Using an Evidence-Centered Design Approach to Examine the Alignment of Computer Science Curricula with Standards
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 the early stages of K-12 Computer Science (CS) curriculum development, standards were not yet established, and the primary objective, especially in younger grades, was to spark students' interest in CS.While this remains a vital goal, the development of the CS standards underscores the importance of standards-aligned curriculum, ensuring equitable, content rich CS education for all students.We show that standards alignment is most useful when it includes details about which aspects of the standards a curriculum aligns with.This paper describes our process of decomposing five middle school CS standards into granular learning targets using an evidence-centered design approach and mapping the learning targets onto individual lessons from one widely popular middle school CS curriculum.We discuss the potential implications of this work on curriculum design, curriculum selection, and teacher professional learning.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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