Foundation

Self-regulated learning

Effective learners work in a cycle. They size up a task, plan an approach, act, monitor how it is going, adjust, and reflect on the result. This cyclical view is the backbone of the Learning Ownership System. It is also why the seven moves are described as moves rather than steps: learners return to them, repeat them, and enter wherever the situation requires.

Self-regulated learning includes cognitive and metacognitive processes, but it also includes motivation, emotion, behaviour, and context. The system therefore treats learning as more than choosing a study technique.

In the book: the seven moves in Part 1, the part openers that identify relevant moves, and the repeated planning, monitoring, adjustment, and transfer prompts.

• Conceptual overviewZimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. doi.org/10.1207/S15430421TIP4102_2
• Conceptual overviewZimmerman, B. J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25(1), 3–17. doi.org/10.1207/s15326985ep2501_2
• Conceptual frameworkPintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16(4), 385–407. doi.org/10.1007/s10648-004-0006-x
• Theoretical synthesisButler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65(3), 245–281. doi.org/10.3102/00346543065003245
• ReviewPanadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, Article 422. doi.org/10.3389/fpsyg.2017.00422

Monitor and Verify

Metacognition and judgments of learning

Students are often imperfect judges of what they know. Material that feels familiar can be mistaken for material that has been learned, and confidence can run ahead of performance. Judgments of learning are influenced by the cues learners use when they estimate whether they will remember or understand something later.

This is why the system separates Monitor, which asks whether understanding is developing, from Verify, which asks whether the learner has evidence that the work is accurate, understood, and defensible.

In the book: Monitor and Verify, the confidence columns in assignment and exam tools, and checks that ask for evidence of understanding rather than a feeling of familiarity.

• Foundational theoryFlavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911. doi.org/10.1037/0003-066X.34.10.906
• Practical reviewTanner, K. D. (2012). Promoting student metacognition. CBE–Life Sciences Education, 11(2), 113–120. doi.org/10.1187/cbe.12-03-0033
• Empirical studiesDunlosky, J., & Rawson, K. A. (2012). Overconfidence produces underachievement: Inaccurate self evaluations undermine students’ learning and retention. Learning and Instruction, 22(4), 271–280. doi.org/10.1016/j.learninstruc.2011.08.003
• Theory and empirical studiesKoriat, A. (1997). Monitoring one’s own knowledge during study: A cue-utilization approach to judgments of learning. Journal of Experimental Psychology: General, 126(4), 349–370. doi.org/10.1037/0096-3445.126.4.349

Direct ancestor of the tools

Wrappers and metacognitive prompts

Exam and assignment wrappers are short, structured prompts completed around a graded task. They ask what the learner did to prepare, what happened, and what should change next time. Many Think First tools extend this idea beyond exams to assignments, AI use, weekly planning, feedback, and recovery.

The evidence is promising rather than settled. Wrappers provide structured opportunities for reflection, but studies of their effects on subsequent grades or measured metacognition have produced mixed results, especially when a wrapper is used only once. Think First therefore treats reflection as a repeated practice rather than a single exercise.

In the book: every tool, especially the Full Assignment and Full Exam Ownership Tools and the Transfer prompts.

• Book chapter and practical modelLovett, M. C. (2013). Make exams worth more than the grade: Using exam wrappers to promote metacognition. In M. Kaplan, N. Silver, D. LaVaque-Manty, & D. Meizlish (Eds.), Using reflection and metacognition to improve student learning: Across the disciplines, across the academy (pp. 18–52). Stylus.
• Research-based synthesisAmbrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: Seven research-based principles for smart teaching. Jossey-Bass.
• Course intervention studySoicher, R. N., & Gurung, R. A. R. (2017). Do exam wrappers increase metacognition and performance? A single course intervention. Psychology Learning & Teaching, 16(1), 64–73. doi.org/10.1177/1475725716661872

Practice First

Attempting before receiving full support

Attempting a demanding problem before receiving a complete explanation can prepare learners to notice important features, compare approaches, and understand later instruction more deeply. This does not mean that all unsupported struggle is useful. Productive attempts require an appropriate task, a psychologically safe environment, and timely opportunities to compare, explain, and learn from what happened.

Practice First translates this principle into a low-risk routine: make an initial attempt, expose your current thinking, and then seek examples, instruction, feedback, or AI support.

In the book: Practice First, the starting-point checks, Pause Before You Prompt, worked-example comparisons, and prompts that ask students to record what they already understand before seeking support.

• Experimental studyKapur, M. (2008). Productive failure. Cognition and Instruction, 26(3), 379–424. doi.org/10.1080/07370000802212669

Practice First and Monitor

Retrieval practice

Bringing information to mind from memory often strengthens long-term retention more than restudying the same material. Rereading is popular because it feels fluent and productive, but that feeling is not reliable evidence of later recall. Students also tend to use retrieval less often than its learning benefits would justify.

In the book: Part 4, the Retrieval and Spacing Plan, Stop Rereading Everything, and self-testing prompts in the exam tools.

• Controlled experimentsRoediger, H. L., III, & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255. doi.org/10.1111/j.1467-9280.2006.01693.x
• Student-strategy studyKarpicke, J. D., Butler, A. C., & Roediger, H. L., III. (2009). Metacognitive strategies in student learning: Do students practise retrieval when they study on their own? Memory, 17(4), 471–479. doi.org/10.1080/09658210802647009
• Meta-analysisAdesope, 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. doi.org/10.3102/0034654316689306

Plan

Spacing and desirable difficulties

Study spread across days generally produces better long-term retention than the same amount of study massed into one period. Other conditions that make practice feel harder in the moment, such as retrieval and interleaving, can also improve later performance.

Not every difficulty is desirable. Useful difficulty engages processes relevant to the learning goal. Difficulty created by unclear instructions, missing prerequisite knowledge, excessive cognitive load, or absent feedback can interfere with learning.

In the book: the Retrieval and Spacing Plan, the expanding-practice schedule, and the desirable-difficulties guidance in Part 4.

• Research reviewDunlosky, 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. doi.org/10.1177/1529100612453266
• Review and quantitative synthesisCepeda, 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. doi.org/10.1037/0033-2909.132.3.354
• Book chapterBjork, 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, R. W. Pew, L. M. Hough, & J. R. Pomerantz (Eds.), Psychology and the real world: Essays illustrating fundamental contributions to society (pp. 56–64). Worth Publishers.
• Research reviewBjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: Beliefs, techniques, and illusions. Annual Review of Psychology, 64, 417–444. doi.org/10.1146/annurev-psych-113011-143823
• Boundary condition and foundational theorySweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. doi.org/10.1207/s15516709cog1202_4

Adjust, Verify, and Transfer

Feedback literacy and evaluative judgment

Feedback changes learning only when the learner interprets it and does something with it. Research has therefore shifted from treating feedback mainly as comments delivered by an instructor to examining learners’ capacity to understand, evaluate, seek, and use information about their work.

Evaluative judgment is the capacity to make informed decisions about the quality of one’s own and others’ work. That capacity is increasingly important when students must judge whether machine-produced work is accurate, appropriate, and genuinely represents their understanding.

In the book: Learn From Feedback in Part 3, When Feedback Is Vague, comparison with criteria and exemplars, and the Verify move.

• Research reviewHattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. doi.org/10.3102/003465430298487
• Conceptual modelNicol, D. J., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199–218. doi.org/10.1080/03075070600572090
• Conceptual frameworkCarless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315–1325. doi.org/10.1080/02602938.2018.1463354
• Conceptual articleTai, J., Ajjawi, R., Boud, D., Dawson, P., & Panadero, E. (2018). Developing evaluative judgement: Enabling students to make decisions about the quality of work. Higher Education, 76, 467–481. doi.org/10.1007/s10734-017-0220-3
• Conceptual article on GenAIBearman, M., Tai, J., Dawson, P., Boud, D., & Ajjawi, R. (2024). Developing evaluative judgement for a time of generative artificial intelligence. Assessment & Evaluation in Higher Education, 49(6), 893–905. doi.org/10.1080/02602938.2024.2335321

Transfer

Reflection

Experience does not automatically become learning. Structured reflection can help learners describe what happened, examine why it happened, and identify an action to carry into future work. Reflection is most useful when it moves beyond recounting events and produces a decision, question, or changed strategy.

The Reflection Ladder applies this progression to academic work and AI use. It does not assume that reflection alone guarantees improvement. The value comes from connecting reflection to adjustment and later action.

In the book: the Reflection Ladder and AI Reflection Ladder at the end of Part 1, plus Transfer prompts throughout the book.

• Foundational theoryDewey, J. (1933). How we think: A restatement of the relation of reflective thinking to the educative process. D. C. Heath.
• Foundational theorySchön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books.
• Structured reflection modelGibbs, G. (1988). Learning by doing: A guide to teaching and learning methods. Further Education Unit, Oxford Polytechnic.

Transfer

Transfer of learning

Transfer occurs when learning from one task, course, or context influences performance in another. Near transfer involves relatively similar situations. Far transfer requires learners to recognise that an idea or strategy is relevant in a context that looks different.

Transfer cannot be assumed simply because a student completed a task successfully. Learners benefit from being asked what should be reused, what must be adapted, and where else the learning might apply.

In the book: the Transfer move, assignment and exam closeout prompts, feedback-to-next-step tools, and questions that ask what to reuse, adapt, or stop doing.

• Review and taxonomyBarnett, 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. doi.org/10.1037/0033-2909.128.4.612

Plan and Adjust

Regulating motivation

Motivation is not only something a learner has or lacks. Learners can use strategies to begin, sustain, or restore effort when a task is boring, difficult, uncertain, or emotionally uncomfortable. These strategies can include changing the task, changing the environment, reconnecting the work to a valued goal, seeking support, or using a small starting commitment.

Think First presents motivation regulation as a repertoire rather than a single formula. The appropriate strategy depends on why motivation has dropped.

In the book: the Motivation Menu, When Starting Stalls, environment checks, small-first-step prompts, and Reset and Recovery.

• Conceptual reviewWolters, C. A. (2003). Regulation of motivation: Evaluating an underemphasized aspect of self-regulated learning. Educational Psychologist, 38(4), 189–205. doi.org/10.1207/S15326985EP3804_1

The Toolkit

Mindset, belonging, and stress

Beliefs about ability, experiences of belonging, and interpretations of stress can influence persistence, but these are distinct research areas. Growth-mindset interventions generally produce small and context-dependent effects. Belonging interventions can benefit some student groups when the surrounding environment provides genuine opportunities to belong. Stress reappraisal has also improved performance in particular high-stakes situations.

Think First treats these ideas as possible supports, not guarantees. It does not promise that changing a belief will automatically change a grade, and it does not place responsibility for an unsupportive environment entirely on the student.

In the book: When It Feels Like Everyone Else Gets It, the Motivation Menu, belonging and support prompts, and the exam-nerves passage in Part 4.

• Accessible theoretical backgroundDweck, C. S. (2006). Mindset: The new psychology of success. Random House.
• National field experimentYeager, D. S., et al. (2019). A national experiment reveals where a growth mindset improves achievement. Nature, 573, 364–369. doi.org/10.1038/s41586-019-1466-yThe author list is shortened on this web page because the study has many contributors.
• Meta-analysesSisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To what extent and under which circumstances are growth mind-sets important to academic achievement? Two meta-analyses. Psychological Science, 29(4), 549–571. doi.org/10.1177/0956797617739704
• Randomized intervention studyWalton, G. M., & Cohen, G. L. (2011). A brief social-belonging intervention improves academic and health outcomes of minority students. Science, 331(6023), 1447–1451. doi.org/10.1126/science.1198364
• Multi-institution field experimentWalton, G. M., et al. (2023). Where and with whom does a brief social-belonging intervention promote progress in college? Science, 380(6644), 499–505. doi.org/10.1126/science.ade4420The author list is shortened on this web page because the study has many contributors.
• Experimental studyJamieson, J. P., Mendes, W. B., Blackstock, E., & Schmader, T. (2010). Turning the knots in your stomach into bows: Reappraising arousal improves performance on the GRE. Journal of Experimental Social Psychology, 46(1), 208–212. doi.org/10.1016/j.jesp.2009.08.015

Plan and Practice First

Starting, planning, and procrastination

Procrastination is better understood as a self-regulation problem than simply a time-management problem or a character flaw. Plans that specify when, where, and how action will begin are generally more effective than broad intentions.

Think First translates this research into practical starting decisions. A learner names a small first action, a time, and a place. The two-minute starter is a practical application of this principle, not a claim that one starting rule works for everyone.

In the book: Make the Assignment Startable, the two-minute starter, When Starting Stalls, implementation-intention prompts, and the Study Session Planner.

• Meta-analytic reviewSteel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65–94. doi.org/10.1037/0033-2909.133.1.65
• Foundational reviewGollwitzer, P. M. (1999). Implementation intentions: Strong effects of simple plans. American Psychologist, 54(7), 493–503. doi.org/10.1037/0003-066X.54.7.493
• Meta-analysisGollwitzer, P. M., & Sheeran, P. (2006). Implementation intentions and goal achievement: A meta-analysis of effects and processes. Advances in Experimental Social Psychology, 38, 69–119. doi.org/10.1016/S0065-2601(06)38002-1

Adjust and Re-enter

Reset and recovery after setbacks

Falling behind, making a mistake, or receiving disappointing feedback can trigger avoidance and harsh self-criticism. A constructive reset acknowledges what happened without turning the setback into a judgment about the whole person.

Experimental research suggests that self-compassion after failure can increase motivation to improve. This does not mean ignoring responsibility. It means responding in a way that supports honest appraisal, repair, and re-entry.

In the book: Reset and Recovery, missed-work triage, staged re-entry, and prompts that separate what happened from the next useful action.

• Experimental studiesBreines, J. G., & Chen, S. (2012). Self-compassion increases self-improvement motivation. Personality and Social Psychology Bulletin, 38(9), 1133–1143. doi.org/10.1177/0146167212445599

Practice First and Verify

Learning with AI

Research on learning with generative AI is new and still developing. In a randomized field experiment with nearly 1,000 high-school mathematics students, unrestricted generative AI improved performance while it was available but reduced later unassisted performance. A guarded tutor that emphasized hints and safeguards largely mitigated that cost.

Cognitive-offloading research shows that external tools change the demands placed on memory and reasoning. The consequences depend on the task, the kind of support, what the learner still has to do, and whether the support remains available.

Research also shows that self-regulated learning matters for how students adopt GenAI. In an international survey of 435 university students, self-efficacy and social support predicted perceived ease of use, while intrinsic motivation and effort regulation predicted perceived usefulness. The relationship between intrinsic motivation and perceived usefulness was stronger among students using GenAI for university learning.

Think First therefore recommends attempting the core thinking first, then using AI in ways that keep the learner explaining, checking, judging, and deciding.

In the book: Part 2, Practice First, Pause Before You Prompt, the AI Use Log, evaluative-judgment prompts, and the Verify move.

• Randomized field experimentBastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2025). Generative AI without guardrails can harm learning: Evidence from high school mathematics. Proceedings of the National Academy of Sciences, 122(26), e2422633122. doi.org/10.1073/pnas.2422633122
• Research reviewRisko, E. F., & Gilbert, S. J. (2016). Cognitive offloading. Trends in Cognitive Sciences, 20(9), 676–688. doi.org/10.1016/j.tics.2016.07.002
• International survey studyMirriahi, N., Marrone, R., Barthakur, A., Gabriel, F., Colton, J., Yeung, T. N., Arthur, P., & Kovanović, V. (2025). The relationship between students’ self-regulated learning skills and technology acceptance of GenAI. Australasian Journal of Educational Technology, 41(2), 16–33. doi.org/10.14742/ajet.10006
• Conceptual article on GenAIBearman, M., Tai, J., Dawson, P., Boud, D., & Ajjawi, R. (2024). Developing evaluative judgement for a time of generative artificial intelligence. Assessment & Evaluation in Higher Education, 49(6), 893–905. doi.org/10.1080/02602938.2024.2335321
• Preprint, not peer reviewedKosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing task. arXiv preprint, arXiv:2506.08872. arxiv.org/abs/2506.08872
• Methodological comment, not peer reviewedStanković, M., Hirche, E., Kollatzsch, S., & Doetsch, J. N. (2026). Comment on: Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing tasks. arXiv preprint, arXiv:2601.00856. arxiv.org/abs/2601.00856

A note on strength of evidence: the Kosmyna study is a small preprint with 54 participants in the first three sessions and 18 in the final session. It has drawn a separate methodological comment posted on arXiv. Both are included because the study is widely discussed and readers should be able to weigh the original report alongside the critique. The Bastani study is a peer-reviewed randomized field experiment with nearly 1,000 students and carries considerably more weight.