The Development of Instruction Media in Board Game to Enhance the Capability in the Development of Thai Textbook and the Happiness in Learning for Undergraduate Students
Bibliographic record
Abstract
The purposes of this research were to: 1) develop and determine the efficiency of instruction media in board games to enhance the capability in the Development of Thai Textbook and the happiness in learning for undergraduate students, 2) compare the undergraduate students’ learning capability in the Development of Thai Textbook before and after learning instruction media in board game and 3) to study the level of happiness in learning the Development of Thai Textbook for undergraduate students towards learning instruction media in board game. The sample group in this research consisted of 27 third year-undergraduate students, majoring in Thai, at the Faculty of Humanities, Srinakharinwirot University. The data was collected by research and development. The data was analyzed by using mean, standard deviation, t-test dependent, and content analysis. The findings of this study were as follows: (1) The efficiency of the instruction media in board games was 84.81/83.83 which was higher than the specified criteria. (2) The average student’s learning capability in the Development of Thai Textbook after learning the instruction media in board games was higher than before using instruction media in board games. (3) The undergraduate students had the highest mean level showing their pleasure in learning the Development of Thai Textbook towards learning instruction media in board game and effective for content analysis regarding the undergraduate students’ learning logs from Reflective Journal, it was found that this instruction media in board game enhanced the capability in the Development of Thai Textbook and the happiness in learning abilities.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".