Date
Publisher
arXiv
The impact of Large Language Models (LLMs) like GPT-3, GPT-4, and Bard in
computer science (CS) education is expected to be profound. Students now have
the power to generate code solutions for a wide array of programming
assignments. For first-year students, this may be particularly problematic
since the foundational skills are still in development and an over-reliance on
generative AI tools can hinder their ability to grasp essential programming
concepts. This paper analyzes the prompts used by 69 freshmen undergraduate
students to solve a certain programming problem within a project assignment,
without giving them prior prompt training. We also present the rules of the
exercise that motivated the prompts, designed to foster critical thinking
skills during the interaction. Despite using unsophisticated prompting
techniques, our findings suggest that the majority of students successfully
leveraged GPT, incorporating the suggested solutions into their projects.
Additionally, half of the students demonstrated the ability to exercise
judgment in selecting from multiple GPT-generated solutions, showcasing the
development of their critical thinking skills in evaluating AI-generated code.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
