Affordances of Multilingual and Multimodal Literacy Engagements of Immigrant High School Students: A Scoping Review
Bibliographic record
Abstract
This article presents a scoping review of literacy research that employs multilingual and multimodal literacy narratives and discussions as tools for enabling immigrant youth to explore their intersectional identities and experiences of inequality. It encourages a re-examination of emerging educational/societal issues, incorporating these interventions as a catalyst for discussion. Utilizing a descriptive-analytic approach for data extraction, this scoping review has mapped out prevailing trends in the literature, research methodologies employed, and the types and objectives of multilingual and multimodal literacy interventions. The findings underscore a growing trend over the past decade in adopting multilingual and multimodal literacy interventions with immigrant youth, often employing collaborative research approaches such as participatory action research. The most frequently utilized multilingual and multimodal texts in such studies include digital storytelling materials (comprising images and video), spoken word poetry, photographs, and bilingual books. These interventions are typically designed to (a) encourage youth to express their knowledge, experiences, and identities; (b) examine and address educational and societal issues and opportunities; and (c) challenge dominant ideologies, practices, and discourses through the voices of immigrant youth. The review discusses the transformative possibilities for immigrant youth and encourages rethinking the language learning, literacy, and curriculum process. The data advocates for eclectic approaches and interventions to help newcomer youth understand their lived experiences and societal issues and encourages educators to respond in kind.
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.
How this classification was reachedexpand
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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".