Learning Sciences & Emergent Technologies Hub

Co-Designing Teaching for a Gen AI World, Together

On April 22, more than 125 participants from local high schools, nonprofit organizations and the University of Pittsburgh came together to solve shared problems of practice around the use of generative AI tools among high school and college students "Co-Designing Teaching for a Gen AI World, Together." The event featured an overview of relevant learning sciences principles (see below "At a Glance: Five Learning Sciences Principles for Instructional Design") as well as a curated list of key problems of practice (see below "At a Glance: Five Problems of Practice.")  Read the Executive Summary Here

At a Glance: Five Learning Sciences Principles for Instructional Design

Cognitive Offloading
Productive Struggle
Metacognition
Expectancy-Value

Motivation shaped by belief, worth, and trade-offs

Students are motivated to engage when they believe they can succeed (expectancy) AND believe the task is worth their effort (value). Perceived cost - time, effort, lost opportunities - can override both.

Bridge to Practice Expectancy-Value   Expectancy-Value infographic

Collaborative Reasoning

At a Glance: Five Problems of Practice

The following is a curated list of key problems of practice (PoP), which the LSET team identified based on interviews with K-12 and higher education faculty, surveys of Pitt faculty and students, and an extensive literature review.

  • Student Awareness of Gen AI Impacts
    How might we design instructional experiences that build students' awareness of when and how GenAI use is helping or harming their learning?   PoP Student Awareness
  • Assessment of Learning Process
    How might we design assessment approaches to focus on students' process of learning related to the developmental goal?   PoP Assessment
  • Intentional GenAI Use/Non-Use in Writing
    How might we design use/non-use of AI within writing tasks to intentionally develop targeted cognitive skills?   PoP Writing
  • Critical Engagement with GenAI Output
    How do we help learners engage in systematic validation processes of Gen AI output?   PoP Validation
  • Shared Understanding of Course Assignments
    How might we increase the shared understanding of the purpose and meaning of courses and course assignments?   PoP Shared Understanding