Nonnative English-Speaking Students’ Lived Learning Experiences With MOOCs in a Regular College Classroom
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="3">The goal of this study was to gain in-depth understanding about nonnative English-speaking students’ lived experiences with massive open online courses (MOOCs) in a regular college classroom. Phenomenological methodology was used to examine those experiences in 24 Korean college students. Individual interviews, an open-ended online survey, observation notes, online weekly journal entries, and social media constituted the data sources. Findings show that students’ lived experiences included (a) wonder and interest, (b) novel learning and teaching practices, (c) preference for video style, (d) learning strategies, (e) motivation to learn, and (f) need for face-to-face interaction. Implications for integrating a MOOC into a regular college course are also presented.</p>
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.002 |
| 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