Learning User Experience Design (LUX) Adding the “L” to UX Research Using Biometric Sensors

• Published in: Research Methods in Learning Design and Technology pp. 146 - 160
• Main Author: Conley, Quincy
• Format: Book Chapter
• Language: English
• Published: United Kingdom Routledge 2021; Taylor & Francis Group
• Edition: 1
• Subjects: Omnipresent; Emerging Research Methodology; Physiological Signal Processing; Electroencephalogram; Cognition Behaviors; GSR Sensor; Person’s Affective State; Galvanic Skin Response; Brain Computer Interface; Underlying Emotional Disposition; User’s Affective State; Gaze Distribution; Biometric Technology; Time Spent; User’s Emotional State; EEG Equipment; Biometric Research; Biometric Sensors; GSR; Sweat Glands; GSR Data; EEG Sensor; Fer; Learning Designers; Educational Design Research
• ISBN: 0367203286; 9780367203269; 9780367203283; 036720326X
• DOI: 10.4324/9780429260919-10

As an emerging research methodology, biometrics is applied using a mix of biometric sensors including, eye-tracking, facial expression recognition, galvanic skin conductance, EEG, and more. These tools provide an extra layer of data for tracking user’s attention as well as their emotions during a learning experience. With proven success, advances in biometric technology give a line of sight into the interrelationships between affective components, all while making it more feasible to minimize biases issues. This chapter is about providing a comprehensive overview of biometric research methods. Furthermore, it will be discussed how learning design and technology (LDT) researchers and designers can use this new approach to help create more efficacious digital learning interventions. This chapter will also cover the connection between a user’s emotional state and the learning process and how biometrics can be used to unveil the hidden affective learning drivers such as attention, motivation, and cognition behaviors.