Empirical analysis of AI help-seeking trajectories in programming courses finds reactive troubleshooting dominates and links to higher submission counts without score differences.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 3verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
Among novice programmers using AI code generators, trust did not predict compliance with suggestions, while performance correlated with both compliance and increased subsequent trust.
Replication survey in three Middle Eastern countries finds language fluency predicts AI trust, with female students in Saudi Arabia showing lower trust than males unlike US patterns.
citing papers explorer
-
AI-Assisted Help-Seeking Trajectories in Programming Education from an SRL-Informed Perspective
Empirical analysis of AI help-seeking trajectories in programming courses finds reactive troubleshooting dominates and links to higher submission counts without score differences.
-
Relationships Between Trust, Compliance, and Performance for Novice Programmers Using AI Code Generation
Among novice programmers using AI code generators, trust did not predict compliance with suggestions, while performance correlated with both compliance and increased subsequent trust.
-
Trust in AI among Middle Eastern CS Students: Investigating Students' Trust and Usage Patterns Across Saudi Arabia, Kuwait and Jordan
Replication survey in three Middle Eastern countries finds language fluency predicts AI trust, with female students in Saudi Arabia showing lower trust than males unlike US patterns.