A Study on Metacognitive Strategy Use in Listening Comprehension by Vocational College Students
Bibliographic record
Abstract
Metacognitive strategies concerning general skills, through which learners manage, direct, regulate and guide their learning. For several decades, researchers have recognized the importance of Metacognitive strategy use for successful English listening comprehension. Most of the previous studies of metacognitive strategies use in China have been carried out among undergraduates, but few focus on that of vocational college students. Therefore, it is necessary to carry out investigation into metacognitive strategies use in English listening comprehension among vocational college students so as to give vocational college English teachers pedagogical implications on how to train their students and facilitate their teaching. The aim of the present study is to make a tentative investigation into the metacognitive strategies use in the listening comprehension among vocational college students. The subjects in the present study consist of one hundred and thirty nine vocational college students in the Jiangxi Blue Sky College. And three instruments were involved in the present study. They are questionnaire, listening comprehension test and interviews. The present research has yielded the following findings: 1. Based upon the results, the frequency of students’ metacognitive strategy use frequency is relatively low, and there is a rather large discrepancy among students ' use of metacognitive strategies in listening. 2. The analysis shows that females employ metacognitive strategies more often than males’ students. There is significant difference in the use of planning strategies, monitoring strategies, self-evaluation strategies and self-regulation strategies, and the most significant difference is shown in monitoring strategies.3. From the results, it is found that the higher score the students get, the more frequently they use the strategies. Especially to the monitoring strategies, there is significant difference between the high score and low score students.4. With regard to the relationship between the employment of metacognitive listening strategies and listening comprehension ability, analysis shows that there is a positive relationship between metacognitive strategies and listening comprehension ability. The more frequently they apply the metacognitive listening strategies, the stronger their listening comprehension ability will be.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".