Extending the L2 Motivational Self System to the Global EAL Classroom
Bibliographic record
Abstract
A growing interest has been witnessed in analysing second language (L2) learner motivation in English as an Additional Language (EAL) instruction around the world. Despite extensive scholarship in this area, revisiting learner motivation is warranted due to some unprecedented developments that impact EAL teaching, such as the prevalence of World Englishes, ethno-linguistically diverse classrooms, and the social as well as situated nature of teaching and learning. The aim of this article is to expand on Dörnyei’s L2 Motivational Self System framework to inform classroom instruction in globally growing EAL teaching. The expansion entails three sociocultural dimensions in the EAL classroom: diversity, inclusivity, and entitlement. This expanded framework can potentially equip EAL educators to better address the demands of a rapidly changing world. Moreover, the framework can also serve as an impetus for learner success in EAL classrooms and the recognition of their individual characteristics, such as self-regulation, autonomy, and agency, which are highly emphasized in postmodern L2 pedagogy.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".