Abstract Today, due to the size of many genomes and the increasingly large sizes of sequencing files, independently analyzing sequencing data is largely impossible for a biologist with little to no programming expertise. As such, biologists are typically faced with the dilemma of either having to spend a significant amount of time and effort to learn how to program themselves or having to identify (and rely on) an available computer scientist to analyze large sequence data sets. That said, the advent of AI‐powered programs like ChatGPT may offer a means of circumventing the disconnect between biologists and their analysis of genomic data critically important to their field. The work detailed herein demonstrates how implementing ChatGPT into an existing Course‐based Undergraduate Research Experience curriculum can provide a means for equipping biology students with no programming expertise the power to generate their own programs and allow those students to carry out a publishable, comprehensive analysis of real‐world Next Generation Sequencing (NGS) datasets. Relying solely on the students' biology background as a prompt for directing ChatGPT to generate Python codes, we found students could readily generate programs able to deal with and analyze NGS datasets greater than 10 gigabytes. In summary, we believe that integrating ChatGPT into education can help bridge a critical gap between biology and computer science and may prove similarly beneficial in other disciplines. Additionally, ChatGPT can provide biological researchers with powerful new tools capable of mediating NGS dataset analysis to help accelerate major new advances in the field.
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An Exploratory Study on the Impact of AI tools on the Student Experience in Programming Courses: an Intersectional Analysis Approach
This work-in-progress paper presents a study that sheds light on the concerns that students may not develop sufficient programming skills and as a result, be less competent with the use of ChatGPT. The potential benefits for students are significant: Access to ChatGPT increases the ability for students to work constructively on their own schedule. The ease of use of ChatGPT may engage students who might otherwise hesitate in asking for support. Before these tools can be meaningfully introduced into a course, work must be done to study the impact of these AI tools on a student's ability to learn. In this study, participants are recruited from introductory Java programming courses at a large public university in the United States. This paper presents preliminary findings from a mixed method study design that consists of a pre-task assessment quiz; and a programming task in one of three conditions: (1) with no external help, (2) with the help of an AI chatbot, or (3) with the help of a generative AI tool like GitHub Copilot; followed by a post-task assessment and an interview on their experience and perceptions of the tools. Our preliminary findings describe our data collection, thematic analysis of the students' prompts and chatGPT responses, and a summary of the experience for 3 students. Our findings demonstrate a range of students' attitudes and behaviors towards chatGPT that provides insight for future research and plans for incorporating such AI tools in a course.
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- Award ID(s):
- 2334319
- PAR ID:
- 10645766
- Publisher / Repository:
- IEEE
- Date Published:
- Page Range / eLocation ID:
- 1 to 5
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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