Event Phone: 1-610-715-0115

Cancellation Policy: If you cancel your registration two weeks or more before the course is scheduled to begin, you are entitled to receive your choice of either a credit for a future seminar (which can be applied toward any of our courses) or a refund of the registration fee (minus a processing fee of $50). 

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 3-Day Livestream Seminar Taught by Charles Crabtree, Ph.D.

AI is rapidly changing teaching, learning, and assessment. Traditional assignments such as take-home essays, reflection papers, and online quizzes no longer reliably show whether students independently understand the material or simply used AI tools effectively. In this workshop, we will explore how AI agents can be used to improve teaching, strengthen assessment, and create more engaging learning environments.

You will learn how to use AI agents to redesign assignments, develop simulations and interactive classroom activities, improve grading and feedback systems, and create more AI-resilient courses. We will focus on practical, transparent workflows that preserve instructor judgment rather than automate teaching.

We will also introduce emerging frameworks such as Model Context Protocol (MCP) and AI integration with learning management systems, such as Moodle, Canvas, and Blackboard. Throughout the workshop, you will work directly with your own syllabi, assignments, rubrics, and course materials.

By the end of the seminar, you will have developed practical, course-ready tools you can immediately apply in your own teaching, including:

• • A course-specific teaching agent workflow.
  • Redesigned assignments and classroom activities adjusted for AI-enabled learning environments.
  • Practical strategies for improving grading consistency, feedback quality, and rubric clarity.
  • Student-facing AI policy language and transparent AI use guidelines.
  • A clear framework for deciding where AI can support teaching and where instructor judgment should remain central.

The workshop is not about tricks with prompts, automated grading, or replacing instructors with AI systems. The focus is on building controlled, transparent, and pedagogically defensible workflows.