In-Lab Programming Tests in a Data Structures Course in C for Non-Specialists
Why this work is in the frame
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Bibliographic record
Abstract
This paper reports on our experiences with in-lab programming tests (i.e., using a compiler and IDE) in a large undergraduate data structures course in C for non-specialists. By adding a suite of in-lab programming tests to our regular assessments (midterm, final exam, programming homework, etc.), we expected students to improve significantly in these areas: (1) programming ability as measured by final exam grades on programming-related questions, (2) confidence in programming ability, and (3) contributions/effectiveness in pair programming partnerships. Goal (1) was not met. Although Goal (2) was met, improved confidence did not translate into improved performance. Goal (3) was partially met. We present data gathered from in-lab programming test assessments, final exam programming assessments, and post-course surveys, including a two-year follow-up survey.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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