Degree Type
Creative Component
Semester of Graduation
Spring 2018
Department
Computer Science
First Major Professor
Dr. Carl K. Chang
Degree(s)
Master of Science (MS)
Major(s)
Computer Science
Abstract
Cognitive processes like working memory, attention play a key role in evaluating any subject's performance at a given task. Instead of proceeding with the methods that use task the completion time or accuracy or runtime of the program, we use human Electroencephalography (EEG) data and its features to quantify the programming expertise of individuals. Motivated by few other works with similar research goals, we use EEG to check if there is any correlation between the cognitive load and the self-reported data. We believe that this study helps to learn further about common threats to validity associated with the research in this area. Hypothesizing that there is no difference between the cognitive load experienced by experts and novices, we collected the EEG data of twenty-three participants in a controlled experiment and examined if the novice and the expert programmers could be grouped based on their EEG data. Emotiv Epoc is used as the Brain Computer Interface device to record the electrical pulses produced in the brain. Main parts of this project include planning and conducting the lab experiment during which participants provide their answers to the given Java programming questions and also to the questions in the given survey, signal analysis and feature extraction, data processing and data clustering. Our results show that there is difference between the cognitive loads experienced by people with different levels of programming expertise.
Copyright Owner
Greeshma Reddy Padiri
Copyright Year
2018
File Format
application/pdf
Recommended Citation
Padiri, Greeshma Reddy, "Using EEG to Assess Programming Expertise against Self-reported Data" (2018). Creative Components. 16.
https://lib.dr.iastate.edu/creativecomponents/16