A Study of Analytical Thinking and Integrated Science Process Skills of High Vocational Diploma Students, 1st Year in Microbiology through Research Based Learning
Bibliographic record
Abstract
This study aims to investigate the effectiveness of a research-based learning management plan microbiology and its impact on vocational education certificate students in the Animal Science department at Mahasarakham College of Agriculture and Technology. The research instruments included five research-based learning plans of microorganisms and their applications, each plan lasting 4 hours, totaling 20 hours. The tools used were a 20-item multiple-choice achievement test on types of microorganisms and their applications, a 15-item multiple-choice test assessing analytical thinking skills, a 15-item multiple-choice test measuring integrated scientific process skills, and a questionnaire measuring student satisfaction with the research-based learning approach. The research findings revealed the following: 1. The research-based learning management plan was effective according to the 80/80 criterion, with a process efficiency (E1) of 85.40 and an outcome efficiency (E2) of 86.00 2. Students’ analytical thinking skills significantly improved after the course at the .05 level of statistical significance. 3. Students’ integrated scientific process skills significantly improved after the course at the .05 level of statistical significance. 4. Students expressed the highest level of satisfaction with the content, teaching methods, and assessment, with an overall satisfaction average of 4.57. The results indicate that the research-based learning management plan is highly effective and contributes positively to the development of students' analytical thinking skills, integrated scientific process skills, and overall satisfaction.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".