Teacher content-language awareness in Canadian immersion teacher education programs
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
Research demonstrates that content, language, and literacy integration is challenging for teachers working in content-based instructional contexts such as immersion and Content and Language Integrated Learning. Although teacher preparation programs for content-based instruction contexts exist, it is unclear whether and how they help pre-/in-service teachers acquire the knowledge and awareness they need to be effective. In recent years, scholars have lamented that research has ignored immersion teacher education and that teachers and teacher educators do not yet fully understand the knowledge base that immersion teachers require. This article reports on an exploratory study that included an examination of web-based program descriptions, course outlines, focus groups with course instructors (N = 11), and teacher candidates (N = 29) to compare immersion teacher education programs at Canadian universities with the goal of better understanding how they develop learners’ Teacher Content-Language Awareness (TCLA) and what challenges they face. Findings include the urgent need to establish general guidelines for content-based teacher education programs as well as the need to include criticality as a fundamental element to all TCLA domains.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.007 | 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