Updated: Jun 20, 2022
As part of the Early Career Framework, it is expected that early career teachers learn that… Explicitly teaching pupils metacognitive strategies linked to subject knowledge, including how to plan, monitor and evaluate, supports independence and academic success.
Many [students] are unaware of their own thinking processes. [Fewer still] are aware of their own thinking processes while they are thinking. When asked, “How are you solving that problem?” They may reply, “I don’t know. I’m just doing it…” They can’t describe the steps and sequences they use before, during and after problem-solving.’ Costa (1991)
The word metacognition is, of course, a compound of ‘meta’, from the Greek word about, and ‘cognition’, which refers to the process of acquiring knowledge and understanding through thought. Hence the rather simple definition – “thinking about one’s thinking”.
Metacognitive knowledge is what a learner knows about the way they learn or how they can engage most efficiently with a particular task, while skills refer to the ability regulate these activities (Muijs and Bokhove, 2020)
The EEF Teaching and Learning Toolkit has metacognition and self-regulation as a low-cost, high-impact strategy for improving pupil progress. Self-regulation and metacognition strategies work through learners monitoring and evaluating their own learning strategies. Some necessary components for successful metacognitive strategies might include:
The EEF suggest the following strategies to implement within your own setting:
Explicit teaching of metacognitive strategies
Teachers modelling their own thinking to demonstrate metacognitive strategies
Opportunities for pupils to reflect on and monitor their strengths and areas of improvement, and plan how to overcome current difficulties.
Providing enough challenge for learners to develop effective strategies, but not so difficult that they struggle to apply a strategy.
Metacognition and self-regulation strategies are most effective when embedded in a school’s curriculum and a specific subject lesson. For example, teaching metacognitive strategies to self-evaluate an essay in history will prove different to a pupil evaluating their methods for mathematical problem solving.
As part of everyday teaching, some of the most common strategies used to embed metacognitive strategies are:
Explicit teaching - With a focus on activating prior knowledge, introducing new knowledge and skills, modelling the application of knowledge and skills, and providing ample opportunity for independent practice and reflection.
Supporting students to plan, monitor, and evaluate their work/learning - Explicitly teaching skills in these areas, and structuring work around these phases, will give students the opportunity to gradually internalise these techniques and use them to take control of their own learning.
Developing rubrics (and wherever possible co-designing them with students) - Assist students with the monitoring of learning and the setting of individual learning goals that are specific, measurable, achievable, realistic and timely (SMART).
Modelling of thinking - Verbalise the thought processes used to consider, analyse and solve problems. This may be as simple as 'thinking aloud'.
Questioning - Both in terms of using questions to engage students, to monitor their progress and stimulate their thinking, as well as valuing questions from students as a form of feedback and an opportunity for clarification/extension of learning.
Edutopia suggest seven strategies for teaching metacognitive strategies within schools and "The Helpful Professor" has a list of thirteen ways to develop your metacognitive skills which you can then translate into your teaching practice.
Metacognition has been discussed on my blog before, in January 2021 and you can read that post here. For a reminder, the following video explains metacognition.
One we understand metacognition, we can then build our lessons to develop the metacognitive strategies of our students.
In their blog Cambridge Assessment discuss that good teachers develop lessons and schemes of work that emphasise specific types of thinking to improve student learning, e.g. drawing inferences, synthesis, hypothesising, analytical reasoning, inquiry, interpretation, etc.
They refer to Biggs and Collis (1982) who developed what they refer to as the SOLO Taxonomy. This starts from the basic premise that as learning progresses it becomes more complex and that it is useful to have a framework to understand the level of complexity. As Biggs himself explains, “the Structure of the Observed Learning Outcome (SOLO) enables students to evaluate their work in terms of its quality, not in terms of how many bits of this and of that they got right. At first we pick up only one or few aspects of the task (Unistructural), then several aspects but they are unrelated (Multistructural), then we learn how to integrate them into a whole (Relational), and finally, we are able to generalise that whole to, as yet, untaught applications (Extended Abstract).”
The following document discusses Learning to learn (metacognition) – what is it and can it be measured which you may find useful.
Further Reading from the ECF
[Further reading recommendations are indicated with an asterisk.]
Alexander R.J. (2020) A Dialogic Teaching Companion, London: Routledge.
*Coe, R., Aloisi, C., Higgins, S., & Major, L. E. (2014) What makes great teaching. Review of the underpinning research. Durham University: UK. Available at: http://bit.ly/2OvmvKO
Donker, A. S., de Boer, H., Kostons, D., Dignath van Ewijk, C. C., & van der Werf, M. P. C. (2014) Effectiveness of learning strategy instruction on academic performance: A meta-analysis. Educational Research Review, 11, 1–26. https://doi.org/10.1016/j.edurev.2013.11.002
Donovan, M. S., & Bransford, J. D. (2005) How students learn: Mathematics in the classroom. Washington, DC: The National Academies Press.
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, Supplement, 14(1), 4–58. https://doi.org/10.1177/1529100612453266
Education Endowment Foundation (2016) Improving Literacy in Key Stage One Guidance Report. [Online] Accessible from: https://educationendowmentfoundation.org.uk/tools/guidance-reports/ [retrieved 10 October 2018].
Education Endowment Foundation (2017) Improving Mathematics in Key Stages Two and Three Guidance Report. [Online] Accessible from: https://educationendowmentfoundation.org.uk/tools/guidance-reports/ [retrieved 10 October 2018].
Education Endowment Foundation (2017) Metacognition and Self-regulated learning Guidance Report. [Online] Accessible from:
https://educationendowmentfoundation.org.uk/tools/guidance-reports/ [retrieved 10 October 2018].
Education Endowment Foundation (2018) Improving Secondary Science Guidance Report. [Online] Accessible from: https://educationendowmentfoundation.org.uk/tools/guidance-reports/ [retrieved 10 October 2018].
*Education Endowment Foundation (2018) Sutton Trust-Education Endowment Foundation Teaching and Learning Toolkit: Accessible from: https://educationendowmentfoundation.org.uk/evidence summaries/teaching-learning-toolkit/ [retrieved 10 October 2018].
Elleman, A. M., Lindo, E. J., Morphy, P., & Compton, D. L. (2009) The Impact of Vocabulary Instruction on Passage-Level Comprehension of School-Age Children: A Meta-Analysis. Journal of Research on Educational Effectiveness, 2(1), 1–44. https://doi.org/10.1080/19345740802539200
Hodgen, J., Foster, C., Marks, R. & Brown, M. (2018) Improving Mathematics in Key Stages Two and Three: Evidence Review. [Online] Accessible from https://educationendowmentfoundation.org.uk/evidence summaries/evidence-reviews/improvingmathematics-in-key-stages-two-and-three/ [retrieved 22 October 2018], 149-157.
Institute of Education Sciences. (2009) Assisting Students Struggling with Mathematics: Response to Intervention for Elementary and Middle Schools. Accessible from: https://ies.ed.gov/ncee/wwc/Docs/PracticeGuide/rti_math_pg_042109.pdf
Jay, T., Willis, B., Thomas, P., Taylor, R., Moore, N., Burnett, C., Merchant, G., Stevens, A. (2017) Dialogic Teaching: Evaluation Report. [Online] Accessible from: https://educationendowmentfoundation.org.uk/projects-and-evaluation/projects/dialogicteaching [retrieved 10 October 2018].
Kalyuga, S. (2007) Expertise reversal effect and its implications for learner-tailored instruction. Educational Psychology Review, 19(4), 509-539.
Kirschner, P., Sweller, J., Kirschner, F. & Zambrano, J. (2018) From cognitive load theory to collaborative cognitive load theory. In International Journal of Computer-Supported Collaborative Learning, 13(2), 213-233.
Leung, K. C. (2015) Preliminary Empirical Model of Crucial Determinants of Best Practice for Peer Tutoring on Academic Achievement Preliminary Empirical Model of Crucial Determinants of Best Practice for Peer Tutoring on Academic Achievement. Journal of Educational Psychology, 107(2), 558–579. https://doi.org/10.1037/a0037698 .
Muijs, D., & Reynolds, D. (2017) Effective teaching: Evidence and practice. Thousand Oaks, CA: Sage.
Pan, S. C., & Rickard, T. C. (2018) Transfer of test-enhanced learning: Meta-analytic review and synthesis. Psychological Bulletin, 144(7), 710–756. http://psycnet.apa.org/doiLanding?doi=10.1037%2Fbul0000151 .
*Rosenshine, B. (2012) Principles of Instruction: Research-based strategies that all teachers should know. American Educator, 12–20. https://doi.org/10.1111/j.1467-8535.2005.00507.x
Sweller, J. (2016). Working Memory, Long-term Memory, and Instructional Design. Journal of Applied Research in Memory and Cognition, 5(4), 360–367. http://doi.org/10.1016/j.jarmac.2015.12.002 .
Tereshchenko, A., Francis, B., Archer, L., Hodgen, J., Mazenod, A., Taylor, B., Travers, M. C. (2018) Learners’ attitudes to mixed-attainment grouping: examining the views of students of high, middle and low attainment. Research Papers in Education, 1522, 1–20. https://doi.org/10.1080/02671522.2018.1452962 .
Van de Pol, J., Volman, M., Oort, F., & Beishuizen, J. (2015) The effects of scaffolding in the classroom: support contingency and student independent working time in relation to student achievement, task effort and appreciation of support. Instructional Science, 43(5), 615-641.
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. https://doi.org/10.1007/s10648-010-9136-5 .
Zimmerman, B. J. (2002) Becoming a Self-Regulated Learner: An Overview, Theory Into Practice. Theory Into Practice, 41(2), 64–70. https://www.jstor.org/stable/1477457?seq=1#page_scan_tab_contents .