Engaging Middle School Students through STEAM Project-Based Learning
Why this work is in the frame
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Bibliographic record
Abstract
This dissertation explores the influence of a combined Science, Technology, Engineering, Arts, and Mathematics education, and project-based learning (STEAM PBL) approach on students’ cognitive and emotional engagement. In an educational landscape marked by the growing popularity of both STEAM education and PBL in K-12 settings, this study aims to understand how STEAM PBL can be harnessed to address declining rates of student engagement. The study is centred around a Grade 7 urban planning project set in a K-8 Modern Orthodox Jewish Day School in Toronto, Canada. The research adopts a qualitative exploratory case-study model of inquiry, encompassing reflective group conversations and observational notes for data collection. Thematic analysis revealed four indicators of cognitive and emotional engagement: (1) students' demonstrated effort, (2) personal connections and the perceived value of learning, (3) the enjoyment and sense of fun in the learning process, and (4) situational interest in learning. Furthermore, it identified four key components of STEAM PBL that fostered student engagement: (1) the development and utilization of soft skills, (2) interactive and hands-on learning, (3) the integration of relevant real-world learning, and (4) the promotion of student choice and agency. By exploring these components and indicators, this dissertation offers valuable insights into the potential of STEAM PBL as a pedagogy to improve student engagement in middle school settings. The findings contribute to the ongoing discourse on innovative pedagogical approaches and student engagement. This research holds implications for educators who are interested in integrating STEAM PBL into their teaching practices, and enriches the expanding body of knowledge on student engagement.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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