The Four Scaffolding Modules for Collaborative Problem-Based Learning through the Computer Network on Moodle LMS for the Computer Programming Course
Why this work is in the frame
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Bibliographic record
Abstract
Scaffolding is a learning approach designed to promote a deeper understanding, it is the support given during the learning process which is tailored to the needs of the student with the intention of helping the student achieve the learning goals, including resources, a compelling task, templates and guides, and guidance on the development of cognitive and social skills. Meanwhile, problem-based learning (PBL) situate learning in complex tasks. Such task require scaffolding to help students engage in sense making, managing their investigations, problem-solving processes, and encouraging students to articulate their thinking and reflect on their learning. This study aimed to develop four scaffolding modules for collaborative problem-based learning through the computer network on Moodle LMS for the computer programming course of undergraduate students, and to analyze the satisfaction of the experts and students after using the developed scaffolding modules. The four scaffolding modules consisted of metacognitive scaffolding, conceptual scaffolding, strategic scaffolding, and procedural scaffolding, each of which represented by a 3-D animation expert cartoon to attract students. The sample group were twenty-two students of small group pilot and six experts. The findings indicated that the degree of satisfaction towards the scaffolding from the experts was high and the degree of the satisfaction towards the scaffolding from the students was also high. This can be used the four scaffolding modules to complete PBL task successfully.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it