The Effect of TPR Tasks on Word Knowledge of Thai Primary School Learners
Bibliographic record
Abstract
Vocabulary acquisition is a fundamental element of mastering the English language, necessitating a comprehensive lexicon that evolves through experiential learning to facilitate accurate comprehension and production of language. The current study examined the impact of Total Physical Response (TPR) tasks on the vocabulary acquisition of Thai primary school students, with a particular focus on the definition of words. It also explored the students’ attitudes towards using TPR tasks for vocabulary learning. The TPR tasks were designed to engage three of the human senses—visual, auditory, and tactile—by incorporating multisensory tasks. Employing a mixed-methods research design, the study involved 27 second graders from a primary school in northeastern Thailand. The research methodology utilized three instruments. From a quantitative perspective, the Receptive Word Knowledge Test (RWKT) and the Productive Word Knowledge Test (PWKT) were administered to assess the students’ vocabulary knowledge before and after the intervention within a single-group pretest-posttest framework. Qualitatively, a focus group interview was conducted to gain deeper insight into the students’ attitudes towards participation in TPR activities. The quantitative data indicated a significant enhancement in both receptive and productive vocabulary knowledge among the participants. Furthermore, the qualitative findings highlighted the advantages of TPR tasks, with students expressing increased enthusiasm and competitive spirit and a shared willingness and pleasure in vocabulary learning through interactive tasks and peer interaction. In conclusion, this study corroborates the efficacy of TPR tasks in significantly advancing Thai primary school students’ receptive and productive vocabulary knowledge.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".