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Online peer feedback that improves argumentative essays
Open access · cc by · source: Europe PMC
A structure-focused online peer feedback module improved university students’ argumentative essay quality across courses and degree levels.
Study at a glance
- Design
- Other — Pre–post evaluation of a structure-focused online peer-feedback essay module
- N
- N=284 · 284 of 330 students across five courses completed the module
- Population
- Bachelor and master students at Wageningen University across course domains
- Outcome
- Argumentative essay quality before vs after guided peer feedback
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
Essay performance improved significantly from pre-test to post-test with a large effect size, including gains across recognized elements of high-quality argumentative writing. Improvements held across course domains and for both bachelor and master students, with only limited level-specific differences on some elements.
Methodology
Researchers designed an online supported peer feedback module centered on argumentative essay structure and implemented it at Wageningen University across bachelor and master courses in several domains. Students wrote essays, exchanged guided peer feedback online, and revised; essay quality was scored before and after the module on recognized argument elements.
Limitations
Without a no-feedback or alternative-feedback control group, the study cannot isolate peer feedback from practice, instructor effects, or other course activities. Results come from one Dutch research university and may not generalize to other writing genres or less structured online setups.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
At Wageningen, 330 students from five domain courses joined an online supported peer-feedback module and 284 completed it. Argumentative-essay performance improved from pre-test to post-test with a large effect (Wilks’ λ = 0.65, F(7, 269) = 20.56, Partial η² = 0.35), including recognised argument elements, across bachelor and master levels. There was no no-feedback control, so practice and instructor effects are not isolated.
Evidence for the claim as stated.
Pre/post windows are not interchangeable designs. Peer feedback and faculty training are single-group rises. The ITS paper randomises after exclusions and adjusts for prior scores. Chatbots contrast two intact classes. Mentoring randomises classrooms and finds a null average with a subgroup gain. COVID UDL is a retrospective perception contrast, not a scored artefact. Calling all of them 'pre-test/post-test evidence that teaching improved' hides those differences.
Evidence for the claim as stated.
Wageningen’s online peer-feedback module (330 enrolled, 284 completers across five domain courses) improved argumentative-essay scores from pre-test to post-test with Partial η² = 0.35 (Wilks’ λ = 0.65, F(7, 269) = 20.56). That is a large within-sample change without a no-feedback control, so it is not an isolated treatment effect of peer feedback versus practice.
Evidence for the claim as stated.
Near-zero and large are both in this set because the contrasts differ. FLEX’s programme-level exam effect is ~0 despite 51% less classroom time (only 24/133 courses significant). Peer feedback’s Partial η² = 0.35 is a single-group pre/post on essays. Science-simulation undergraduates (n = 1,034; 536 male, 498 female) reported high engagement and satisfaction with no control-group d at all. You cannot rank those as competing estimates of 'whether blended learning works'.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Pre/post windows are not interchangeable designs. Peer feedback and faculty training are single-group rises. The ITS paper randomises after exclusions and adjusts for prior scores. Chatbots contrast two intact classes. Mentoring randomises classrooms and finds a null average with a subgroup gain. COVID UDL is a retrospective perception contrast, not a scored artefact. Calling all of them 'pre-test/post-test evidence that teaching improved' hides those differences.
- Supports · Faculty training that shifts teaching innovation attitudes
- Supports · Can a dialogue ITS fix fraction multiplication?
- Supports · Do educational chatbots raise project-course grades?
- Supports · Can showing shared interests improve student-teacher mentoring?
- Supports · Did remote COVID teaching feel less engaging to students?
Near-zero and large are both in this set because the contrasts differ. FLEX’s programme-level exam effect is ~0 despite 51% less classroom time (only 24/133 courses significant). Peer feedback’s Partial η² = 0.35 is a single-group pre/post on essays. Science-simulation undergraduates (n = 1,034; 536 male, 498 female) reported high engagement and satisfaction with no control-group d at all. You cannot rank those as competing estimates of 'whether blended learning works'.
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