Extensive Viewing: Extra‐Curricular Language Learning Outside the Classroom Walls
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
The benefits of exposing language learners to large amounts of input through extensive reading programs continues to receive attention in English as a foreign or second language teaching situations. However, reading only provides learners with written input but exposure to aural input may be even more vital and hard to come by for learners. A potential source of aural input that can provide learners with opportunities to encounter the large amount of spoken input needed to improve their listening skills is viewing television program episodes. With appropriate guidance from teachers, learners can be pointed toward best practice in choosing and viewing television episodes leading to increased language learning opportunities and learner autonomy outside of the classroom. This entry outlines the potential benefits of viewing television, then presents a principle‐based framework for implementing an extensive viewing program. Finally, areas of research into learning through television that need further investigation are suggested.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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