Read my Generative AI Statement for the broader philosophy and policy governing the use of generative AI in my courses. This page explains what the AI-Integrated Classroom means in practice and how learning is evaluated when AI is part of the normal working environment.
In an AI-Integrated Classroom, generative AI is treated as a normal part of modern intellectual and professional work. In many of my courses, especially programming courses, you may be expected or required to use AI as part of your work. The goal is not simply to teach you how to obtain answers from AI. The goal is to teach you how to use AI while continuing to develop the knowledge, judgment, and skills the course is designed to teach.
The central rule is simple:
You are responsible for understanding and being able to work with everything you submit, regardless of whether you created it yourself, created it with AI, or had AI generate substantial portions of it.
AI may be permitted, encouraged, or required depending on the course and assignment. When AI is required, its use is part of the course just as other professional tools are part of the course. You may be expected to develop proficiency in using AI effectively, critically, and responsibly.
More AI use is not automatically better. The objective is to use AI appropriately and effectively, not to maximize how much work you delegate to it.
AI can generate code, explanations, tests, documentation, designs, research summaries, and other material. You remain responsible for determining whether that material is correct, appropriate, and complete.
If AI produces an error and you submit it, it is still your error. If AI produces work that you do not understand, possession of that work does not demonstrate that you have learned the material.
Generative AI can now produce work that previously would have been strong evidence of student ability. A correct program, polished explanation, or well-written document is still useful evidence, but it may not by itself demonstrate that you possess the knowledge and skills represented by that work.
The artifact is evidence, not necessarily proof.
For that reason, assessment in an AI-Integrated Classroom may use multiple forms of evidence, including (but not limited to):
In programming courses, version control is part of the development process and may also provide evidence of how your work developed. You may be required to develop incrementally, test your work, make meaningful commits, and maintain a professional repository history as you complete assignments.
Version control does not reveal your private thought process, and it does not automatically prove who generated a particular piece of code. It does, however, preserve useful evidence of development, revision, testing, correction, and the progression of a software project.
You may be asked to explain, trace, debug, modify, extend, or otherwise demonstrate understanding of work you submitted. This may occur as a normal part of grading and does not necessarily mean that you are suspected of academic misconduct.
If understanding is part of the learning objective, being unable to demonstrate that understanding may reduce or eliminate credit even when the submitted artifact appears to be correct.
Becoming proficient with AI is valuable, but it is not a substitute for becoming proficient in the subject of the course. For example, obtaining a working program from AI does not by itself demonstrate programming competence.
You may therefore be evaluated both on your ability to use AI effectively and on your understanding of the underlying discipline. These are related skills, but they are not the same skill.
The AI-Integrated Classroom does not attempt to keep AI out of your education. It teaches you to use AI without surrendering the responsibility to think, learn, evaluate, verify, and make decisions for yourself.
The goal is for you to become more capable because you use AI—not less capable because you depend on it.
The AI-Integrated Classroom is the educational application of Intellectual Agency: principles and practices for maintaining human competence, judgment, learning, and responsibility in the age of artificial intelligence.