Collaborative Summative Assessment: Means for Enduring Learning and Attainment of 21st Century Skills in the Online Platform
Bibliographic record
Abstract
The use of collaborative assessment as a form of summative evaluation during online learning targets Sustainable Development Goal (SDG) 4 which aims at ensuring sustainable development in education through student assessment. Moreover, collaborative assessment is an interactive process that enables students to work together and get engaged in shared decision-making toward mutually-defined goals. This research aimed to examine the impact of online distance learning on collaborative assessment among High School students according to grade level and sex. This research will help educate learners on the value of collaboration during online distance learning, and will strengthen global citizenship. This study used a cross-sectional survey of quantitative research design with 252 high school students as participants. Significant findings revealed that both Junior and Senior high school students, as well as male and female students, agree that collaborative summative assessment during online learning helped them in the attainment of good academic performance, easier completion of tasks, enhanced communication skill, evident cooperation, and submission of quality output. Moreover, inferential analysis showed no significant difference on the impact of online distance learning on collaborative summative assessment as perceived by grade level, t(17) = 2.11, p = 0.15 and sex, t(17) = 2.11, p = 0.24. Therefore, regardless of grade level and sex, the new mode of learning platform proved to be an efficient avenue for students to work together in the achievement of a common goal despite the challenges presented by online distance learning.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".