Emergency remote assessment practices in higher education in sub-Saharan Africa during COVID-19
Bibliographic record
Abstract
Following the disruptions to in-person schooling during COVID-19 and the need for emergency remote teaching, this study explored the assessment experiences of teacher educators in Ghana. Through a qualitative transcendental phenomenological approach, purposive criterion sampling was used to select 25 teacher educators from 15 teacher training institutions in Ghana who participated in online teaching during COVID-19 school closure. The findings show that teacher-centered approaches to assessment dominate emergency remote assessment practices of teacher educators. Hodgepodge grading and general feedback were more prevalent during remote assessment. Teachers were also found to randomly select a few students to provide individualized feedback due to the large class size. Challenges including limited knowledge of the use of the online teaching platform for assessment, inadequate professional training and access to technological resources, and concerns about academic dishonesty were reported. However, teachers reported that their involvement in abrupt remote teaching and assessment has been a learning opportunity for them to develop new skills, which is imperative for their professional development.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".