Technology and Emotions: AI-Driven Software Prototyping for the Analysis of Emotional States and Early Detection of Risky Behaviors in University Students

Technology-assisted emotion analysis opens new possibilities for the early identification of risk behaviors that may impact the well-being of university students, contributing to the creation of healthier, safer, and more proactive educational environments. This pilot study aimed to design and develop a technological prototype capable of analyzing students’ emotional states and anticipating potential risk situations. A mixed-methods approach was adopted, employing qualitative methods in the ideation, design, and prototyping phases and quantitative methods for laboratory validation to assess the system’s accuracy. Additionally, mapping and meta-analysis techniques were applied and integrated into the chatbot’s responses. As a result, an educational technological innovation was developed, featuring a chatbot structured with a rule-based dialogue tree, complemented by an ontology for knowledge organization and a pre-trained artificial intelligence (AI) model, enhancing the accuracy and contextualization of user interactions. This solution has the potential to benefit the educational community and is also relevant to legislative stakeholders interested in education and student well-being, institutional leaders, academic and well-being coordinators, school counselors, teachers, and students.

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Publication Details

Journal
Education Sciences
Published
2025-03-11
DOI
https://doi.org/10.3390/educsci15030350
Citations
3
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
9.74

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article

Technology and Emotions: AI-Driven Software Prototyping for the Analysis of Emotional States and Early Detection of Risky Behaviors in University Students

Alba Catherine Alves-Noreña, Juan Pablo Hernández-Ramos, María José Rodríguez Conde, José William Castro Salgado
3 citations
Education Sciences
Engineering Education and Technology
9.74
article

Technology and Emotions: AI-Driven Software Prototyping for the Analysis of Emotional States and Early Detection of Risky Behaviors in University Students

Alba Catherine Alves-Noreña, Juan Pablo Hernández-Ramos, María José Rodríguez Conde, José William Castro Salgado
article en
3 citations

Abstract

Technology-assisted emotion analysis opens new possibilities for the early identification of risk behaviors that may impact the well-being of university students, contributing to the creation of healthier, safer, and more proactive educational environments. This pilot study aimed to design and develop a technological prototype capable of analyzing students’ emotional states and anticipating potential risk situations. A mixed-methods approach was adopted, employing qualitative methods in the ideation, design, and prototyping phases and quantitative methods for laboratory validation to assess the system’s accuracy. Additionally, mapping and meta-analysis techniques were applied and integrated into the chatbot’s responses. As a result, an educational technological innovation was developed, featuring a chatbot structured with a rule-based dialogue tree, complemented by an ontology for knowledge organization and a pre-trained artificial intelligence (AI) model, enhancing the accuracy and contextualization of user interactions. This solution has the potential to benefit the educational community and is also relevant to legislative stakeholders interested in education and student well-being, institutional leaders, academic and well-being coordinators, school counselors, teachers, and students.

Education SciencesVol. 15(3)
Universidad de Salamanca (ES), Military University Nueva Granada (CO)
Universidad Militar Nueva Granada
Openalex Percentile: Top 3%
Engineering Education and Technology
9.74
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Technology and Emotions: AI-Driven Software Prototyping for the Analysis of Emotional States and Early Detection of Risky Behaviors in University Students — Alba Catherine Alves-Noreña, Juan Pablo Hernández-Ramos, et al. · Education Sciences (2025) | TGRS Research Map | TGRS