Join the College of Engineering Faculty Teaching Fellows for a community speed session on pedagogical practices in computing, construction, and engineering, hosted by the Engineering and Computing Education Core.
This hour and a half long session will include several short presentations from Faculty Teaching Fellows on using AI in the classroom, peer instruction, and other assessment and instructional strategies.
Full details of each presentation, with a description from the presenter:
- Tony Roebuck – Integrating a Flipped Classroom Model with Universal Design for Learning (UDL) to Increase Sense of Belonging in Students: “A flipped classroom aligns with the principles of Universal Design for learning by providing multiple means of representation, engagement, and expression, allowing for flexibility in learning and catering to diverse student needs; essentially making learning more accessible for all learners.”
- Milad Roohi – AI-Augmented, Open-Source Computational Learning for Engineering Education: “AI-augmented computational learning in engineering education leverages Artificial (or Augmented) Intelligence (Al) to improve teaching methodologies, optimize learning experiences, and enhance problem-solving skills for engineering students. It integrates AI-driven tools, adaptive learning systems, and intelligent tutoring to create more effective, personalized, and scalable education.”
- Moe Alahmad – Self-Assessment of Ways of Lerning: Keep-Stop-Start: “Purpose of this activity to learn from the students about the class's Content, Form, and Function dynamics. This is used to improve the learning setting via changes the instructor implements as an outcome of the feedback.”
- Bhuvana Gopal – Peer Instruction: “A small group pedagogy where students answer real time mini quizzes during a lecture, and discuss possible outcomes with peers to answer the same questions again.”
- Emmeline Watson – AI-Driven Learning: Enhancing Discussions and Podcasting in the Classroom: “I will share insights on implementation, benefits, and challenges, demonstrating how AI can enhance both student participation and learning outcomes.”
- David Mabie – Empty Outlines: “Lectures are structured around a handout that includes talking points, figures, examples problems etc.”
- Sangjin Ryu – Infusing Personal Passion into Teaching: Japanese Animation and Teaching: xxxxx.
- Quiming Yao – AI as a ‘solution’ in computer science’s muddiest points: ”Use a simple sentence to describe the most difficult part or most confusing part in learning materials, and ask AI for solutions.”
We welcome all faculty in the College to join via Zoom on March 31 at 2:30 p.m.
If you would like to attend, please register at the link below.
More details at: https://go.unl.edu/speedsession