2026 ASEE Annual Conference & Exposition

Effective self-regulated learning (SRL), the process through which learners take active control of their learning by planning, monitoring, and reflecting on their progress toward academic goals—is a critical skill for both academic achievement and lifelong professional success in engineering. Engineers must continuously adapt to emerging technologies, tools, and methodologies, yet many undergraduates progress through engineering programs without mastering the skills needed to learn effectively and independently. Research consistently shows that engineering students frequently rely on inefficient strategies such as rereading, highlighting, and rote memorization—approaches that undermine conceptual understanding, long-term retention, and the transferability of knowledge.
Although the importance of SRL for student success is widely recognized, there remains limited understanding of effective ways to help students strengthen this skill. Prior studies indicate that SRL interventions are most impactful when situated within the learning context; however, how instructors can effectively support students in enacting SRL within engineering courses is still underexplored. Common pedagogies in engineering education—such as project-based learning, formative assessment design, exam wrappers, and flipped classrooms—implicitly encourage students to plan, monitor, and evaluate their learning. Yet research suggests that such indirect activation, while valuable, is often insufficient to cultivate metacognitive awareness or promote the transfer of SRL skills to new contexts. Recent work highlights the importance of explicit SRL instruction, enabling students to develop the cognitive and metacognitive skills required to intentionally and effectively integrate evidence-based learning strategies into their learning processes.
This NSF Improving Undergraduate STEM Education (IUSE) Engaged Student Learning (ESL) level 1 project develops, implements, and evaluates course-integrated SRL interventions that leverage the synergy between explicit instruction and indirect promotion of SRL in engineering courses. The explicit component teaches evidence-based learning strategies, such as active recall, concept mapping, elaboration, self-explanation, and spaced or interleaved practice, while fostering growth mindset and metacognitive reflection. The indirect component embeds these strategies within authentic engineering coursework through evidence-based learning strategies assignments, projects, and post-exam reflections, prompting students to plan, monitor, and regulate their learning as part of disciplinary problem-solving. Grounded in SRL theory, the project examines the feasibility, student engagement, perceptions, and preliminary impact of integrating SRL instruction directly into core engineering courses, with particular attention to changes in students’ motivation, use of effective learning strategies, and course performance.
During the first two project years, we have implemented the interventions in four foundational courses in Mechanical and Aerospace Engineering (MAE 30A, Statics and Intro to Dynamics, MAE 131A – Solid Mechanics I) and Electrical and Computer Engineering (ECE100 – Linear Electronic Systems; ECE 35 – Introduction to Analog Design), reaching over 1500 students. We used a mixed-methods research method combining quantitative and qualitative data to examine (1) how students’ learning strategies, motivation, and mindset changed before and after the intervention, (2) how participation intensity predicted performance, and (3) how students perceived their learning processes through reflections and feedback. Across courses, students benefit from the course-integrated SRL interventions regarding performance, effective learning strategy use, and motivation. At the same time, the study identified key design characteristics, including task relevance, scaffolding, feedback, and incentive structure, that most strongly influenced participation, offering valuable guidance for refining engagement strategies and improving scalability.