Interaction, modality, and word engagement as factors in lexical learning in a Chinese context
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
This study investigates the roles of collaborative output, the modality of output, and word engagement in vocabulary learning and retention by Chinese-speaking undergraduate EFL learners. The two treatment groups reconstructed a passage that they had read in one of two ways: (1) dyadic oral interaction while producing a written report (Written Output); (2) dyadic oral interaction followed by an oral report (Oral Output). A control group completed a reading comprehension task (Reading) based on the same passage. Four posttests revealed that Oral Output led to significantly better productive and receptive lexical learning than Reading all the way to the last posttest. Written Output led to significantly better productive and receptive lexical learning than Reading on posttest 2, but not on posttests 3 and 4. However, the difference in lexical learning between the Written and Oral Output conditions did not achieve significance. Interaction analysis found that the Oral and Written Output groups differed in the types of word processing they favoured as well as in the frequency of their word engagement. The article discusses the reasons why collaborative output facilitates lexical learning; considers the association between the Output performers’ word engagement and lexical retention; and suggests what might have contributed to the better success of the Oral Output group in their lexical retention.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 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 it