Teaching higher order thinking skills to gifted students: A meta-analysis
Bibliographic record
Abstract
The current study examined the effects of higher order thinking skills (HOTS) interventions with gifted students in Taiwan. A total of 25 studies published between 1997 and 2017 were included. Twenty-nine effect sizes were extracted for the 25 studies. The small number of existing studies indicates a lack of scholarly attention to HOTS in gifted education in Taiwan in the past two decades. On the other hand, the effect sizes, ranged from 0.26 to 2.01, with a mean of 0.78 and standard deviation of 0.39, showed moderately large effect sizes for these interventions, which can be interpreted as evidence for general effectiveness. Subgroup analyses indicated that intervention effects did not vary significantly by grade level, type of program, intervention dosage, and type of dissemination. However, a statistically significant difference was found between the effect sizes in different types of instructional design (i.e. stand-alone HOTS unit vs. integrated HOTS unit). Implications are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 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 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".