Application of a CALL System in the Acquisition of Adverbs in English
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
In the paper, we examine whether and the extent to which CALL grammar instruction contributes to improving learners' performance and confidence in positioning adverbs in an English sentence. Over a two-week period two groups of ESL learners were exposed to six hours of grammar instruction. One group had teacher-fronted instruction while the other was exposed to CALL software. Both groups completed identical tasks in terms of format, instruction, task features, content and feedback. The groups were given a pretest, an immediate posttest, and a delayed posttest. Results showed a significant improvement on the intuition task and a significant confidence improvement on both intuition and production tasks for the computer group. The in-class and the control group showed no significant gains. It is hypothesized that frequency of exposure and practice accounted for the difference between the in-class and the computer group. It is also recognized that students' control of learning, availability of immediate feedback, and non-existence of negative psychological effect that can follow face-to-face negative feedback also contributed to the difference that was found.
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 | 0.001 | 0.000 |
| 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) | 0.000 | 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 it