Using Activity Theory to Explain Differences in Patterns of Dyadic Interactions in an ESL Class
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
Variations in how L2 learners work in pairs/groups have been noted by a number of researchers. However, explanations for such variations are often made in terms of differences in L2 proficiency or culture. What has often been overlooked is the participants' orientation to an activity and, in particular, their motives and goals. The importance of human motives and goals in explaining human behaviour is encapsulated in activity theory (Leont'ev, 1981). It is this theoretical perspective that guided the study reported in this article. The study attempted to explain variations found in the ways students interacted in pairs in a university ESL class. The data consist of interviews with eight participants who formed four case study pairs, each case exemplifying a distinct pattern of dyadic interaction. The findings suggest that patterns of dyadic interaction can be traced to the nature of the participants' goals and to whether or not members of the dyad share these goals.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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