Students’ Perceptions of the Effectiveness of Assessment Feedback as a Learning Tool in an Introductory Problem-solving Course
Bibliographic record
Abstract
There have been calls in the literature for reforms to assessment to enhance student learning (Shepard, 2000). In many instances, this refers to the need to move from traditional assessment procedures that are characterized as content-heavy, summative, and norm-referenced approaches to more constructivist and student-centred approaches, often characterized as more “…flexible, integrative, contextualized, process oriented, criteria referenced and formative” (Ellery, 2008, p. 421). Whereas summative assessment techniques rarely allow students to act on the feedback provided, formative feedback provided throughout the learning process can be used to improve future work and promote learning (Ellery, 2008; Higgins, Hartley & Skelton, 2002) by providing students an opportunity to learn from mistakes. Allowing students to learn from their mistakes makes good pedagogical sense. To date there has been little research examining students’ use of feedback (Higgins, Hartley, and Skelton, 2002). In an effort to begin to add to the literature in this area, this paper describes a study that explored the effectiveness of oral and written formative feedback when students were provided the opportunity to use it. The paper begins by reviewing literature related to assessment and how assessment relates to feedback in general. It then presents what the research has found in relation to students’ perspectives of effective feedback and how they use it. The paper ends by presenting the results and discussion. La documentation fait état de demandes de réforme de l’évaluation pour améliorer l’apprentissage des étudiants (Shepard, 2000). Dans plusieurs cas, cela traduit le besoin de passer des procédures d’évaluation traditionnelles caractérisées par la lourdeur de leur contenu, par leur aspect sommatif et par leurs approches normatives à des approches plus constructivistes et centrées sur les étudiants, souvent qualifiées de plus « ... souples, intégratives, contextualisées, axées sur les processus, balisées par des critères et formatives » (Ellery, 2008, p. 421). Alors que les techniques d’évaluation sommative permettent rarement aux étudiants de se conformer à la rétroaction fournie, la rétroaction formative tout au long du processus d’apprentissage peut être utilisée pour améliorer les travaux futurs et favoriser l’apprentissage (Ellery, 2008; Higgins, Hartley et Skelton, 2002) en donnant l’occasion aux étudiants d’apprendre de leurs erreurs. Sur le plan pédagogique, permettre aux étudiants d’apprendre de leurs erreurs a du sens. À ce jour, il y a eu peu de recherche sur l’utilisation que font les étudiants de la rétroaction (Higgins, Hartley et Skelton, 2002). Le présent article se veut un ajout à la documentation dans ce domaine. Ses auteurs décrivent une étude qui porte sur l’efficacité de la rétroaction formative orale et écrite lorsque les étudiants ont eu l’occasion de l’utiliser subséquemment. Les auteurs commencent par une analyse de la documentation sur l’évaluation et sur les liens généraux entre cette dernière et la rétroaction. Ils présentent ensuite les résultats de recherche liée aux perspectives des étudiants sur la rétroaction efficace et sur l’utilisation qu’ils en font. Enfin, ils terminent par une présentation des résultats et par une discussion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".