LLM adoption varies substantially across CS subfield assignments under a shared instructional intervention, with highest use in Algorithms (89.6%) and Web Development (80.6%) and lowest in Software Engineering (15.2%)¶

Claim · All claims
Evidence · 1 study · associational r1 · q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? LLM adoption differed significantly across the seven assignments, ranging from 15.2% (Software Engineering) to 89.6% (Algorithms). → Nizamani 2026

Evidence¶

Nizamani 2026¶

Nizamani, S. B., Lee, Y., Donekal Chandrashekar, N., Ellis, M., & Ramakrishnan, N. (2026). Understanding Student Use of Large Language Models Across Computer Science Subfields. https://arxiv.org/abs/2610.01158 doi:10.48550/arxiv.2610.01158

q3 · i? · associational · r1

Descriptive analysis of post-assignment reflection surveys from 211 students who completed all seven assignments in a within-subject course design. The results section reports that "Algorithms (89.6%) and Web Development (80.6%) showing the highest usage, and Software Engineering the lowest (15.2%)"; Networking and Databases showed moderate adoption (58.3%).

"LLM adoption varied substantially by assignment, with Algorithms (89.6%) and Web Development (80.6%) showing the highest usage, and Software Engineering the lowest (15.2%)."

Discussion¶

Related Claims¶

• Student LLM usage patterns varied across data science courses: Course-BD showed the highest frequency and over-reliance with near-zero perceived learning effect
• Verification strategy type varies by assignment context: testing is more common in structured tasks (Algorithms 87.8%) while web search is more common in open-ended tasks (HCI 56.0%) — related
• Prompt-count distributions differ significantly across assignments, with moderate prompting most common and extended prompting (10+) rare except in Algorithms (18.0%) — related
• Students predominantly conceptualize the LLM as an Assistant rather than Peer or Expert, and role distributions differ significantly across assignments — related
• Verification is nearly universal among LLM users, and most students combine multiple verification strategies rather than relying on a single one — related