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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. 

While implementing with caution, Artificial Intelligence (AI) holds potential to help nations address pressing social issues, such as homelessness, climate change, and healthcare accessibility. With the existing and potential economic and social benefits of AI, it is crucial to integrate AI learning in undergraduate education. This paper presents the preliminary findings of a course project that engages students to learn AI by prototyping solutions to address important social issues in their communities among 120 undergraduate MIS students. Students worked in groups and developed chatbots that addressed a variety of community issues during COVID-19. A survey study shows students’ enhanced understanding and mastery of AI concepts and applications, empowerment of contributing to their communities through AI innovation, and an emerging awareness of diversity, equity, and ethical issues in the community and AI technologies. We conclude with implications of learning AI, innovation, and ethics through the lens of AI for social good. 

The Nation's research enterprise faces a shortage of data scientists. Expanding the pipeline of data science students, particularly from underrepresented populations, requires educational institutions to increase awareness of data science and inspire a passion for data in students as they begin their academic careers. In this tutorial we discuss the development and delivery of a free seminar designed to provide hands-on lessons in the use of both Apache Spark and Jupyter notebooks to students from any academic background in an approachable, no-risk environment. An explanation of the seminar resources, exercises, and implementation guidelines are included, as are lessons learned from several successful seminars held both in-person and virtually at two institutions of high education. 

The Python Foundations seminar emphasizes a hands-on approach and is designed to reach a diverse student population to provide them with the entry-level programming skills required in data science. The creation of the seminar materials has been funded by a three-year federal grant and has followed a systematic approach to enhance the student learning experience and raise student awareness of data science. The seminar materials—structured in three parts: pre-seminar, live seminar, and post-seminar—are licensed under the Creative Commons Attribution-ShareAlike 4.0 International license to encourage adoption by any institution. To foster interest in the seminar, students have the possibility to earn a digital badge attesting to their newly acquired skills.