Experiencing the needs and challenges of ELLs: Improving knowledge and efficacy of pre-service teachers through the use of a language immersion simulation
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
Pre-service teachers need to understand how to support ELLs in their future classrooms, yet evidence suggests that pre-service ELL training may not be as effective as we need it to be. One promising strategy for increasing pre-service teachers’ efficacy and knowledge around teaching ELLs is through a shock-and-show simulation. This strategy incorporates a Swedish-language immersion experience that simulates what it may like to be an ELL and the strategies that can help support these students. There were two phases: a lesson with limited scaffolding (shock) and an extensively scaffolded lesson (show). Our participants included 87 pre-service teachers who filled out pre- and post-surveys, including closed- and open-ended questions. t-Tests were used to determine whether differences in the scores from the two surveys were significant. We analyzed qualitative data using an interpretive approach to the development of codes, categories, and themes, which we triangulated with descriptive statistics to describe the frequency of the emergent codes. Our findings suggest that shock-and-show experiences may benefit pre-service teachers’ knowledge and efficacy around ELL instruction. We theorize that the emotional component of the experience connected to the cognitive aspects may help foster greater learning among pre-service teachers concerning the difficulties and needs of ELLs.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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