9 citations · 9 across the 1 of their papers we have counts for
4 papers
Say What? Examining Text and Voice Input Modalities for Prompt-Based Programming in Computing Education
Kaitlin Riegel, Yan Cathy Hua, Paul Denny +4
Large language models (LLMs) are increasingly integrated into computing education, yet nearly all prior research has focused on text-based interactions. As voice-enabled interfaces…
When AI Is Wrong on Purpose: How Students Respond to Buggy GenAI Code
Victor-Alexandru Pădurean, Kaitlin Riegel, Alkis Gotovos +6
As Generative AI (GenAI) becomes increasingly central to software development, CS education is integrating prompt-centered workflows where students describe intended program behavi…
Understanding Student Perceptions, Mistakes, and Debugging Approaches when Solving Natural Language Programming Tasks
Victor-Alexandru Pădurean, Kaitlin Riegel, Gweneth Barbre +7
Learning to communicate with code-generating AI models is an emerging skill for novice programmers. One recent pedagogical approach, Prompt Problems, has students solve computation…
Development of the Measure of Assessment Self-Efficacy (MASE) for Quizzes and Exams
Kaitlin Riegel, Tanya Evans, Jason M. Stephens
Self-efficacy is a significant construct in education due to its predictive relationship with achievement. Existing measures of assessment-related self-efficacy concentrate on stud…