Evaluating the Efficacy and Impacts of Remote Pair Programming for Introductory Computer Science Students
Bibliographic record
Abstract
With the increase in online learning, instructors are looking for novel ways of supporting student learning and getting students to collaborate in online environments. Pair programming allows students to brainstorm and problem-solve in teams and has been found to help with improving code design, attitudes toward computer science, productivity, and performance. However, past work has focused on face-to-face, in-person collaboration, and it is unclear whether these benefits will translate to an online context. This work replicates several studies evaluating the effects and benefits of in-person pair programming in an online environment. In an introduction to programming course, students participated in weekly online sessions where they were asked to solve a set of exercises in pairs or individually. We measure task performance and student opinions on the activities and perceptions of remote pair programming. Our study found that remote pair programming had little to no impact on the time taken, promising but not statistically significant impacts on code correctness, and statistically significant impacts on students’ perceptions of both their own experience and the efficiency and efficacy of pair programming. Our findings show that some, but not all, of the benefits of pair programming can be replicated in an online context.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".