Helping Preservice Content-Area Teachers Relate to English Language Learners: An Investigation of Attitudes and Beliefs
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
In the United States and Canada, as in many other countries, it has become common for teachers not specifically trained in English as a second language (ESL) to have immigrant and minority language students in their classrooms. These students, who are generally learning English along with the culture of their new countries, present many challenges for their teachers, who are often not appropriately trained to meet their needs. Often teachers of mathematics, science, and other content-area courses feel less than prepared for these students and lack the skills needed to accommodate instruction to their unique needs. In addition, these same teachers often harbor attitudes and beliefs about immigrant students that are not conducive to the development of a safe learning environment and are difficult to alter. This article describes how a community-based service-learning project (CBSL) was used to begin to investigate the attitudes and beliefs of preservice content-area teachers toward English language learners (ELLs). In this study many participants exhibited some level of change in their attitudes about working with 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 | 0.003 | 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 | 0.001 | 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