The Transfer of Learning Associated with Audio Feedback on Written Work
Bibliographic record
Abstract
This study examined whether audio feedback provided to undergraduates (N=51) about one paper would prove beneficial in terms of improving their grades on another, unrelated paper of the same type. We examined this issue both in terms of student beliefs about learning transfer, as well as their actual ability to transfer what had been learned on one assignment to another, subsequent assignment. Results indicated that students believed that they would be able to transfer what they had learned via audio feedback. Moreover, results also suggested that students actually did generalize the overarching comments about content and structure made in the audio files to a subsequent paper, the content of which differed substantially from the initial one. Both students and teaching assistants demonstrated very favourable responses to this type of feedback, suggesting that it was both clear and comprehensive. Cette étude examine la question de savoir si le feedback audio donné à des étudiants de premier cycle (N=51) concernant un travail écrit pouvait les aider à améliorer leur note pour un autre travail d’un autre ordre mais du même type. Nous avons examiné la question à la fois en termes des croyances des étudiants concernant le transfert des connaissances, ainsi qu’en termes de leur capacité réelle à transférer ce qu’ils avaient appris à propos d’un travail à un autre travail rédigé ultérieurement. Les résultats ont indiqué que les étudiants pensaient être capables de transférer ce qu’ils avaient appris par le biais d’un feedback audio. De plus, les résultats ont également indiqué que les étudiants avaient effectivement généralisé les commentaires principaux sur le fond et la forme présentés dans les fichiers audio et les avaient appliqués à un travail ultérieur dont le contenu était considérablement différent du premier. Tant les étudiants que les assistants enseignants ont fourni des réponses très favorables à ce type de feedback, suggérant que le tout était clair et compréhensible.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.054 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.018 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".