Undergraduate Students’ Use of Metacognitive Strategies While Reading and the Relationship Between Strategy Use and Reading Comprehension Skills
Bibliographic record
Abstract
Background: Lately in national and international reports, there has been an increasing interest on the significance of the development of reading skills. Countries are facing the problem of a decrease in reading habits (Niemann, 2016; Iyengar, 2007). Method: This study examines the perceived use of metacognitive strategies among undergraduate students during reading, which encompasses the use of metacognitive strategies before, during and after reading. The sample group comprised 236 students at Primary Education (PE) and Social Studies Teaching (SST), Language & Literature (LL) and Sociology departments during 2014–2015 academic year. The data were collected using the Metacognitive Awareness of Reading Strategies Inventory (MARSI) and reading comprehension achievement tests (informative and narrative). Results: Overall strategy use among the sample group was “high”. Whether there was a significant difference among students’ perceived use of strategies in reading based on gender, grade, faculty and department was investigated. The results indicated a significant difference based on gender and grade level. Finally, it was found that as the reading comprehension increased in narrative texts, so did the strategy use in overall scale as well as in Global Reading Strategies and Problem Solving Strategies sub-scales. Conclusion: The findings indicated gender differences in the use of reading strategies. It can be suggested that students be provided with reading strategies training that considers the gender differences in the use of metacognitive strategies in reading. In addition, based on the grade difference between freshmen and senior students, in favor of senior students and arising from including strategy use training in the curriculum, reading and learning strategies training could be provided for students during undergraduate education.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".