Conference Agenda

In the last decade, higher education has increasingly incorporated educational mobile applications, but the evidence on their use as microlearning support aimed at student participation is still scattered. This systematic review aims to identify recent studies on mobile applications based on microlearning directed at higher education students and to show their effects on participation/engagement and academic performance. The methodology involved a search in the Scopus database using the PICO framework and PRISMA guidelines, yielding 335 initial records, of which 66 studies met the inclusion criteria. After analysis, it was observed that most of the studies report improvements in student participation and learning experience, and approximately one quarter of the studies also report increases in academic performance, especially when the apps combine short microlearning units, interactive activities, and gamification and feedback elements. In conclusion, mobile applications based on microlearning constitute a promising strategy to strengthen student participation and, to a lesser extent, academic performance in higher education, although more rigorous studies with a greater presence of Latin American contexts are still needed.

This article presents a classroom innovation experience implemented during the 2025 academic year in the Data Management and Analysis course, part of the Innovation Engineering program at Siglo 21 University. The study explores how integrating Project-Based Learning (PBL) and the Positive Education framework (PERMA model) strengthens technical competencies while fostering social commitment among students. The methodology involved developing data analysis and visualization projects using Power BI, centered on the "Technology and Society" axis. By curating public datasets, 49 students addressed critical issues such as the digital divide, educational equity, and environmental impact. The findings identified three distinct group performance profiles: methodical, techno-centric, and asynchronous. The conclusions highlight that linking technical rigor with a community-focused purpose acts as a catalyst for intrinsic motivation and academic achievement. Ultimately, this work demonstrates that when data science education transcends purely instrumental learning to address ethical and social challenges, it not only facilitates the mastery of analytical tools but also fosters a professional identity dedicated to transforming data into actionable knowledge for social well-being.

Due to the importance of having adequate financial knowledge, it is essential to educate students so they can develop skills that allow them to properly manage their personal finances and improve their economic well-being. The objective of this research is to identify the relationship between financial education and financial inclusion among students from a university in South Lima, to highlight the importance of having a solid financial foundation in a digital context. The methodology of this research follows a quantitative approach. The study is basic in nature, correlational in scope, and uses a non-experimental design. The study population consisted of 244 students, from which a sample of 150 students was selected. The instrument used was a survey composed of 20 items related to financial education and 20 items related to financial inclusion. The analysis based on the results obtained showed a reliability coefficient of 0.872 for the financial education questionnaire and 0.848 for the financial inclusion questionnaire. In addition, a positive, direct, and statistically significant relationship was identified between the study variables, with a Spearman’s Rho coefficient of 0.642. The main conclusion is the need to promote training programs for both teachers and students to improve their financial knowledge and highlight the importance of financial inclusion from an early age. This will facilitate access to various financial products and services available in the market, which can be used more efficiently through digital channels.

Digital identity has become a key element of the student experience in higher education, in a context marked by the digital transformation of universities and the expansion of virtual learning environments. The objective of this study was to analyse research trends on digital identity in higher education through a bibliometric review of scientific output indexed in the Scopus database from 2005 to 2025. The study was conducted using a quantitative approach, with a non-experimental design and a descriptive–analytical scope. Through a systematic search and the application of inclusion and exclusion criteria, a corpus of 64 scientific articles was compiled. The analysis was conducted using the Bibliometrix/Biblioshiny and VOSviewer tools, which enabled the examination of the temporal evolution of publications and the co-occurrence of keywords to identify the main thematic clusters. The results show sustained growth in scientific output since 2019 and a fragmented structure of the research field. Thematic analysis identified digital identity as a central theme, linked to higher education, social media use, and psychosocial dimensions. It is concluded that digital identity in university education constitutes a multidimensional phenomenon in the process of consolidation.

This study explores the digital transformation of learning and the impact of educational technologies on the quality and effectiveness of distance education (distance education); for which an empirical study is carried out with data from higher education institutions in various countries between 2020 and 2024, evaluating variables such as student satisfaction, learning outcomes and retention, where a significant improvement in perceived quality and a positive relationship between the use of interactive technologies and educational effectiveness were obtained, and implications for institutional policies, curriculum design and technological adoption are discussed.

The main objective of this study was to examine how electronic word-of-mouth (WOM) and teacher-related social norms (SN) influenced behavioral intention (BI) and actual use behavior (USEB) of generative AI chatbots among university students in northern Peru, while testing BI as a mediator and sex as a moderator. A quantitative, non-experimental, cross-sectional, explanatory design was employed. Data were collected through a structured Likert-scale questionnaire (1–5) from 520 students in Trujillo, Piura, and Lambayeque, and the proposed model was estimated using PLS-SEM with 5,000-bootstrap resampling. The findings indicated moderately high levels of WOM,
SN, BI, and USEB, alongside adequate reliability and convergent/discriminant validity. WOM positively and strongly predicted BI (β=0.56;p<0.001), whereas SN also increased BI but with a smaller effect (β=0.24; p<0.001). BI, in turn, showed a robust association with USEB
(β=0.71; p<0.001). Significant indirect effects supported mediation for WOM→USEB (β=0.40) and SN→USEB (β=0.17). Sex significantly moderated the WOM→BI path but did not yield a conclusive moderation for SN→BI. Overall, adoption was concluded to be a socially mediated process, primarily driven by peer communication.