TY - GEN
T1 - Classification Model Based on Chatbot and Unsupervised Algorithms to Determine Psychological Intervention Programs in Peruvian University Students
AU - Huamán, Baldwin
AU - Gómez, Dante
AU - Lévano, Danny
AU - Valles-Coral, Miguel
AU - Navarro-Cabrera, Jorge Raul
AU - Pinedo, Lloy
N1 - Publisher Copyright:
© 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2022
Y1 - 2022
N2 - A strategy that supports the student’s academic and personal formation is that university consider tutoring as a mechanism that supports with favorable results to fight against the desertion of students. However, there are related problems in performing student segmentation and conducting psychological interventions. The objective was to formulate a classification model for intervention programs in university students based on unsupervised algorithms. For this, we carried out a non-experimental, simple descriptive study on a population of 60 university students; we carried out the data extraction process through a chatbot that applied the BarOn ICE test. After we obtained the data, the unsupervised k-means algorithm was used to group the students into sets determined based on the closest mean value obtained from the psychological test. We built a model for classifying students based on their answers to the BarOn ICE test based on K-means, with which we obtained five groups. The model classifies students by applying a different mathematical method to that used by the models applied by psychologists.
AB - A strategy that supports the student’s academic and personal formation is that university consider tutoring as a mechanism that supports with favorable results to fight against the desertion of students. However, there are related problems in performing student segmentation and conducting psychological interventions. The objective was to formulate a classification model for intervention programs in university students based on unsupervised algorithms. For this, we carried out a non-experimental, simple descriptive study on a population of 60 university students; we carried out the data extraction process through a chatbot that applied the BarOn ICE test. After we obtained the data, the unsupervised k-means algorithm was used to group the students into sets determined based on the closest mean value obtained from the psychological test. We built a model for classifying students based on their answers to the BarOn ICE test based on K-means, with which we obtained five groups. The model classifies students by applying a different mathematical method to that used by the models applied by psychologists.
KW - Artificial Intelligence
KW - Automated classification
KW - Grouping
KW - K-means
KW - University Tutoring
UR - http://www.scopus.com/inward/record.url?scp=85145251126&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-22324-2_15
DO - 10.1007/978-3-031-22324-2_15
M3 - Conference contribution
AN - SCOPUS:85145251126
SN - 9783031223235
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 191
EP - 203
BT - Data and Information in Online Environments - Third EAI International Conference, DIONE 2022, Proceedings
A2 - Pinto, Adilson Luiz
A2 - Arencibia-Jorge, Ricardo
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd EAI International Conference on Data and Information in Online Environments, DIONE 2022
Y2 - 28 July 2022 through 29 July 2022
ER -