Enhancement of collaboration activities utilizing 21st century learning design rubric
Bibliographic record
Abstract
Twenty first century learners have incredibly diverse learning interests, needs, and aspirations. Engaging middle school students and sculpting successful, confident, and creative learners is a constant endeavor for educators [4]. In the 21st century classroom environments in which students can develop the skills they need in workplace. Collaboration occurs when students work together to create, discuss challenge and develop deeper critical thinking. In today’s workplace, collaboration is essential as only few tasks are completed alone (Calgary and Park, 2016). The collaborative project-based curriculum used in this classroom develops the higher order thinking skills, effective communication skills, and knowledge of technology that students will need in the 21st century workplace. The study therefore aims to promote collaboration skills among learners as it is deemed as one of the top 21st century skills. Collaborative learning unleashes a unique intellectual and social synergy. This study aims to enhance the collaborative skills of students through conducting collaboration activities in learning the Ecosystem. This research utilizes pretest-posttest and employs descriptive research designs. It uses modified activities about the lesson on Ecosystem and utilizes a Collaboration Rubric to rate the modified activities. The activities were rated by ten In-Service teachers and there are 105 students who participated in doing the activities. The paired t-test is then used to analyze the data. The In-Service teachers evaluated the 1st and 2nd adapted activity and are rated as fair. Thus, the modified activities were enhanced since the ratings of each activity did not meet the criterion of the collaboration rubric. As for the 3rd adapted activity is rated as excellent and is ready for implementation. The evaluators provided comments and suggestions such as producing colored pictures on the activities, omitting some questions, and making the words simpler to enhance the activities. The findings of the study shows the students’ performance in the posttest is higher than the pretest which indicates that there is a significant difference between the two tests given. The students’ conceptual understanding was also improved after conducting the activities. Some students’ outputs were Outstanding, Satisfactory, Fairly Satisfactory and Did Not Meet the Expectation. These results indicate that the students learned and developed their collaborative skills. The students found the activity interesting, enjoyable and useful. Furthermore, they understood the concept behind the activity.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".