Using a Complexity Approach to Study the Interpersonal Dynamics in Teacher-Student Interactions: A Case Study of Two Teachers
Bibliographic record
Abstract
In the present study, complex dynamic systems theory and interpersonal theory are combined to describe the teacher-student interactions of two teachers with different interpersonal styles. The aim was to show and explain the added value of looking at different steps in the analysis of behavioral time-series data (i.e., observations of teacher and student behaviors) that are described by Warner (1998): (1) the general level and overall coordination, (2) the presence of linear, quadratic and cubic trends in behavior, (3) the coherence and phase in cyclical trends that are superimposed on the linear, quadratic and cubic trends, and (4) the residual fluctuations, when studying the fit between teacher and student interpersonal behavior. Interactional fit is conceptualized, and described in each step of the time-series analysis, using the principle of complementarity (e.g., Kiesler, 1996). Results showed that the teacher-student interactions of the teacher with the most desirable interpersonal style largely followed the complementarity principle, whereas the interactions of the teacher with the less desirable interpersonal style did not. These results are discussed in light of the hypotheses and limitations of the study.
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How this classification was reachedexpand
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".