Plurilingualism in Practice: A Narrative of the Backgrounds, Beliefs, and Experiences of Second Language Teachers Integrating Language and Cultural Diversity in North American Classrooms
Bibliographic record
Abstract
This qualitative, multiple-narrative case study examined the plurilingual practices oftwelve second language (L2) teachers across classrooms in Canada, Mexico, and the United States. The research focused on the participants’ backgrounds, beliefs, and experiences to understand how these aspects influenced teachers to embrace such ideological and pedagogical change and include language and cultural diversity as part of their teaching practices, further examining how the overall experience implementing a plurilingual approach in the classroom relates to their prior monolingual practices as both teachers, learners, and users of languages, and uncovering existing paradoxes between these L2 teachers’ beliefs and their experiences with plurilingual approaches in the classroom. Data include three semi-structured, in-depth interviews with each participant, classroom observations, teaching artifacts, and curriculum documents. The interviews served as the primary data point for the analysis, while the additional collected data was mainly used to sustain and ii contrast what was reported in the interviews. The adopted theoretical framework combined elements of sociocultural theory (Lantolf, 2000; Vygotsky, 1978) and complex dynamic systems theory (Larsen-Freeman, 1997, 2011; Larsen-Freeman & Cameron, 2008), and it provided the lens to the understanding of plurilingualism and the analysis of the nature of these L2 teachers’ practices and their different features, in particular their backgrounds, beliefs, and experiences. The participants’ distinguishing features encompass a diversity of backgrounds, varied language learning and teaching experiences, and distinctive contextual perspectives reported in the study, shedding light on how they view diversity as a resource and a natural part of the language learning process. The showcased participating teachers are engaged, reflexive, innovative adopters, and they may serve as models to help create favorable opportunities for lasting transformative educational approaches and point to a more grassroots, bottom-up reform in Second Language Educ. Findings further suggest that while teaching experience and agency are key factors that helped these teachers align their practices more consistently with their beliefs, more professional development and resources are needed to support the broader adoption of plurilingual approaches and overcome the potential barriers to the inclusion of linguistic and cultural diversity in the L2 classroom.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.024 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| 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".