Communication in Training Future EFL Teachers: Simulation and Roleplay in the English Classroom
Bibliographic record
Abstract
The issue under investigation is topical and significant. Being a communicative language acquisition method, simulation and roleplays develop future teachers' language competencies and pedagogical competence, playing a unique role in forming teacher-student, teacher-parent communication patterns. The article aims at studying the place simulation/roleplay have in this process and its specific features. The authors describe how roleplays and simulations are introduced into the English classroom, examples of supplying study books with roleplay tasks. The methods applied to explore the problem were observation and questionnaire administered to the students at the end of the course. Their analysis has permitted the authors to arrive at several conclusions. The most remarkable conclusion is that introducing simulation/roleplay into the study process significantly influences students' communication skills and academic performance, forming their pedagogic competences and communication patterns. Furthermore, the findings revealed that simulation/roleplay in training foreign language teachers should be well-planned and organized; the author gives some advice concerning it. The study results could be highly substantial for teachers of universities preparing future foreign language teachers.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".