Paulo Carvalho, an assistant professor in Carnegie Mellon University's Human Computer Interaction Institute, has received a National Science Foundation (NSF) Faculty Early Career Development (CAREER) Award. The grant will support his research into the reciprocal relationship between student motivation and learning strategies.    

Researchers have long identified study techniques that can improve learning and help students retain information, but students do not always use these methods or may eventually abandon them. Carvalho's project will examine the role motivation plays in that disconnect. Specifically, he will study how motivation influences a student's willingness to use effortful and effective study strategies and how the perceived difficulty of those strategies influences motivation.    

Through a combination of controlled laboratory experiments and real-world studies in introductory college chemistry courses, Carvalho aims to better understand when these strategies succeed and which students benefit most from them. The findings will provide a roadmap for developing next-generation, AI-driven learning tools. By understanding the "motivation friction" students encounter, Carvalho hopes to create systems that don't just track accuracy, but also intelligently adapt to support student persistence and engagement when material gets difficult.

Carvalho's broader research focuses on learning engineering — using computational modeling, large-scale educational data mining and AI to transform how we understand student cognition. By applying these methods to real-world digital classrooms, he works to design adaptive technologies that mirror the effectiveness of one-on-one human tutoring.

The CAREER program supports early career faculty who have the potential to serve as academic role models in research and education. Carvalho's award is supported by the NSF STEM Education Directorate's Core Research program.

For more information, visit the NSF CAREER Award website.