Revista Iberoamericana de Tecnologias del Aprendizaje最新文献

{"title":"Fostering Accessibility Through Problem-Based Learning—Developing Serious Games in HCI Education: Experience Report in Developing for Older Adults","authors":"Valéria Farinazzo Martins;André Luiz Satoshi Kawamoto;Cibelle Albuquerque de la Higuera Amato;Maria Amelia Eliseo;Ismar Frango Silveira","doi":"10.1109/RITA.2025.3567528","DOIUrl":"https://doi.org/10.1109/RITA.2025.3567528","url":null,"abstract":"Although accessibility and digital inclusion are increasingly present in our daily lives, researchers have dedicated little effort debating these topics in Computer Science courses in Brazil. This paper presents a PBL (Problem-Based Learning) approach to Human-Computer Interaction classes which encourages students to discuss and consider accessibility issues during the systems project. As a result, the students created serious games aimed at the older people audience. This topic can be explored to increase students’ motivation, engagement, and commitment in the development of computational systems. This paper describes all the development phases suggested by our approach and outlines evaluation with students and teachers and discussion on the results from its application.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"125-133"},"PeriodicalIF":1.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144232179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Investigation Into Dropout Indicators in Secondary Technical Education Using Explainable Artificial Intelligence","authors":"Francisco da Conceição Silva;Andre Macedo Santana;Rodrigo Miranda Feitosa","doi":"10.1109/RITA.2025.3566095","DOIUrl":"https://doi.org/10.1109/RITA.2025.3566095","url":null,"abstract":"With the increasing application of Artificial Intelligence (AI) in education, it becomes essential to understand the factors influencing school dropout, as the educational context demands reliable decision-making. This study investigates dropout indicators in secondary-level technical courses at a Brazilian institution, using Explainable AI (XAI) techniques applied to Machine Learning models. The study analyzed data from 15,084 students to identify the main factors contributing to school dropout, utilizing predictive models and applying the explainability techniques LIME and SHAP to highlight key dropout factors, thereby improving prediction transparency. The results show that decision tree-based models performed best, with Random Forest achieving 85% Recall, effectively identifying students at risk of dropout. LIME and SHAP consistently highlighted school attendance, family income, and place of residence as key dropout factors. The analysis of the explainers showed that students with low attendance and lower income are more likely to drop out. These findings highlight the importance of targeted educational policies, such as scholarship programs, transportation assistance, and personalized academic support, especially for vulnerable students. This study contributes to the understanding of factors associated with school dropout and provides insights for the formulation of more effective educational policies. Strategies such as scholarship programs, transportation assistance, and academic monitoring can be implemented to reduce dropout rates.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"105-114"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10981760","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Skills for Empowering Migrant Women: A Basic Education Program","authors":"Catalina Guerrero-Romera;José-Antonio Gómez-Hernández;Dor a Sales Salvador;Miguel-Ángel Vera-Baceta;José Antonio Merlo Vega;Aurora Cuevas-Cerveró","doi":"10.1109/RITA.2025.3542560","DOIUrl":"https://doi.org/10.1109/RITA.2025.3542560","url":null,"abstract":"In the 21st century, technologies have become an essential element in the daily lives of all people and a basic resource for participating in society and exercising their full rights as citizens. Nonetheless, not all the population has the necessary resources to be able to access and be digitally trained, which is why the digital divide is one of the great challenges nowadays, especially for the migrant population. This double digital and social divide can occur to a greater extent in women, creating a series of gaps that hinder their full social inclusion and make it necessary to acquire basic competences and skills that contribute to promoting and exercising their rights on an equal footing in society. The purpose of this paper is to present a basic digital education programme aimed at migrant women that includes different contents and activities aligned with the European DigComp Framework at the basic level. It is expected that this training will have an impact on their level of digital performance and on fostering their participation and social inclusion.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"134-138"},"PeriodicalIF":1.0,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144232165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Collaborative Programming as a Didactic Learning Strategy in CS1 Courses","authors":"Oscar Revelo Sánchez;Alexander Barón Salazar;Manuel Ernesto Bolaños","doi":"10.1109/RITA.2025.3541541","DOIUrl":"https://doi.org/10.1109/RITA.2025.3541541","url":null,"abstract":"Concepts and skills related to the basic constructs of programming (variables, types, expressions, assignment, simple input and output, and conditional control and iteration structures) are a key component in the education of future software developers. Initial programming courses (CS1) tend to have a high academic mortality rate. This is reflected in low student grades, indicating that students are not achieving the required academic competencies. Seeking alternative ways to improve student performance in CS1 courses, this paper proposes as a didactic learning strategy the use of collaborative programming/coding, mediated by the integrated development environment Visual Studio Code and its add-on Live Share, in solving computer programming problems or challenges. The results of a controlled experiment in which this collaborative tool was used in different CS1 courses of the Faculty of Engineering of the University of Nariño in San Juan de Pasto - Colombia are presented.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"32-38"},"PeriodicalIF":1.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing Intervention Strategies Employed in Response to Automated Academic-Risk Identification: A Systematic Review","authors":"Augusto Schmidt;Cristian Cechinel;Emanuel Marques Queiroga;Tiago Primo;Vinicius Ramos;Andréa Sabedra Bordin;Rafael Ferreira Mello;Roberto Muñoz","doi":"10.1109/RITA.2025.3540161","DOIUrl":"https://doi.org/10.1109/RITA.2025.3540161","url":null,"abstract":"Predicting in advance the likelihood of students failing a course or withdrawing from a degree program has emerged as one of the widely embraced applications of Learning Analytics. While the literature extensively addresses the identification of at-risk students, it often doesn’t evolve into actual interventions, focusing more on reporting experimental outcomes than on translating them into real-world impact. The goal of early identification is straightforward, empowering educators to intervene before actual failure or dropout, but not enough attention is paid to what happens after the students are flagged as at risk. Interventions like personalized feedback, automated alerts, and targeted support can be game-changers, reducing failure and dropout rates. However, as this paper shows, few studies actually dig into the effectiveness of these strategies or measure their impact on student outcomes. Even more striking is the lack of research targeting stakeholders beyond students, like educators, administrators, and curriculum designers, who play a key role in driving meaningful interventions. The paper explores recent literature on automated academic risk prediction, focusing on interventions in selected papers. Our findings highlight that only about 14% of studies propose actionable interventions, and even fewer implement them. Despite these challenges, we can see that a global momentum is building around Learning Analytics, and institutions are starting to tap into the potential of these tools. However, academic databases, loaded with valuable insights, remain massively underused. To move the field forward, we propose actionable strategies, like developing intervention frameworks that engage multiple stakeholders, creating standardized metrics for measuring success and expanding data sources to include both traditional academic systems and alternative datasets. By tackling these issues, this paper doesn’t just highlight what is missing; it offers a roadmap for researchers and practitioners alike, aiming to close the gap between prediction and action. It’s time to go beyond identifying risks and start making a real difference where it matters most.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"77-85"},"PeriodicalIF":1.0,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data Mining for Enhancing Learning and Assessment to a Microcompetence-Based Methodology in Higher Education","authors":"Aurelio Lopez-Fernandez;Federico Divina;Francisco A. Gomez-Vela;Miguel García-Torres","doi":"10.1109/RITA.2025.3532879","DOIUrl":"https://doi.org/10.1109/RITA.2025.3532879","url":null,"abstract":"This work introduces an innovative teaching methodology based on microcompetences applied in a higher education context. The intervention involved creating a repository of practical case studies in the form of quizzes and integrating microcompetences into each course activity. The digital tool Sapiens was used to identify learning deficiencies and provide both collective and individualized feedback. The results indicate a significant increase in student participation and academic performance compared to previous years. Furthermore, students voluntarily used virtual teaching modalities to reinforce their knowledge, particularly in more complex areas. Data mining techniques identified performance patterns among students, highlighting the methodology’s effectiveness in improving both transversal and specific competences. The study’s findings underscore the importance of implementing microcompetency-based methodologies in higher education to enhance the quality of learning and continuous assessment. This approach not only facilitated a deeper understanding of course content but also promoted critical thinking, abstract reasoning, and interpersonal skills, preparing students for future academic and professional challenges. Additionally, the flexibility and adaptability of the digital tools used provided a seamless transition across different teaching modalities, such as in-person, hybrid, and online formats. Thus, the implementation of this innovative methodology has demonstrated its potential to significantly improve student engagement, participation, and academic success, thereby contributing to a more effective and comprehensive educational experience in higher education.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"22-31"},"PeriodicalIF":1.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143361192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2024 Index IEEE Revista Iberoamericana de Tecnologias del Aprendizaje Vol. 19","authors":"","doi":"10.1109/RITA.2025.3531978","DOIUrl":"https://doi.org/10.1109/RITA.2025.3531978","url":null,"abstract":"","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"19 ","pages":"418-430"},"PeriodicalIF":1.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10846973","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Predictive Model for the Early Identification of Student Dropout Using Data Classification, Clustering, and Association Methods","authors":"Patricia Mariotto Mozzaquatro Chicon;Leo Natan Paschoal;Sandro Sawicki;Fabricia Roos-Frantz;Rafael Z. Frantz","doi":"10.1109/RITA.2025.3528369","DOIUrl":"https://doi.org/10.1109/RITA.2025.3528369","url":null,"abstract":"Technology development has led to increased data generated in education, sparking interest in information extraction to support educational management through automated data analysis. Using such data to create models identifying students likely to drop out has drawn research interest. A crucial factor in reducing dropout rates is the systematic and early identification of the level of student engagement, especially by detecting the students’ behavior profile in the virtual environment, such as grades in assessments. There are predictive models based on data mining processes that identify students prone to dropping out. Unfortunately, the predictive models do not characterize the profiles of these students or the specific trends associated with these profiles. This article aims to fill a gap by presenting a study that identifies and tracks the profiles of undergraduate students likely to drop out, starting with an analysis of academic performance. We propose a predictive model beyond classification by combining data mining techniques such as decision trees, clustering, and frequent pattern analysis. Decision trees, a data mining technique that uses a tree-like graph to represent decisions and their possible consequences, identify students at risk of failure from the entire dataset. Clustering analysis, a data mining technique that groups similar data points together, groups students based on similar characteristics (e.g., students who scored between 0 and 30 points on a specific activity). Frequent pattern analysis, a data mining technique that identifies patterns that occur frequently in a dataset, uncovers the underlying factors contributing to low performance (e.g., identify which activities had the most significant influence on a specific group’s low performance). This integrated approach predicts dropout risk with 93.9% precision and provides a deeper understanding of student profiles and the trends associated with academic failure. The model’s practical application is demonstrated through a study.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"12-21"},"PeriodicalIF":1.0,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143361194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perception Disparity Between Women and Men on the Gender Gap in STEM at a Spanish University","authors":"Ana Belén González-Rogado;Ana Belén Ramos-Gavilán;María Ascensión Rodríguez-Esteban;Alicia García-Holgado","doi":"10.1109/RITA.2024.3522255","DOIUrl":"https://doi.org/10.1109/RITA.2024.3522255","url":null,"abstract":"The gender gap in engineering is one of the problems in achieving gender equality in society. In this context, the “Engineering with a Gender Perspective” project, an equality initiative developed at the Higher Polytechnic School of Zamora (HPSZ), University of Salamanca, aims to understand the university community’s perception of the gender gap and gender equality and to promote interest in STEAM (Science, Technology, Engineering, Arts, Mathematics) subjects, particularly among female students. To achieve these objectives, a questionnaire tailored to Engineering and Architecture, which had previously been validated for Computer Engineering, was administered and discussed to the entire educational community at the HPSZ. The first WE (Women in Engineering) Challenge Competition was also launched for pre-university students. The challenges, devised by women, were designed to demonstrate the relevance of engineering in everyday life, to inspire pre-university students to pursue STEAM disciplines. The study examines responses to the questionnaire from both students and faculty at the HPSZ, analysing differences in perceptions between men and women regarding gender equality, the gender gap, and gender stereotypes. The findings indicate significant differences in perceptions of the gender gap, particularly among the student population. However, there are no significant differences in views on gender equality and gender stereotypes. Overall, the university community at the HPSZ recognises the importance of achieving gender equality and eliminating stereotypes. Nevertheless, there seems to be some uncertainty regarding their stance on the gender gap issue. Active engagement across all educational levels, focusing on early education, is crucial for reducing inequality in the STEAM field, eradicating gender stereotypes, and fostering interest in STEAM disciplines.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"1-11"},"PeriodicalIF":1.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143361193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Transformation in the Educational Community of the Dominican Republic: Exploring the Role of Sociodemographic Environments and Gender in Digital Competence","authors":"Jesús Manuel Soriano-Alcantara;Francisco D. Guillén-Gámez;Julio Ruiz-Palmero","doi":"10.1109/RITA.2024.3513702","DOIUrl":"https://doi.org/10.1109/RITA.2024.3513702","url":null,"abstract":"The purpose of this study was to have a more general and holistic view of the basic digital competencies self-perceived by the main agents of the educational community (teachers, students and parents) of all educational stages (Early Childhood Education, Primary Education, Secondary Education and Higher education). Specifically, the incidence of sociodemographic settings (urban-rural) and gender (female-male) in the Dominican Republic was analyzed and compared, for each educational stage. To achieve these purposes, an ex post facto design was used, and with a non-probabilistic sampling of 1149 participants. Among the main findings, the digital competencies of teachers are satisfactory and high in all educational stages and sociodemographic settings environments, while the group of students and parents shows lower scores, especially in the early educational stages. Regarding gender, no significant differences were found in the group of students for any educational stage, while in the group of teachers and parents, differences were found in some educational stages, in favor of the male gender. These findings suggest the need to design specific interventions to improve students and parents’ digital competencies, especially in Primary Education and rural areas, where minimum levels are observed. In addition, the importance of considering gender differences in the digital competencies of teachers and parents is highlighted to promote equity and equal access to digital education.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"19 ","pages":"379-388"},"PeriodicalIF":1.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142858895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}