The Role of Gender in the Use of Metacognitive Awareness Reading Strategies among Biology Students
Bibliographic record
Abstract
Metacognitive Awareness Reading Strategies used by students while reading academic material is one of thefactors that lead to students’ future academic achievement. This study aims to determine the association betweengender and gender differences in the perceived use of Metacognitive Awareness Reading Strategies (Global,Problem-Solving & Support Reading strategies) among Biology students in a Matriculation College situated inState of Kedah, Malaysia. In this study, 318 Matriculation College students participated, in which 97 malestudents and 221 female students studied Biology as one of the subjects. They rated their own perceived uselevel of Metacognitive Awareness Reading Strategies using Metacognitive Awareness of Reading StrategiesInventory (MARSI) adapted from Mokhtari and Reichard (2002). The findings show that female students useMetacognitive Awareness Reading Strategies more frequently compared to male students while readingacademic materials. The findings show that students apply problem-solving strategies the most compared to theother metacognitive reading strategies, while the least used strategy is the global reading strategy. However,there are no significant difference between males and females for both these strategies. In comparison, male andfemale students differ in the application of Support Reading Strategies, where more females use the strategiescompared to males. Students themselves should learn Metacognitive Awareness Reading Strategies and applythem in their Biology reading. Global reading strategies, too, should be given more attention as this is the leastused strategy. A more balanced use of all the metacognitive strategies would help students to improve their levelof achievement as each strategy has its own strengths. Future research should investigate the ways to nurturemetacognitive skills in reading as one of the strategies to improve reading comprehension and futureperformance in Biology.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".