A Case-Control Study of Student Performance in a Blended Learning Environment
Bibliographic record
Abstract
This paper discusses student performancein a fourth-year computer-aided design course under twodelivery modes: one using a blended learning format andthe other based on a classical lecture style. Specifically, thefinal exam results following the blended learning approach(2017) are compared to those from the previous four years(2012 to 2016), where the latter delivery was based on aclassical lecture style.Course enrolment during the study period varied froma minimum of 68 students for the 2012 cohort to amaximum of 122 registrations in 2017. Meanwhile, themean cumulative grade point average (CGPA) of eachcohort varied from a minimum of 6.71 ± 1.21 (mean ± SD)in 2012 to a maximum of 7.10 ± 1.33 (mean ± SD) in 2014;the mean CGPA in 2017 was 6.87 ± 1.31 (mean ± SD).While the class average in the final exam for each yeartracked more-or-less the entrance CGPA, the distributionof grades did not. Instead, the blended learning cohortshowed the lowest proportion of students achieving below50% on the final exam.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".