The correlates of flow in the L2 classroom: Linking basic L2 task features to learner flow experiences
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
Abstract Flow is an intrinsic motivational state associated with full task engagement, positive affect, and enhanced performance. While research has examined how different language tasks interact with flow experiences, no study has examined learner flow experiences in a wide range of tasks using an experience sampling method to determine how universal basic task features (e.g., modality, participant structure, information distribution, and targeted skills) interact with flow. The present study aims to respond to this gap in the research. Participants were 13 teachers and 327 students from 18 intact French L2 classes in a Canadian postsecondary school. Teachers selected and implemented an average of six tasks from their personal repertoires at random moments throughout the semester. Immediately following each task, learners anonymously completed a flow experience questionnaire ( N = 1408; α = 0.91), and teachers a task description questionnaire containing 17 basic task features ( N = 81). Statistical analyses show that 10 of the 17 variables significantly interacted with learners’ flow experiences. The results not only validate a frequently used flow measurement and establish norms for future research but also outline a framework language teachers can use to evaluate and modify practices to improve learners’ subjective classroom experience.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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