AI Training Modules for Students
Coming in fall 2026, the student training modules for AI are online, asynchronous, and interdisciplinary modules that aim to equip students with the knowledge and skills to navigate the AI landscape in their academic and professional careers. Created by a group of faculty consultants and CTL staff members, these modules cover fundamental ideas including how AI works, its ethical implications, significance for academic integrity, and specific student applications of AI with consideration to these areas. The modules will be available in D2L for all faculty, and they can be used all at once or in pieces to fit the needs of individual classes.
Learning Outcomes
The student training modules for AI were designed for the following learning outcomes, each of which corresponds with a specific module.
- Explain the core details of how artificial intelligence works and compare different types and models of AI.
- Examine the role and consequences of academic integrity within a variety of AI use cases to evaluate issues related to authorship, attribution, intellectual property, and responsible AI use.
- Assess the ethical implications of AI to make informed choices about AI use across local and global settings.
- Adapt AI tools and strategies for appropriate academic and professional use.
Module Structure
Each module addresses a distinct area for AI literacy. While the modules are scaffolded and can be used to build upon each other in order, they can also be used discretely depending on the needs of specific courses.
The modules consist of a combination of written content and interactive activities to help students apply their knowledge and achieve the learning outcomes.
The modules use the following structure:
- Foundations of AI: This module explains how AI works and how AI models are trained so that students can understand and differentiate between the types of AI and define related concepts. Students will investigate how AI is used in real-world situations and learn what effective AI prompting looks like.
- Academic Integrity: This module defines how AI fits into DePaul’s academic integrity policy to help students navigate the varying AI policies implemented in their courses. Students will learn how to cite and disclose their use of AI, if it is permitted in their classes, and they will gain clarity around how AI detectors work and what to do if their work is flagged.
- Ethical Considerations of AI: This module explores the multitude of ethical concerns that are raised with AI use. Framed as "Rights to Protect" and "Responsibilities to Fulfill", each concept in this module raises questions for students to evaluate as they think about the effects of AI on various personal and professional sectors.
- Using AI as a Student: This module provides practical applications for AI in academic and professional settings. With consideration to the concepts of the previous modules, the content in this module will equip students with actionable strategies for effective and responsible use of AI.