Perceived Assessment Instructional Skill Needed by Primary School Teachers for Improving Teaching in Enugu State
Bibliographic record
Abstract
This study was carried out to investigate the perceived assessment instructional skill needed by primary school teachers for improving teaching in Enugu State, Nigeria. Two research questions and two null hypotheses guided the study. Descriptive survey design was used in the study. The population of the study consisted of 10, 415 public primary school teachers in Enugu State. Sample size of the study was 1,196 teachers, comprising of 579 males and 617 female teachers. Multistage sampling technique was used in the selection of the sample size. Iinstrument used for data collection was ‘Perceived Assessment Instructional Skill Needed by Teachers Questionnaire (PAISNTQ). To determine the internal consistency of the instrument, Cronbach Alpha was usedand the result yielded 0.87. The data collected from questionnaire were analyzed using mean, standard deviation and T-test statistics. The results of the analysis revealed that assessment instructional skills teachers are: assessing the area of pupils’ needs through observation; finding out areas of weakness and strength in pupils by asking them questions; assigning homework, quiz and examination to pupils. Also, the results of the analysis revealed that there is no statistically significant difference in the mean rating of male and female teachers on the perceived assessment instructional skill needed by primary school teachers for improved teaching; and that there is no statistically significant difference in the mean rating of teachers in urban and rural public primary schools on the perceived assessment instructional skills needed by primary school teachers for improved teaching. Based on the findings of the study, the researchers recommended, among others, that the assessment instructional skills discussed in this study should be integrated into the teacher education curriculum; and that primary school teachers should be constantly appraised in the area of assessment instructional skills.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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, 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".