Pith. sign in

REVIEW 2 cited by

Exploring the Role of AI Assistants in Computer Science Education: Methods, Implications, and Instructor Perspectives

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2306.03289 v2 pith:6ZA5MC44 submitted 2023-06-05 cs.HC

classification cs.HC
keywords computerscienceassistantsstudentscapabilitiescourseseducationinstructors
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

The use of AI assistants, along with the challenges they present, has sparked significant debate within the community of computer science education. While these tools demonstrate the potential to support students' learning and instructors' teaching, they also raise concerns about enabling unethical uses by students. Previous research has suggested various strategies aimed at addressing these issues. However, they concentrate on the introductory programming courses and focus on one specific type of problem. The present research evaluated the performance of ChatGPT, a state-of-the-art AI assistant, at solving 187 problems spanning three distinct types that were collected from six undergraduate computer science. The selected courses covered different topics and targeted different program levels. We then explored methods to modify these problems to adapt them to ChatGPT's capabilities to reduce potential misuse by students. Finally, we conducted semi-structured interviews with 11 computer science instructors. The aim was to gather their opinions on our problem modification methods, understand their perspectives on the impact of AI assistants on computer science education, and learn their strategies for adapting their courses to leverage these AI capabilities for educational improvement. The results revealed issues ranging from academic fairness to long-term impact on students' mental models. From our results, we derived design implications and recommended tools to help instructors design and create future course material that could more effectively adapt to AI assistants' capabilities.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Insights from the Frontline: GenAI Utilization Among Software Engineering Students

    cs.HC 2024-12 accept novelty 6.0 of 10

    Students found generative AI helpful for incremental learning and initial implementation, but challenging for first-time concept learning and advanced implementation, with causes traced to intrinsic AI faults and gaps.

  2. Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools

    cs.CY 2024-12 conditional novelty 5.0 of 10

    Computing educators are adopting GenAI faster than they are formalizing policies, and both educators and developers see code reading, evaluation, and problem decomposition as rising in importance over syntax recall.

Pith tools