2026 ASEE Annual Conference & Exposition

From Textbook to Reality: AI‑Crafted Homework Narratives and Student Perceptions of Real-World Relevance

Presented at Mechanical Engineering (MECH) Session 2: AI and Emerging Technologies in Mechanical Engineering Education

This evidence-based Work in Progress (WIP) paper explores the incorporation of Artificial Intelligence (AI)-generated narratives in homework assignments in undergraduate-level thermodynamics course and shares initial findings regarding students’ perspectives on the real-world relevance of the homework questions.
Homework is a cornerstone of education, providing opportunities for practice and deeper understanding of concepts. Traditionally, homework assignments are criticized for lacking relevance to real-world experiences, which can limit motivation and the perceived value of academic work, especially in courses without laboratory activities. Recent innovations in educational practices emphasize narrative-rich, contextually meaningful assignments that bridge classroom learning with real-life applications, triggering both emotional and cognitive engagement.
In this study, narrative homework problems were initially drafted with the assistance of generative AI tools, which were prompted with textbook problem statements and then human curated for factual genuineness and clarity. The advent of such AI support offers a new way to generate diverse, realistic, and personalized experiences, both for teachers and students. By surveying students, this study aims to understand how the integration of AI-generated narratives in homework assignments of a theoretical course improves students' perceived relevance, engagement, and understanding of academic content.
Our preliminary results point to a trade off: while narrative framing can improve understanding and perceived real world relevance of the homework questions, the additional contextual detail may also introduce extraneous cognitive load. Future iterations of the narratives will therefore adjust the amount and placement of contextual information to better balance this engagement-load trade off. The future work will identify effective strategies and key challenges for integrating AI into engineering education in this context.
The authors intend to present a postcard to share the preliminary findings from this WIP study.

Authors

Dr. Rubaiya Murshed http://orcid.org/https://0000-0001-7661-893X Embry-Riddle Aeronautical University - Prescott [biography]

Dr. Murshed is a faculty in the department of Mechanical Engineering at Embry-Riddle Aeronautical University in the Prescott campus. She is currently at her first year of academic profession. She is currently exploring education research. She has recently received an innovative teaching grant and student-as-partner grant from the center for teaching and learning excellence at Embry-Riddle. Her paper, published at the ASEE Annual Conference in 2025, received the second best paper award in the New Engineering Educator (NEE) division
Mr. Dario Ajdini Embry-Riddle Aeronautical University - Prescott [biography]

Dario Ajdini is an international student from Italy currently pursuing a degree in Mechanical Engineering in the United States. His academic interests are centered on energy and its application within engineering systems and modern technology. Through his coursework and academic development, he has cultivated a strong interest in improving energy efficiency and exploring engineering solutions to contemporary challenges. His long-term professional goal is to establish a career in the energy sector and contribute to the advancement of efficient and sustainable energy systems.
Rojvan Dersim Duderi Karaer Embry-Riddle Aeronautical University - Prescott [biography]

Rojvan Karaer is an undergraduate student from the Netherlands at Embry-Riddle Aeronautical University, currently pursuing a Bachelor of Science in Aerospace Engineering. Aerodynamics, flight mechanics, and the application of engineering ideas to actual aircraft systems are his areas of scholarly interest. He has good analytical and problem-solving abilities thanks to his coursework and project experience, especially in computational techniques and engineering analysis. He is particularly interested in finding creative answers to challenging engineering problems and improving system performance. His long-term career objective is to work on sustainable and effective aircraft design in order to progress the aerospace sector.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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