Engaging students of color in physiological computing with insights from eye-tracking

Abstract

Computing involving physiological data such as heart rate and electrodermal activity has been used as a way to enrich K-12 students’ computing learning experiences. This study explored a novel way to engage elementary students of color as “developers” through a series of physiological computing lessons during a summer learning program. Learners used real-time physiological data (i.e. muscle energy) as computer inputs to build computer programs. The study used an explanatory mixed method by combining multi-dimensional eye-tracking metrics data with qualitative investigation to reveal the visual attention of students with different programming proficiency levels. The regression analysis revealed three statistically significant predictors of students’ programming performances. Subsequent qualitative case studies provided additional insights into students’ problem-solving processes. Interpretations and caveats are presented and discussed.

Keywords:

• Technology integration
• mixed methods
• computer science
• elementary (grades 3-5)

Disclosure statement

The authors report there are no competing interests to declare.

Additional information

Notes on contributors

Feiya Luo

Dr. Feiya Luo is currently an assistant professor of Instructional Technology at The University of Alabama. Her research expertise is in elementary computer science (CS) education and computational thinking (CT) integration through the use of innovative educational technologies.

Ruohan Liu

Dr. Ruohan Liu is a postdoctoral research associate in the school of curriculum, instruction, and special education at the University of Virginia. Her research focus on promoting STEM education in elementary grades.

Fatema Nasrin

Fatema Nasrin is a Graduate Research Assistant in the ELPTS program and a Ph.D. student in the Educational Psychology Program at The University of Alabama. She holds a Master of Arts in Educational Psychology from The University of Alabama.

Idowu David Awoyemi

Idowu David Awoyemi is currently a Graduate Research Assistant, Graduate School Ambassador and a Ph.D. student of Instructional Technology in the department of Educational Leadership, Policy and Technology Studies.

Chris Crawford

Dr. Chris Crawford is an Assistant Professor at the University of Alabama’s Department of Computer Science. He directs the Human-Technology Interaction Lab (HTIL). His research focuses on human-robot interaction and Brain-Computer Interfaces (BCIs). He has investigated systems that provide computer applications and robots with information about a user’s cognitive state.

Wenchao Ma

Dr. Wenchao Ma is an applied researcher who has a broad interest in psychometrics and its applications in education, psychology and other social sciences. His current research focuses on cognitive diagnosis models and how they can be used to support the use of assessments for learning.