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We describe a pedagogical study in which we designed and implemented a module for undergraduate Management Information Systems (MIS) students, aimed at preparing them for an increasingly AI-impacted business environment and society. We developed a learning module that taps their inherent motivation to make a meaningful difference, challenging them to ideate applications of AI for social good (AI4SG), focused specifically on sustainability. We piloted the module in an existing introductory MIS course, first establishing a range of fundamental AI capabilities through hands-on demos and study cases. Then, with instructor guidance, the student teams, working in a social entrepreneurship "start-up" context, identified sustainability challenges impacting their own communities and worked together to propose and pitch AI-powered solutions. The results suggest that students find this approach deepened their understanding of sustainability issues in their communities, improved their knowledge of how AI could address social issues, and improved their confidence in their ability to innovate.
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This content will become publicly available on April 11, 2026
Developing Chatbots for Sustainability: Experiential Learning in an Undergraduate Business Course
This paper presents an experiential learning pedagogy that teaches undergraduate business management information systems students hands-on AI skills through the lens of sustainability. The learning modules aim to empower undergraduate business students to gain interest and confidence in AI knowledge, skills, and careers, to sharpen their higher order thinking abilities, and to help them gain a deeper understanding of sustainability issues. Students learn AI through developing chatbots that address pressing sustainability issues within their own communities. Results of the pilot study indicate that students have increased self-efficacy in AI, more positive attitudes towards AI learning and AI-related careers, enhanced sustainability awareness, and more confidence in their ability to innovate.
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- Award ID(s):
- 2142783
- PAR ID:
- 10595653
- Publisher / Repository:
- Proceedings of the AAAI Conference on Artificial Intelligence
- Date Published:
- Journal Name:
- Proceedings of the AAAI Conference on Artificial Intelligence
- Volume:
- 39
- Issue:
- 28
- ISSN:
- 2159-5399
- Page Range / eLocation ID:
- 29087 to 29094
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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