Enhancing Critical Reading Through Metacognitive Scaffolding in Flipped-Classroom
Bibliographic record
Abstract
Critical reading is paramount for students to comprehend texts efficiently during and beyond their academic studies. Searching for and filtering information is crucial in distinguishing between important and unimportant content. Despite its significance, students often lack proper instruction in critical reading, highlighting a need for effective learning models. The Metacognitive, Scaffolding in Flipped Classroom (Ms-Flics) model addresses this gap by combining metacognitive reading and scaffolding strategies in a flipped classroom. This study evaluates the model’s efficacy in enhancing students’ critical reading skills. The research employs quantitative methods, conducted with grade 9 students in Surakarta, Indonesia, comparing pre- and post-treatment test results. Using cluster random sampling, two classes of 65 students were administered tests before and after the intervention. Analysis using paired T-tests revealed a significant improvement post-treatment. The findings underscore the effectiveness of the Ms-Flics model in enhancing critical reading skills among grade 9 students. The study contributes theoretically by proposing a novel learning model that integrates metacognitive reading, scaffolding strategies, and flipped classroom approaches to improve critical reading skills.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| 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 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".