The informational value of feedback choices for performance and revision in a digital assessment game
Bibliographic record
Abstract
Purpose This study aims to examine the impact of the informational value of feedback choices (confirmatory versus critical feedback) on students’ performance, their choice to revise and the time they spend designing posters and reading feedback in a computer-based assessment game, Posterlet. Design/methodology/approach An empirical correlational study was conducted to collect the choices to seek confirmatory or critical feedback and to revise posters in a poster design task from 106 grade 8 students from a middle school in California via Posterlet. Findings The results of the study show that critical uninformative feedback is associated with students’ performance, and critical informative feedback is associated with their learning strategies (i.e. feedback dwell time and willingness to revise), while confirmatory informative feedback is negatively associated with both performance and learning strategies. Research limitations/implications The study controlled the choice students were given regarding the valence of their feedback but not regarding the informational value of their feedback. Additionally, the study was conducted with middle-school students, and more research is needed to ascertain whether the results generalize to other populations. Practical implications The findings can be used to balance the design of the informational content of feedback messages to support student performance in an open-ended, creative design task. This study may also inform the design and implementation of agents (e.g. virtual characters) able to provide user-adaptive feedback for online interactive learning environments. Originality/value This study constitutes the first research to examine the informational value of feedback that is chosen rather than received, the latter being the prevalent model of delivering feedback in education.
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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 | 0.006 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".