RT info:eu-repo/semantics/article
T1 Analysis of the Learning Process through Eye Tracking Technology and Feature Selection Techniques
A1 Sáiz Manzanares, María Consuelo
A1 Ramos Pérez, Ismael
A1 Arnaiz Rodríguez, Adrián
A1 Rodríguez Arribas, Sandra
A1 Almeida, Leandro
A1 Martin, Caroline Françoise
K1 Machine learning
K1 Cognition
K1 Eye tracking
K1 Instance selection
K1 Clustering
K1 Information processing
K1 Enseñanza
K1 Teaching
K1 Psicología
K1 Psychology
K1 Tecnología
K1 Technology
AB In recent decades, the use of technological resources such as the eye tracking methodology is providing cognitive researchers with important tools to better understand the learning process. However, the interpretation of the metrics requires the use of supervised and unsupervised learning techniques. The main goal of this study was to analyse the results obtained with the eye tracking methodology by applying statistical tests and supervised and unsupervised machine learning techniques, and to contrast the effectiveness of each one. The parameters of fixations, saccades, blinks and scan path, and the results in a puzzle task were found. The statistical study concluded that no significant differences were found between participants in solving the crossword puzzle task; significant differences were only detected in the parameters saccade amplitude minimum and saccade velocity minimum. On the other hand, this study, with supervised machine learning techniques, provided possible features for analysis, some of them different from those used in the statistical study. Regarding the clustering techniques, a good fit was found between the algorithms used (k-means ++, fuzzy k-means and DBSCAN). These algorithms provided the learning profile of the participants in three types (students over 50 years old; and students and teachers under 50 years of age). Therefore, the use of both types of data analysis is considered complementary.
PB MDPI
SN 2076-3417
YR 2021
FD 2021-07
LK http://hdl.handle.net/10259/6238
UL http://hdl.handle.net/10259/6238
LA eng
NO European Project “Self-Regulated Learning in SmartArt” 2019-1-ES01-KA204-065615.
DS Repositorio Institucional de la Universidad de Burgos
RD 19-abr-2024