Learning Sciences & Emergent Technologies Hub

Resources

Resources: LSET

Courses

LSET shares a compilation of courses related to AI and other emergent technologies available at the University of Pittsburgh.

  • HAIL has gathered data on the people, centers, and courses connected with AI. This is a link to HAIL’s Rol-AI-Dex which can be used to search for Pitt AI-related courses.
  • This spreadsheet is provided by HAIL and lists the known Pitt AI-related courses available at the University.
  • INFSCI 1499 Special Topics - AI Literacy: Foundations for Critical Thinking and Informed Use
    Faculty: LRDC Research Scientist Angela Stewart
    This course introduces students from all backgrounds to the essential concepts of artificial intelligence (AI) and its growing role in society - no technical experience required. Students will learn how to recognize AI in everyday life, understand what it can and cannot do, and critically examine its impacts across contexts such as education, government, or media. Through discussions, interactive activities, case studies, and hands-on engagement with popular AI tools, students will develop the skills to evaluate when and how AI should be used. They will also learn to communicate its limitations and possibilities to general audiences and apply it thoughtfully in their personal, educational, and career pursuits. By the end of this course, students will be equipped with the knowledge and confidence to navigate a world increasingly shaped by artificial intelligence and make informed decisions about how these technologies influence their lives and futures.
  • AI PowerUP Class
    Registration information coming soon

Weekly AI in Higher Education Report

LSET member Alan Lesgold uses Manus to produce a fully LLM-generated weekly report summarizing key articles related to AI in HigherEd. The goal is to provide a sense of the issues and developments in policy and practice. These Manus-generated reports are not reviewed by humans and should be read with recognition that there could be inaccuracies. Each summarized article includes a link to the source and we recommend reviewing the original article before using or acting on the summarized content.

2026 Quarter 3
2026 Quarter 2
2026 Quarter 1

Publications

LSET does not, as a collective, produce publications but individual LSET members’ relevant publications are shared here.

  • Coelho, R., & McCollum, A. (2025). Illuminating socially distributed identity resources in student writing through artificial intelligence to support the design of culturally informed learning experiences. Discourse Processes.
  • Coelho, R., Cheng, J., Pea, R., Schunn, C., & Liu, J. (2025). Advancing quantum information science pre-college education: The case for learning sciences collaboration. e-print.
  • Coelho, R., Bjune, A., E., Ellingsen, S., Solheim, B., M., Thormodsæter, R., Wasson, B., & Cotner, S. (2025). A call for clarity: Biology students advocate for guidelines for the use of generative AI in higher education. (2025). Journal of Science Education and Technology.
  • Savelka, J., Ashley, K.D., Gray, M.A., Westermann, H., & Xu, H. (2023). Explaining Legal Concepts with Augmented Large Language Models (GPT-4). Proceedings of the International Conference on Artifical Intelligence and Law (ICAIL 2023), University of Minho Law School, Braga, Portugal.

White Papers

LSET does not, as a collective, produce white papers but individual LSET members often write blog posts, white papers, position papers, and the like. This section shares these individually produced artifacts.

Resources: Pitt