Investigating Pre-service English Teachers' Identity Construction Using Multimodal Discourse Analysis
Bibliographic record
Abstract
The study of teacher identity has been booming since it was proposed in the last century, and the popularity has not subsided. Some scholars explored teacher identity from the macroscopic perspective using educational narrative and critical discourse analysis, while others explored it with micro-conversational analysis. Among the previous research, few studies focused on the process of pre-service teachers’ identity construction with multimodal discourse analysis. Adopting multimodality design framework for identity construction, this multi-case study of two student teachers examined four dimensions of teacher identity including framing, selection, foregrounding and arrangement. The results indicated a variety of differences in the types of teacher identities which two student teachers constructed. Student teacher A was more inclined to construct authoritative and knowledgeable teacher identity, while student teacher B constructed guiding and amiable teacher identity. It was found that different student teacher identities had different effects on classroom teaching. On the one hand, constructing teachers’ authority too much resulted in less teacher-student interaction and low student participation in the classroom. On the other hand, building an excessively intimate relationship between teacher and students led to poor classroom discipline.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".