Enhancing Collaborative Problem-Solving Competencies by Using STEM-Based Learning Through the Dietary Plan Lessons
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This classroom action research aims to investigate the development of collaborative problem-solving competencies using STEM-based learning through dietary plan lessons. The participants included 77 twelfth-grade students in the 2018 academic year in the science-technology program in a public school under the supervision of the Ministry of University Affairs. Two types of instruments were used in the study: 1) ten lesson plans of the biomolecules unit equivalent to eighteen lesson periods; 2) data collection instruments, including collaborative problem-solving competencies observation sheets, students’ learning reflections, and informal interview protocols. The data analysis involved frequencies, percentages, and content analysis. The results of the study revealed that the students improved all three competencies. Regarding the first competency, “Establishing and Maintaining Shared Understanding,” the students were accustomed to having a dominant member assigning the task while other members passively followed the orders. When they encountered a problem, each member individually solved it or asked the teachers for help without a group discussion. However, after the instruction, the students improved their communication skills by discussing the task processes with the other group members. Moreover, when a problem occurred, they approached it as a shared responsibility instead of as an individual’s duty. Therefore, the problem was collectively sorted out and successfully solved. In terms of the second competency, “Taking Appropriate Action to Solve the Problem,” the students had previously been assigned their roles by the group leaders without consideration of the strengths and weaknesses of each member, resulting in an unsuccessful task. After the instruction, everyone became more collaborative in considering the task at hand and discussed the role that best suited each member. When they encountered a problem, everyone collectively planned the appropriate steps toward the solution. With regard to the third competency, “Establishing and Maintaining Team Organization,” the students had not previously reflected on their performance, but after the activities, they learned to provide feedback to improve other members’ understanding and carry out the task more efficiently. A challenge that emerged in implementing the activities involved the time issue. It is important to manage time effectively and to challenge the students to collaboratively solve the problem. The instructional activities should be conducted continuously by rotating students into new groups where they can practice their teamwork skills with others. Moreover, the collaborative problem-solving activities are found to be applicable not only for a STEM-based approach but also for a project-based approach.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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