Course: MTRL 251, Materials Engineering
Instructor: Dr. Amir M. Dehkhoda, Assistant Professor of Teaching, Department of Materials Engineering, Faculty of Applied Science
Dr. Amir Dehkhoda employed Generative AI to revamp a core engineering course, thermodynamics, to boost student engagement and comprehension. In collaboration with faculty, students, and GenAI specialists, Dr. Dehkhoda explores effective GenAI tools and strategies for question generation and the creation of digital aids, promising a significant impact on student participation and overall learning experience. This approach not only enhances learning experiences but also fosters a culture of innovation, suggesting significant potential for applying these methods across various courses. The initiative aims to refine pedagogical practices through strategic GenAI tool integration, highlighting the evolving role of technology in education. His work integrates GenAI models for educational content, employing advanced AI like GPT-3.5, 4, Gemini, DALL-E, Eduaide, and Llama 2. It fine-tunes GenAI settings for optimal performance and rigorously assesses the quality of generated content and images, revealing GenAI’s potential in creating relevant educational materials. However, challenges in accurate visual representation persist.
In this article, Dr. Dehkhoda shares what motivated him to incorporate Generative AI tools into his teaching practice.
Was there a particular challenge, opportunity, or example (e.g., a colleague’s success or research insights) that motivated you?
I first noticed students using ChatGPT for small tasks, which made me realize that the adoption of Generative AI in education is inevitable. As educators, we have a responsibility to equip students with the skills to use these tools effectively, understanding both their strengths and limitations.
From my own experience, I found that GenAI can be particularly efficient for simple tasks, which encouraged me to explore its potential in my teaching. One of my key motivations was using GenAI to support a newly redesigned course by generating question banks, streamlining content creation, and enhancing student engagement. Additionally, my participation in UBC’s GenAI community sessions introduced me to various ways of integrating these tools into teaching and learning, further reinforcing my decision to experiment with their application in the classroom.
How do you see Generative AI supporting active or engaged learning in your course?
I have found that students are naturally curious about Generative AI, as it is a rapidly evolving tool that is beginning to impact their academic and professional lives. Whenever I introduce GenAI in class, I immediately notice increased engagement, particularly among first- and second-year engineering students. Beyond sparking curiosity, I have explored the potential of GenAI in active learning through a recent research project conducted under UBC’s Students as Partners (SaP) program. In this project, we investigated the ability of GenAI to create visual aids that illustrate complex and abstract concepts in a core engineering course. After extensive iterations and prompt engineering, we successfully generated images using non-scientific analogies to represent these abstract concepts. These visuals were integrated into the course, and the preliminary student feedback has been quite positive. However, this remains a challenging task that requires further refinement and research to ensure its effectiveness.
Another way we have incorporated GenAI into active learning is through assignments that encourage students to engage critically with the technology. In the same core course mentioned above (through SaP project), we designed an activity where students are asked to manually generate both conceptual and numerical questions and then create similar questions using GenAI tools. They are also required to solve these questions both manually and with GenAI, comparing the solutions to analyze the tool’s capabilities, shortcomings, and limitations in a technical context. This activity helps students develop a deeper understanding of both the subject matter and the role of AI in engineering problem-solving.
To ensure the responsible use of GenAI in learning, UBC has provided informative guidelines on safe AI usage, particularly concerning personal data protection. These guidelines help create a structured and ethical framework for incorporating AI tools into the learning experience.
What aspects of GenAI do you value most in your teaching? e.g. generate discussion, develop critical thinking/analysis, brainstorm ideas, creative thinking, etc.
So far, I have primarily used Generative AI in two key areas: developing question banks and creating visual aids for abstract concepts in a core engineering course. One of the aspects I value most is GenAI’s ability to generate non-scientific analogies for complex concepts. These visuals help students engage more effectively with the material, making abstract ideas more accessible and improving overall comprehension.
Additionally, I have designed activities where students use GenAI to generate conceptual and numerical questions, then compare the AI-generated content with manually created questions and solutions. This exercise encourages students to critically evaluate the accuracy, capabilities, and limitations of GenAI in a technical context. Developing this analytical mindset is essential, as it prepares students to use these tools responsibly and effectively in their future engineering careers.
Overall, I value GenAI’s role in fostering critical thinking, engagement, and active learning, helping students not only grasp complex topics but also reflect on the broader implications of AI in engineering problem-solving.
How does your use of AI align with broader trends in your discipline or at your institution? What role does collaboration play in your use of Generative AI in teaching?
There is a growing interest in Generative AI at UBC, with an emerging community focused on its integration into teaching and learning. Collaboration has been key to this effort, particularly through initiatives led by CTLT and recently ICICS Centre for Artificial Intelligence Decision-making and Action (CAIDA), which have organized seminars and workshops to explore GenAI’s capabilities, limitations, and best practices for its use in education. I believe that effective collaboration is crucial for integrating GenAI meaningfully into teaching and learning activities. I have been engaged with this community from its early stages and have witnessed a significant increase in interest among faculty members. That said, we must approach this transition with caution. While there is great potential, some trends in GenAI are overstated or overestimated, and we need a balanced perspective to ensure responsible adoption.
On a larger scale, we have partnered with colleagues from other departments to explore the development of a Retrieval-Augmented Generation (RAG) model at UBC. This initiative aims to create a structured template for our courses, improving the accuracy and relevance of Large Language Model (LLM) outputs in an academic setting. By leveraging collaboration across disciplines, we hope to refine AI-driven tools to better support engaged and effective teaching and learning. Ultimately, I see GenAI as part of a broader shift toward more interactive and engaged learning. However, careful consideration of its limitations, along with continued interdisciplinary collaboration, will be essential for its successful and responsible integration into higher education.
Have AI tools been used to enhance peer-to-peer collaboration, and what has been the impact on student learning experiences?
We have recently designed an activity where students, working in teams, use Generative AI tools to generate questions and then evaluate the accuracy, quality, and relevance of these AI-generated questions compared to manually created ones. This activity was one of the key outcomes of our Students as Partners (SaP) project, and we are currently implementing it in the course this term.
Since the activity is still in progress, we do not yet have concrete data on its impact on peer-to-peer collaboration or student learning experiences. However, we are in the process of designing surveys to assess its effectiveness. These surveys will be shared with students at the end of the course to gather feedback on how the activity influenced their engagement, teamwork, and critical thinking skills. The survey data will also help us refine and improve this activity for better implementation in future iterations.
We have recently designed an activity where students, working in teams, use Generative AI tools to generate questions and then evaluate the accuracy, quality, and relevance of these AI-generated questions compared to manually created ones. This activity was one of the key outcomes of our Students as Partners (SaP) project, and we are currently implementing it in the course this term.
Since the first round of implementing this activity is still in progress, we do not yet have concrete data on its impact on peer-to-peer collaboration or student learning experiences. However, we are in the process of designing surveys to assess its effectiveness. These surveys will be shared with students at the end of the course to gather feedback on how the activity influenced their engagement, teamwork, and critical thinking skills. The survey data will also help us refine and improve this activity for better implementation in future iterations.
What advice would you give to other educators interested in integrating Generative AI into their teaching?
My main advice to educators interested in integrating Generative AI into their teaching is to give it a try and remain open to the outcomes. There are many resources available to explore AI integration, along with established “safe” protocols to guide its responsible use, which can be found here:
Discussions around AI in education are diverse, with both strong support and valid concerns. These debates are important and understandable, but the reality is that GenAI is here to stay. Rather than resisting it, we should focus on how to use it effectively and ethically to enhance teaching and learning.
At the same time, it’s crucial to acknowledge that GenAI still has limitations and shortcomings that need to be carefully examined. If you have an idea for using AI in your course, experiment with it, assess its effectiveness, and refine your approach. Most importantly, we must remember that the role of educators and the human factor in using GenAI is critical. AI can be a powerful tool, but it is not a replacement for human expertise, judgment, and mentorship. As educators, our guidance ensures that students develop critical thinking skills, ethical awareness, and a nuanced understanding of AI’s capabilities and limitations.
Our role is to shape how AI is used in education, ensuring it complements—not replaces—the human elements of learning. Engaging with the GenAI community—whether through institutional initiatives, research collaborations, or peer discussions—can provide valuable insights and support. After all, we are a community of educators and researchers striving to improve student learning experiences and make a meaningful impact!