AI Essentials for Teaching and Learning

A One-Day Seminar for Virginia Tech Educators

Join the TLOS team on August 20 or August 21, 2025, from 10:00 a.m. to 3:00 p.m., to build confidence, capacity, and curiosity around using artificial intelligence (AI)—no technical background required. 

AI Essentials for Teaching and Learning is a one-day hybrid event designed to help Virginia Tech educators discover the core skills, concepts, and conversations shaping higher education in the age of AI. Four 60-minute interactive workshops will explore these critical topics: AI literacy, effective prompting, practical teaching workflows, and designing AI-conscious courses. The series will offer research-informed strategies, space for reflection, and real-world examples tailored to the Virginia Tech community.

Two dates are available; choose either day to complete the full program.

Only 20 in-person spaces are available per day. Registered participants will receive a Canvas email requesting that they indicate how they plan to attend.

Schedule

Workshop 1: AI Literacy for Higher Education (Foundational)

Overview
What does it mean to be AI-literate in a university setting? AI offers both potential and complexity—making it essential for academics to build core skills and maintain a human-centered perspective. This workshop combines practical insight with ethical reflection to equip participants for thoughtful, confident use of AI in academic work. 

Learning Objectives
Participants will be able to

• Describe the human role in guiding and interpreting AI outputs in educational contexts.
  

• Identify core components of AI literacy in line with frameworks from Educause and the Digital Education Council.
  

• Explore ethical considerations for teaching and learning with Virginia Tech’s Responsible and Ethical AI Principles.

Facilitator: Aaron Bond 

Workshop 2: Effective Prompting (Foundational)

Overview
This session focuses on practical prompting strategies that help faculty get better results from AI tools. Participants will explore techniques such as answer leveling and chain-of-thought prompting, troubleshoot common issues, and select appropriate tools and models for different use cases.

Learning Objectives
Participants will be able to

• Identify currently approved AI platforms at Virginia Tech and data risk levels as defined by the Division of Information Technology.
  

• Implement strategies for mitigating risk, such as anonymization, aggregation, and substitution.
  

• Apply different prompting techniques, such as contextual, answer leveling, and chain-of-thought.
  

• Identify common technical issues and strategies to address them.
  

• Evaluate the appropriateness of available tools, features, and models based on task requirements and use case needs.

Facilitated by Daniel Yaffe

Workshop 3: Quick-Win Teaching Workflows (Foundational)

Overview
Designed for time-strapped faculty, this workshop explores quick and practical ways to integrate AI into existing teaching workflows. Participants will examine everyday instructional tasks—such as designing rubrics or lesson plans—and identify areas where AI can improve efficiency or enhance student support.  

Learning Objectives
Participants will be able to

• Analyze current teaching processes to identify opportunities for AI integration.
  

• Identify common use cases and workflows for streamlining instructional tasks.
  

• Define custom agents and GPTs and the types of use cases they are well-suited for.
  

• Create a simple AI-assisted workflow to improve instructional efficiency.

Facilitated by Daron Williams

Workshop 4: Designing AI-Conscious Courses (Foundational)

Overview
As artificial intelligence (AI) continues to shape the landscape of higher education, course design is changing too. In this workshop, educators explore the role of AI in the classroom. Participants will investigate frameworks for integrating AI policies, supporting student literacy, and designing assignments that account for or leverage generative AI tools.

Learning Objectives
Participants will be able to

• Compare three key approaches for integrating AI into the classroom and implications for course policies.
  

• Design or adapt an assignment that either incorporates or anticipates the use of generative AI.
  

• Identify strategies for building students’ AI literacy and ethical awareness.
  

• Evaluate course design for alignment with institutional and pedagogical goals related to AI use.

Facilitated by Larry Cox II