LA TOMA DE CONCIENCIA SOBRE EL APRENDIZ DE LENGUA DE HERENCIA EN CLASES DE ESPAÑOL COMO SEGUNDA LENGUA: CREENCIAS Y ACTITUDES DEL PROFESOR
Bibliographic record
Abstract
With the growing number of English language learners throughout the United States enrolled in the foreign language class representing their heritage language, it is increasingly important for foreign language methodology courses to address how to plan for, instruct, and assess the diverse needs of these students in the K-12 foreign language classroom. Their needs as heritage language learners are different than those of second language learners. Therefore, in order to teach these language learners, teachers should possess specific competencies, not typically evident in foreign language teaching methodology courses. The present study is a preliminary effort to integrate a module on teaching heritage language learners into a foreign language teaching methodology course and to evaluate the development of teacher candidates’ declarative knowledge, beliefs, and conceptualizations about heritage language learners and heritage language instruction. Participants (N=30) are pre-service 9-12 Spanish teachers at two postsecondary institutions in the Eastern United States. The results demonstrate that teacher candidates move beyond conceiving heritage language learners as similar to second language learners and proceed toward perceiving them as culturally and linguistically diverse learners of Spanish, as evidenced through surveys and lesson plans.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".