Home
Instructional Considerations for
AI in Education
Using AI
AI should be used to support and extend human thinking, not replace it. When the goal is to enhance creativity, analysis, or problem-solving, AI is an appropriate tool. When the goal is to substitute human judgment or effort entirely, it becomes a less appropriate use.
AI-Supported Learning
Integrating AI into engineering coursework helps students prepare for real-world challenges. By applying AI to authentic problems, students practice predictive analysis, optimization, and decision-making—skills essential for modern engineering practice.
AI Guidance Statements
We provide sample statements and best practices for AI use in course syllabi. These examples help instructors set clear expectations for students and promote effective, responsible integration of AI in the classroom.
AI Academic Integrity and Ethics
We highlight key issues of academic integrity and ethics when using AI in coursework and research. To support instructors and students, we share articles, policy examples, and online resources that encourage responsible use of AI.
Introduction to AI in Education
The purpose of this resource is to provide guidance and resources on the use of Artificial Intelligence (AI) in the Grainger College of Engineering. For explicit use policies, please refer to appropriate governing documents (e.g., course syllabi, unit bylaws, etc.).
Broadly speaking, AI is a technology that allows machines and computers to mimic and simulate human learning and comprehension, leading to apparent decision-making, creativity, and autonomy. This technology has been used for decades, colloquially identified as “machine learning” and “deep learning” in recent years. However, most recent attention has focused on generative AI (gen AI). Gen AI is a technology that can create original text, images, videos, etc. Gen AI utilizes deep learning and machine learning to take inputted data (initially either user-supplied or via a repository), synthesize it, and output it in a way that is original based on the user’s query. The inputted data is now typically in a repository, known as the “training data”. In certain instances, this training data is tera- or petabytes in size and may be sourced from the internet.
Gen AI is important as it is the next technological tool in education. Just as math curricula have evolved from the slide rule, to a simple calculator, to a graphing calculator, engineering curricula should harness gen AI as an effective tool to promote teaching and learning.
Users of gen AI at the University of Illinois could include everyone. Gen AI can be used by faculty for idea creation, lesson planning, or rubric creation. Students can utilize gen AI for writing and proofreading documents, lab reports, and essays, and they can also use it for code generation and verification. Creating *good* content via gen AI requires the user to understand the problem and craft/edit gen AI prompts and responses. A simple input into a gen AI algorithm will most likely lead to a poor, or even nonsensical, result.
AI platforms are constantly evolving, with new releases and updates appearing frequently. Leading platforms include ChatGPT, Microsoft Copilot, Claude, Google Gemini, and Illinois Chat, among many others. These services often offer multiple tiers—free, paid, or subscription-based—each with different capabilities and features.
This resource provides platform-agnostic guidance applicable across AI tools. While we may reference specific platforms for illustration, the principles and strategies presented here translate broadly to most AI systems.