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Paper Type
ERF
Abstract
In this research, we explore the integration of Artificial Intelligence (AI), particularly ChatGPT, into an introductory graduate software development course. The objective is to equip students with relevant and effective AI skills without compromising learning. We focus on the balance between leveraging AI for efficiency and ensuring that students engage with the learning material without becoming overly reliant on AI. The study first assesses the extent to which ChatGPT is capable in solving the systems development life cycle activities taught in class. We then propose an approach that leverages a flipped classroom model to facilitate in-class practice, complemented by guided ChatGPT usage for completing assignments. In addition, we propose a study design to evaluate both student learning and ChatGPT effectiveness in this approach. The paper contributes to university education by researching effective strategies for AI integration that prepare students for an AI-assisted workplace.
Paper Number
1727
Recommended Citation
Greiner, Martina, "Balancing AI integration and Learning in Software Development Education" (2024). AMCIS 2024 Proceedings. 7.
https://aisel.aisnet.org/amcis2024/is_education/is_education/7
Balancing AI integration and Learning in Software Development Education
In this research, we explore the integration of Artificial Intelligence (AI), particularly ChatGPT, into an introductory graduate software development course. The objective is to equip students with relevant and effective AI skills without compromising learning. We focus on the balance between leveraging AI for efficiency and ensuring that students engage with the learning material without becoming overly reliant on AI. The study first assesses the extent to which ChatGPT is capable in solving the systems development life cycle activities taught in class. We then propose an approach that leverages a flipped classroom model to facilitate in-class practice, complemented by guided ChatGPT usage for completing assignments. In addition, we propose a study design to evaluate both student learning and ChatGPT effectiveness in this approach. The paper contributes to university education by researching effective strategies for AI integration that prepare students for an AI-assisted workplace.
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