“Now that I have the confidence to speak, I can talk to people”: Understanding the value and place of cocurricular and extracurricular activities hosted by university language learning centers.
Bibliographic record
Abstract
In recent years, research on informal language learning has expanded significantly (Dressman & Sadler, 2020), highlighting its role in increasing learner motivation, confidence, and real-world communicative competence (Montrul, 2019, Mihre & Fiskum, 2021, Polat & Kim, 2014, Arndt, 2019). However, very few studies (Reva, 2012; Cabrera Arias, 2022) have examined institutionally organized informal activities within university language centers that are designed to complement formal instruction. This qualitative study investigates Cocurricular and Extracurricular Activities (CECA) within two Quebec university language learning centers. Using a phenomenological approach, ecological framework, and reflective thematic analysis, the research explores students’ value perception of CECAs as well as the role that CECAs play within the programs investigated. The findings reveal that CECAs are highly valued by participants, providing a unique opportunity to enhance confidence and competence, particularly in "real-life" language use and cultural competence, and emphasizes the importance of facilitators who are credited for creating a supportive, low-pressure environment for students. Despite their recognized benefits, administrators highlight challenges such as resource limitations and lack of visibility within academic institutions. Overall, this study underscores the potential of CECAs to bridge the gap between formal classroom instruction and real-world language use
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".