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

• URL: http://arxiv.org/abs/2404.17443v1
• Date: Fri, 26 Apr 2024 14:29:16 GMT
• Title: "ChatGPT Is Here to Help, Not to Replace Anybody" -- An Evaluation of Students' Opinions On Integrating ChatGPT In CS Courses
• Authors: Bruno Pereira Cipriano, Pedro Alves,
• Abstract summary: Large Language Models (LLMs) like GPT and Bard are capable of producing code based on textual descriptions. LLMs will have profound implications for computing education, raising concerns about cheating, excessive dependence, and a decline in computational thinking skills.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

Related papers

• "Give me the code" -- Log Analysis of First-Year CS Students' Interactions With GPT [0.0]
  This paper analyzes the prompts used by 69 freshmen undergraduate students to solve a certain programming problem within a project assignment. Despite using unsophisticated prompting techniques, our findings suggest that the majority of students successfully leveraged GPT. Half of the students demonstrated the ability to exercise judgment in selecting from multiple GPT-generated solutions.
  arXiv  Detail & Related papers  (2024-11-26T20:11:46Z)
• Evaluating GPT-4 at Grading Handwritten Solutions in Math Exams [48.99818550820575]
  We leverage state-of-the-art multi-modal AI models, in particular GPT-4o, to automatically grade handwritten responses to college-level math exams. Using real student responses to questions in a probability theory exam, we evaluate GPT-4o's alignment with ground-truth scores from human graders using various prompting techniques.
  arXiv  Detail & Related papers  (2024-11-07T22:51:47Z)
• GPT-4 as a Homework Tutor can Improve Student Engagement and Learning Outcomes [80.60912258178045]
  We developed a prompting strategy that enables GPT-4 to conduct interactive homework sessions for high-school students learning English as a second language. We carried out a Randomized Controlled Trial (RCT) in four high-school classes, replacing traditional homework with GPT-4 homework sessions for the treatment group. We observed significant improvements in learning outcomes, specifically a greater gain in grammar, and student engagement.
  arXiv  Detail & Related papers  (2024-09-24T11:22:55Z)
• Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants [176.39275404745098]
  We evaluate whether two AI assistants, GPT-3.5 and GPT-4, can adequately answer assessment questions. GPT-4 answers an average of 65.8% of questions correctly, and can even produce the correct answer across at least one prompting strategy for 85.1% of questions. Our results call for revising program-level assessment design in higher education in light of advances in generative AI.
  arXiv  Detail & Related papers  (2024-08-07T12:11:49Z)
• Integrating ChatGPT in a Computer Science Course: Students Perceptions and Suggestions [0.0]
  This experience report explores students' perceptions and suggestions for integrating ChatGPT in a computer science course. Findings show the importance of carefully balancing using ChatGPT in computer science courses.
  arXiv  Detail & Related papers  (2023-12-22T10:48:34Z)
• Can ChatGPT Play the Role of a Teaching Assistant in an Introductory Programming Course? [1.8197265299982013]
  This paper explores the potential of using ChatGPT, an LLM, as a virtual Teaching Assistant (TA) in an introductory programming course. We evaluate ChatGPT's capabilities by comparing its performance with that of human TAs in some of the important TA functions.
  arXiv  Detail & Related papers  (2023-12-12T15:06:44Z)
• "It's not like Jarvis, but it's pretty close!" -- Examining ChatGPT's Usage among Undergraduate Students in Computer Science [3.6936132187945923]
  Large language models (LLMs) such as ChatGPT and Google Bard have garnered significant attention in the academic community. This study adopts a student-first approach to comprehensively understand how undergraduate computer science students utilize ChatGPT.
  arXiv  Detail & Related papers  (2023-11-16T08:10:18Z)
• Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots [36.760677949631514]
  ChatGPT was released to provide coherent and useful replies based on analysis of large volumes of data. Our preliminary evaluation concludes that ChatGPT performed differently in each subject area including finance, coding and maths. There are clear drawbacks in its use, such as the possibility of producing inaccurate or false data. Academic regulations and evaluation practices need to be updated, should ChatGPT be used as a tool in education.
  arXiv  Detail & Related papers  (2023-05-25T17:35:57Z)
• Exploring User Perspectives on ChatGPT: Applications, Perceptions, and Implications for AI-Integrated Education [40.38809129759498]
  ChatGPT is most commonly used in the domains of higher education, K-12 education, and practical skills training. On one hand, some users view it as a transformative tool capable of amplifying student self-efficacy and learning motivation. On the other hand, there is a degree of apprehension among concerned users.
  arXiv  Detail & Related papers  (2023-05-22T15:13:14Z)
• A Categorical Archive of ChatGPT Failures [47.64219291655723]
  ChatGPT, developed by OpenAI, has been trained using massive amounts of data and simulates human conversation. It has garnered significant attention due to its ability to effectively answer a broad range of human inquiries. However, a comprehensive analysis of ChatGPT's failures is lacking, which is the focus of this study.
  arXiv  Detail & Related papers  (2023-02-06T04:21:59Z)
• ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback [54.142719510638614]
  In this paper, we frame the problem of providing feedback as few-shot classification. A meta-learner adapts to give feedback to student code on a new programming question from just a few examples by instructors. Our approach was successfully deployed to deliver feedback to 16,000 student exam-solutions in a programming course offered by a tier 1 university.
  arXiv  Detail & Related papers  (2021-07-23T22:41:28Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.