts: Antidotes for analogy-induced misconception in advanced knowledge acquisition. In S. Vosniadou & A. Ortony (Eds.), Similarity and Analogical Reasoning (pp. 498–531). Cambridge University Press.
Duit, R. (1991). On the role of analogies and metaphors in learning science. Science Education, 75(6), 649–672.
Taber, K. S. (2001). The mismatch between assumed prior knowledge and the learner’s conceptions: A typology of learning impediments. Educational Studies, 27(2), 159–171.
Motivation and self-determination theory
Howard, J. L., Bureau, J., Guay, F., Chong, J. X. Y., & Ryan, R. M. (2021). Student motivation and associated outcomes: A meta-analysis from Self-Determination Theory. Perspectives on Psychological Science, 16(6), 1300–1323.
Bureau, J. S., Howard, J. L., Chong, J. X. Y., & Guay, F. (2022). Pathways to student motivation: A meta-analysis of antecedents of autonomous and controlled motivations. Review of Educational Research, 92(4), 527–569.
Hanus, M. D., & Fox, J. (2015). Assessing the effects of gamification in the classroom: A longitudinal study on intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Computers & Education, 80, 152–161.
LLM failure modes in education
Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, O., & Mariman, R. (2025). Generative AI can harm learning. Proceedings of the National Academy of Sciences, 122(2).
SycEval study (2025). Sycophancy in AI tutoring interactions. Presented at FAccT 2025.
Wang, X., & Fan, S. (2025). ChatGPT and learning outcomes: A meta-analysis. (51 studies, g = 0.867.)
AI tutoring systems and constrained architectures
VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221.
Demszky, D., Liu, J., Mancenido, Z., Cohen, J., Hill, H., Jurafsky, D., & Hashimoto, T. (2024). Can AI improve the quality of human tutoring? A randomized controlled trial with Tutor CoPilot. Proceedings of EMNLP 2024.
MWPTutor (ETH Zurich, 2024). LLM dialogue within finite state transducers for math word problem tutoring.
SocraticLM (2024). Fine-tuning for Socratic tutoring dialogue. NeurIPS 2024.
Corbett, A. T., & Anderson, J. R. (1994). Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction, 4(4), 253–278.
Proven adaptive learning platforms
Pane, J. F., Griffin, B. A., McCaffrey, D. F., & Karam, R. (2014). Effectiveness of Cognitive Tutor Algebra I at scale. Educational Evaluation and Policy Analysis, 36(2), 127–144. (RAND Corporation MATHia study.)
Falmagne, J.-C., Koppen, M., Villano, M., Doignon, J.-P., & Johannesen, L. (1990). Introduction to knowledge spaces: How to build, test, and search them. Psychological Review, 97(2), 201–224. (Foundational Knowledge Space Theory behind ALEKS.)
Muralidharan, K., Singh, A., & Ganimian, A. J. (2019). Disrupting education? Experimental evidence on technology-aided instruction in India. American Economic Review, 109(4), 1426–1460. (Mindspark RCT.)
Teaching at the Right Level
Banerjee, A., Banerji, R., Berry, J., Duflo, E., Kannan, H., Mukerji, S., Shotland, M., & Walton, M. (2017). From proof of concept to scalable policies: Challenges and solutions, with an application. Journal of Economic Perspectives, 31(4), 73–102.
Pratham (multiple years). Teaching at the Right Level program evaluations. J-PAL affiliated.
Video and multimedia learning
Mayer, R. E. (2009). Multimedia Learning (2nd ed.). Cambridge University Press.
Guo, P. J., Kim, J., & Rubin, R. (2014). How video production decisions affect student engagement: An empirical study of MOOC videos. Proceedings of ACM L@S 2014, 41–50.
Szpunar, K. K., Khan, N. Y., & Schacter, D. L. (2013). Interpolated memory tests reduce mind wandering and improve learning of online lectures. Proceedings of the National Academy of Sciences, 110(16), 6313–6317.