A Comparison of Selected Assessment Results before and during the COVID-19 Pandemic in One University in South Africa
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
The study examined the impact of coursework-only assessment, as made necessary at the onset of the COVID-19 pandemic, adopting a quantitative research approach with 1013 students. The data obtained were analysed using SPSS version 27.0 to obtain descriptive and inferential statistics. The results revealed significant differences between the 2019- and 2020 marks for the same courses. In two of the science courses (T2 and T3), the mean scores for 2019 were significantly higher than the mean scores for 2020. In the mathematics course, the 2020 marks were significantly higher than the marks for 2019. While a normal distribution was assumed for the science courses, the mathematic course showed marks that were skewed to the right. A higher number of distinctions in the F1 course and a significant decline in the mean scores for T1 and T2 implies that there is a need for professional development of lecturers teaching in the online space. It is, therefore, recommended that higher education lecturers need adequate professional development on setting and administering online assessments. The assessment should test adequate lower- and higher-order cognitive skills for sufficient testing of student knowledge during online assessments. Furthermore, a variety of assessment methods and a diversity of tasks may be used to ensure the reliability of the assessment outcomes.
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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 | 0.000 | 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 it