Use of Blended Learning for Effective Implementation of English-Medium Instruction in a Non-English Higher Education Context
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
<p class="apa">Although researchers agree with the strengths of an English-medium instruction (EMI) in addressing internationalization of a non-English higher education (HE) context, its implementation in classrooms has been widely criticized, mostly because of ineffective delivery of course content and a lack of evidence of English improvement. Grounded upon a critical review of the current state of internationalization of Korean HE and the subsequent examination of supplementary interview data from 15 college students who have taken EMI courses, this study proposes a model which integrates critical factors of EMI into one framework. This model aims at guiding the EMI policy from initiation to implementation. A major feature of this model is blended learning as a strategy to address the shortcomings of current EMI in this context and to facilitate the allocation of diverse online materials to scaffold EMI instruction. The benefits of the approach are presented from the perspectives both of policy-makers and of classroom participants.</p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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 it