Demystifying AI for Higher Education – A Framework for Innovation

Audience Level: 
All
Session Time Slot(s): 
Institutional Level: 
Higher Ed
Abstract: 

In this workshop, leaders from the Nittany AI Alliance will share a framework for both identifying and evaluating opportunities in the Higher Education context for applying Artificial Intelligence (AI) and Machine Learning (ML) in pursuit of an improved student experience. Additionally, they will provide an overview of AI/ML, what it can offer the higher education industry, and why AI/ML is emerging as a massive opportunity in Higher Education.

Extended Abstract: 

Artificial Intelligence and related technologies present new and powerful tools with the potential to dramatically impact the student experience. The Nittany AI Alliance at Penn State has developed a series of strategies to advance the exploration and application of these technologies to improve the student experience at Penn State and beyond. These strategies focus on three primary domains, 1) engaging students, faculty, and staff in exploring, driving, and developing innovations 2) stimulating innovations applying AI to educational challenges, and 3) pursuing partnerships with industry.

In this workshop, leaders from the Nittany AI Alliance will share a framework they have developed for both identifying and evaluating opportunities in the Higher Education context for applying Artificial Intelligence (AI) and Machine Learning (ML) in pursuit of an improved student experience. Additionally, they will provide an overview of AI/ML, what it can offer the higher education industry, and why AI/ML is emerging as a massive opportunity for controlling the cost and time to degree while simultaneously improving the student experience at schools both small and large. 

Learning Outcomes:

Upon completion of this workshop, participants will be able to

  • evaluate potential opportunities for improving existing processes in their organization using the supplied framework
  • articulate the broad affordances of Artificial Intelligence and Machine Learning within the Higher Education context
  • describe a minimum of three potential strategies for launching AI related initiatives at their institutions

Methods:

This workshop will focus on 1) providing a brief overview of AI and its affordances, 2) engaging participants in the use of a defined framework for evaluating opportunities to leverage AI, and 3) facilitating dialogue and interactions amongst participants to elicit and capture innovative ideas. The structure of the workshop will be as follows:

  1. Welcome and Icebreaking activity (5 minutes)
  2. Intro to AI and the framework (10 minutes)
  3. Small Group discussions (10 minutes)
  4. Large Group dialogue (10 minutes)
  5. Strategies and Moving Forward (10 minutes)

The presenters will leverage an online question voting system throughout the workshop to facilitate dialogue and provide the opportunity for anonymous questions. Discussions will follow a Think-Pair-Share and World Café protocol tailored for the workshop topic.

Materials:

The presenters will provide participants with an archive of the digital materials to allow them to apply the framework presented during the workshop at their home institutions.

Participants are not required to bring anything to the workshop beyond their own curiosity and willingness to actively engage their colleagues. A mobile device will be helpful for use of the online question system, but is not required for workshop participation.

Audiences:

This workshop is primarily tailored to individuals interested in and responsible for encouraging and supporting innovations at their institution or those with a desire to leverage innovative technologies to free themselves from routine and process driven work to focus on the more complex and deeply impactful work best left to humans.

Conference Session: 
Concurrent Session 4
Conference Track: 
Leadership and Institutional Strategy
Session Type: 
Express Workshop
Intended Audience: 
Administrators
Design Thinkers
Faculty
Technologists