Pedagogical Strategies Used to Enact Formative Assessment in Science Classrooms: Physical Sciences Teachers' Perspectives
Bibliographic record
Abstract
The importance of the enactment of formative assessment as a pedagogical tool in science teaching and learning cannot be over-emphasized. Teachers encounter pedagogical challenges when enacting formative assessment in science classrooms. These pedagogical challenges underscore the need to explore teachers' perspectives on pedagogical strategies used to enact formative assessment in science classrooms. This study examined grade 10 Physical Sciences teachers' perspectives on pedagogical strategies they adopted to enact formative assessment in science classrooms in diverse schools in South Africa. The empirical investigation invoked the sociocultural theory as a conceptual lens to provide insightful elucidation into the nature of teachers' perspectives on pedagogical strategies used to enact formative assessment in science classrooms. A generic qualitative research approach was employed. Data were collected through semi-structured focus group interviews and classroom observations. The study involved 12 purposively selected grade 10 Physical Sciences teachers as participants. The findings revealed that grade 10 Physical Sciences teachers adopted various pedagogical strategies when enacting formative assessment in science classrooms. However, meaningful enactment of formative assessment in science classrooms was largely hampered by a myriad of contextual factors such as class size and general lack of essential resources. It is recommended that teacher professional development interventions coordinated by the Department of Basic Education ought to make provision for meaningful opportunities to enhance teacher professional capacity required for coherent enactment of formative assessment as an essential tenet in science education. Theoretical implications for pedagogic innovation are discussed.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".