Parliamo Italiano: Drama and Italian Language Acquisition among University Students
Bibliographic record
Abstract
As communities across Canada are becoming increasingly diverse and multilingual there is a growing need for progressive approaches to language acquisition. Language learners often experience immense feelings of shame and foreign language anxiety which presents challenges within the learning process. (Bordreault 2010, Sağlamel and Kayaoğlu 2013, and Jordan 2015) Drama has proved itself as a medium with which participants can express themselves in a manner that is not accessible otherwise and therefore, its potential in language-learning environments is extremely promising. (Brown 2008, Dervishai 2009, Ntelioglou 2011, and Stinson and Winston 2015) The question that we are exploring is: How does drama impact language learners’ abilities and confidence in speaking and understanding a foreign language? To answer this question, in the month of March, we will facilitate four 1-hour workshops over the course of one week with first year Italian language students at the University of Windsor. Using critical drama practices learned from the Drama in Education & Community program at the university, we will lead participants in drama activities that will be facilitated and experienced solely in Italian. Over the course of the study, we will be using reflective praxis, observation, and questionnaire research methodologies to measure potential changes in the participant’s abilities and attitudes towards speaking a foreign language. We hypothesize that the subjects of this study will show increased confidence and ability when interacting with the Italian language. We hope that our findings will benefit the growing body of research surrounding language acquisition and inform future practices in the classroom as the student body continues to grow into a diverse and multilingual community.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".