Learning Literature: The Research Behind Effective Study Techniques | Unisium

From Masterful Learning 15 min read Updated 9/9/2025
learning-science cognitive-psychology ACT-R retrieval-practice spaced-repetition self-explanation interleaving evidence-based

Since 2015 I’ve explored how people actually learn—first through my online course Primal Learning, then a PhD in physics education, and now postdoctoral work at the University of Bergen. This path in cognitive science shaped both Masterful Learning and Unisium, especially strategies like retrieval practice, spaced repetition, and self-explanation.

ACT-R (Adaptive Control of Thought-Rational) has been especially instrumental in forming my understanding of how learning actually works. John Anderson’s cognitive architecture provides the most compelling framework I’ve encountered for understanding memory, skill acquisition, and the mechanisms behind effective learning strategies.

This bibliography represents the research foundation that shaped every recommendation in Masterful Learning. While the book is written for students rather than academics—keeping inline citations minimal—every strategy is grounded in decades of rigorous cognitive science research.

How to use this list: Dive into the theories and papers that interest you the most. The strategy-specific sections let you explore particular strategies like retrieval practice and spaced repetition. The complete reference list serves researchers and skeptics who want to verify claims and explore further.

Table of Contents


Theoretical Foundations

ACT-R & Cognitive Architecture

Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89(4), 369-406.

Anderson, J. R. (1983). The Architecture of Cognition. Lawrence Erlbaum Associates.

Anderson, J. R. (1987). Skill acquisition: Compilation of weak-method problem solutions. Psychological Review, 94(2), 192-210.

Anderson, J. R. (1990). The Adaptive Character of Thought. L. Erlbaum Associates.

Anderson, J. R. (1991). The adaptive nature of human categorization. Psychological Review, 98(3), 409-429.

Anderson, J. R. (1993). Rules of the Mind. Psychology Press.

Anderson, J. R. (2002). Spanning seven orders of magnitude: A challenge for cognitive modeling. Cognitive Science, 26(1), 85-112.

Anderson, J. R. (2007). How Can the Human Mind Occur in the Physical Universe? Oxford University Press.

Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. L. (2004). An integrated theory of the mind. Psychological Review, 111(4), 1036-1060.

Anderson, J. R., & Lebiere, C. (1998). The Atomic Components of Thought. Lawrence Erlbaum Associates.

Anderson, J. R., Bothell, D., Lebiere, C., & Matessa, M. (1998). An integrated theory of list memory. Journal of Memory and Language, 38(4), 341-380.

Anderson, J. R., & Fincham, J. M. (1994). Acquisition of procedural skills from examples. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(6), 1322-1340.

Anderson, J. R., & Fincham, J. M. (2014). Extending problem-solving procedures through reflection. Cognitive Psychology, 74, 1-34.

Anderson, J. R., Lee, H. S., & Fincham, J. M. (2014). Discovering the structure of mathematical problem solving. NeuroImage, 97, 163-177.

Anderson, J. R., Borst, J. P., Fincham, J. M., Ghuman, A. S., Tenison, C., & Zhang, Q. (2018). The common time course of memory processes revealed. Psychological Science, 29(9), 1463-1474.

Anderson, J. R., Betts, S., Bothell, D., Hope, R., & Lebiere, C. (2019). Learning rapid and precise skills. Psychological Review, 126(5), 727-760.

Anderson, J. R., Betts, S., Bothell, D., & Lebiere, C. (2021). Discovering skill. Cognitive Psychology, 129, 101410.

Anderson, J. R., Fincham, J. M., & Douglass, S. (1997). The role of examples and rules in the acquisition of a cognitive skill. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23(4), 932-945.

Anderson, J. R., Fincham, J. M., & Douglass, S. (1999). Practice and retention: A unifying analysis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25(5), 1120-1136.

Anderson, J. R., & Reder, L. M. (1999). The fan effect: New results and new theories. Journal of Experimental Psychology: General, 128(2), 186-197.

Anderson, J. R., Reder, L. M., & Lebiere, C. (1996). Working memory: Activation limitations on retrieval. Cognitive Psychology, 30(3), 221-256.

Anderson, J. R., & Schooler, L. J. (1991). Reflections of the environment in memory. Psychological Science, 2(6), 396-408.

Anderson, J. R., & Schunn, C. D. (2000). Implications of the ACT-R learning theory: No magic bullets. Advances in Instructional Psychology, 5, 1-34.

Lee, H. S., & Anderson, J. R. (2013). Student learning: What has instruction got to do with it? Annual Review of Psychology, 64, 445-469.

Lee, H. S., Fincham, J. M., Betts, S., & Anderson, J. R. (2014). An fMRI investigation of instructional guidance in mathematical problem solving. Trends in Neuroscience and Education, 3(1), 50-62.

Lee, H. S., Betts, S., & Anderson, J. R. (2016). Learning problem-solving rules as search through a hypothesis space. Cognitive Science, 40(5), 1036-1079.

Logan, G. D. (1988). Toward an instance theory of automatization. Psychological Review, 95(4), 492-527.

Lovett, M. C., Daily, L. Z., & Reder, L. M. (2000). A source activation theory of working memory: Cross-task prediction of performance in ACT-R. Cognitive Systems Research, 1(2), 99-118.

Pavlik, P. I., & Anderson, J. R. (2005). Practice and forgetting effects on vocabulary memory: An activation-based model of the spacing effect. Cognitive Science, 29(4), 559-586.

Pavlik, P. I., & Anderson, J. R. (2008). Using a model to compute the optimal schedule of practice. Journal of Experimental Psychology: Applied, 14(2), 101-117.

Taatgen, N. A. (2013). The nature and transfer of cognitive skills. Psychological Review, 120(3), 439-471.

Taatgen, N. A., & Anderson, J. R. (2002). Why do children learn to say “broke”? A model of learning the past tense without feedback. Cognition, 86(2), 123-155.


Elaborative Encoding & Generative Learning

Anderson, J., & Reder, L. (1979). An elaborative processing explanation of depth processing. In L. S. Cermak & F. I. M. Craik (Eds.), Levels of Processing in Human Memory (pp. 385-403).

Bradshaw, G. L., & Anderson, J. R. (1982). Elaborative encoding as an explanation of levels of processing. Journal of Verbal Learning and Verbal Behavior, 21(2), 165-174.

Fiorella, L., & Kuhlmann, S. (2020). Creating drawings enhances learning by teaching. Journal of Educational Psychology, 112(4), 811-822.

Fiorella, L., & Mayer, R. E. (2014). Learning as a Generative Activity: Eight Learning Strategies that Promote Understanding. Cambridge University Press.

Gjerde, V. (2025). Short introductory videos for elaborative encoding of physics principles. Nordic Journal of STEM Education, 9(1), 101-117.

Lehman, M., & Karpicke, J. D. (2016). Elaborative retrieval: Do semantic mediators improve memory? Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(10), 1573-1591.

Reder, L. M., Liu, X. N. L., Keinath, A., & Popov, V. (2016). Building knowledge requires bricks, not sand: The critical role of familiar constituents in learning. Psychonomic Bulletin & Review, 23(1), 271-277.

Stein, B. S., & Bransford, J. D. (1979). Constraints on effective elaboration: Effects of precision and subject generation. Journal of Verbal Learning and Verbal Behavior, 18(6), 769-777.

Stein, B. S., Littlefield, J., Bransford, J. D., & Persampieri, M. (1984). Elaboration and knowledge acquisition. Memory & Cognition, 12(5), 522-529.


Retrieval Practice & Testing Effects

Abel, M., & Bäuml, K. H. T. (2020). Would you like to learn more? Retrieval practice plus feedback can increase motivation to keep on studying. Cognition, 201, 104316.

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.

Butler, A. C. (2010). Repeated testing produces superior transfer of learning relative to repeated studying. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36(5), 1118-1133.

Carpenter, S. K. (2012). Testing enhances the transfer of learning. Current Directions in Psychological Science, 21(5), 279-283.

Carpenter, S. K., Pan, S. C., & Butler, A. C. (2022). The science of effective learning with spacing and retrieval practice. Nature Reviews Psychology, 1(9), 496-511.

Chan, J. C. K., Meissner, C. A., & Davis, S. D. (2018). Retrieval potentiates new learning: A theoretical and meta-analytic review. Psychological Bulletin, 144(11), 1111-1146.

Gjerde, V., Holst, B., & Kolstø, S. D. (2020). Retrieval practice of a hierarchical principle structure in university introductory physics: Making stronger students. Physical Review Physics Education Research, 16(1), 013103.

Gjerde, V., Marisaldi, M., Oksavik, K., Olafsson, K., Spångberg, H., & Holst, B. (2025). Mandatory retrieval test to incentivize retrieval practice of physics principles. Physical Review Physics Education Research, 21(1), 010119.

Grimaldi, P. J., & Karpicke, J. D. (2012). When and why do retrieval attempts enhance subsequent encoding? Memory & Cognition, 40(4), 505-513.

Karpicke, J. D. (2012). Retrieval-based learning: Active retrieval promotes meaningful learning. Current Directions in Psychological Science, 21(3), 157-163.

Karpicke, J. D., & Blunt, J. R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331(6018), 772-775.

Karpicke, J. D., & Roediger, H. L. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249-255.

Kornell, N., Hays, M. J., & Bjork, R. A. (2009). Unsuccessful retrieval attempts enhance subsequent learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(4), 989-998.

Kornell, N., Klein, P. J., & Rawson, K. A. (2015). Retrieval attempts enhance learning, but retrieval success (versus failure) does not matter. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41(1), 283-294.

Pan, S. C., & Rickard, T. C. (2018). Transfer of test-enhanced learning: Meta-analytic review and synthesis. Psychological Bulletin, 144(7), 710-756.

Pastötter, B., & Bäuml, K. H. (2014). Retrieval practice enhances new learning: The forward effect of testing. Frontiers in Psychology, 5, 286.

Roediger, H. L., & Karpicke, J. D. (2006). The power of testing memory: Basic research and implications for educational practice. Perspectives on Psychological Science, 1(3), 181-210.

Rowland, C. A. (2014). The effect of testing versus restudy on retention: A meta-analytic review of the testing effect. Psychological Bulletin, 140(6), 1432-1463.

Yang, C. L., Luo, L., Vadillo, M. A., Yu, R. J., & Shanks, D. R. (2021). Testing (quizzing) boosts classroom learning: A systematic and meta-analytic review. Psychological Bulletin, 147(4), 399-435.


Self-Explanation & Worked Examples

Aleven, V., & Koedinger, K. R. (2002). An effective metacognitive strategy: Learning by doing and explaining with a computer-based cognitive tutor. Cognitive Science, 26(2), 147-179.

Atkinson, R. K., Renkl, A., & Merrill, M. M. (2003). Transitioning from studying examples to solving problems: Effects of self-explanation prompts and fading worked-out steps. Journal of Educational Psychology, 95(4), 774-783.

Bisra, K., Liu, Q., Nesbit, J. C., Salimi, F., & Winne, P. H. (2018). Inducing self-explanation: A meta-analysis. Educational Psychology Review, 30(3), 703-725.

Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13(2), 145-182.

Chi, M. T. H. (2000). Self-explaining expository texts: The dual processes of generating inferences and repairing mental models. Advances in Instructional Psychology, 5, 161-238.

Chi, M. T. H., de Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439-477.

Chi, M. T. H., & VanLehn, K. A. (1991). The content of physics self-explanations. Journal of the Learning Sciences, 1(1), 69-105.

Gjerde, V., Havre Paulsen, V., Holst, B., & Kolstø, S. D. (2022). Problem solving in basic physics: Effective self-explanations based on four elements with support from retrieval practice. Physical Review Physics Education Research, 18(1), 010136.

Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001). When problem solving is superior to studying worked examples. Journal of Educational Psychology, 93(3), 579-588.

Renkl, A. (1997). Learning from worked-out examples: A study on individual differences. Cognitive Science, 21(1), 1-29.

Renkl, A. (2002). Worked-out examples: Instructional explanations support learning by self-explanations. Learning and Instruction, 12(5), 529-556.

Renkl, A. (2014). Toward an instructionally oriented theory of example-based learning. Cognitive Science, 38(1), 1-37.

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.

Renkl, A., Stark, R., Gruber, H., & Mandl, H. (1998). Learning from worked-out examples: The effects of example variability and elicited self-explanations. Contemporary Educational Psychology, 23(1), 90-108.

Richey, J. E., & Nokes-Malach, T. J. (2013). How much is too much? Learning and motivation effects of adding instructional explanations to worked examples. Learning and Instruction, 25, 104-124.

Rittle-Johnson, B., Loehr, A. M., & Durkin, K. (2017). Promoting self-explanation to improve mathematics learning: A meta-analysis and instructional design principles. ZDM Mathematics Education, 49(4), 599-611.

VanLehn, K., Jones, R. M., & Chi, M. T. H. (1992). A model of the self-explanation effect. Journal of the Learning Sciences, 2(1), 1-59.

Wittwer, J., & Renkl, A. (2010). How effective are instructional explanations in example-based learning? A meta-analytic review. Educational Psychology Review, 22(4), 393-409.


Expertise & Problem Solving

Alexander, P. A. (2003). The development of expertise: The journey from acclimation to proficiency. Educational Researcher, 32(8), 10-14.

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.

Chi, M. T. H., Glaser, R., & Rees, E. (1982). Expertise in problem solving. In R. J. Sternberg (Ed.), Advances in the Psychology of Human Intelligence (Vol. 1). Erlbaum.

Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102(2), 211-245.

Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363-406.

Hardiman, P. T., Dufresne, R., & Mestre, J. P. (1989). The relation between problem categorization and problem solving among experts and novices. Memory & Cognition, 17(5), 627-638.

Larkin, J., McDermott, J., Simon, D. P., & Simon, H. A. (1980). Expert and novice performance in solving physics problems. Science, 208(4450), 1335-1342.

VanLehn, K. (1996). Cognitive skill acquisition. Annual Review of Psychology, 47, 513-539.


Distributed Practice & Spacing Effects

Bahrick, H. P. (1979). Maintenance of knowledge: Questions about memory we forgot to ask. Journal of Experimental Psychology: General, 108(3), 296-308.

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.

Ebbinghaus, H. (1885/1964). Memory: A Contribution to Experimental Psychology. Dover Publications.

Karpicke, J. D., & Roediger, H. L. (2007). Expanding retrieval practice promotes short-term retention, but equally spaced retrieval enhances long-term retention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(4), 704-719.

Karpicke, J. D., & Roediger, H. L. (2010). Is expanding retrieval a superior method for learning text materials? Memory & Cognition, 38(1), 116-124.

Latimier, A., Peyre, H., & Ramus, F. (2020). A meta-analytic review of the benefit of spacing out retrieval practice episodes on retention. Educational Psychology Review, 33(4), 959-987.

Logan, J. M., Castel, A. D., Haber, S., & Viehman, E. J. (2012). Metacognition and the spacing effect: The role of repetition, feedback, and instruction on judgments of learning for massed and spaced rehearsal. Metacognition and Learning, 7(3), 175-195.

Pashler, H., Rohrer, D., Cepeda, N. J., & Carpenter, S. K. (2007). Enhancing learning and retarding forgetting: Choices and consequences. Psychonomic Bulletin & Review, 14(2), 187-193.

Pavlik, P. I., & Anderson, J. R. (2005). Practice and forgetting effects on vocabulary memory: An activation-based model of the spacing effect. Cognitive Science, 29(4), 559-586.

Pavlik, P. I., & Anderson, J. R. (2008). Using a model to compute the optimal schedule of practice. Journal of Experimental Psychology: Applied, 14(2), 101-117.

Rawson, K. A., & Dunlosky, J. (2011). Optimizing schedules of retrieval practice for durable and efficient learning: How much is enough? Journal of Experimental Psychology: General, 140(3), 283-302.


Interleaved Practice

Birnbaum, M. S., Kornell, N., Bjork, E. L., & Bjork, R. A. (2013). Why interleaving enhances inductive learning: The roles of discrimination and retrieval. Memory & Cognition, 41(3), 392-402.

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.

Rohrer, D., & Taylor, K. (2007). The shuffling of mathematics problems improves learning. Instructional Science, 35(6), 481-498.

Rohrer, D., Taylor, K., & Sholar, B. (2010). Tests enhance the transfer of learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36(1), 233-239.

Samani, J., & Pan, S. C. (2021). Interleaved practice enhances memory and problem-solving ability in undergraduate physics. npj Science of Learning, 6(1), 31.

Yan, V. X., Bjork, E. L., & Bjork, R. A. (2016). On the difficulty of mending metacognitive illusions: A priori theories, fluency effects, and misattributions of the interleaving benefit. Journal of Experimental Psychology: General, 145(7), 918-933.


Pretesting & Error Generation

Hausman, H., & Rhodes, M. G. (2018). When pretesting fails to enhance learning concepts from reading texts. Journal of Experimental Psychology: Applied, 24(3), 331-346.

James, K. K., & Storm, B. C. (2019). Beyond the pretesting effect: What happens to the information that is not pretested? Journal of Experimental Psychology: Applied, 25(4), 576-587.

Kornell, N., Hays, M. J., & Bjork, R. A. (2009). Unsuccessful retrieval attempts enhance subsequent learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(4), 989-998.

Lee, H. S., & Ahn, D. (2018). Testing prepares students to learn better: The forward effect of testing in category learning. Journal of Educational Psychology, 110(2), 203-217.

Pan, S. C., & Carpenter, S. (2023). Prequestioning and pretesting effects: A review of empirical research, theoretical perspectives, and applications. Educational Psychology Review, 35(3), 73.

Pan, S. C., & Sana, F. (2021). Pretesting versus posttesting: Comparing the pedagogical benefits of errorful generation and retrieval practice. Journal of Experimental Psychology: Applied, 27(2), 237-257.

Richland, L. E., Kornell, N., & Kao, L. S. (2009). The pretesting effect: Do unsuccessful retrieval attempts enhance learning? Journal of Experimental Psychology: Applied, 15(3), 243-257.


Multiple Learning Strategies Research

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.

Gjerde, V. (2021). Integrating cognitive learning strategies into physics instruction: Developing students’ approaches to physics and learning [Doctoral dissertation]. University of Bergen.

Gjerde, V., Holst, B., & Kolstø, S. D. (2021). Integrating effective learning strategies in basic physics lectures: A thematic analysis. Physical Review Physics Education Research, 17(1), 010124.

Karpicke, J. D., & Blunt, J. R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331(6018), 772-775.

Karpicke, J. D., & Smith, M. A. (2012). Separate mnemonic effects of retrieval practice and elaborative encoding. Journal of Memory and Language, 67(1), 17-29.

Roelle, J., Froese, L., Krebs, R., Obergassel, N., & Waldeyer, J. (2022). Sequence matters! Retrieval practice before generative learning is more effective than the reverse order. Learning and Instruction, 80, 101634.

Roelle, J., & Nückles, M. (2019). Generative learning versus retrieval practice in learning from text: The cohesion and elaboration of the text matters. Journal of Educational Psychology, 111(8), 1341-1361.

Waldeyer, J., Heitmann, S., Moning, J., & Roelle, J. (2020). Can generative learning tasks be optimized by incorporation of retrieval practice? Journal of Applied Research in Memory and Cognition, 9(3), 355-369.


Complete Reference List

For researchers, educators, and the curious. All references above plus additional supporting literature, organized alphabetically for easy scanning.

Abel, M., & Bäuml, K. H. T. (2020). Would you like to learn more? Retrieval practice plus feedback can increase motivation to keep on studying. Cognition, 201, 104316.

Agarwal, P. K., Bain, P. M., & Chamberlain, R. W. (2012). The value of applied research: Retrieval practice improves classroom learning and recommendations from a teacher, a principal, and a scientist. Educational Psychology Review, 24(3), 437-448.

Agarwal, P. K., Finley, J. R., Rose, N. S., & Roediger, H. L. (2017). Benefits from retrieval practice are greater for students with lower working memory capacity. Memory, 25(6), 764-771.

Aleven, V., & Koedinger, K. R. (2002). An effective metacognitive strategy: Learning by doing and explaining with a computer-based cognitive tutor. Cognitive Science, 26(2), 147-179.

Alexander, P. A. (2003). The development of expertise: The journey from acclimation to proficiency. Educational Researcher, 32(8), 10-14.

Anderson, J. R. (1990). The Adaptive Character of Thought. L. Erlbaum Associates.

Anderson, J. R. (1991). The adaptive nature of human categorization. Psychological Review, 98(3), 409-429.

Anderson, J. R. (2002). Spanning seven orders of magnitude: A challenge for cognitive modeling. Cognitive Science, 26(1), 85-112.

Anderson, J. R., Bothell, D., Lebiere, C., & Matessa, M. (1998). An integrated theory of list memory. Journal of Memory and Language, 38(4), 341-380.

Anderson, J. R., & Fincham, J. M. (1994). Acquisition of procedural skills from examples. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(6), 1322-1340.

Anderson, J. R., & Fincham, J. M. (2014). Extending problem-solving procedures through reflection. Cognitive Psychology, 74, 1-34.

Anderson, J. R., Fincham, J. M., & Douglass, S. (1997). The role of examples and rules in the acquisition of a cognitive skill. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23(4), 932-945.

Anderson, J. R., Fincham, J. M., & Douglass, S. (1999). Practice and retention: A unifying analysis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25(5), 1120-1136.

Anderson, J. R., & Reder, L. M. (1999). The fan effect: New results and new theories. Journal of Experimental Psychology: General, 128(2), 186-197.

Anderson, J. R., & Schooler, L. J. (1991). Reflections of the environment in memory. Psychological Science, 2(6), 396-408.

Anderson, J. R., & Schunn, C. D. (2000). Implications of the ACT-R learning theory: No magic bullets. Advances in Instructional Psychology, 5, 1-34.

Anderson, J. R., Lee, H. S., & Fincham, J. M. (2014). Discovering the structure of mathematical problem solving. NeuroImage, 97, 163-177.

Anderson, J. R., Borst, J. P., Fincham, J. M., Ghuman, A. S., Tenison, C., & Zhang, Q. (2018). The common time course of memory processes revealed. Psychological Science, 29(9), 1463-1474.

Anderson, J. R., Betts, S., Bothell, D., Hope, R., & Lebiere, C. (2019). Learning rapid and precise skills. Psychological Review, 126(5), 727-760.

Anderson, J. R., Betts, S., Bothell, D., & Lebiere, C. (2021). Discovering skill. Cognitive Psychology, 129, 101410.Antony, J. W., Ferreira, C. S., Norman, K. A., & Wimber, M. (2017). Retrieval as a fast route to memory consolidation. Trends in Cognitive Sciences, 21(8), 573-576.

Badeau, R., White, D. R., Ibrahim, B., Ding, L., & Heckler, A. F. (2017). What works with worked examples: Extending self-explanation and analogical comparison to synthesis problems. Physical Review Physics Education Research, 13(2), 020112.

Bangert-Drowns, R. L., Kulik, J. A., & Kulik, C. L. C. (1991). Effects of frequent classroom testing. Journal of Educational Research, 85(2), 89-99.

Barbieri, C. A., Miller-Cotto, D., Clerjuste, S. N., & Chawla, K. (2023). A meta-analysis of the worked examples effect on mathematics performance. Educational Psychology Review, 35(1), 1-34.

Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn?: A taxonomy for far transfer. Psychological Bulletin, 128(4), 612-637.

Barron, K., & Hulleman, C. (2014). Expectancy-value-cost model of motivation. International Encyclopedia of the Social & Behavioral Sciences (2nd ed., Vol. 8, pp. 503-509).

Bellana, B., Mansour, R., Ladyka-Wojcik, N., Grady, C. L., & Moscovitch, M. (2021). The influence of prior knowledge on the formation of detailed and durable memories. Journal of Memory and Language, 121, 104264.

Bereiter, C., & Scardamalia, M. (1993). Surpassing Ourselves: An Inquiry into the Nature and Implications of Expertise. Open Court.

Berthold, K., & Renkl, A. (2009). Instructional aids to support a conceptual understanding of multiple representations. Journal of Educational Psychology, 101(1), 70-87.

Berthold, K., Röder, H., Knörzer, D., Kessler, W., & Renkl, A. (2011). The double-edged effects of explanation prompts. Computers in Human Behavior, 27(1), 69-75.

Bielaczyc, K., Pirolli, P. L., & Brown, A. L. (1995). Training in self-explanation and self-regulation strategies: Investigating the effects of knowledge acquisition activities on problem solving. Cognition and Instruction, 13(2), 221-252.

Biwer, F., Egbrink, M. G. A. o., Aalten, P., & de Bruin, A. B. H. (2020). Fostering effective learning strategies in higher education – A mixed-methods study. Journal of Applied Research in Memory and Cognition, 9(2), 186-203.

Bjork, R. A. (1994). Memory and metamemory considerations in the training of human beings. Metacognition: Knowing About Knowing (pp. 185-205).

Bradshaw, G. L., & Anderson, J. R. (1982). Elaborative encoding as an explanation of levels of processing. Journal of Verbal Learning and Verbal Behavior, 21(2), 165-174.

Buchin, Z. L., & Mulligan, N. W. (2023). Retrieval-based learning and prior knowledge. Journal of Educational Psychology, 115(1), 22-35.

Burkholder, E. W., Miles, J. K., Layden, T. J., Wang, K. D., Fritz, A. V., & Wieman, C. E. (2020). Template for teaching and assessment of problem solving in introductory physics. Physical Review Physics Education Research, 16(1), 010123.

Baars, M., Leopold, C., & Paas, F. (2018). Self-explaining steps in problem-solving tasks to improve self-regulation in secondary education. Journal of Educational Psychology, 110(4), 578-595.

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FAQ

What is ACT-R in learning science?

ACT-R (Adaptive Control of Thought-Rational) is a cognitive architecture developed by John Anderson that models how human memory and skill acquisition work. It explains why certain learning strategies like spaced repetition and retrieval practice are so effective by showing how memory strengthens through activation patterns and practice schedules.

What are the most effective evidence-based study techniques?

The research consistently supports these core strategies:

  • Elaborative encoding: Connecting new information to existing knowledge by trying to answer questions
  • Retrieval practice: Building strong memories of key knowledge units by retrieving from memory
  • Self-explanation: Explaining experts’ solutions in your own words
  • Problem solving: Learning by doing and solving problems
  • Spaced repetition: Reviewing material at increasing intervals
  • Interleaving: Mixing different types of problems or topics
  • Pre- and posttesting: Testing yourself before and after information input

How do I start with effective learning strategies today?

Start by using Unisium’s learning tools or read Masterful Learning for detailed implementation strategies.


Ready to put this research into practice? Explore these evidence-based learning strategies:


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