Effect of Project-Based Learning Towards Collaboration among Students in the Design and Technology Subject
Bibliographic record
Abstract
Teaching Design and Technology that focuses only on the end product had led to students less exposure to collaboration skills in their learning. Therefore, a study that determines the teaching method in applying collaboration skills among students and its effect is required. The two teaching methods used were the ‘doing a project’ method for the control group and project-based learning for the treatment group. A quasi-experimental study was carried out with a nonequivalent control group. Two groups were selected from two different daily schools consisting of 34 students for the control group and 32 students for the treatment group. A pre-test, followed by an intervention for 7 weeks was carried out. After the intervention, a post-test was carried out for both groups. A questionnaire regarding collaboration skills was used in both tests. The data obtained were analyzed descriptively and by inference. The pre-test showed that there was no significant difference in the level of collaboration of both groups. However, the results of the post-test showed that the level of collaboration in the treatment group is significantly higher than in the control group. Thus, the study showed that collaboration can be applied and cultivated among students by using project-based learning. This can be achieved by structured discussion from explicit planning, and student-centered learning activities with teaching and learning aids that support the execution of students’ project work.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".