Development of an Experiential Learning Management Model to Develop Career Skills for Primary School Students
Bibliographic record
Abstract
The objectives of this research were (1) to develop the experiential learning management model to develop career skills for primary school students, and (2) to evaluate the effectiveness of the experiential learning management model. The sample was divided into two groups: (1) the sample used to evaluate the appropriateness of the learning management model, namely 5 experts in learning management model development and career skills development of students, were obtained by purposive sampling; (2) the sample used to evaluate the effectiveness of the learning management model consisted of 30 students in grade 6 of Ban Khek Noi School, which obtained by simple random sampling. Data analysis statistics were mean, standard deviation, and repeated measure ANOVA. Research findings showed that (1) the experiential learning management model was appropriate at a high level; (2) the students career skills after using the learning management model at a very good level; and (3) the post-career skills scores of the students who learned from the experiential learning management model were significantly higher than their pre-career skills score at the .05 level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".