AI and Student Learning (2025)
About This Course
AI and Student Learning
Course Description
Artificial intelligence (AI) has made a remarkable entry into education, leaving educators with a mix of emotions. This course will help educators navigate this new frontier by exploring different types of AI and their applications, the ethical challenges and dilemmas of AI in education, the impact of AI on teaching and learning, and the design of activities and assessments that incorporate AI. Upon completion of the course, participants will have the knowledge necessary to make informed decisions about how AI can be effectively integrated into their teaching practices.
Self-Paced Course
1 Credit USBE or SUU
Level: Beginner
Cost: Free to Utah Educators
Instructor
Braxton Thornley
Braxton specializes in using technology to personalize learning and utilizing artificial intelligence to promote student success. Before joining UEN’s professional development team, Braxton worked as a high school language arts teacher and digital learning coach in Jordan School District. During his time in Jordan, Braxton was recognized as a “Most Valuable Educator” by Instructure and the Utah Jazz, a “Top Fifty Imaginative Teacher” by Disney, and one of the district’s twelve “Outstanding Educators of the Year” in 2022. Braxton holds ESL, educational technology, and instructional coaching endorsements in addition to a Bachelor’s degree in English education from Utah Tech University. He is currently pursuing an M.Ed. in K-12 School Leadership at the University of Utah.
Expected Learning Outcomes
- Explain key terms and ideas related to generative artificial intelligence.
- Discuss their philosophies of education in relation to the rise of generative artificial intelligence and Utah’s Portrait of a Graduate.
- Describe the ethical considerations surrounding the use of generative artificial intelligence in various educational and non-educational contexts.
- Design learning tasks and assessments that center a process over a product.
- Write simple and complex prompts.
- Describe the current limitations of large language models and those limitations’ implications for the use of generative artificial intelligence in the classroom.
- Describe the current state of image-, music-, and video-generation AI tools.
- Generate educational resources using education-specific AI tools, such as MagicSchool, SchoolAI, or Skill Struck.
- Evaluate the efficacy of learning activities designed around student-facing use cases for generative artificial intelligence.
- Evaluate and critique the use of generative AI tools in classroom environments.
Final Assessment
The assignment requires participants to evaluate three scenarios by completing a graphic organizer. For each scenario, participants must categorize the described AI implementation based on the Student-Facing AI Checklist, justify their categorization using ethical principles, identify potential improvements, and assess whether the AI tool used in the scenario was the best choice.
Participants can complete coursework anytime at their own pace. Modules stay open all year, and assignments are accepted through December 31, 2025. The instructor grades at least twice a month, typically around the 1st and 15th.