Computer Assisted Language Learning and EFL Teachers’ Literacy: A Case in Iran
Bibliographic record
Abstract
Computer assisted language learning (CALL) literacy is an issue of great concern not sufficiently dealt with in the literature of language teaching and learning. This study examines CALL literacy by Iranian EFL teachers. Reviewing the literature and some models of computer, information, and technology literacy, to collect the data, a questionnaire in Likert scale composed of four sections of computer mediated communication (CMC) tools, online information literacy, multimedia literacy, and basic computer skills was utilized. Following the data analysis by SPSS package, the findings showed Iranian EFL teachers’ moderate level of CALL literacy; however, their literacy on CMC tools was below the satisfactory level. Further, there was a significant relationship between the teachers’ literacy and their academic degree, yet the relationship between their CALL literacy and their teaching experience as well as the difference between the teachers’ literacy and gender was found insignificant. The study has implications for EFL teachers in educational systems supporting CALL-based pedagogy.
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How this classification was reachedexpand
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 | 0.066 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".