Pub Date : 2025-08-15DOI: 10.1109/RITA.2025.3599155
José G. Mercado-Rojas;Rasikh Tariq;Juan A. Marchina-Herrera;Inna Artemova;Jorge Sanabria-Z
Citizen science projects that use Internet of Things (IoT) devices are transforming environmental education by enabling real-time, participatory data collection. However, few initiatives integrate Artificial Intelligence (AI) to support the analysis and prediction of environmental dynamics, as well as their interpretation and deeper learning outcomes. This article presents a framework for incorporating AI into IoT-based citizen science educational systems, exemplified by the SKILIKET project. SKILIKET combines quantitative sensor data (e.g., temperature, CO2, humidity, UV, and noise) with qualitative human observations (e.g., perceived smells, sounds, and visual cues) collected via a mobile app to help participants better understand socioecological phenomena in their environments. Using a Design-Based Research (DBR) approach, the study explores AI functionalities that could support environmental interpretation, predictive analytics for heterogeneous environmental data, and conversational agents for reflective learning. Preliminary tests show that AI-powered predictive models aid pattern recognition and foster participant reflection. The proposed framework outlines principles for modular AI integration, emphasizing user-centered design, ethical data practices, and alignment with STEM education goals. It establishes a foundation for AI-supported citizen science education, aiming to foster critical thinking, civic participation and proactive environmental stewardship.
{"title":"Framework for AI Integration in Citizen Science: Insights From the SKILIKET Project","authors":"José G. Mercado-Rojas;Rasikh Tariq;Juan A. Marchina-Herrera;Inna Artemova;Jorge Sanabria-Z","doi":"10.1109/RITA.2025.3599155","DOIUrl":"https://doi.org/10.1109/RITA.2025.3599155","url":null,"abstract":"Citizen science projects that use Internet of Things (IoT) devices are transforming environmental education by enabling real-time, participatory data collection. However, few initiatives integrate Artificial Intelligence (AI) to support the analysis and prediction of environmental dynamics, as well as their interpretation and deeper learning outcomes. This article presents a framework for incorporating AI into IoT-based citizen science educational systems, exemplified by the SKILIKET project. SKILIKET combines quantitative sensor data (e.g., temperature, CO2, humidity, UV, and noise) with qualitative human observations (e.g., perceived smells, sounds, and visual cues) collected via a mobile app to help participants better understand socioecological phenomena in their environments. Using a Design-Based Research (DBR) approach, the study explores AI functionalities that could support environmental interpretation, predictive analytics for heterogeneous environmental data, and conversational agents for reflective learning. Preliminary tests show that AI-powered predictive models aid pattern recognition and foster participant reflection. The proposed framework outlines principles for modular AI integration, emphasizing user-centered design, ethical data practices, and alignment with STEM education goals. It establishes a foundation for AI-supported citizen science education, aiming to foster critical thinking, civic participation and proactive environmental stewardship.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"200-208"},"PeriodicalIF":1.0,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896777","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}
Pub Date : 2025-08-11DOI: 10.1109/RITA.2025.3597848
Luis Magdiel Oliva-Córdova;Inés Álvarez-Icaza;Carlos Enrique George-Reyes
Critical thinking is a key competency in higher education, particularly in digital environments that demand analysis, judgment, and informed decision-making. Generative Artificial Intelligence (GenAI) represents an emerging opportunity to enhance complex cognitive skills in educational settings. A quasi-experimental research design with a mixed-methods approach was employed and applied to a sample of university students aiming to address the research question: What is the impact of using GenAI tools on the development of critical thinking in university students? The educational intervention consisted of structured workshops that incorporated GenAI tools into activities aimed at developing six dimensions of critical thinking: remembering, understanding, applying, analyzing, evaluating, and creating. Results showed significant improvements in applying (p =.002), analyzing (p =.0008), and evaluating (p =.003), all associated with higher-order thinking skills. Three dimensions -remembering, understanding, and creating- showed statistically significant changes. However, students’ perception showed a notable increase in the value of GenAI use. Additionally, participants highlighted the usefulness of GenAI for generating ideas, decision making, and promoting deeper reflections. The study concludes that the intentional integration of GenAI technologies, when aligned with clear educational goals, can produce a meaningful and positive impact on the development of critical thinking in university contexts. These findings offer empirical support for designing innovative, ethically grounded learning experiences that incorporate GenAI to strengthen cognitive development in higher education.
{"title":"Evaluation of Generative AI Use to Foster Critical Thinking in Higher Education","authors":"Luis Magdiel Oliva-Córdova;Inés Álvarez-Icaza;Carlos Enrique George-Reyes","doi":"10.1109/RITA.2025.3597848","DOIUrl":"https://doi.org/10.1109/RITA.2025.3597848","url":null,"abstract":"Critical thinking is a key competency in higher education, particularly in digital environments that demand analysis, judgment, and informed decision-making. Generative Artificial Intelligence (GenAI) represents an emerging opportunity to enhance complex cognitive skills in educational settings. A quasi-experimental research design with a mixed-methods approach was employed and applied to a sample of university students aiming to address the research question: What is the impact of using GenAI tools on the development of critical thinking in university students? The educational intervention consisted of structured workshops that incorporated GenAI tools into activities aimed at developing six dimensions of critical thinking: remembering, understanding, applying, analyzing, evaluating, and creating. Results showed significant improvements in applying (p =.002), analyzing (p =.0008), and evaluating (p =.003), all associated with higher-order thinking skills. Three dimensions -remembering, understanding, and creating- showed statistically significant changes. However, students’ perception showed a notable increase in the value of GenAI use. Additionally, participants highlighted the usefulness of GenAI for generating ideas, decision making, and promoting deeper reflections. The study concludes that the intentional integration of GenAI technologies, when aligned with clear educational goals, can produce a meaningful and positive impact on the development of critical thinking in university contexts. These findings offer empirical support for designing innovative, ethically grounded learning experiences that incorporate GenAI to strengthen cognitive development in higher education.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"237-243"},"PeriodicalIF":1.0,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145051072","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}
Pub Date : 2025-07-29DOI: 10.1109/RITA.2025.3593422
Fabián Andrés Jalk Duque;Sonia Valbuena Duarte;Francisco Juan Racedo Niebles
Computational thinking (CT) is recognized as an essential macro-skill that can be developed at any age and in various contexts, being a key component in science, technology, engineering, and mathematics (STEM) disciplines. For this purpose, the design and development of an interactive simulation to measure the charge-mass ratio of the electron, using Helmholtz coils to generate a uniform magnetic field, is presented. Based on Lorentz’s law, it describes how electrons accelerated by an electric field are deflected in circular trajectories under the influence of a magnetic field. The studio uses GeoGebra software to create a virtual lab environment where users can control experimental variables such as acceleration current and voltage. Results obtained from the simulation align with established theoretical and experimental values for the electron charge-mass ratio, suggesting its potential as a supplementary educational resource.
{"title":"Computational Thinking Through a Dynamic Simulation of the Electron Charge-Mass Ratio","authors":"Fabián Andrés Jalk Duque;Sonia Valbuena Duarte;Francisco Juan Racedo Niebles","doi":"10.1109/RITA.2025.3593422","DOIUrl":"https://doi.org/10.1109/RITA.2025.3593422","url":null,"abstract":"Computational thinking (CT) is recognized as an essential macro-skill that can be developed at any age and in various contexts, being a key component in science, technology, engineering, and mathematics (STEM) disciplines. For this purpose, the design and development of an interactive simulation to measure the charge-mass ratio of the electron, using Helmholtz coils to generate a uniform magnetic field, is presented. Based on Lorentz’s law, it describes how electrons accelerated by an electric field are deflected in circular trajectories under the influence of a magnetic field. The studio uses GeoGebra software to create a virtual lab environment where users can control experimental variables such as acceleration current and voltage. Results obtained from the simulation align with established theoretical and experimental values for the electron charge-mass ratio, suggesting its potential as a supplementary educational resource.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"191-199"},"PeriodicalIF":1.0,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773264","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}
Pub Date : 2025-07-07DOI: 10.1109/RITA.2025.3586806
Jorge Marques Prates;Carlos Alario-Hoyos;José Carlos Maldonado
Massive Open Online Courses (MOOCs) are digital courses that offer open learning content, reaching a broad audience of students. In the realm of Software Engineering Education, MOOCs can be integrated with methodologies like flipped classrooms and blended learning. However, effectively evaluating the use of MOOCs poses a challenge due to the absence of defined metrics for assessing their quality. In this context, this study aims to scrutinize the quality of MOOCs, specifically focusing on Software Engineering. The research questions investigate several aspects through a Systematic Mapping Mapping, including the quality criteria for MOOC evaluation, specific characteristics relevant to Software Engineering education, the application of quality models, the relationship between standardized concepts in MOOCs and their quality, and the benefits of quality assessments conducted by accreditation agencies. The research endeavors to offer a comprehensive insight into quality assessment within the MOOC landscape, with a particular emphasis on Software Engineering Education. The results encompass the identification of quality criteria for evaluating MOOCs in the field of Software Engineering, as well as a deeper understanding of the particular characteristics that impact the quality of these courses.
{"title":"Toward Enhanced Quality Assessment in Software Engineering MOOCs","authors":"Jorge Marques Prates;Carlos Alario-Hoyos;José Carlos Maldonado","doi":"10.1109/RITA.2025.3586806","DOIUrl":"https://doi.org/10.1109/RITA.2025.3586806","url":null,"abstract":"Massive Open Online Courses (MOOCs) are digital courses that offer open learning content, reaching a broad audience of students. In the realm of Software Engineering Education, MOOCs can be integrated with methodologies like flipped classrooms and blended learning. However, effectively evaluating the use of MOOCs poses a challenge due to the absence of defined metrics for assessing their quality. In this context, this study aims to scrutinize the quality of MOOCs, specifically focusing on Software Engineering. The research questions investigate several aspects through a Systematic Mapping Mapping, including the quality criteria for MOOC evaluation, specific characteristics relevant to Software Engineering education, the application of quality models, the relationship between standardized concepts in MOOCs and their quality, and the benefits of quality assessments conducted by accreditation agencies. The research endeavors to offer a comprehensive insight into quality assessment within the MOOC landscape, with a particular emphasis on Software Engineering Education. The results encompass the identification of quality criteria for evaluating MOOCs in the field of Software Engineering, as well as a deeper understanding of the particular characteristics that impact the quality of these courses.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"172-181"},"PeriodicalIF":1.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646433","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}
Pub Date : 2025-06-30DOI: 10.1109/RITA.2025.3584364
Juan D. Velásquez;Patricia Jaramillo;Sara Ibarra
This comprehensive literature review examines the dynamic evolution of business analytics education, with a focus on curriculum innovation, experiential learning, and emerging pedagogical strategies. Analyzing 103 scholarly articles from 2012 to 2024, the study identifies three core themes: Curriculum Innovation for Industry Competencies, Experiential Learning in Analytical Decision-Making, and Innovative Pedagogies for Skill Development. These themes are further examined through nine critical dimensions: Curriculum Design, Analytical Skills Development, Industry Collaboration, and Technology-Enhanced Learning. The review highlights the increasing importance of aligning curricula with industry demands, integrating data literacy and ethical considerations, and utilizing technology to enhance learning outcomes. Challenges such as the academic-industry gap and the need for ongoing faculty development are also discussed. This review synthesizes current trends in business analytics education. It offers insights for future curriculum innovation and industry collaboration, emphasizing the need to equip graduates with essential competencies for the modern workforce.
{"title":"Trends in Business Analytics Education: Innovation, Learning, and Pedagogy","authors":"Juan D. Velásquez;Patricia Jaramillo;Sara Ibarra","doi":"10.1109/RITA.2025.3584364","DOIUrl":"https://doi.org/10.1109/RITA.2025.3584364","url":null,"abstract":"This comprehensive literature review examines the dynamic evolution of business analytics education, with a focus on curriculum innovation, experiential learning, and emerging pedagogical strategies. Analyzing 103 scholarly articles from 2012 to 2024, the study identifies three core themes: Curriculum Innovation for Industry Competencies, Experiential Learning in Analytical Decision-Making, and Innovative Pedagogies for Skill Development. These themes are further examined through nine critical dimensions: Curriculum Design, Analytical Skills Development, Industry Collaboration, and Technology-Enhanced Learning. The review highlights the increasing importance of aligning curricula with industry demands, integrating data literacy and ethical considerations, and utilizing technology to enhance learning outcomes. Challenges such as the academic-industry gap and the need for ongoing faculty development are also discussed. This review synthesizes current trends in business analytics education. It offers insights for future curriculum innovation and industry collaboration, emphasizing the need to equip graduates with essential competencies for the modern workforce.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"160-171"},"PeriodicalIF":1.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144671255","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}
Pub Date : 2025-06-30DOI: 10.1109/RITA.2025.3584241
Elisabete Galeazzo;Rodrigo Anjos de Souza;Henrique E. Maldonado Peres;Maurício O. Pérez Lisboa;Wesley Beccaro;Leopoldo R. Yoshioka
Analog-to-digital (AD) conversion is a widely covered topic in Electrical and Electronic Engineering undergraduate programs. To enhance the effectiveness of learning and to engage students in this subject, hands-on activities, such as laboratory experiments, are essential bridging theory and practice. However, it has been observed that many students experience difficulties in learning this topic. One of the reasons is the students’ lack of practical skills in carrying out experimental hardware assemblies and handling instruments. Furthermore, note that the high cost of laboratory teaching infrastructure limits the availability of a sufficient quantity of materials and hardware equipment, especially when it is necessary to accommodate numerous students in practical activities simultaneously. To address these challenges, this study proposes a user-friendly Virtual Instrument (VI) developed in LabVIEW® to enhance the understanding and learning of AD conversion concepts. The VI allows users to select different signal types and configure the AD converter parameters, so the resulting effect of these modifications can be immediately viewed on the student computer screen. Due to its versatility, the computational tool has been applied to Electrical Engineering students at the Escola Politécnica of the Universidade de São Paulo (EPUSP) since 2020. It was first implemented during the social isolation caused by the COVID-19 pandemic and later incorporated into the Electrical Instrumentation course as an additional resource for in-person classes. To evaluate the effectiveness of the VI, an analysis was conducted with 59 students — 29 who exclusively performed the AD conversion experiment using the VI and 30 who used traditional electronics bench infrastructure. The first group achieved a mean grade of 8.78, compared to a mean grade of 7.53 for the control group, which used the laboratory infrastructure. These findings suggest that students using the VI statistically outperformed their counterparts, with an average grade improvement of 16.6%. Therefore, we consider our approach a valuable complementary resource for teaching fundamental AD conversion concepts, with potential for application in other areas of engineering, such as in telecommunications, embedded systems, signal processing, among others.
模数转换（AD）是电气与电子工程本科课程中广泛涉及的主题。为了提高学习的有效性并吸引学生参与这门学科，动手活动，如实验室实验，是理论和实践之间必不可少的桥梁。然而，据观察，许多学生在学习这一主题时遇到了困难。其中一个原因是学生缺乏进行实验硬件组装和操作仪器的实践技能。此外，请注意，实验室教学基础设施的高成本限制了足够数量的材料和硬件设备的可用性，特别是当需要同时容纳众多学生进行实践活动时。为了解决这些挑战，本研究提出了在LabVIEW®中开发的用户友好型虚拟仪器（VI），以增强对AD转换概念的理解和学习。VI允许用户选择不同的信号类型并配置AD转换器参数，因此这些修改的结果效果可以立即在学生计算机屏幕上查看。由于其通用性，自2020年以来，该计算工具已应用于圣保罗大学（EPUSP） Escola politcnica的电气工程专业学生。它最初是在COVID-19大流行造成的社会隔离期间实施的，后来被纳入电气仪表课程，作为面对面课程的额外资源。为了评估VI的有效性，对59名学生进行了分析，其中29名学生专门使用VI进行AD转换实验，30名学生使用传统的电子实验台基础设施。第一组的平均成绩为8.78，而使用实验室基础设施的对照组的平均成绩为7.53。这些发现表明，使用VI的学生在统计上表现优于其他学生，平均成绩提高了16.6%。因此，我们认为我们的方法是教授基本AD转换概念的宝贵补充资源，具有在其他工程领域应用的潜力，例如电信，嵌入式系统，信号处理等。
{"title":"Assessing Fundamentals of Analog-to-Digital Conversion Using Virtual Experiments in Electrical Engineering","authors":"Elisabete Galeazzo;Rodrigo Anjos de Souza;Henrique E. Maldonado Peres;Maurício O. Pérez Lisboa;Wesley Beccaro;Leopoldo R. Yoshioka","doi":"10.1109/RITA.2025.3584241","DOIUrl":"https://doi.org/10.1109/RITA.2025.3584241","url":null,"abstract":"Analog-to-digital (AD) conversion is a widely covered topic in Electrical and Electronic Engineering undergraduate programs. To enhance the effectiveness of learning and to engage students in this subject, hands-on activities, such as laboratory experiments, are essential bridging theory and practice. However, it has been observed that many students experience difficulties in learning this topic. One of the reasons is the students’ lack of practical skills in carrying out experimental hardware assemblies and handling instruments. Furthermore, note that the high cost of laboratory teaching infrastructure limits the availability of a sufficient quantity of materials and hardware equipment, especially when it is necessary to accommodate numerous students in practical activities simultaneously. To address these challenges, this study proposes a user-friendly Virtual Instrument (VI) developed in LabVIEW® to enhance the understanding and learning of AD conversion concepts. The VI allows users to select different signal types and configure the AD converter parameters, so the resulting effect of these modifications can be immediately viewed on the student computer screen. Due to its versatility, the computational tool has been applied to Electrical Engineering students at the Escola Politécnica of the Universidade de São Paulo (EPUSP) since 2020. It was first implemented during the social isolation caused by the COVID-19 pandemic and later incorporated into the Electrical Instrumentation course as an additional resource for in-person classes. To evaluate the effectiveness of the VI, an analysis was conducted with 59 students — 29 who exclusively performed the AD conversion experiment using the VI and 30 who used traditional electronics bench infrastructure. The first group achieved a mean grade of 8.78, compared to a mean grade of 7.53 for the control group, which used the laboratory infrastructure. These findings suggest that students using the VI statistically outperformed their counterparts, with an average grade improvement of 16.6%. Therefore, we consider our approach a valuable complementary resource for teaching fundamental AD conversion concepts, with potential for application in other areas of engineering, such as in telecommunications, embedded systems, signal processing, among others.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"152-159"},"PeriodicalIF":1.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623983","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}
Pub Date : 2025-06-26DOI: 10.1109/RITA.2025.3583369
Cindy Espinoza;Jesús Carretero
Student dropout is a significant challenge in higher education, generating frustration in society and wasting resources. As a result, student retention constitutes a constant challenge for higher education institutions everywhere. This work focuses on the question: Can intelligent predictive data analysis techniques be applied to reduce the dropout rate in public and private universities? To answer this question, we have adopted an exploratory methodological approach based on historical data from approximately 13,715 applicants who later became university students. Unlike other research, based on publicly available data and statistics, our work relies on five years of actual data of students whose behavior has been synthesized in 27 variables related to socioeconomic, academic, and family factors and analyzes it. This paper has two main contributions. First, we propose intelligent predictive data analytics techniques and demonstrate that it is possible to profile and target the applicant for higher education as a strategy to reduce the dropout rate and improve their student welfare, so that the dropout probability can be used as part of an early warning in the recruitment process. Second, we propose a methodology for the segmentation and/or archetyping of applicants, which can be part of a corrective alert in the adaptation process. The profiling model and archetyping are replicable in private and public universities since we use easily extractable generic variables that do not require the university to have a high level of maturity in data management processes. Therefore, our results contribute to educational data mining (EDM), demonstrating that intelligent predictive data analysis techniques can be used to profile and archetype private and public university applicants for higher education. The evaluation of our solution proved that the neural network model profiled the dropout applicants with an accuracy higher than up to 97%, after which unsupervised learning was applied to generate archetypes.
{"title":"Profiling and Archetyping of Higher Education Applicants Using Intelligent Data Analysis Techniques","authors":"Cindy Espinoza;Jesús Carretero","doi":"10.1109/RITA.2025.3583369","DOIUrl":"https://doi.org/10.1109/RITA.2025.3583369","url":null,"abstract":"Student dropout is a significant challenge in higher education, generating frustration in society and wasting resources. As a result, student retention constitutes a constant challenge for higher education institutions everywhere. This work focuses on the question: Can intelligent predictive data analysis techniques be applied to reduce the dropout rate in public and private universities? To answer this question, we have adopted an exploratory methodological approach based on historical data from approximately 13,715 applicants who later became university students. Unlike other research, based on publicly available data and statistics, our work relies on five years of actual data of students whose behavior has been synthesized in 27 variables related to socioeconomic, academic, and family factors and analyzes it. This paper has two main contributions. First, we propose intelligent predictive data analytics techniques and demonstrate that it is possible to profile and target the applicant for higher education as a strategy to reduce the dropout rate and improve their student welfare, so that the dropout probability can be used as part of an early warning in the recruitment process. Second, we propose a methodology for the segmentation and/or archetyping of applicants, which can be part of a corrective alert in the adaptation process. The profiling model and archetyping are replicable in private and public universities since we use easily extractable generic variables that do not require the university to have a high level of maturity in data management processes. Therefore, our results contribute to educational data mining (EDM), demonstrating that intelligent predictive data analysis techniques can be used to profile and archetype private and public university applicants for higher education. The evaluation of our solution proved that the neural network model profiled the dropout applicants with an accuracy higher than up to 97%, after which unsupervised learning was applied to generate archetypes.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"139-151"},"PeriodicalIF":1.0,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581718","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}
Pub Date : 2025-06-24DOI: 10.1109/RITA.2025.3582716
Luciano Rovanni do Nascimento;Rodrigo Henrique Cunha Palácios;Márcio Mendonça;Lucas Botoni de Souza;José Augusto Fabri
This work aims to develop a board game called Prog-poly, based on the classic Monopoly board game to try to mitigate the facts reported by the students, and consequently assist in the teaching of programming language. The learning of programming languages is considered difficult by students of higher education in computing areas. The main reasons for this fact, according to students, are abstraction, logical reasoning, rigor in the use of programming languages. Increase the motivation level of students introducing programming languages learning through gamification aspects, thus aiding students to perform better in class. Initial evidence shows that the board game can help in the teaching activity, besides motivating the classes. To test Prog-poly board game, a mini-experiment was conducted with groups of students to compare Prog-poly efficiency with traditional teaching methods in the learning of algorithms, student motivation and fun factor. The authors obtained the following data: 95% of students answered Prog-poly motivates learning algorithms, 85% that the game offers learning algorithms, 80% considered the game to be a less tiring way of learning. Although initial results are presented, future works aim to compare their efficiency in teaching algorithms with the traditional way.
{"title":"Prog-Poly: A Board Game for Project-Based Learning in Programming and Software Engineering","authors":"Luciano Rovanni do Nascimento;Rodrigo Henrique Cunha Palácios;Márcio Mendonça;Lucas Botoni de Souza;José Augusto Fabri","doi":"10.1109/RITA.2025.3582716","DOIUrl":"https://doi.org/10.1109/RITA.2025.3582716","url":null,"abstract":"This work aims to develop a board game called Prog-poly, based on the classic Monopoly board game to try to mitigate the facts reported by the students, and consequently assist in the teaching of programming language. The learning of programming languages is considered difficult by students of higher education in computing areas. The main reasons for this fact, according to students, are abstraction, logical reasoning, rigor in the use of programming languages. Increase the motivation level of students introducing programming languages learning through gamification aspects, thus aiding students to perform better in class. Initial evidence shows that the board game can help in the teaching activity, besides motivating the classes. To test Prog-poly board game, a mini-experiment was conducted with groups of students to compare Prog-poly efficiency with traditional teaching methods in the learning of algorithms, student motivation and fun factor. The authors obtained the following data: 95% of students answered Prog-poly motivates learning algorithms, 85% that the game offers learning algorithms, 80% considered the game to be a less tiring way of learning. Although initial results are presented, future works aim to compare their efficiency in teaching algorithms with the traditional way.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"209-219"},"PeriodicalIF":1.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896776","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}
Pub Date : 2025-06-23DOI: 10.1109/RITA.2025.3582262
Evelyn Del Pezo Izaguirre;María J. Abásolo;César A. Collazos
UNESCO emphasizes the need for inclusive and quality education for all. In this context, the present article introduces BlipBla, a mobile and collaborative application designed to teach lip reading to preschool-aged deaf children. The development of BlipBla integrates active pedagogical methodologies, mobile technologies, and an accessible interface that facilitates interaction between teachers and students without requiring advanced reading and writing skills. The main contributions of this work include: 1) the design of an educational tool that incorporates vocabulary and sentences with clear grammatical structure; 2) the implementation of a customizable and collaborative environment; and 3) the validation of the application based on the ISO 25010 standard, which reported functional compliance above 94% in both the administrator and student environments. It is concluded that BlipBla represents a significant advancement in the development of accessible resources tailored to the needs of the deaf child community, and further testing with end users is projected to strengthen its usability and educational reach.
{"title":"BlipBla Mobile and Collaborative App to Teach Lip Reading to Children Who Are Deaf","authors":"Evelyn Del Pezo Izaguirre;María J. Abásolo;César A. Collazos","doi":"10.1109/RITA.2025.3582262","DOIUrl":"https://doi.org/10.1109/RITA.2025.3582262","url":null,"abstract":"UNESCO emphasizes the need for inclusive and quality education for all. In this context, the present article introduces BlipBla, a mobile and collaborative application designed to teach lip reading to preschool-aged deaf children. The development of BlipBla integrates active pedagogical methodologies, mobile technologies, and an accessible interface that facilitates interaction between teachers and students without requiring advanced reading and writing skills. The main contributions of this work include: 1) the design of an educational tool that incorporates vocabulary and sentences with clear grammatical structure; 2) the implementation of a customizable and collaborative environment; and 3) the validation of the application based on the ISO 25010 standard, which reported functional compliance above 94% in both the administrator and student environments. It is concluded that BlipBla represents a significant advancement in the development of accessible resources tailored to the needs of the deaf child community, and further testing with end users is projected to strengthen its usability and educational reach.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"182-190"},"PeriodicalIF":1.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680768","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}
Pub Date : 2025-04-28DOI: 10.1109/RITA.2025.3565180
Benjamín Maraza-Quispe;Victor Hugo Rosas-Iman;Giuliana Feliciano-Yucra;Atilio Cesar Martínez-Lopez;Lita Marianela Quispe-Flores;Edwin Reyes-Villalba;Pedro Pablo Nina-Mita
The research analyzes the impact of ChatGPT on the development of investigative competencies in students of regular basic education, focusing on three main aspects: its role in information retrieval, its contribution to the generation of accurate and relevant content, and its usability in fostering investigative skills. An experimental design was applied to a sample of 100 students, with 50 students using ChatGPT during the development of learning sessions and a control group of 50 students conducting their sessions through traditional methods. The students developed research projects evaluated according to six key criteria: coherence, precision, originality, content depth, problem-solving ability, and source management. Descriptive and comparative statistical analyses indicated that the experimental group outperformed the control group in coherence, precision, and originality. However, the control group showed better performance in source management, suggesting that traditional methodologies remain more effective for handling bibliographic references and searching for reliable sources. Regarding content depth and problem-solving ability, both groups achieved similar results, with a slight advantage observed in the experimental group. In summary, ChatGPT improves students’ coherence, precision, and originality in research tasks. Nonetheless, it is recommended to integrate its use with traditional methods to strengthen source management and ensure the comprehensive development of investigative competencies, promoting the ethical and responsible use of technology.
{"title":"Enhancing Research Capabilities in Teaching and Learning: The Transformative Impact of ChatGPT","authors":"Benjamín Maraza-Quispe;Victor Hugo Rosas-Iman;Giuliana Feliciano-Yucra;Atilio Cesar Martínez-Lopez;Lita Marianela Quispe-Flores;Edwin Reyes-Villalba;Pedro Pablo Nina-Mita","doi":"10.1109/RITA.2025.3565180","DOIUrl":"https://doi.org/10.1109/RITA.2025.3565180","url":null,"abstract":"The research analyzes the impact of ChatGPT on the development of investigative competencies in students of regular basic education, focusing on three main aspects: its role in information retrieval, its contribution to the generation of accurate and relevant content, and its usability in fostering investigative skills. An experimental design was applied to a sample of 100 students, with 50 students using ChatGPT during the development of learning sessions and a control group of 50 students conducting their sessions through traditional methods. The students developed research projects evaluated according to six key criteria: coherence, precision, originality, content depth, problem-solving ability, and source management. Descriptive and comparative statistical analyses indicated that the experimental group outperformed the control group in coherence, precision, and originality. However, the control group showed better performance in source management, suggesting that traditional methodologies remain more effective for handling bibliographic references and searching for reliable sources. Regarding content depth and problem-solving ability, both groups achieved similar results, with a slight advantage observed in the experimental group. In summary, ChatGPT improves students’ coherence, precision, and originality in research tasks. Nonetheless, it is recommended to integrate its use with traditional methods to strengthen source management and ensure the comprehensive development of investigative competencies, promoting the ethical and responsible use of technology.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"115-124"},"PeriodicalIF":1.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949294","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}
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