Effects of Interactive Text Chat and Independent Writing on Iranian EFL Language Learning
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
The present Study tries to examine the degree of significance of interaction for foreign language learning by investigating results of dichotomous kinds of home work tasks. The researcher tried to compare: (a) interactive assignment, accomplished through text chat activities, and (b) individual assignment, accomplished through independent writing activities. For six weeks participants in two separate intermediate- level English classes in a between-subjects design were exposed to the two different situations and accomplished the supposed activities three times a week. In the assigned interactive situation, learner pairs involved in real-time text-chat sessions, accomplishing activities planned to promote interaction and collaboration via opinion-gaps or information- reasoning-. While In the individual situation, learners accomplished similar writing tasks alone. The same language input was provided in both conditions and the essential production, over an equivalent amount of time was the same in two conditions as well. Language improvements were examined via pre- and post-tests of writing, vocabulary, and speaking. Learners in the interactive situation revealed more obvious gains in oral production and vocabulary knowledge than learners in the individual situation, but it was found that learners’ writing accuracy or complexity did not differ. Comparison of the outcomes of the present study at the beginning of the survey and later in the study reveals that learners in the interactive situation created more English types and tokens in their activities than learners in the individual situation too. Thus the obtained findings of the study support the advantages of assigning interactive activities for foreign language production and acquisition.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".