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Teaching with AI

This guide provides tips for understanding AI and using it in your teaching. From the team behind the Center for Teaching and Learning guide

Transforming Education with AI

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Introduction

While AI tools are still in the early adoption stage within the teaching and learning environment, their potential impact could mirror what we’ve already seen in industry. AI is used to automate workflows in manufacturing and provide diagnostics in engineering. As a health sciences university, our faculty and students may have encountered AI in clinical settings, such as patient notes or medical imaging analysis. From personalized learning feedback to content development to creative assessments, you have a new tool to support your teaching.

Why AI Matters for Educators

Definition of AI and Relevance to Education

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Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy.

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Learn more: IBM's Artificial Intelligence page.

“AI can be described as enabling two broad shifts from today’s use of technology in schools: (1) from capturing data to detecting patterns in data and (2) from providing access to instructional resources to automating decisions about teaching and learning processes.  ”

Learn more: AI and the Future of Teaching and Learning   |   Office of Educational Technology, US ED

In higher education, AI is revolutionizing traditional approaches by:

  • Personalizing learning experiences through adaptive learning platforms
  • Automating administrative tasks, freeing up time for meaningful student interactions
  • Providing detailed feedback on student work
  • Enhancing students' research capabilities with advanced data analysis tools
  • Elevating simulation-based training with AI-enhanced virtual patients and scenarios
  • Improving accessibility for diverse learners through AI-powered assistive technologies

Evolution of Healthcare AI

A Timeline of Innovation

Understanding the role of AI in healthcare - research and clinical - will be essential in the job setting. As a health sciences university with programs in nursing, optometry, physical therapy, and more, AI literacy becomes more important.

 

Scroll horizontally to view timeline.

AI in Healthcare

AI in Health Sciences

Did You Know?

In 1975, the National Institutes of Health sponsored the first AI in Medicine workshop at Rutgers University!

Artificial Intelligence in medicine is not new. As a health sciences university, supporting our students' understanding and developing their proficiency with AI is a necessity.

AI is driving significant advancements in health sciences:

  • Enhancing clinical decision-making through AI-powered diagnostic support systems
  • Revolutionizing medical imaging with AI-assisted interpretation and analysis
  • Improving patient care and monitoring with AI-driven predictive analytics
  • Advancing health informatics and data analysis for research and public health initiatives

Explore Further

AI Will Transform Teaching and Learning. Let’s Get it Right. (Stanford University Human-Centered Artificial Intelligence)

AI's Ascendance in Medicine: A Timeline (Cedars Sinai) "Scientists began laying the groundwork for artificial intelligence (AI) in the early 1950s and were exploring multiple AI medical applications by the 1970s. In the years since, the empowering technology has proliferated."

Developing reliable AI tools for healthcare (Google DeepMind) A must read! This is theoretical work. The question: " when is AI more accurate, and when is a human?"  A Google proposal: "CoDoC (Complementarity-driven Deferral-to-Clinical Workflow), an AI system that learns when to rely on predictive AI tools or defer to a clinician for the most accurate interpretation of medical images."

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