Collaborative Research: Using Adaptive Lessons to Enhance Motivation, Cognitive Engagement, And Achievement Through Equitable Classroom Preparation

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This project aims to serve the national interest by responding to the call to address the grand challenge of advancing personalized learning (National Academy of Engineering). This research and development (R&D) project will embark on a comprehensive conceptual replication and adaption effort to examine the degree to which prior knowledge, in the form of pre-class adaptive learning platform (APL) lessons/learning modules, is associated with student affective and cognitive outcomes in blended active learning classrooms. In a blended active learning classroom, students are expected to prepare before class, for example, by reviewing prior knowledge using videos and online assessments. Five engineering core courses taught at the sophomore and junior levels will serve as classroom settings for testing adaptive learning. This testing will be done by comparing "one-size-fits-all" pre-class activities delivered via the Learning Management System (LMS) with adaptive and flexible pre-class lessons delivered via an adaptive learning platform (ALP). Courses include Statistical Testing and Regression, Linear Circuits and Systems, Fluid Systems, Engineering Fluid Mechanics, and Computational Methods. A set of published assessments, including concept inventories, will be administered to compare students' cognitive and affective outcomes in the LMS and ALP environments. This R&D project will be used to (1) develop, improve, and deploy ALP lessons as well as the comparative LMS content in addition to in-class and post-class exercises for five courses at three institutions; (2) compare cognitive outcomes (i.e., conceptual, procedural, and higher-order problem-solving) and affective outcomes (cognitive engagement and academic motivation) with adaptive learning (experimental) vs. without adaptive learning (control) for blended classroom preparation; (3) analyze ALP analytics/metrics to study student learning behaviors (such as time spent on pre-class preparation, number of quiz attempts, and early completion counts) and their relationship to the outcomes; and (4) communicate findings and best practices via open educational materials, journal/conference articles, social media, websites, and faculty workshops. The development and research effort will be conducted through a collaboration of engineering and engineering education faculty and researchers at three institutions: the University of South Florida, the University of Central Florida, and the University of Pittsburgh. The investigation will focus on the role and association of prior knowledge (as fostered by student participation in pre-class activities and differential levels of student preparedness) with students' cognitive and affective outcomes, such as achievement, cognitive engagement, and academic motivation. The quantitative and qualitative mixed methods study will be framed by student background factors and student demographics (e.g., GPA, gender, ethnicity, age, Pell Grant status, transfer status), existing, published, and tested assessment instruments, and theories of and approaches to adaptive learning with AI-enhanced technology (RealizeIT). Parametric and non-parametric statistical approaches/methods and deductive and inductive approaches/framing will guide the data collection, analysis, and interpretation. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports creating, exploring, and implementing promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.