Appraisal of Assessment Skills of Basic Science Education Teachers: Towards Quality Assurance
Bibliographic record
Abstract
Assessment is a very important programme in education. Assessment information shows the level of achievement of objective. Important decisions are made about the learner and education system based on results of assessment. Whatever the parents know about quality of education is through the assessment reports of their wards. Considering its primordial role in education, it is not safe to conduct assessment in a haphazard manner. Assessment requires some levels of competency to be able to ask the right questions and elicit the desired responses. Educational system in Nigeria has been accused of poor quality due to poor skills acquisition of the graduates. Can the problem be traced to wrong mode of assessment? Primary education is the foundation- laying stage of which if the problem is detected and corrected at this level, quality would be assured. This is the reason the researcher carried out study to ascertain the assessment competence of basic (Primary 1-6) teachers who assess and certify pupils that move to secondary level. 93 copies of lesson plan written by the teachers were critiqued in terms of adequacy of specific objectives and evaluation questions meant to be used in ascertaining the achievement of the objectives. 4 research questions guided the study. Findings showed lack of direct link between the specific objectives and the question items used in assessing them. There was preponderance of assessment questions at the knowledge level of cognitive domains. It was recommended among others that teachers need capacity building in the area of assessment of learning. Again, the current arrangement where a single teacher teaches all the subjects should be reviewed.
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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 | 0.037 | 0.083 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".