Pub Date : 2025-11-19DOI: 10.1109/RITA.2025.3634558
Bing Yu;Jing Gong;Yumei Shan
In this paper, the E-learning ability (learners’ ability to efficiently utilize digital tools and resources) and academic performance of university students were investigated by means of a questionnaire survey. The E-learning ability was considered from five aspects, including conscious ability. A total of 689 questionnaires were distributed, and 646 questionnaires were recycled. The rationality of the questionnaire was verified by project analysis. According to the collected data, the differences in different aspects of E-learning ability and academic performance in terms of gender, age, and major were analyzed. The results showed that both the overall E-learning ability and academic performance of university students need to be improved. In terms of gender, only the technical ability had a significant difference (t = 3.947, p = 0.000). In terms of grade, there were significant differences in management ability, evaluation ability, and academic performance (p <0.01). In terms of major, the E-learning ability and academic performance had significant differences (p <0.01). The influence of E-learning ability on students’ academic performance was analyzed by regression analysis, and it was found that conscious, technical, and management abilities had positive predictive effects on academic performance. The results verify that E-learning ability has a positive impact on students’ academic performance, and university students should pay attention to improving E-learning ability.
本文采用问卷调查的方法，对大学生的E-learning能力（学习者有效利用数字工具和资源的能力）和学习成绩进行了调查。E-learning能力从五个方面考虑，包括意识能力。共发放问卷689份，回收问卷646份。通过项目分析验证了问卷的合理性。根据收集到的数据，分析不同性别、年龄、专业的学生在E-learning能力和学习成绩的不同方面的差异。结果表明，大学生的整体网络学习能力和学习成绩都有待提高。在性别方面，只有技术能力有显著差异（t = 3.947, p = 0.000）。在年级上，管理能力、评价能力、学业成绩差异有统计学意义（p <0.01）。在专业方面，E-learning能力和学业成绩有显著差异（p <0.01）。通过回归分析分析网络学习能力对学生学业成绩的影响，发现意识能力、技术能力和管理能力对学业成绩有正向预测作用。研究结果验证了E-learning能力对学生学业成绩有积极影响，大学生应重视提高E-learning能力。
{"title":"The Impact of E-Learning Ability on Students’ Academic Performance: Using Regression Analysis","authors":"Bing Yu;Jing Gong;Yumei Shan","doi":"10.1109/RITA.2025.3634558","DOIUrl":"https://doi.org/10.1109/RITA.2025.3634558","url":null,"abstract":"In this paper, the E-learning ability (learners’ ability to efficiently utilize digital tools and resources) and academic performance of university students were investigated by means of a questionnaire survey. The E-learning ability was considered from five aspects, including conscious ability. A total of 689 questionnaires were distributed, and 646 questionnaires were recycled. The rationality of the questionnaire was verified by project analysis. According to the collected data, the differences in different aspects of E-learning ability and academic performance in terms of gender, age, and major were analyzed. The results showed that both the overall E-learning ability and academic performance of university students need to be improved. In terms of gender, only the technical ability had a significant difference (t = 3.947, p = 0.000). In terms of grade, there were significant differences in management ability, evaluation ability, and academic performance (p <0.01). In terms of major, the E-learning ability and academic performance had significant differences (p <0.01). The influence of E-learning ability on students’ academic performance was analyzed by regression analysis, and it was found that conscious, technical, and management abilities had positive predictive effects on academic performance. The results verify that E-learning ability has a positive impact on students’ academic performance, and university students should pay attention to improving E-learning ability.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"422-427"},"PeriodicalIF":1.0,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674777","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 : 2025-11-17DOI: 10.1109/RITA.2025.3633807
Siria Yahaira Valenzuela-Arvizu;Hugo Alexander Rozo-García;María Soledad Ramírez-Montoya
In the current landscape of higher education, fostering high-level cognitive skills such as Complex Thinking (CT) requires digital platforms that not only enable meaningful learning but also meet key criteria of usability, accessibility, and inclusion. Evaluating these dimensions becomes particularly relevant when platforms incorporate emerging technologies, including Artificial Intelligence (AI), as complementary tools to support and enrich the user experience. This study presents the results of the piloting of a Likert-type instrument designed to assess the technical and pedagogical usability, accessibility/inclusiveness, and the effectiveness of AI as a support tool in an educational platform focused on CT development. A non-experimental quantitative design of descriptive transactional type was applied to 218 users of a platform with AI integration. The findings indicate that: a) the restructuring of the instrument improved its reliability, validity, and coherence, consolidating a relevant model for evaluating educational platforms; b) the validation process highlights the need to assess platforms through technical and pedagogical lenses to ensure usability, accessibility, and inclusion; c) the inclusion of the AI dimension responds to the imperative of addressing emerging technologies from evaluative and pedagogical perspectives, making the instrument timely and context-aware; d) the instrument demonstrates cross-cutting potential and adaptability to various platforms, reinforcing its utility for advancing equitable digital education aligned with the Sustainable Development Goals (SDGs). This study contributes to the comprehensive evaluation of usability in educational platforms with AI integration, expanding the notion of usability to include pedagogical, inclusive, and accessible design principles, and offering a robust tool to assess user experience in technologically mediated learning environments.
{"title":"Instrument SmartUsability—Complexity, Usability, and AI-Driven Educational Platform: Validation With Pilot Study","authors":"Siria Yahaira Valenzuela-Arvizu;Hugo Alexander Rozo-García;María Soledad Ramírez-Montoya","doi":"10.1109/RITA.2025.3633807","DOIUrl":"https://doi.org/10.1109/RITA.2025.3633807","url":null,"abstract":"In the current landscape of higher education, fostering high-level cognitive skills such as Complex Thinking (CT) requires digital platforms that not only enable meaningful learning but also meet key criteria of usability, accessibility, and inclusion. Evaluating these dimensions becomes particularly relevant when platforms incorporate emerging technologies, including Artificial Intelligence (AI), as complementary tools to support and enrich the user experience. This study presents the results of the piloting of a Likert-type instrument designed to assess the technical and pedagogical usability, accessibility/inclusiveness, and the effectiveness of AI as a support tool in an educational platform focused on CT development. A non-experimental quantitative design of descriptive transactional type was applied to 218 users of a platform with AI integration. The findings indicate that: a) the restructuring of the instrument improved its reliability, validity, and coherence, consolidating a relevant model for evaluating educational platforms; b) the validation process highlights the need to assess platforms through technical and pedagogical lenses to ensure usability, accessibility, and inclusion; c) the inclusion of the AI dimension responds to the imperative of addressing emerging technologies from evaluative and pedagogical perspectives, making the instrument timely and context-aware; d) the instrument demonstrates cross-cutting potential and adaptability to various platforms, reinforcing its utility for advancing equitable digital education aligned with the Sustainable Development Goals (SDGs). This study contributes to the comprehensive evaluation of usability in educational platforms with AI integration, expanding the notion of usability to include pedagogical, inclusive, and accessible design principles, and offering a robust tool to assess user experience in technologically mediated learning environments.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"461-469"},"PeriodicalIF":1.0,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830808","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 : 2025-11-07DOI: 10.1109/RITA.2025.3630467
Juan Carlos Suárez Gómez;Mónica Marcela Sánchez Duarte;Andrés Chiappe;Laura Fontán de Bedout
Educational inclusion and addressing diversity are the primary challenges facing the education sector in the 21st century. This article explores the potential of Artificial Intelligence (AI) as a supportive tool for educators working with students with Functional Diversity (FD), aiming to foster the development of autonomy in learning. It examines how AI can facilitate teaching practices in diverse classrooms and assist students with these characteristics, promoting their autonomy. The analysis suggests that AI offers significant opportunities to provide personalized support to this population by delivering immediate feedback, tailored resources, and improving teachers’ classroom management. In this sense, the integration of AI can help create truly inclusive educational spaces, benefiting not only the target population but also educators and their families. However, discussions regarding the security and ethical considerations of AI in handling the personal data of the educational agents involved remain ongoing.
{"title":"Redefining Inclusive Education: The Transformative Impact of Artificial Intelligence in Students Learning Autonomy","authors":"Juan Carlos Suárez Gómez;Mónica Marcela Sánchez Duarte;Andrés Chiappe;Laura Fontán de Bedout","doi":"10.1109/RITA.2025.3630467","DOIUrl":"https://doi.org/10.1109/RITA.2025.3630467","url":null,"abstract":"Educational inclusion and addressing diversity are the primary challenges facing the education sector in the 21st century. This article explores the potential of Artificial Intelligence (AI) as a supportive tool for educators working with students with Functional Diversity (FD), aiming to foster the development of autonomy in learning. It examines how AI can facilitate teaching practices in diverse classrooms and assist students with these characteristics, promoting their autonomy. The analysis suggests that AI offers significant opportunities to provide personalized support to this population by delivering immediate feedback, tailored resources, and improving teachers’ classroom management. In this sense, the integration of AI can help create truly inclusive educational spaces, benefiting not only the target population but also educators and their families. However, discussions regarding the security and ethical considerations of AI in handling the personal data of the educational agents involved remain ongoing.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"372-380"},"PeriodicalIF":1.0,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560795","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}
This study explores the impact of ludoeducational robotics on second language learning through the implementation of two interactive applications developed for the Ludibot robot. The aim was to assess whether these applications, based on constructivist and interactionist principles, could enhance learner motivation, improve vocabulary and grammar acquisition, and support meaningful engagement in French language learning. A total of 82 postgraduate students in Mexico participated in individual 45-minute sessions guided by a French instructor. During these sessions, students interacted with Ludibot using voice and computer peripherals to engage with the educational games. Data was collected through a 20-item post-session questionnaire exploring perceptions of educational robotics. The results showed high levels of user satisfaction, particularly regarding usability and motivation. Quantitative data confirmed that students found the experience enjoyable and valuable, though some expressed concerns about overreliance on technology. The system’s technical foundation involves two main architectures employing specialized components, a custom nonlinear control law for locomotion, and the integration of external sensors like the Kinect. The study contributes to the growing field of ludoeducational robotics by offering a pedagogically grounded model that integrates robotics, gamification, and language didactics. Key implementation challenges included ensuring precise Kinect sensor calibration and developing robust communication protocols for the real-time interaction between multiple subsystems. It demonstrates that non-adaptive robots can still provide effective learning experiences when carefully designed. The findings support the inclusion of robotics in language education and point to the need for further research on adaptive systems, diverse learner populations, and long-term learning outcomes.
{"title":"Experimental Study of Ludoeducational Robotics to Teaching of a Second Language: Human–Robot Interaction and Play Among Students in Mexico","authors":"Eduardo Vázquez Bonilla;Anilú Franco-Árcega;Virgilio López-Morales;Manuel Alejandro Ojeda-Misses","doi":"10.1109/RITA.2025.3627590","DOIUrl":"https://doi.org/10.1109/RITA.2025.3627590","url":null,"abstract":"This study explores the impact of ludoeducational robotics on second language learning through the implementation of two interactive applications developed for the Ludibot robot. The aim was to assess whether these applications, based on constructivist and interactionist principles, could enhance learner motivation, improve vocabulary and grammar acquisition, and support meaningful engagement in French language learning. A total of 82 postgraduate students in Mexico participated in individual 45-minute sessions guided by a French instructor. During these sessions, students interacted with Ludibot using voice and computer peripherals to engage with the educational games. Data was collected through a 20-item post-session questionnaire exploring perceptions of educational robotics. The results showed high levels of user satisfaction, particularly regarding usability and motivation. Quantitative data confirmed that students found the experience enjoyable and valuable, though some expressed concerns about overreliance on technology. The system’s technical foundation involves two main architectures employing specialized components, a custom nonlinear control law for locomotion, and the integration of external sensors like the Kinect. The study contributes to the growing field of ludoeducational robotics by offering a pedagogically grounded model that integrates robotics, gamification, and language didactics. Key implementation challenges included ensuring precise Kinect sensor calibration and developing robust communication protocols for the real-time interaction between multiple subsystems. It demonstrates that non-adaptive robots can still provide effective learning experiences when carefully designed. The findings support the inclusion of robotics in language education and point to the need for further research on adaptive systems, diverse learner populations, and long-term learning outcomes.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"358-371"},"PeriodicalIF":1.0,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145510155","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 : 2025-10-30DOI: 10.1109/RITA.2025.3627111
Juárez-Hernández Julia Guadalupe;Fragoso-Díaz Olivia Graciela;Álvarez-Rodríguez Francisco Javier;Rojas-Pérez Juan Carlos
The advancement of information and communication technologies has facilitated access to learning resources, thereby transforming the manner in which knowledge is acquired both within the context of formal education and within the context of job training. However, one of the problems that accompanies the learning resources is the lack of methods to assess their quality so that users may select the best ones in order to achieve the learning objectives. One of the attributes that has been extensively mentioned in the literature as important to achieve learning objectives is completeness, which refers to how much information a resource must contain in order to support a learning objective. However, there are not recognized methods to measure completeness. This work objective is to develop a method and a system for evaluating completeness of learning resources employed in the context of workplace training. It is crucial to ensure the completeness of a resource in order to determine whether it contains the required information to achieve the learning objective for an organization. The method for completeness evaluation comprises the formal definition of a business process, the identification of its products, and a comparison of its products with the content of the learning resources, using natural language processing and six similarity measures. Forty learning resources were assessed for completeness; the results show that a considerable number of the evaluated learning resources exhibit significant deficiencies in terms of completeness. The method is a first approach to measure completeness from a business process, and some limitations were identified. It assumes equal importance among all content elements in a resource; it penalizes extensive resources such as books, and depends heavily on well-documented business processes. Furthermore, completeness should be considered alongside other quality attributes to ensure a more comprehensive evaluation of learning resources.
{"title":"Completeness in Learning Resources: A Business Process Perspective","authors":"Juárez-Hernández Julia Guadalupe;Fragoso-Díaz Olivia Graciela;Álvarez-Rodríguez Francisco Javier;Rojas-Pérez Juan Carlos","doi":"10.1109/RITA.2025.3627111","DOIUrl":"https://doi.org/10.1109/RITA.2025.3627111","url":null,"abstract":"The advancement of information and communication technologies has facilitated access to learning resources, thereby transforming the manner in which knowledge is acquired both within the context of formal education and within the context of job training. However, one of the problems that accompanies the learning resources is the lack of methods to assess their quality so that users may select the best ones in order to achieve the learning objectives. One of the attributes that has been extensively mentioned in the literature as important to achieve learning objectives is completeness, which refers to how much information a resource must contain in order to support a learning objective. However, there are not recognized methods to measure completeness. This work objective is to develop a method and a system for evaluating completeness of learning resources employed in the context of workplace training. It is crucial to ensure the completeness of a resource in order to determine whether it contains the required information to achieve the learning objective for an organization. The method for completeness evaluation comprises the formal definition of a business process, the identification of its products, and a comparison of its products with the content of the learning resources, using natural language processing and six similarity measures. Forty learning resources were assessed for completeness; the results show that a considerable number of the evaluated learning resources exhibit significant deficiencies in terms of completeness. The method is a first approach to measure completeness from a business process, and some limitations were identified. It assumes equal importance among all content elements in a resource; it penalizes extensive resources such as books, and depends heavily on well-documented business processes. Furthermore, completeness should be considered alongside other quality attributes to ensure a more comprehensive evaluation of learning resources.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"347-357"},"PeriodicalIF":1.0,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145455899","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}
Teaching programming requires instructors to help students develop complex problem-solving and logical reasoning skills. Active Learning Methodologies (ALMs) have the potential to enhance this process, but their adoption in programming education remains limited due to various challenges. This study, from the instructors’ perspective, explores the use of ALMs in programming education across Brazil, identifying key barriers, perceived benefits, and strategies for wider adoption through an online survey of programming instructors. The findings reveal a wide range of programming languages, tools, and platforms in use, as well as 11 key motivators and 19 benefits associated with ALM adoption. Results highlight the diversity of teaching practices, the positive impact of ALMs on student engagement and learning outcomes, and the need for institutional support and further research. By identifying the factors that influence ALM adoption, the study provides valuable insights for educators, institutions, and policymakers seeking to enhance programming instruction through more active and effective learning approaches.
{"title":"Investigating the Use of Active Learning Methodologies in Programming Education: Findings From a Brazilian National Survey","authors":"Ivanilse Calderon;Ana Carolina Oran;Williamson Silva;Eduardo Feitosa","doi":"10.1109/RITA.2025.3625548","DOIUrl":"https://doi.org/10.1109/RITA.2025.3625548","url":null,"abstract":"Teaching programming requires instructors to help students develop complex problem-solving and logical reasoning skills. Active Learning Methodologies (ALMs) have the potential to enhance this process, but their adoption in programming education remains limited due to various challenges. This study, from the instructors’ perspective, explores the use of ALMs in programming education across Brazil, identifying key barriers, perceived benefits, and strategies for wider adoption through an online survey of programming instructors. The findings reveal a wide range of programming languages, tools, and platforms in use, as well as 11 key motivators and 19 benefits associated with ALM adoption. Results highlight the diversity of teaching practices, the positive impact of ALMs on student engagement and learning outcomes, and the need for institutional support and further research. By identifying the factors that influence ALM adoption, the study provides valuable insights for educators, institutions, and policymakers seeking to enhance programming instruction through more active and effective learning approaches.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"381-390"},"PeriodicalIF":1.0,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560796","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 : 2025-10-13DOI: 10.1109/RITA.2025.3620720
Federico Larroca;Gonzalo Belcredi;Romina García Camargo;Gastón García González;Lucas Inglés;Camilo Mariño;Martín Randall
This article presents and discusses a communications-themed Capture the Flag (CTF) competition designed to enhance visibility and engagement with Electrical and Communications Engineering (ECE). In response to declining enrollments in ECE disciplines worldwide, and in line with pedagogical research advocating for early technical exposure, our initiative leverages Software Defined Radio (SDR) as both a teaching tool and a medium for community building. The CTF features two complementary formats: a virtual edition, designed for technically advanced students and professionals, and an in-person edition, aimed at high-school students and the general public. The virtual challenges are based on recorded IQ signals, requiring participants to decode messages using SDR tools like GNU Radio, guided by appealing narrative clues. The in-person version takes the form of a treasure hunt using live radio signals—initially with SDRs and later simplified to smartphone-accessible signals such as audio, Bluetooth or Wi-Fi. In addition to describing in detail both versions of the CTF, we share pivotal lessons learned in our five years’ experience. During this time, the CTF has grown into a robust educational and outreach platform, fostering a community of SDR practitioners, supporting curriculum development, and motivating students to pursue careers in telecommunications. We are convinced that this kind of hands-on, narrative-driven technical challenges can play a significant role in demystifying complex concepts, stimulating interest in ECE, and bridging gaps between education, industry, and the public.
{"title":"Gamifying Signals: Communications-Themed Capture the Flag for Outreach, Engagement, and Education","authors":"Federico Larroca;Gonzalo Belcredi;Romina García Camargo;Gastón García González;Lucas Inglés;Camilo Mariño;Martín Randall","doi":"10.1109/RITA.2025.3620720","DOIUrl":"https://doi.org/10.1109/RITA.2025.3620720","url":null,"abstract":"This article presents and discusses a communications-themed Capture the Flag (CTF) competition designed to enhance visibility and engagement with Electrical and Communications Engineering (ECE). In response to declining enrollments in ECE disciplines worldwide, and in line with pedagogical research advocating for early technical exposure, our initiative leverages Software Defined Radio (SDR) as both a teaching tool and a medium for community building. The CTF features two complementary formats: a virtual edition, designed for technically advanced students and professionals, and an in-person edition, aimed at high-school students and the general public. The virtual challenges are based on recorded IQ signals, requiring participants to decode messages using SDR tools like GNU Radio, guided by appealing narrative clues. The in-person version takes the form of a treasure hunt using live radio signals—initially with SDRs and later simplified to smartphone-accessible signals such as audio, Bluetooth or Wi-Fi. In addition to describing in detail both versions of the CTF, we share pivotal lessons learned in our five years’ experience. During this time, the CTF has grown into a robust educational and outreach platform, fostering a community of SDR practitioners, supporting curriculum development, and motivating students to pursue careers in telecommunications. We are convinced that this kind of hands-on, narrative-driven technical challenges can play a significant role in demystifying complex concepts, stimulating interest in ECE, and bridging gaps between education, industry, and the public.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"328-337"},"PeriodicalIF":1.0,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351908","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 : 2025-10-13DOI: 10.1109/RITA.2025.3620839
María de Los Ángeles Martínez-Mercado;Gisela Elízabeth López-Bustamante;Azucena Minerva García-León;Elva Patricia Puente-Aguilar;Daniela del Carmen Bacre-Guzmán
This study analyzes the perception and level of learning in artificial intelligence (AI) topics among Industrial Engineering students at a university in northern Mexico. Using a quantitative approach, a survey was administered to 64 students, focusing on dimensions such as perceived learning, academic and professional use of AI, and the perceived importance of its curricular integration. The findings reveal a limited perception of AI learning among Industrial Engineering students, with the Internet of Things and Data Security and Protection emerging as the highest-rated topics. In contrast, low levels of learning were reported in Predictive Maintenance, Deep Learning, and Quality Control. While 85% of participants consider the inclusion of AI in the curriculum to be essential, only 50% report using these tools in workplace settings. A strong association was identified between Predictive Maintenance and Quality Control, suggesting thematically relevant links for the discipline. These results highlight a gap between theoretical training and practical application of AI, indicating clear opportunities to strengthen its curricular integration.
{"title":"Artificial Intelligence Learning: Perceptions and Challenges in the Profile of Industrial Engineering Students","authors":"María de Los Ángeles Martínez-Mercado;Gisela Elízabeth López-Bustamante;Azucena Minerva García-León;Elva Patricia Puente-Aguilar;Daniela del Carmen Bacre-Guzmán","doi":"10.1109/RITA.2025.3620839","DOIUrl":"https://doi.org/10.1109/RITA.2025.3620839","url":null,"abstract":"This study analyzes the perception and level of learning in artificial intelligence (AI) topics among Industrial Engineering students at a university in northern Mexico. Using a quantitative approach, a survey was administered to 64 students, focusing on dimensions such as perceived learning, academic and professional use of AI, and the perceived importance of its curricular integration. The findings reveal a limited perception of AI learning among Industrial Engineering students, with the Internet of Things and Data Security and Protection emerging as the highest-rated topics. In contrast, low levels of learning were reported in Predictive Maintenance, Deep Learning, and Quality Control. While 85% of participants consider the inclusion of AI in the curriculum to be essential, only 50% report using these tools in workplace settings. A strong association was identified between Predictive Maintenance and Quality Control, suggesting thematically relevant links for the discipline. These results highlight a gap between theoretical training and practical application of AI, indicating clear opportunities to strengthen its curricular integration.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"338-346"},"PeriodicalIF":1.0,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405357","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 : 2025-10-08DOI: 10.1109/RITA.2025.3613135
Andrea Lazarte-Aguirre;Rafael Fernández-Concha;Nicolás Núñez
In a highly competitive context where generative artificial intelligence (GAI) tools are gaining increasing relevance in educational learning environments, it is essential to understand the motivations and factors driving graduate students to adopt these technologies. This study systematically identifies the factors influencing graduate students’ intentions to use GAI tools. Students and alumni from a graduate business school in Peru were surveyed to assess their intentions regarding GAI technology usage. The study builds on the Unified Theory of Acceptance and Use of Technology (UTAUT) by incorporating GAI literacy as a variable. In late 2024, 251 participants from diverse backgrounds completed a questionnaire, which was then analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS 4.1.0.2. This analysis aimed to uncover key factors influencing GAI adoption in higher education. The findings reveal that performance expectancy (PE), effort expectancy (EE), and perceived risk (PR) significantly influence the intention to use GAI, whereas facilitating conditions (FC) and social influence (SI) do not. Furthermore, prior experience with GAI moderates the relationships between FC, SI, and the intention to use GAI. These insights into the factors shaping GAI adoption intentions are vital for informing strategies to ethically leverage artificial intelligence (AI) in business and academia. By understanding user motivations, organizations can develop targeted policies and training programs to ensure responsible AI integration and maximize its potential benefits.
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Pub Date : 2025-10-06DOI: 10.1109/RITA.2025.3616857
Rômulo Afonso L. V. de Omena;John Vitor T. da Silva;Manoel Messias de O. Rodrigues;Maurício Freitas Dos Santos Filho;Sarah Kauane L. Silva;Heshelley Roberta M. L. Costa;Débora Ruthe N. Moraes;Arthur da Rocha Albuquerque;Johnny Guilherme da Silva;Victor Gabriel de Jesus Oliveira;Marina Marra M. de Oliveira;Heloise Rayane da R. Santos;Ana Luisa de P. S. Melo;Hewerton Nascimento da Silva;Mariana Paulino Dos Santos;José Kawê S. M. da Silva;Allisson Luiz N. da Silva;Jacksiel José de Abreu
An education model with pillars on science, technology, engineering, and mathematics (STEM) is increasingly necessary to prepare our students for future jobs. A didactic tool that can engage students in STEM is robotics. A study area of robotics, mobile robotics is a rich tool that generates enthusiasm in students and involves diverse disciplines. While commercial robotic platforms for education exist, their high cost and limited customizability often pose challenges, particularly within the Brazilian public education system. This paper presents an experience with ten technical secondary school students focused on developing two distinct low-cost mobile robots: a differential drive and an omnidirectional one, sponsored by a research foundation. The primary objectives were to investigate the impact of a maker-approach environment on the enhancement of STEM skills and to provide accessible robotic platforms for future educational projects. Students, divided into pairs, worked collaboratively on various aspects of robot development, including chassis design, power supply, motor drive, data acquisition, and simulation and coding, utilizing computational tools like Tinkercad, AutoCAD, Arduino IDE, and ROS 2. This project aimed to answer how such an initiative could foster specific STEM competencies and what challenges and perceptions arise from the students’ perspective. The experience demonstrated that students not only developed STEM skills but also contributed valuable robotic platforms to the academic community. The initiative underscores the importance of foundational support in equipping the Brazilian education system to prepare students with skills vital for future professions.
{"title":"Enhancing STEM Skills With the Design of Mobile Robots: An Experience With Technical Secondary School Students","authors":"Rômulo Afonso L. V. de Omena;John Vitor T. da Silva;Manoel Messias de O. Rodrigues;Maurício Freitas Dos Santos Filho;Sarah Kauane L. Silva;Heshelley Roberta M. L. Costa;Débora Ruthe N. Moraes;Arthur da Rocha Albuquerque;Johnny Guilherme da Silva;Victor Gabriel de Jesus Oliveira;Marina Marra M. de Oliveira;Heloise Rayane da R. Santos;Ana Luisa de P. S. Melo;Hewerton Nascimento da Silva;Mariana Paulino Dos Santos;José Kawê S. M. da Silva;Allisson Luiz N. da Silva;Jacksiel José de Abreu","doi":"10.1109/RITA.2025.3616857","DOIUrl":"https://doi.org/10.1109/RITA.2025.3616857","url":null,"abstract":"An education model with pillars on science, technology, engineering, and mathematics (STEM) is increasingly necessary to prepare our students for future jobs. A didactic tool that can engage students in STEM is robotics. A study area of robotics, mobile robotics is a rich tool that generates enthusiasm in students and involves diverse disciplines. While commercial robotic platforms for education exist, their high cost and limited customizability often pose challenges, particularly within the Brazilian public education system. This paper presents an experience with ten technical secondary school students focused on developing two distinct low-cost mobile robots: a differential drive and an omnidirectional one, sponsored by a research foundation. The primary objectives were to investigate the impact of a maker-approach environment on the enhancement of STEM skills and to provide accessible robotic platforms for future educational projects. Students, divided into pairs, worked collaboratively on various aspects of robot development, including chassis design, power supply, motor drive, data acquisition, and simulation and coding, utilizing computational tools like Tinkercad, AutoCAD, Arduino IDE, and ROS 2. This project aimed to answer how such an initiative could foster specific STEM competencies and what challenges and perceptions arise from the students’ perspective. The experience demonstrated that students not only developed STEM skills but also contributed valuable robotic platforms to the academic community. The initiative underscores the importance of foundational support in equipping the Brazilian education system to prepare students with skills vital for future professions.","PeriodicalId":38963,"journal":{"name":"Revista Iberoamericana de Tecnologias del Aprendizaje","volume":"20 ","pages":"290-301"},"PeriodicalIF":1.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886578","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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