Join us to discuss how generative AI is shaping your discipline in terms of education and research. The meetings will be led by a faculty member for 25 minutes followed by 20 minutes of discussions. 

The April 30 session will be led by Emily Jensen, PhD student in computer science and cognitive sciences. 

Title: Skill acquisition using automated feedback from generative AI systems.

Abstract: Providing automated feedback to learners is rapidly emerging as a key application of generative AI in education and workforce training. Our work looks at using generative AI for tasks that involve learners acquiring skills in “psychomotor” tasks such as flying drones or operating a robotic arm. In these contexts, learners complete a set of “practice tasks” that involve teleoperating these systems through a user interface. Such skills are in high demand across a variety of disciplines including aerospace, construction, defense, and medicine. We demonstrate how generative AI systems can be prompted to provide feedback to learners for such tasks with the prototypical example of landing a drone.

We will demonstrate a system that we have built here at CU Boulder that provides feedback for simple desktop-based control tasks and present some preliminary results. We will also discuss how AI-generated feedback can be a useful tool to quickly integrate into existing technical systems.

Join us to discuss how generative AI is shaping your discipline in terms of education and research. The meetings will be led by a faculty member for 25 minutes followed by 20 minutes of discussions. 

The April 30 session will be led by Emily Jensen, PhD student in computer science and cognitive sciences. 

Title: Skill acquisition using automated feedback from generative AI systems.

Abstract: Providing automated feedback to learners is rapidly emerging as a key application of generative AI in education and workforce training. Our work looks at using generative AI for tasks that involve learners acquiring skills in “psychomotor” tasks such as flying drones or operating a robotic arm. In these contexts, learners complete a set of “practice tasks” that involve teleoperating these systems through a user interface. Such skills are in high demand across a variety of disciplines including aerospace, construction, defense, and medicine. We demonstrate how generative AI systems can be prompted to provide feedback to learners for such tasks with the prototypical example of landing a drone.

We will demonstrate a system that we have built here at CU Boulder that provides feedback for simple desktop-based control tasks and present some preliminary results. We will also discuss how AI-generated feedback can be a useful tool to quickly integrate into existing technical systems.