Principles of Embedded Assessment in School-Based Making
Bibliographic record
Abstract
While there is growing interest among educators in bringing the maker movement into school environments, many schools struggle to closely integrate making into their existing core curriculum, mostly due to the difficulty in assessing learning in maker classrooms. Because of the unique nature of maker-centered learning as a pedagogy, conventional assessment methods often fall short. To address this issue, we conducted a study to design assessment in maker classrooms using a design-based research approach, working closely with middle school maker teachers and coaches. Applying the concept of embedded assessment that is commonly used in digital learning environments into in-person maker classrooms, we explored how assessment that captures diverse learning occur in the process of making. This paper reports on the four design principles of embedded assessment in school-based making that emerged from literature reviews as well as interviews and workshops with the partnering educators. By closely examining the contexts of maker classrooms, we discuss challenges and opportunities for assessment in maker classrooms that can help teachers approach assessment as activities that are seamlessly embedded in the classroom culture, norms, and activities that students are engaged in.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".