Effects of feedback timing on second language vocabulary learning: Does delaying feedback increase learning?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Feedback, or information given to learners regarding their performance, is found to facilitate second language (L2) learning. Research also suggests that the timing of feedback (whether it is provided immediately or after a delay) may affect learning. The purpose of the present study was to identify the optimal feedback timing for L2 vocabulary learning. This study differs from previous feedback timing studies in two important respects. First, unlike some previous studies, feedback timing was not confounded with lag to test (interval between the last encounter with a given item and the posttest). Second, in order to test the view that delayed feedback may be particularly effective when learners make few errors during learning, the present study manipulated the frequency of practice to influence learning phase performance. In this study, 98 Japanese college students studied 16 English–Japanese word pairs. Immediate feedback was given immediately after each response, whereas delayed feedback was withheld until all target items were practised. Learning was measured by posttests administered immediately, 1 week, and 4 weeks after the treatment. Results suggested that when lag to test is controlled, feedback timing may have little effect on L2 vocabulary learning regardless of the frequency of errors during learning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.006 |
| 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 it