STEAM Camp: Teaching Middle School Students Mathematics, Science and Coding through Digital Designs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this study, we explore how to teach mathematics, science and coding through digital tools, design projects, and global competencies. We explore the question: How do upper elementary school children develop an understanding of mathematics and science coupled with coding through digital design? The theoretical framework adopted for this study is Kafai and Burke’s (2014) definition of Computational Participation: a shift from code to actual applications; a shift from tools to communities; a shift from starting from scratch to remixing; and a shift from screens to tangibles. We conducted a qualitative case study interlinked with Design-Based Research. Both STEAM camps were an outreach program for students in grades 4-8 in Ontario, Canada. The two camps were designed and facilitated by a research team from the Faculty of Education. The research team developed the curriculum through an iterative process (design-test-revise-repeat).  There were 43 students registered in the STEAM camps, and 34 of them participated in the study. We collected observation, interviews, audio/video recordings, and survey data as well as pictures of the students’ work. Our main findings were that students were provided with opportunities to: 1) develop a deeper understanding of curricular concepts; 2) engage more with the digital tools when they were remixing, improving, and reimaging the design; and 3) apply their knowledge to global competencies. The findings of this research have implications for improvements in researching, designing, and implementing design projects as part of a pedagogical approach to teaching mathematics and science, coupled with coding, in an interdisciplinary context.
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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 | 0.020 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it