Key ideas
Core concepts
- Students need to be told when they are incorrect; avoiding explicit correction leaves them unsure whether they understand or hold misconceptions. Directive feedback suits novices who lack knowledge, while non-directive feedback suits relative experts who can self-correct.
- Identifying trends and reteaching beats extensive individual written marking, which costs hours and has little learning benefit.
Feedback is information provided to students about their performance, designed to improve work quality rather than judge the student personally.
Connected to
Use Booklets | Question Level Analysis | Fluency | Exit Ticket | Implementation Fidelity
Telling students they are incorrect
Some teachers feel telling students they’re wrong will demotivate them. This misguided kindness is counterproductive. Avoiding explicit correction means students have no idea whether they understand or hold misconceptions (Hattie & Timperley, 2007). Uncertainty about correctness undermines confidence more than clear feedback. Feedback should improve the work, not judge the person (Butler, 1988; Kluger & DeNisi, 1996).
Matching feedback to expertise
The effectiveness of feedback depends on student expertise. Novices and experts require different approaches (Fyfe & Rittle-Johnson, 2016; Kalyuga et al., 2003).
Directive feedback tells students exactly what they got wrong and how to correct it. This works best for novices, who likely lack knowledge or have misconceptions (Shute, 2008), because they receive clear guidance about specific steps to improve (Hattie & Timperley, 2007).
Non-directive feedback tells students they’ve made a mistake and leaves the correction to them. Relative experts can think through the question and self-correct (Kalyuga et al., 2003). Novices cannot: they lack the Fluency to identify their mistake independently (Sweller et al., 2019). Dropping hints frustrates struggling students, who need explicit instruction, not puzzles (Chi et al., 1989).
The feedback model of Hattie and Timperley
Hattie and Timperley (2007) developed a model examining when, how, and why feedback affects learning. Effective feedback addresses three questions. “Where am I going?” (feed up): students need clear goals and success criteria, so feedback should reference the intended learning and what successful performance looks like. “How am I going?” (feedback): students need information about their current performance relative to goals, identifying the gap between current and desired performance. “Where to next?” (feed forward): students need strategies for closing the gap, so feedback should include specific actions for improvement, not just identification of errors.
The model also distinguishes four levels at which feedback operates. Task-level feedback addresses how well tasks are understood or performed, including correctness of answers and specific errors; it builds knowledge and corrects misconceptions but transfers little to other tasks. Process-level feedback addresses the strategies used to complete tasks, including how to approach problems and which strategies work better; it is more effective than task feedback because it transfers across similar tasks. Self-regulation feedback targets students’ ability to monitor and direct their own learning, developing self-assessment skills and metacognitive awareness, and builds independent learning capacity. Self-level feedback consists of personal evaluations and praise (“good job!”, “well done”); it is the least effective for learning because it says nothing about the task, process, or strategies for improvement, and praise focused on the person rather than the work can undermine motivation and learning.
Effective feedback therefore requires clear goals and success criteria, information about current performance relative to goals, strategies for closing the gap, appropriate timing, and focus on the task not the person. Quality matters more than quantity (Hattie & Timperley, 2007).
Feedback during independent practice
Walk around the room checking progress and providing feedback. Standardise the format using booklets and explicit work layout expectations. Track student progress systematically rather than casually watching: actively monitor with a clipboard and write down common issues to address.
Respond immediately. Make frequent affirmations and corrections. When many students make the same mistake, stop the class and reteach explicitly, focusing on widespread issues rather than individual problems.
Against marking and written comments
Individual written feedback may be an inefficient use of limited teacher time with minimal learning benefit (Kluger & DeNisi, 1996). Extensive written comments often have little impact on student learning (Butler, 1988). Individual marking takes roughly 5 minutes per student, totalling 2.5 hours for a class of 30. With five classes, this is an entire work day writing comments. Students are unlikely to read comments, let alone act on them (Lipnevich & Smith, 2009).
A more effective approach involves three steps. First, spend 10 minutes scanning entire class work for quick trend analysis. Second, spend 10 minutes planning how to address common issues. Third, identify trends during lesson circulation and address them immediately (Rosenshine, 2012). This takes 20 minutes instead of 150 and provides feedback that students can act upon (Black & Wiliam, 2009). Exams still need to be marked for formal assessment.
The marking workload problem
Marking is the biggest driver of unsustainable workload and teacher stress. Elliott and Baird’s (2016) Oxford/EEF evidence review found “striking disparity between the enormous amount of effort invested in marking books, and the very small number of robust studies” supporting extensive marking. UK teachers spend approximately nine hours weekly marking, with 72% writing targets for improvement on all or most work and over 50% identifying and correcting errors on all or most work. The review emphasised: “Quality of feedback should not be confused with the quantity.”
UCL research by Jerrim analysing 9,405 teachers across five countries found “marking is the key driver of work stress among teachers” and “time that teachers spend upon marking is particularly detrimental to their wellbeing;” an additional hour of marking has a stronger negative wellbeing impact than other activities. The UK Independent Teacher Workload Review Group on Marking (2016) concluded “written marking has become unnecessarily burdensome” with a cultural expectation that “you must spend hours marking to be a good teacher,” yet “quantity of feedback should not be confused with the quality.” Marking was the largest single contributor to unsustainable workload in the 2014 Workload Challenge.
UK teachers average 49.5 hours weekly (2019 Department for Education survey of 7,287 teachers), down from 54.4 in 2016 but still well beyond contracted hours. Some 70% of UK primary teachers and 76% of secondary teachers report they cannot complete workload within contracted hours. Australian teachers work 46.4 hours weekly compared to the OECD average of 41 hours, and spend 24.9 hours weekly on non-teaching activities against the OECD average of 18.2.
Education Endowment Foundation principles for sustainable feedback offer alternatives: mark less but mark better, focusing on high-leverage assignments; distinguish error types (careless mistakes need only marking as incorrect, while conceptual errors require hints leading to principles); avoid grading with comments, since students focus on grades and ignore comments; use live marking in class for immediate targeted feedback; and employ student self-assessment with success criteria and structured peer assessment protocols. This maintains or improves learning whilst reducing marking from nine to four-five hours weekly.
Exam feedback
Question Level Analysis doesn’t produce valid data and rarely yields useful information. It is mostly for reporting, not feedback.
A three-column method works better. While marking, take a spare sheet of paper and create three columns: things to reteach, things to embed into retrieval, and things to build into schemes next year. As you mark, categorise issues accordingly. Widespread errors go into the reteach column, individual declarative knowledge gaps into the retrieval column, and major unanticipated misconceptions into the schemes column.
Don’t return papers straight away. First, reteach everything in the reteach column with understanding checks and practice. Then return papers at the end with a solutions copy, and offer individual support by telling students to ‘see me during break if you have questions’.
Show-call
Use show-call when many students make mistakes or produce substandard work (Lemov, 2015). Pause the class to address widespread issues. Use a visualiser or tablet camera to show examples (Black & Wiliam, 2009), and use mini-whiteboards to ensure all students meet expected standards.
References
Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21(1), 5-31. https://doi.org/10.1007/s11092-008-9068-5
Butler, R. (1988). Enhancing and undermining intrinsic motivation: The effects of task-involving and ego-involving evaluation on interest and performance. British Journal of Educational Psychology, 58(1), 1-14. https://doi.org/10.1111/j.2044-8279.1988.tb00874.x
Department for Education. (2019). Teacher workload survey 2019. https://www.gov.uk/government/publications/teacher-workload-survey-2019
Elliott, V., & Baird, J. (2016). A marked improvement? A review of the evidence on written marking. Education Endowment Foundation. https://educationendowmentfoundation.org.uk/
Independent Teacher Workload Review Group. (2016). Eliminating unnecessary workload around marking. Department for Education. https://www.gov.uk/government/publications/reducing-teacher-workload-marking-policy-review-group-report
Jerrim, J., Sims, S., & Taylor, H. (2020). Teacher workload and well-being: New international evidence. UCL Institute of Education. https://johnjerrim.com/
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. https://doi.org/10.1207/s15516709cog1302_1
Fyfe, E. R., & Rittle-Johnson, B. (2016). Feedback both helps and hinders learning: The causal role of prior knowledge. Journal of Educational Psychology, 108(1), 82-97. https://doi.org/10.1037/edu0000053
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81-112. https://doi.org/10.3102/003465430298487
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38(1), 23-31. https://doi.org/10.1207/S15326985EP3801_4
Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254-284. https://doi.org/10.1037/0033-2909.119.2.254
Lemov, D. (2015). Teach like a champion 2.0: 62 techniques that put students on the path to college. Jossey-Bass.
Lipnevich, A. A., & Smith, J. K. (2009). Effects of differential feedback on students’ examination performance. Journal of Experimental Psychology: Applied, 15(4), 319-333. https://doi.org/10.1037/a0017841
Rosenshine, B. (2012). Principles of instruction: Research-based strategies that all teachers should know. American Educator, 36(1), 12-19.
Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153-189. https://doi.org/10.3102/0034654307313795
Sweller, J., van Merriënboer, J. J. G., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31(2), 261-292. https://doi.org/10.1007/s10648-019-09465-5