Back to all available

Beginners coding with AI: Prompts make the difference

artificial-intelligence
computer-education
data-mining-and-machine-learning
emerging-technologies

Abstract

Generative AI (GenAI) has transformed the nature of programming education. GenAI assistants can perform various programming tasks such as coding and debugging. The study aims to explore the effectiveness of ChatGPT and Copilot in learning MATLAB programming. A mixed-methods approach was used to collect quantitative and qualitative data through programming exercises, a survey, and an interview. The study involved 148 pre-university students who used both GenAI assistants in four dimensions: code generation, code explanation, bug fixing, and partial code completion. A total of 78 students responded to the survey, and 21 students were involved in the follow-up interview. Data analysis revealed that (1) students who adopted two GenAI assistants performed better in programming; though the result was not statistically significant, (2) students perceived that ChatGPT outperformed Copilot in the four dimensions measured, and (3) major themes revealed the strengths and weaknesses of ChatGPT in learning programming. The findings underscore the importance of prompt engineering and the skills required as a navigator. This study suggests a wider implication of programming education, highlighting the need for teaching essential skills required for effective use of GenAI assistants, instead of drawing a definite conclusion about the evolving technologies. Program developers must adapt alongside evolving GenAI assistants, suggesting the need for versatile and sustainable education.
Ask to review this manuscript

Notes for potential reviewers

  • Volunteering is not a guarantee that you will be asked to review. There are many reasons: reviewers must be qualified, there should be no conflicts of interest, a minimum of two reviewers have already accepted an invitation, etc.
  • This is NOT OPEN peer review. The review is single-blind, and all recommendations are sent privately to the Academic Editor handling the manuscript. All reviews are published and reviewers can choose to sign their reviews.
  • What happens after volunteering? It may be a few days before you receive an invitation to review with further instructions. You will need to accept the invitation to then become an official referee for the manuscript. If you do not receive an invitation it is for one of many possible reasons as noted above.
  • PeerJ Computer Science does not judge submissions based on subjective measures such as novelty, impact or degree of advance. Effectively, reviewers are asked to comment on whether or not the submission is scientifically and technically sound and therefore deserves to join the scientific literature. Our Peer Review criteria can be found on the "Editorial Criteria" page - reviewers are specifically asked to comment on 3 broad areas: "Basic Reporting", "Experimental Design" and "Validity of the Findings".
  • Reviewers are expected to comment in a timely, professional, and constructive manner.
  • Until the article is published, reviewers must regard all information relating to the submission as strictly confidential.
  • When submitting a review, reviewers are given the option to "sign" their review (i.e. to associate their name with their comments). Otherwise, all review comments remain anonymous.
  • All reviews of published articles are published. This includes manuscript files, peer review comments, author rebuttals and revised materials.
  • Each time a decision is made by the Academic Editor, each reviewer will receive a copy of the Decision Letter (which will include the comments of all reviewers).

If you have any questions about submitting your review, please email us at [email protected].