Global ETD Search

1	Adaptive Learning Grundtman, Per January 2017 (has links) The purpose of this project is to develop a novel proof-of-concept system in attempt to measure affective states during learning-tasks and investigate whether machine learning models trained with this data has the potential to enhance the learning experience for an individual. By considering biometric signals from a user during a learning session, the affective states anxiety, engagement and boredom will be classified using different signal transformation methods and finally using machine-learning models from the Weka Java API. Data is collected using an Empatica E4 Wristband which gathers skin- and heart related biometric data which is streamed to an Android application via Bluetooth for processing. Several machine-learning algorithms and features were evaluated for best performance. adaptive learning machine learning e-learning biosyncing biometric sensors Empatica E4 Intelligent Tutoring Systems WEKA Computer and Information Sciences Data- och informationsvetenskap Engineering and Technology Teknik och teknologier