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"ChatGPT Is Here to Help, Not to Replace Anybody" -- An Evaluation of Students' Opinions On Integrating ChatGPT In CS Courses

Bruno Pereira Cipriano, Pedro Alves

TL;DR

This paper investigates CS first-year students' attitudes toward integrating AI code-generation tools like ChatGPT into CS courses. Through a structured survey of 52 participants within a Data-Structures and Algorithms course that included a GPT-based exercise, the study analyzes five research questions on academic use, training needs, learning impact, teaching practices, and professional futures. The findings show broad student support for GPT in academic contexts, notable variation in prompting proficiency, and a preference for guided training and curricular inclusion of GPT-oriented activities, rather than unregulated reliance. The work contributes practical recommendations for educators on prompt-engineering instruction, supervised LLM-based exercises, and assessment of prompting skills, offering timely guidance for integrating AI copilots into computing education while preserving core cognitive skills and teacher roles.

Abstract

Large Language Models (LLMs) like GPT and Bard are capable of producing code based on textual descriptions, with remarkable efficacy. Such technology will have profound implications for computing education, raising concerns about cheating, excessive dependence, and a decline in computational thinking skills, among others. There has been extensive research on how teachers should handle this challenge but it is also important to understand how students feel about this paradigm shift. In this research, 52 first-year CS students were surveyed in order to assess their views on technologies with code-generation capabilities, both from academic and professional perspectives. Our findings indicate that while students generally favor the academic use of GPT, they don't over rely on it, only mildly asking for its help. Although most students benefit from GPT, some struggle to use it effectively, urging the need for specific GPT training. Opinions on GPT's impact on their professional lives vary, but there is a consensus on its importance in academic practice.

"ChatGPT Is Here to Help, Not to Replace Anybody" -- An Evaluation of Students' Opinions On Integrating ChatGPT In CS Courses

TL;DR

This paper investigates CS first-year students' attitudes toward integrating AI code-generation tools like ChatGPT into CS courses. Through a structured survey of 52 participants within a Data-Structures and Algorithms course that included a GPT-based exercise, the study analyzes five research questions on academic use, training needs, learning impact, teaching practices, and professional futures. The findings show broad student support for GPT in academic contexts, notable variation in prompting proficiency, and a preference for guided training and curricular inclusion of GPT-oriented activities, rather than unregulated reliance. The work contributes practical recommendations for educators on prompt-engineering instruction, supervised LLM-based exercises, and assessment of prompting skills, offering timely guidance for integrating AI copilots into computing education while preserving core cognitive skills and teacher roles.

Abstract

Large Language Models (LLMs) like GPT and Bard are capable of producing code based on textual descriptions, with remarkable efficacy. Such technology will have profound implications for computing education, raising concerns about cheating, excessive dependence, and a decline in computational thinking skills, among others. There has been extensive research on how teachers should handle this challenge but it is also important to understand how students feel about this paradigm shift. In this research, 52 first-year CS students were surveyed in order to assess their views on technologies with code-generation capabilities, both from academic and professional perspectives. Our findings indicate that while students generally favor the academic use of GPT, they don't over rely on it, only mildly asking for its help. Although most students benefit from GPT, some struggle to use it effectively, urging the need for specific GPT training. Opinions on GPT's impact on their professional lives vary, but there is a consensus on its importance in academic practice.
Paper Structure (15 sections, 3 figures)

This paper contains 15 sections, 3 figures.

Table of Contents

  1. Introduction
  2. Related work
  3. Experimental Context
  4. The ChatGPT requirement and exercise
  5. Survey
  6. Methodology
  7. Results
  8. RQ1: What is the opinion/sentiment of first-year students regarding the academic use of tools like ChatGPT?
  9. RQ2: To what extent can first-year students take advantage of tools like ChatGPT without any specific or formal training?
  10. RQ3: What is the impact of ChatGPT on the learning experience of first-year students?
  11. RQ4: What is the impact of ChatGPT on current teaching practices?
  12. RQ5: What is the opinion of first-year students regarding the influence of AI-based code generation tools (like ChatGPT) on their professional future?
  13. Recommendations for CS Educators
  14. Limitations
  15. Conclusions

Figures (3)

  • Figure 1: Responses to the question "[Q2.3] What percentage of the exercises' code was generated by ChatGPT?".
  • Figure 2: Responses to some of the questions related to RQ3 (impact of ChatGPT on students' learning experience). The questions were on 1-5 scale, with 1 (lighter color) being the 'lesser' option and 5 (darker color) being the 'greater' option.
  • Figure 3: Pie chart for question "[Q4.1] Do you think it makes sense to include this type of exercises in the curriculum?". All students agree with having GPT-based exercises, but they are divided in terms of evaluation scheme.