English Second Language Students in a Grade 11 Biology Class: Relationships between Language and Learning.
Bibliographic record
Abstract
For English-as-a-Second-Language (ESL) students learning academic content is complex. The purpose of this study is to explore and gain an understanding of ESL students' participation and learning in grade 11 biology classes in a secondary school in Vancouver, British Columbia. The paper reports on one aspect of the study--the mediational role of language in learning biology terms and concepts. The main question guiding this aspect of the study was: what are the relationships between language and the ESL students' learning of biology terms and concepts? This question was explored by focusing on the following: teaching, how the teacher explains terms and concepts; and learning, how students' interpret terms and concepts in the teacher's oral explanations and written questions. The significance of this study lies in the provision of insights into particular language and content-related issues associated with both the learning and teaching of science in a mainstream secondary science classroom. Results suggest the following: (1) talking about language is integral to biology teaching and learning; (2) teaching involves more than showing and describing concepts in isolation; (3) English words in science worksheets often elicit functional explanations that support the construction of discourses of reasoning; and (4) new labels in second language may refer to a different set of features associated with the concept. (Contains 34 references, 4 figures, and 1 table.) (KFT) Reproductions supplied by EDRS are the best that can be made from the original document. Kamini Jaipal UBC Paper presented at AERA, Seattle, 2001 04/08/01 ENGLISH SECOND LANGUAGE STUDENTS IN A GRADE 11 BIOLOGY CLASS: RELATIONSHIPS BETWEEN LANGUAGE AND LEARNING Introduction In a study on the status of ESL in British Columbia schools, Naylor (1994) reports that teachers are unsure about how to teach ESL students in mainstream classes. Krug lySmolska (1995) also reports that the teachers in her study seemed ill-equipped to deal with students experiencing language difficulties in their classrooms (p. 54). For ESL students, learning academic content is complex. ESL students need to learn the English language and to use that language for learning. Their success as learners depends both on the acquisition of English language skills and academic content (Mohan, 1986). There is strong evidence that ESL students need from 4 to 6 years to acquire the level of English language proficiency required to participate fully in classroom settings (Cummins, 1981; Wong-Filmore, 1986). These research findings suggest that there is a need to examine ESL students' learning in mainstream academic classes in an effort to provide support for both ESL students and teachers.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.003 | 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 teacher head, 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".