Improving Mathematics Learning Through Computational Participation
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
Computational Participation (CP) expands upon Computational Thinking (CT) by incorporating themes of problem-solving, creativity, and digital collaboration and communication. In the Fall of 2021, we partnered with two school boards to facilitate Professional Learning (PL) sessions with a broad community of educators and co-facilitated learning sessions with select classroom teachers. Both PL and co-facilitation learning sessions related to curriculum expectations for mathematics and coding. Instead of teaching coding for coding’s sake, our goal was to prepare teachers to use coding to help students understand mathematics under the pedagogical framework of CP. The questions guiding our overall research were to identify ways teachers can integrate CP while teaching mathematics in a meaningful way and identify the various learning opportunities that students gain when CP is integrated. Our research indicated that CP results in learning environments supportive of collaborative learning, communication, increased student engagement, and perseverance. In addition to this, teachers experienced a positive shift in their mindset toward cross-curricular planning. One persistent challenge in infusing digital coding with mathematics in this study was the lack of 1-to-1 technology in classrooms, which could interrupt momentum and disrupt student motivation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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