Using digital technologies with immigrant plurilingual language learners: A research synthesis
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
With massive migratory flows observed around the world, schools are experiencing an unprecedented increase in the enrolment of children who speak multiple languages. Educators are called upon to facilitate immigrant plurilingual students’ inclusion and development of functional competencies in the target language(s), often using digital technologies (DTs) to promote language learning and plurilingual teaching practices. This research synthesis explores the research trends, methods, and findings from studies focused on the use of DTs with immigrant plurilingual language learners. The results highlight that DTs are used in heterogeneous contexts to support the development of immigrant plurilingual students’ overall language proficiency, (multi)literacies, engagement, as well as identity development. However, teachers and learners may require additional support to use DTs and plurilingual practices to their full potential. These concerns point to the need for ongoing professional learning and contextualised supports for educators at the intersection of these areas.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it