The Effect of Shifting to Student-Centered Learning: Implementing Student-Centered Reading
Bibliographic record
Abstract
The "traditional" forms of teaching are extremely familiar to students, who frequently favor learning that is focused on receiving instruction and reproducing knowledge. This study aims to examine the effects of these traditional forms of teaching practices, such as teacher-centered learning on EFL learners' engagement in implementing student-centered reading. The study uses an observation checklist and interview as tools for collecting data from twelve EFL elementary reading classes and their teachers. The statistically analyzed data has shown that whenever reading activities demand deeper, personalized discussion, the learners engage less and rely more on their teachers for assistance. When interacting with non-communicative tasks, EFL students take full ownership of their own learning; however, when interacting with communicative tasks, they require teacher prompting. Furthermore, learners' collaboration with each other on achieving reading tasks was, in most cases, either done to some extent or in a very limited range. Thus, EFL learners maintained dependency in carrying out reading activities through their preference for non-communicative tasks over communicative tasks and their collaboration upon reading activities in a limited range. Based on this, the design of communicative reading activities demands prompting, and learners need to be encouraged and guided for engagement. Students may be more receptive and interested if they are more informed about the advantages and effectiveness of student-centered learning. In spite of the effectiveness of student-centered learning in many contexts, it needs to be redefined to fit within the culture and specific EFL learning and teaching contexts.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".