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David M. Woods; Andrea Hulshult – Information Systems Education Journal, 2025
IT/IS educators continue to work to develop content and activities for teaching Agile practices, processes, and methodologies to their courses to ensure students have the skills expected by businesses. Given the wide range of tools and technologies that fall under the umbrella of Agile and the wide range of places where Agile is applied, educators…
Descriptors: Information Technology, Information Science Education, Computer Science Education, Teaching Methods
Mark Frydenberg; Anqi Xu; Jennifer Xu – Information Systems Education Journal, 2025
This study explores student perceptions of learning to code by evaluating AI-generated Python code. In an experimental exercise given to students in an introductory Python course at a business university, students wrote their own solutions to a Python program and then compared their solutions with AI-generated code. They evaluated both solutions…
Descriptors: Student Attitudes, Programming, Computer Software, Quality Assurance
David R. Firth; Adam Gonzales; Michelle Louch; Bryan Hammer – Information Systems Education Journal, 2025
ChatGPT is having an impact on students, and information systems (IS) and computing academic professionals alike. Our goal for this paper is to help faculty and students know the conditions in which generative AI such as ChatGPT should or should not be used. To that end, we describe the development of a 2x2 matrix. On the horizontal axis we have…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Information Systems
A Comparison of Generative AI Solutions and Textbook Solutions in an Introductory Programming Course
Ernst Bekkering; Patrick Harrington – Information Systems Education Journal, 2025
Generative AI has recently gained the ability to generate computer code. This development is bound to affect how computer programming is taught in higher education. We used past programming assignments and solutions for textbook exercises in our introductory programming class to analyze how accurately one of the leading models, ChatGPT, generates…
Descriptors: Higher Education, Artificial Intelligence, Programming, Textbook Evaluation
Frank Lee; Clinton Baxter – Information Systems Education Journal, 2023
The Cross Industry Standard Process for Data Mining (CRISP-DM) framework was developed in the 1990s and has been widely used as the most relevant and comprehensive leading principle for conducting analytics projects. Despite the wide acceptance and adoption of the CRISP-DM framework, the current business analytics discipline often focuses on the…
Descriptors: Artificial Intelligence, Court Litigation, Data Analysis, Information Systems
Christine Ladwig; Dana Schwieger; Reshmi Mitra – Information Systems Education Journal, 2025
The rapid rise of AI use is creating some very serious legal and ethical issues such as bias, discrimination, inequity, privacy violations, and--as creators everywhere fear--theft of protected intellectual property. Because AI platforms "learn" by scraping training materials available online or what is provided to them through their…
Descriptors: Copyrights, Plagiarism, Intellectual Property, Computer Software
Embracing Artificial Intelligence to Improve Self-Directed Learning: A Cybersecurity Classroom Study
Jim Marquardson – Information Systems Education Journal, 2024
Generative artificial intelligence (AI) tools were met with a mix of enthusiasm, skepticism, and fear. AI adoption soared as people discovered compelling use cases--developers wrote code, realtors generated narratives for their websites, students wrote essays, and much more. Calls for caution attempted to temper AI enthusiasm. Experts highlighted…
Descriptors: Artificial Intelligence, Capstone Experiences, Computer Security, Information Security
Ernst Bekkering – Information Systems Education Journal, 2025
Undergraduate research can stimulate students' interest, especially in STEM disciplines. This research can be formally offered in different formats such as Undergraduate Research Experiences (UREs). One of these is Course-based Undergraduate Research Experiences (CUREs), which are offered as an integral part of scheduled courses. CUREs have been…
Descriptors: Undergraduate Students, Research Training, Computer Science Education, Student Interests
Mitra, Reshmi; Schwieger, Dana; Lowe, Robert – Information Systems Education Journal, 2023
Many universities have, or are facing, the task of providing high quality essential customer services with fewer financial and human resources. The growing diversity of students, their needs and proficiencies, along with the increasing variety of university program offerings, make providing customized, ondemand, automated solutions crucial to…
Descriptors: Universities, Academic Advising, Artificial Intelligence, Faculty Workload
Christine Ladwig; Dana Schwieger – Information Systems Education Journal, 2024
Hollywood screenwriters worry about Artificial Intelligence (AI) replacements taking over their jobs. Famous museums litigate to protect their art from AI infringement. A major retailer scraps a machine-learning based recruitment program that was biased against women. These are just a few examples of how AI is affecting the world of work,…
Descriptors: Computer Science Education, Curriculum Development, Information Systems, Information Science Education
Bajracharya, Biju; Khan, Mohammad Shoeb – Information Systems Education Journal, 2023
The Autonomous Vehicles (AV) are a self-driving vehicle capable of sensing its environment and operating with minimal or no human intervention converting into a fully or partially automated vehicle. These automated vehicles have great potential to revolutionize the automotive industry and our daily lives. Thus, they are receiving a lot of…
Descriptors: Motor Vehicles, Interdisciplinary Approach, Computer Science Education, Artificial Intelligence
Liu, Xiaoming; Schwieger, Dana – Information Systems Education Journal, 2023
Rapid advancements and emergent technologies add an additional layer of complexity to preparing computer science and information technology higher education students for entering the post pandemic job market. Knowing and predicting employers' technical skill needs is essential for shaping curriculum development to address the emergent skill gap.…
Descriptors: Network Analysis, Employment Opportunities, Information Technology, Computer Science Education