Insights in Flexible Assessment from Students’ and Teachers’ Perspectives: A Focus Group Study
Bibliographic record
Abstract
The advantages and drawbacks of components of flexible assessment have been studied mostly from the standpoint of students and, to a lesser extent, teachers. A gap persists in understanding the collective perspectives of teachers and students concerning flexible assessment. This study aimed to explore experiences and perspectives of students and teachers regarding flexible assessment within the specific context of nursing education. Seven focus groups comprised four sessions with teachers and three with students, each involving 5-8 participants. Results showed that students and teachers have a predominantly positive perspective towards flexible assessment. They acknowledge the opportunities that flexible assessment provides for diverse forms to present evidence. However, concerns were raised regarding the design of flexible assessments, issues of fairness in rating evidence, and the understanding among teachers and students regarding the assessment processes. Additionally, discussions focused on the perceived benefit of flexible assessments, particularly concerning the time investment required for their implementation and evaluation. In conclusion, the success of flexible assessments is contingent on the careful consideration of its design, ensuring equitable evaluation of evidence, and fostering comprehensive understanding among both teachers and students. Recognizing potential disparities in views of students and teachers offers valuable insights into the effectiveness of flexible assessment. Achieving a balance between the flexibility of assessment formats, aligned forms of evidence, and an appropriate rating methodology is crucial for effective implementation.
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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 | 0.031 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| 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".