Exploring College Students' EFL Learning Engagement in the Context of Blended Learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Engagement is a leading indicator of learning performance and outcomes. Blended learning in College English courses in China has been prevalent for years, yet it is still necessary to explore and enhance student interest, motivation, and outcomes through further research. Given the critical impact of academic engagement on student success, investigating how students engage in blended learning activities is important. This research presented English language learners' engagement in blended learning behaviorally, cognitively, and emotionally between online learning and in-person delivery modalities. It aimed to improve the instructional pedagogies to engage English language learners not only behaviorally, cognitively, but emotionally as well. The research aimed to help teachers gain a comprehensive understanding that will enable them to adjust current methods and identify more effective delivery strategies for improved outcomes. Learners' Engagement in Foreign Language Classroom, developed by Hiver et al. (2020), is taken in this research. In total of 223 EFL students in a Chinese university participated in this survey. The study has some main findings: in the EFL blended learning, online learning shows lower cognitive engagement but higher emotional engagement than in-person learning; blended EFL Learning engagement wasn't affected by gender or degree program levels; there are significant differences between online and in-person learning on the behavioral and cognitive engagement. According to the results, some pedagogical implications were discussed.
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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 | 0.024 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 it