The Effects of Blended Learning Instruction on Vocabulary Knowledge of Thai Primary School Students
Bibliographic record
Abstract
The present study aimed to investigate the effects of blended learning instruction on vocabulary knowledge of Thai primary school students and students' perceptions toward learning vocabulary through blended learning instruction. A mixed-methods approach was used. Quantitatively, a single group pretest-posttest design was used to measure students' vocabulary knowledge after ten weeks of vocabulary lessons via blended learning instruction. The qualitative method focused on students' perceptions toward blended learning instruction. There were a total of eight student participants at a small school in Kosumphisai, Maha Sarakham province. Three students were in fifth grade and five students in sixth grade. Two research instruments were used in this study: a pre-and-post-test and an in-depth interview. The quantitative results revealed that the post-test score was higher than the pretest score. The blended learning instruction can improve the students' vocabulary knowledge. The qualitative results showed that students had positive attitudes toward blended learning instruction on vocabulary teaching.
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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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".