Impacts of Learning Management System on Learner Autonomy in EFL Learning
Bibliographic record
Abstract
The integration of interactive online communication into different educational settings has been widely researched since the emergence of web 2.0 technology. It has been particularly identified to give EFL students more opportunities to express ideas, enhance their engagement in learning activities and promote their confidence during virtual interactions. These benefits coincide with attributes of a learning environment that can foster learner autonomy. Therefore, this paper reported an investigation on the impacts of the employment of a Learning Management System (LMS) in an EFL course. Data extracted from individual interviews with four undergraduate students in a Vietnamese university was analyzed to illustrate possible effects of LMS in students’ ability to initiate, monitor and evaluate their learning process. The presentation went to with a discussion on the cyclic relationship among these three capabilities and students’ perspective on socializing and academic activities. It concluded with implications for EFL teaching practices with the adoption of LMS and put forward suggestions for further research.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".