Instructional practices and students’ reading performance: a comparative study of 10 top performing regions in PISA 2018
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This comparative study investigated the associations between instructional practices and students’ reading performance among 10 top performing regions that participated in the Program for International Student Assessment (PISA) 2018. A nationally representative sample consisting of 80,016 15-year-old students from 5 Asian regions (B-S-J-Z [China], Singapore, Macao, Hong Kong, and Korea) and 5 Western regions (Estonia, Canada, Finland, Ireland, and Poland) were included. A secondary analysis of PISA survey and assessment data was conducted. T test and ANOVA analyses revealed systematic differences in instructional practices of the 10 regions. B-S-J-Z (China) had significantly higher levels of teacher support, teacher-directed instruction, and teacher stimulation than the other sample regions. Asian regions tended to have higher levels of teacher support, teacher-directed instruction, teacher feedback, adaptive instruction, and teacher enthusiasm compared with Western regions, although variations were also found within Asian regions or within Western regions. Hierarchical linear regression (HLR) analyses indicated that reading performance was positively predicted by teacher support, adaptive instruction, teacher stimulation, and teacher enthusiasm, but negatively predicted by teacher-directed instruction and teacher feedback. This study sheds light on the effective instructional practices for optimizing students’ reading performance across different cultural contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it