Studying how students learn earns faculty 2026 Teaching Scholar Award
Three Virginia Tech faculty members are examining learning from the students’ side of the classroom, turning questions about motivation, technology, and understanding into better approaches to teaching.
Winners of the 2026 Teaching Scholar Award include (from left) Margaret Ellis, Brett Jones, and Sally Hamouda. Photos courtesy of subjects. Photo collage by Christina Franusich for Virginia Tech.
For Margaret Ellis, Brett Jones, and Sally Hamouda, some of the most consequential questions about teaching begin not with what happens at the front of a classroom, but with what happens among the students sitting in it.
What makes them engage? What causes them to struggle? When does technology deepen learning — and when might it circumvent it? And how can evidence gathered in one classroom ultimately improve learning across disciplines, and even institutions?
Their pursuit of answers draws on expertise, technology, and ideas from beyond their own fields. That work earned the three faculty members recognition through the 2026 Teaching Scholar Award for Scholarship of Teaching and Learning. Presented by the Center for Excellence in Teaching and Learning, the award recognizes faculty who systematically investigate teaching and learning and share their findings so others can examine, test, and build upon them.
From research to results
Since 2019, Ellis, professor of practice in the Department of Computer Science, and Jones, professor in the School of Education, have combined expertise in computer science and educational psychology to study student motivation, engagement, and achievement.
Using Jones’ MUSIC Model of Motivation, their research examines the way students’ perceptions of the classroom environment shape the effort they invest — and ultimately, how well they perform.
For Ellis, the findings inspired changes in the classroom: breaking complex programming projects into smaller milestones, reducing the weight of major assessments, clarifying expectations, and providing more frequent feedback.
Their collaboration has influenced the learning experiences of more than 6,000 students and produced a growing body of peer-reviewed scholarship.
With support from a nearly $400,000 National Science Foundation grant, their research also showed that when teaching assistants are trained on the MUSIC model, "they foster a more positive motivational climate," said Ellis. That, in turn, leads to measurable improvements in both student expectations and performance.
Margaret Ellis and Brett Jones. Photo courtesy of Margaret Ellis.
Similarly, Hamouda, collegiate professor in the Department of Computer Science, examines where understanding can falter — and how emerging technologies and authentic experiences can help strengthen it.
Across both undergraduate and graduate courses, her scholarship examines persistent misconceptions in computing, project-based learning, authentic and global datasets, and the rapidly evolving role of generative artificial intelligence in education.
With grant support from Virginia Tech’s Technology-enhanced Learning and Online Strategies (TLOS), she has extended the work beyond a single course or classroom.
“Receiving this award is especially meaningful because it recognizes the role of TLOS in creating innovative learning experiences for students of all ages,” Hamouda said.
Those efforts include CodeKids, which brings hands-on computer science and AI activities to K-12 students, and Datopia, an immersive platform that allows university students to explore global datasets through virtual reality.
“I've seen how real-world experiences make complex ideas more accessible and engaging,” Hamouda said. “These projects have reinforced my belief that students learn best when they can connect technology to the world around them.”
Sally Hamouda. Photo by Tonia Moxley for Virginia Tech.
That same philosophy shapes her classroom teaching. In Database Management Systems, Hamouda redesigned the course around real-world and global datasets, incorporating structured checkpoints, peer evaluation, real-time polling, and individual practice to better reveal whether students understand underlying concepts.
Together, their work shows what can happen when the boundaries between disciplines, technologies, and learning environments become more porous. Questions raised in one classroom draw on expertise from another and return as better teaching.
