Interchangeable Positions in Interaction Sequences in Science Classrooms
Bibliographic record
Abstract
Triadic dialogue, the Initiation, Response, Evaluation sequence typical of teacher /student interactions in classrooms, has long been identified as a barrier to students’ access to learning, including science learning. A large body of research on the subject has over the years led to projects and policies aimed at increasing opportunities for students to learn through interactive dialogue in classrooms. However, the triadic dialogue pattern continues to dominate, even when teachers intend changing this. Prior quantitative research on the subject has focused on identifying independent variables such as style of teacher questioning that have an impact, while qualitative researchers have worked to interpret the use of dialogue within the whole context of work in the classroom. A recent paper offers an alternative way to view the triadic dialogue pattern and its origin; the triadic dialogue pattern is an irreducible social phenomenon that arises in a particular situation regardless of the identity of the players who inhabit the roles in the turn-taking sequence (Roth & Gardner, 2012). According to this perspective, alternative patterns of dialogue would exist which are alternative irreducible social phenomena that arise in association with different situations. The aim of this paper is to examine as precisely as possible, the characteristics of dialogue patterns in a seventh-eighth grade classroom during science inquiry, and the precise situations from which these dialogue patterns emerge, regardless of the staffing (teacher or students) in the turn-taking sequence. Three different patterns were identified each predominating in a particular situation. This fine-grained analysis could offer valuable insights into ways to support teachers working to alter the kinds of dialogue patterns that arise in their classrooms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".