Public Speaking in EFL Postgraduate Courses in Italy: A Case Study with Students of Political Science, University of Genoa
Bibliographic record
Abstract
The teaching of soft skills in EFL postgraduate courses is increasingly part of the Italian university curricula, albeit with some delay compared to foreign universities. Postgraduate English language courses need to focus on the use of language in foreseeable situations by creating opportunities to use the language in public contexts. Meetings, presentations, debates are the activities that young people will increasingly be called upon to engage in. Rather than solely on theoretical knowledge learned previously, these activities develop the practical use of language, in front of an audience, with a structured discourse and with some emphasis on the non-verbal elements of communication. Although these aspects may appear daunting to students, more often than not, they have been able to overcome their anxiety, not only in relation to the embarrassment of speaking a foreign language in public, but even to the mere act of speaking in public, which represents an obstacle in itself. In this study a case of Italian postgraduate students of Political Science was carried out and analysed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 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".