Date
Publisher
arXiv
Dual-submission homework, where students submit work, receive feedback and
then revise has gained attention as a way to foster reflection and discourage
reliance on online answer repositories. This study analyzes 13 years of exam
data from a computer architecture course to compare student performance under
single versus dual-submission homework conditions. Using pooled t-tests on
matched exam questions, we found that dual-submission significantly improved
outcomes in a majority of cases. The results suggest that reflective
resubmission can meaningfully enhance learning and may serve as a useful
strategy in today's AI-influenced academic environment. This full research
paper also discusses pedagogical implications and study limitations.
Study at a glance
- Question: Does revising homework after getting feedback improve student exam performance compared to submitting homework once?
- Setting and data: 13 years of exam data from a computer architecture course.
- Method: Compares student exam performance under single versus dual homework submission conditions using matched questions (pooled t-tests).
Why it matters
Dual-submission homework has gained attention as a way to foster reflection and discourage reliance on online answer repositories. Comparing student performance under single versus dual-submission conditions examines whether reflective revision supports learning in AI-influenced academic environments.
Key findings
- In a college computer architecture course, submitting homework twice with feedback significantly improved exam outcomes in a majority of cases.
- Evidence suggests that reflective resubmission of homework can meaningfully enhance student learning.
- Reflective resubmission may serve as a useful learning strategy in today's AI-influenced academic environment.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
Who age?
Study design
