Task engagement and comprehensibility in interaction
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
Abstract This exploratory study examined the relationship between second language (L2) English speakers’ comprehensibility and their interactional behaviors as they engaged in a conversation with fellow L2 speakers. Thirty-six pairs of L2 English university students completed a 10-minute academic discussion task and subsequently rated each other’s comprehensibility. Transcripts of their conversation were coded for eight measures of task engagement, including cognitive/behavioral engagement (idea units, language-related episodes), social engagement (encouragement, responsiveness, task and time management, backchanneling, nodding), and emotional engagement (positive affect). Speakers who showed more encouragement and nodding were perceived as easier to understand, whereas those who produced more frequent language-focused episodes and demonstrated more responsiveness were rated as harder to understand. These findings provide initial evidence for an association between L2 speakers’ interactional behaviors and peer-ratings of comprehensibility, highlighting L2 comprehensibility as a multifaceted and interaction-driven construct.
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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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