Mobile-Learning-Based Exploration of English Reading Teaching Reform for Non-English Majors in China
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
Under the development of the information age, traditional Chinese teaching model of college English reading courses can no longer meet the needs of the times, and needs to be reformed urgently. From the perspective of mobile learning, this paper tries to combine modern educational technology with classroom teaching by using an online English reading learning platform, and explores the construction of a new teaching model. This model tries to form effective teaching supervision and assessment through the combination of online and offline teaching model, in-class and after-class teaching model, as well as real-time and dynamic big data monitoring, which breaks the closed classroom teaching environment, enriches the teaching content and means, complements and improves the teaching method of traditional Chinese college English reading courses. The aim of this study is to enrich teaching content, reform traditional teaching model and construct a new teaching model for English reading courses through the teaching practice of the online English reading platform, and further optimize the use of the platform by collecting and analyzing effective assessment and feedback, so as to make full use of the online reading platform and improve the mobile reading teaching model. 
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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 | 0.002 | 0.009 |
| 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 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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