A new initiative at USF鈥檚 College of Engineering aims to revolutionize engineering education through adaptive learning technology. Spearheaded by Principal Investigator Autar Kaw and Co-Principal Investigator Rasim Guldiken, this project is part of a larger national effort to advance personalized learning and optimize classroom preparation for STEM students. Supported by a $383,172 grant from the National Science Foundation (NSF), this research addresses the National Academy of Engineering's grand challenge of enhancing personalized education. Learn more about the award .
The project will test adaptive learning modules in five key engineering courses offered at the sophomore and junior levels: Statistical Testing and Regression, Linear Circuits and Systems, Fluid Systems, Engineering Fluid Mechanics, and Computational Methods. The goal is to evaluate how a tailored, pre-class adaptive learning platform (ALP) impacts student outcomes in these courses, as opposed to traditional "one-size-fits-all" materials delivered through the standard Learning Management System (LMS).
Using adaptive lessons, USF researchers hope to assess improvements in students' cognitive and affective outcomes, such as engagement, motivation, and problem-solving skills. The ALP lessons are designed to meet each student at their individual level, adapting based on their understanding and interactions with course materials. By preparing before class using these tailored resources, students can enter the classroom better equipped for deeper engagement in active learning environments.
Artur Kaw reports, 鈥淪ince 2016, using adaptive learning in the Computational Methods course has enhanced students' cognitive learning and course satisfaction. Adaptive learning customizes the experience and decreases students' time on the course. In 2022 and 2023, data from the platform was used to identify students needing one-on-one tutoring early in the semester. Previous grants focused on the flipped classroom approach, though. The current grant investigates whether ALP lessons in the more common blended classroom modality can achieve similar or better outcomes.鈥�
A Typical ALP lesson
This research also emphasizes data-driven insights into student learning behavior. The project will collect and analyze data on how much time students spend on preparation, their quiz attempt frequencies, and how early they complete assignments. These analytics will then be correlated with performance outcomes to determine the platform's effectiveness.
As a collaborative effort, the project involves researchers and engineering education faculty from three institutions: USF, the University of Central Florida, and the University of Pittsburgh. The collaboration will focus on understanding the role of prior knowledge in students' academic success, including examining how factors like engagement and motivation vary based on individualized preparation.
In addition to fostering improved student outcomes, the researchers aim to disseminate their findings to a broader academic community. They will publish open educational materials, journal articles, and best practices, along with hosting faculty workshops to share insights into implementing adaptive learning.
A typical knowledge map in a ALP lesson
This initiative is part of the NSF's IUSE: EDU Program, which funds projects that enhance STEM education effectiveness for all students. With its emphasis on adaptive technology and innovative teaching practices, the project at USF's College of Engineering aims to create a more inclusive and successful learning environment, contributing to the NSF's broader mission to support high-impact educational research in STEM.
Students and faculty at USF can look forward to a future where personalized learning might reshape the engineering curriculum, making it more adaptable and engaging for all students. The research project reflects a growing trend in academia to prioritize flexible, student-centered education, paving the way for future engineers to not only succeed but thrive in an ever-evolving field.