Gamification in L2 teaching and learning: Linguistic risk-taking at play
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Gamification is increasingly popular in second language acquisition research and has been correlated with higher motivation and engagement. The use of gameplay elements in non-game environments has been shown to be beneficial; however, research on gamification and taking linguistic risks is scant. A linguistic risk is an authentic communicative act that learners take in their second language and that can be considered “risky” due to factors such as making mistakes, etc. In this article, a Linguistic Risk-Taking Initiative (LRTI) implemented at the bilingual campus of the University of Ottawa was analyzed based on a gameinformed framework. An analytical tool drawing on existing research in the field was developed to evaluate the initiative. Based on the analysis, the LRTI passport booklet and digital app, which are central to the initiative, were found mostly aligned with gamification parameters but further improvements of the design of the initiative are needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it