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Emily Jensen, PhD candidate in computer science
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 ��ƷSM����ӰƬ 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.

Kayla Kohake and the Office of Academic Leadership and Innovation (ALI) Learning Design Team
Abstract: The Learning Design Team with the Office of Academic and Learning Innovation (ALI) at the ��ƷSM����ӰƬ has recently released an exploratory course called “AI for Course Design.” This scaled, online course, which is hosted on Coursera, curates materials about AI and dives into how instructors at ��ƷSM����ӰƬ are currently integrating generative AI (GAI) into their courses for student activities and/or the development of course materials.  In this presentation, we share the perspectives, insights, and practices from those who participated in our Coursera course. We will highlight varied approaches to AI-integrated teaching and learning then discuss with participants what the future of education might look like. We encourage attendees to openly share their perspectives on integrating AI into their classrooms and engage in critical discourse about the benefits and challenges of GAI in education. 

Ivan Portilla, Applied Math
Abstract: Join us for an enlightening talk on "Leveraging ChatGPT in Education: Insights and Strategies"! Discover how generative AI is revolutionizing teaching and learning by personalizing education, automating administrative tasks, and supporting students around the clock. We'll dive into the practical applications, share real-life examples, and discuss the challenges and ethical considerations of integrating AI tools like ChatGPT into educational settings. Whether you're an educator, administrator, or just interested in the future of education, this talk will provide valuable insights into the effective and responsible use of AI in classrooms. Don't miss out on learning how to navigate this exciting new frontier!

Danny Dig, Computer Science
Abstract: Many are asking will Generative AI and Large Language Models (LLMs) put programmers out of business? This talk offers a refreshing perspective. We delve into how Generative AI is empowering a new wave of computing enthusiasts, untrained in traditional software development, to innovate, change, and evolve programs. We first present upcoming features in leading IDEs that harness Generative AI. These features not only aid developers but also cater to computing enthusiasts and helps them by (i) explaining code, bug fixes, summarizing recent changes, (ii) generating documentation, commit messages, name suggestions, etc. However, a top concern remains the trustworthiness of the solutions provided by Generative AI. While many solutions resemble the ones produced by expert developers, LLMs are known to produce “hallucinations” – solutions that seem plausible at first, but are deeply flawed. To increase our trust in LLM solutions, we conducted novel research that synergistically merges the creative prowess of LLMs with the safety net of static and dynamic analysis from program transformation systems. The evaluation results show the usefulness of our novel approach, heralding a new era where LLMs become effective AI assistants for both developers and enthusiasts. We hope to inspire you with ideas on how LLMs can help us broaden the field of programming and help you and your work and research go even further.

In this session, we explored how to:

• Formulate effective prompts using AI for different purposes (e.g., generating discussion, guiding problem-solving, stimulating creative thinking)
• Use context and formatting cues to guide AI responses
• Work with Generative AI in a way that complements and enhances traditional teaching methods, rather than replacing them.

Diane Sieber, Associate Professor, Herbst Program
I’ve developed guides and exercises for students to learn to write more productively and at higher quality by co-authoring with generative AI.  Results so far–after 3 semesters of iteration–indicate that generative AI can “level the playing field” for students who arrive at ��ƷSM����ӰƬ with writing deficits or less extensive writing backgrounds: both dialogic co-authoring with AI and use of generative AIs as shame-free/face-saving writing coaches lift up students to functional writing levels and lay a foundation for developing advanced writing proficiency. These approaches help faculty to address student writing challenges more effectively and with less time investment. Our course materials also address the ethics of generative AI use, as well the ethics of genAI training and data sourcing.

  Download Diane's writing prompts

Bobby Hodgkinson, Teaching Assistant Professor, Smead Aerospace
In our recent projects, we've focused on increased efficiency through AI integrations, including the use of a sentiment analysis tool for Aerospace lab course peer evaluations, which integrates with Canvas for efficient document handling and uses ChatGPT to paraphrase lower scores with constructive feedback. We've also introduced a lab report grading assist tool that employs ChatGPT to match specific sections with grading rubric criteria and are in the early stages of creating a Diversity, Equity, and Inclusion (DEI) assistant tool to guide faculty in making course materials more DEI-friendly. My aim is to lead a discussion on the role of AI in personalized education, exploring the concept of an "AI tutor" for tailoring learning experiences, and using AI to increase the efficiency of the grading process to give students more meaningful feedback in a shorter amount of time.

 William Kuskin, Associate Dean for Digital Education
The New York Times label 2012 “The Year of the MOOC,” Thomas Friedman of the New York Times announced “Welcome the college education revolution.”  It was not until 2019, however, that the real revolution in digital learning came to every classroom, not as a great disruption, but as a collateral effect of quarantine. William Kuskin will explore the development of the MS-EE as following out the promises of the initial, failed, revolution, and lead a discussion of how we might imagine a greater use of digital education overall.

Abby Rose, Program Manager for the Office of Engineering Digital Education
Erica Reid, Program & Marketing Manager for the Department of Electrical, Computer & Energy Engineering
Kaitlyn Rye, Graduate Advisor, MS-DS
If you can do the work–and prove it–you’re admitted! That is the motto of ��ƷSM����ӰƬ’s MEEM, MSDS, and MSEE on Coursera programs. No application, no transcripts, no letters of recommendation, nothing. This system of Performance Based Admissions (PBA), by which students can elect to take a for-credit course without going through an admissions process and gain admission to the degree program if they achieve and maintain a grade level, has consequences for how we consider online learning overall. Representatives from the Office of Digital Engineering, the Data Science Program, and the Department of Electrical, Computer, and Energy Engineering will share Boulder’s performance-based admissions experience and results from 3 years of admissions and graduations. In this session, presenters will share Boulder’s pure performance-based admissions experience and showcase learning behaviors and teaching practices that lead to student success.

Christy Bozic, EMP Faculty Director
Ron Duren, Teaching Assistant Professor
Jessica Leeker, Stephen M. Dunn Professor of Engineering Management and Entrepreneurship
Michael Readey, EMP Associate Faculty Director
The Engineering Management Program launched its first degree on the Coursera platform, the ME-EM, on Monday, August 23, with an initial set of three courses and 214 students. Profs. Bozic, Duren, Leeker, and Readey will discuss their work in creating these early courses, as well as their goals for the degree program overall.

Randall Fullington, Executive Director for Academic and Learning Innovation
Jenny Lane, Assistant Director of Program Development
Scott Millspaugh, Assistant Director of Learning Experience Design
The Office of Academic and Learning Innovation is the campus’ central facilitator for at-scale for-credit and non-credit programs and courses. ALI collaborates with faculty and staff to grow ��ƷSM����ӰƬ into the vanguard of online education, while also inspiring the campus to rethink on-campus and hybrid learning experiences. Randall Fullington, Scott Millspaugh, and Jenny Lane will conclude the semester’s seminars by partnering with us to think about the future of higher education at ��ƷSM����ӰƬ.