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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Evaluation and Research in Education (IJERE)
Macea-Anaya, Mario
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Computer Science & IT Education Engineering

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Influence of information and communication technologies on academic resilience in vulnerable contexts Macea-Anaya, Mario; Vargas-Moreno, Jeny; Baena-Navarro, Rubén
International Journal of Evaluation and Research in Education (IJERE) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v14i4.31486

Abstract

This study investigates how the use of information and communication technologies (ICT) influences the academic resilience of high school students in Soacha, Colombia, an area with significant socioeconomic challenges. The objective of the research is to analyze whether greater access to and proper use of ICT can improve students’ ability to face academic and emotional adversities. A mixed methodology was applied, combining quantitative surveys and qualitative interviews with 300 students from three educational institutions, measuring ICT use and academic resilience through validated scales. The findings revealed a significant positive correlation (r=0.95) between ICT use and academic resilience, demonstrating that students who used ICT more frequently showed higher levels of self-efficacy, better stress management, and more efficient academic organization. These results highlight the importance of integrating ICT into educational policies in vulnerable contexts, given their impact on both academic performance and students’ emotional well-being. It is recommended to prioritize digital competence training in educational institutions to strengthen students' abilities to face academic and emotional challenges.
Interpretable artificial intelligence system for personalized cognitive stimulation Baena-Navarro, Rubén; Carriazo-Regino, Yulieth; Macea-Anaya, Mario
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp164-176

Abstract

The growing need to preserve cognitive health in aging populations has intensified interest in adaptive digital interventions that provide personalized and interpretable support. This study presents a web-based cognitive stimulation system for older adults integrating a multilayer perceptron (MLP) classifier, expert-derived symbolic rules, and explainable artificial intelligence (XAI) techniques, including Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME). The platform was evaluated through a 24-week intervention involving 150 participants aged 65 years and older, combining baseline cognitive profiling, rule-guided recommendation logic, and neural prediction to support individualized task allocation. Compared with a control group, participants in the intervention arm showed statistically significant improvements in cognitive outcomes (p <0.05), with measurable gains in memory- and attention-related tasks. The explainability component enabled examination of model behavior at the level of individual features through feature attribution analysis and symbolic consistency checks, supporting interpretation beyond aggregate performance metrics. Unlike approaches dependent on high-end extended reality (XR) infrastructures or game centered interaction, the system was implemented to operate under low connectivity conditions and was tested with participants from diverse educational backgrounds. This hybrid configuration provides an interpretable basis for cognitive support initiatives adaptable to community settings contexts.
Co-Authors Baena-Navarro, Rubén Carriazo-Regino, Yulieth Vargas-Moreno, Jeny