The Upshot of L2 Instructors’ Motivational Strategies in South Indian Technical Classroom Milieu during COVID-19
Bibliographic record
Abstract
Motivation is an inevitable factor in Second Language (L2) learning and teaching; moreover, various motivational strategies are involved in this factor. In the teaching-learning process, motivational strategies are paramount to robust the attainment of L2 learners and instructors. This study aims to investigate the use of motivational strategies given by the L2 instructors in technical classrooms (online) during the COVID-19 pandemic. A simple random sampling method is used to collect data amongst 159 L2 instructors in South India. The questionnaire with a five-point Likert scale was used to collect the responses from the informants. The collected data were analyzed using mean, standard deviation, internal reliability, and correlation. The study results revealed that various motivational strategies are not carried out meritoriously in an online class. Therefore, notable changes have occurred in the use of strategies in the virtual classroom. Stakeholders could utilize the strategies effectively and support the instructors’ community for balanced growth.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".