Development of an Instrument to Explore Teacher Roles Based on Perceptions of English Learners in Online Learning 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
In order to examine teacher roles in ELT contexts more specifically, this study aims to develop an instrument (A Scale of Teacher Role Inventory, in short STRI) that measures teacher roles based on the perceptions of English learners in online learning context. The instrument was constructed under the conceptual framework of role theory by Coppola (2002) and on the basis of the scenario of open-ended question responded by 296 university students as well as an interview of 15 university students in previous investigations. A tentative questionnaire of 46 items was designed and later administered to 251 university students for the pilot study. In order to validate the instrument, both item analysis and exploratory factor analysis were conducted to delete 19 less valid items and develop the final version of a scale with 27 items. Statistical results showed that KMO was .938 (p = .000 < .005) and 27 items fell into three main factors: cognitive role, affective role and managerial role. The Cronbach’s Alpha value of the final 27-item scale is .924, which indicates that it is a fairly reliable measurement. To further validate this final version of 27-item instrument, the questionnaire was administered to 153 university students. The results showed that the scale is reliable and valid with Cronbach’s Alpha value of .955. The research findings suggested that this instrument of STRI could be used to scrutinize the specific tasks of teachers and reveal possible role changes not only in online learning modes but also across different instructional contexts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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