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%)¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r1 · q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? Testing rates varied significantly across assignments (χ2 = 133.03, df = 6, p < 0.001), highest in Algorithms (87.8%) and lowest in HCI (27.5%). → Nizamani 2026 q3 i? Web search usage varied significantly across assignments (χ2 = 22.79, df = 6, p < 0.001), highest in HCI (56.0%) and lowest in Databases (32.5%). → Nizamani 2026 (2)

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 testing as a verification strategy among LLM users across the seven assignments. The article reports "Algorithms had the highest testing rate (87.8%), while HCI had the lowest (27.5%)" with a significant chi-square (χ 2 = 133.03, df = 6, p < 0.001); no effect size is printed.

"Algorithms had the highest testing rate (87.8%), while HCI had the lowest (27.5%). Networking (61.0%), Software Engineering (65.6%), and Web Development (57.6%) showed moderate testing usage, whereas Machine Learning (30.6%) and HCI (27.5%) showed lower reliance on testing. This variation was statistically significant (χ 2 = 133.03, df = 6, p < 0.001)."

Nizamani 2026 (2)¶

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 web search as a verification strategy among LLM users across the seven assignments. The article reports usage "ranging from 32.5% in Databases to 56.0% in HCI", with higher use in more conceptual or open-ended tasks; χ 2 = 22.79, df = 6, p < 0.001; no effect size is printed.

"Web search usage also varied across assignments, ranging from 32.5% in Databases to 56.0% in HCI. Higher web search usage was observed in HCI (56.0%), Web Development (49.4%), and Machine Learning (47.1%), indicating greater reliance on external information sources in more conceptual or open-ended tasks. This variation was also statistically significant (χ 2 = 22.79, df = 6, p < 0.001)."

Discussion¶

Related Claims¶

• Manual reasoning is the most consistently used verification method across assignments, with no significant difference in its use across subfields — related
• Prompt-count distributions differ significantly across assignments, with moderate prompting most common and extended prompting (10+) rare except in Algorithms (18.0%) — related
• Verification is nearly universal among LLM users, and most students combine multiple verification strategies rather than relying on a single one — related
• 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%) — related