The Effects of Using MS Teams Mobile Application on Language Learners’ Motivation During and After the Covid-19 Pandemic
Bibliographic record
Abstract
Motivation has long been recognized as a critical component of language learners' success. According to Self-Determination Theory (SDT), an autonomously motivated student is more likely to be engaged in a learning activity. As the learners' needs for autonomy, competence, and relatedness ought to be accommodated, these basic psychological needs of learners (BPNs) must be addressed to sustain autonomous motivation. Although there is a substantial number of literature that addresses the role of these three components in the context of mobile-assisted language learning (MALL) and their relationship to autonomous motivation (Kohnke, 2020; Alamer, 2021b; Kartal, 2019; Ali, 2019), the use of Microsoft Teams is almost never addressed. This study aimed to examine the relationship between the informal use of mobile apps by teachers, such as messaging applications, and their students' levels of motivation. This study involved one group of students divided into six sections with the same level of proficiency, who were enrolled in a foundation course in English at a private university in the United Arab Emirates (N = 344). The students were studied over a period of time (Phase 1 and Phase 2 groups of the same population). The analyses were carried out by the use of ANOVA with repeated measures and a t-test. Participants' autonomy and competence were found to have increased slightly as a result of the study. The study, however, failed to demonstrate any significant impacts on anxiety, self-confidence, engagement with language tasks, nor on actual achievement.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".