Teaching and Learning in an Integrated Curriculum Setting: A Case Study of Classroom Practices
Bibliographic record
Abstract
Curriculum integration, while a commonly used educational term, remains a challenging concept to define and examine both in research and in classroom practice. Numerous types and definitions of curriculum integration exist in educational research, while, in comparison, teachers tend to focus on curriculum integration simply as a mixing of subject areas. To better understand curriculum integration in practice, this thesis details a case study that examines both teacher and student perspectives regarding a grade nine integrated unit on energy. Set in a public secondary school in Ontario, Canada, I comprehensively describe and analyze teacher understandings of, and challenges with, the implementation of an integrated unit, while also examining student perspectives and academic learning. My participants consisted of two high school teachers, a geography teacher and a science teacher, and their twenty-three students. Using data gathered from interviews before, during, and after the implementation of a 16-lesson unit, as well as observations throughout, I completed a case description and thematic analysis. My results illustrate the importance of examining why teachers choose to implement an integrated unit and the planning and scheduling challenges that exist. In addition, while the students in this study were academically successful, clarification is needed regarding whether student success can be linked to the integration of these two subjects or the types of activities these two teachers utilized.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".