Psychosocial Classroom Environment and Academic Efficacy in Canadian High School Mathematics Classes
Bibliographic record
Abstract
Psychosocial Classroom Environment and Academic Efficacy in Canadian High School Mathematics ClassesDuring the past three decades, independent research has been conducted in the fields of classroom psychosocial environment and academic self-efficacy.Both classroom environment and academic efficacy have been associated with cognitive and affective student outcomes (Bandura, 1997; Fraser, 1998a).However, as noted by Lorsbach and Jinks (1999), no research has investigated the possible link between psychosocial learning environments and student academic selfefficacy.This research note reports the results of a preliminary Canadian study of students' perceptions of classroom environment and academic efficacy that serves as a pilot for a wider cross-national investigation of the same issue.Whereas classroom environment research focuses on the atmosphere, tone, or ambience of classrooms, usually from the students' perspective, academic efficacy research draws attention to the importance of fostering self-belief and self-regulatory capabilities in students (Pajares & Kranzler, 1995;Zimmerman, 1995).Although not explicitly recognized by efficacy theorists, some of these efficacy sources can be attributed hypothetically to the psychosocial learning environment that students experience in their schools and classrooms.It is plausible that learning environment contributes to academic efficacy.The present study makes two distinctive contributions to the field of learning environments.It was the first study to investigate the relationship between classroom environment and academic efficacy with a sample of Canadian high school mathematics students.In addition, by using scales from two well-established classroom environment instruments, it was possible to establish unique and joint contributions of each instrument in explaining academic efficacy. Research Design and ContextThe sample consisted of 951 (490 male, 461 female) students drawn from grade 8 and grade 10 classes in four Canadian high schools.Researchers in Australia and Asia have recently developed a classroom environment instrument called the What Is Happening in This Classroom questionnaire (WIHIC, Aldridge & Fraser, 2000; Fraser, 1998b).Although the WIHIC is comprehensive, it is not
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".