Does spaced practice have the same effects on different second language vocabulary learning activities? Fill‐in‐the‐blanks versus flashcards
Bibliographic record
Abstract
Abstract This study examined the effects of spaced practice on second language (L2) vocabulary learning under different learning conditions. One hundred fifty Korean learners of L2 English were divided into five groups: one control (no treatment) and four experimental groups based on learning condition (fill‐in‐the‐blanks vs. flashcards) and spacing type (massed [no spacing interval] vs. spaced [1‐day interval]). The participants studied 48 low‐frequency English words. Results showed that the effects of spaced practice were greater for fill‐in‐the‐blanks than flashcards on an immediate posttest and that spaced practice was more effective than massed practice for both activities on a 2‐week delayed posttest with no overall significant difference between the learning gains from the two activities. Feedback timing (immediate, delayed) did not affect vocabulary learning in either activity.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".