Teacher’s Relational Strategies and Student Perceptions in a Thai University Classroom Context
Bibliographic record
Abstract
Teacher-student relationships play a pivotal role in fostering student engagement and learning outcomes. However, research on relational strategies in Thai EFL university classrooms remains limited. This study explores the relational strategies employed by an experienced Thai university English teacher in a Phonology course and examines students’ perceptions of their impact on classroom engagement and learning. Using a qualitative case study approach, data were collected through semi-structured interviews, classroom observations, and field notes. Thematic content analysis identified four key relational strategies: personal conversations, off-topic discussions, maintaining a positive classroom atmosphere, and avoiding student singling out. Findings indicate that most students perceived these strategies as beneficial in creating a supportive and engaging learning environment, enhancing motivation, participation, and confidence. However, some students reported concerns about lesson flow disruptions due to off-topic discussions. This study highlights the significance of relational strategies in shaping student experiences and suggests integrating relational training into teacher professional development to optimize student engagement and learning outcomes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".