READINESS LEVEL OF PRIMARY SCHOOL TEACHERS IN KLANG DISTRICT, SELANGOR IN THE IMPLEMENTATION OF IN-CLASS ASSESSMENT FROM THE ASPECT OF KNOWLEDGE
Bibliographic record
Abstract
This study is an attempt to identify teachers’ level of knowledge in the implementation of In-class Assessment in schools. Among the purposes of PDB is to ensure the pupils find the education acquired enjoyable. According to the findings by Halimah Jamil and Rozita Radhiah Said (2019), South Korea, the United States of America and Canada are among the countries that have long practiced assessment in their education system. As a whole, this research opted to use the quantitative research method to uncover and understand problems that occur in the implementation of PBD by teachers in schools. The Cross-Sectional Survey method will be used due to the huge size of the population. The researcher uses questionnaires as a tool for this survey. The researcher will use descriptive analysis to analyse the data. The data findings, obtained from the questionnaires distributed to 500 respondents which are later analysed using descriptive statistics through calculations on the frequency analysis, mean value, percentage, and standard deviation, show that the level of teachers’ comprehension in the implementation of PBD in schools is high. Aside from that, through the one-way Anova test in this research, small significant differences are seen between the teachers’ knowledge in the implementation of PBD and their year of service. Although all teachers have a high level of knowledge, the data shows that teachers who have been in service longer have a higher level of knowledge compared to those who are new in service. In conclusion, the implementation level of PBD in Primary Schools in the state of Selangor is high. It is hoped that the implication of this study will help to solve problems, or to determine methods or approaches that can be applied in the effort to increase teachers’ level of knowledge during the implementation of PBD.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".