ChatGPT and the Future of Undergraduate Computer Science:
Challenges, Opportunities and Recommendations
Research Question
What are the strengths and weaknesses of ChatGPT when answering questions related to logic and theory in Computer Science?
To what degree can undergraduate computer science students rely on ChatGPT for solving their take-home exams and assignments?
What factors should instructors take into account while designing take-home exams and assignments for students who may potentially use ChatGPT?
How can ChatGPT be constructively used by students and instructors to enhance their learning and teaching experience respectively?
Methodology
Undergraduate computer science subjects
Graduate Aptitude Test in Engineering
Data Structures and Algorithms
Operating Systems
Database Management Systems (DBMS)
Machine Learning
Programming Questions from LeetCode
Future direction of CS pedagogy
Students
Instructors
Use ChatGPT to generate guide questions
Use ChatGPT for initial ideation and write-ups and then build upon these through their own skills
Formulate their own timeline and space
Train students in prompt engineering
Design. questions that require critical thinking and higher cognitive skills that cannot be easily solved by providing prompt
For take home assessments, questions that are precise and objective in nature might be a better way to test a student’s knowledge compared to subjective questions
New evaluation styles like giving students a topic where they will design a problem, then they will generate a solution and test cases
Future Work
Enhancing the answer of AI tools to make them more relevant and accurate
More inclusive and expansive data
Challenges
Variability in ChatGPT’s accuracy and the need for prompt
contextualization
Higher accuracy for subjective and theoretical questions
Bias in ChatGPT’s underlying language model