Authors:
De Omena, Rômulo Afonso L. V. and Da Silva, John Vitor T. and Rodrigues, Manoel Messias de O. and Filho, Maurício Freitas dos Santos and Silva, Sarah Kauane L. and Costa, Heshelley Roberta M. L. and Moraes, Débora Ruthe N. and Albuquerque, Arthur da Rocha
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.
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Authors:
Domínguez-Dorado, Manuel and Rodríguez-Pérez, Francisco J. and Cortés-Polo, David and Galeano-Brajones, Jesús and Calle-Cancho, Jesús
Abstract:
Situational awareness is crucial in cybersecurity to identify, understand, and anticipate cyber threats, and to make effective decisions during cyber crises. This study evaluates the effectiveness of a hands-on approach based on interactive scenarios using FLECO Studio software, integrated into the holistic management model CyberTOMP, compared to a traditional lecture-based approach framed within the same model. An experiment was designed with 200 participants, divided into a treatment group (70%) and a control group (30%). Both groups received training aimed at increasing their level of situational awareness in cybersecurity, with assessments conducted before and after the training. The treatment group employed the interactive scenario-based approach modeled with FLECO Studio, while the control group received traditional lecture-based training. To mitigate potential biases, preventive measures were implemented during the design and analysis of the study. The statistically analyzed results illustrated a significant improvement (up to 54%) in the situational awareness level of the treatment group, along with a strongly positive perception of effectiveness among the participants. These findings suggest that the interactive scenario-based approach, using tools embedded within a comprehensive holistic framework, significantly enhances the acquisition of situational awareness capabilities in cybersecurity compared to a traditional lecture-based approach.
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Authors:
González-Pérez, Laura Icela and García-Peñalvo, Francisco José and Argüelles-Cruz, Amadeo José
Abstract:
The responsible integration of Artificial Intelligence in Education (AIED) offers a strategic opportunity to align learning environments with the principles of Society 5.0, fostering human–technology synergy in support of quality education and social well-being. This study presents a systematic review of 36 peer-reviewed articles (2021–2025) focused on educational applications that employ learning analytics (LA) through data-driven approaches and integrate machine learning (ML) models as part of their empirical evidence. Each study was analyzed according to three key dimensions: the context of AIED application, the data-driven approach adopted, and the ML model implemented. The findings reveal a persistent disconnect between the AI models employed and the available educational data, which in many cases are limited to access logs or manually recorded grades that fail to capture deeper cognitive processes. This limitation constrains both the effective training of ML models and their pedagogical utility for delivering meaningful interventions such as personalized learning pathways, real-time feedback, early detection of learning difficulties, and monitoring and visualization tools. Another significant finding is the absence of psychopedagogical frameworks integrated with quality standards and data governance, which are essential for advancing prescriptive and ethical approaches aligned with learning goals. It is therefore recommended that educational leaders foster AIED applications grounded in data governance and ethics frameworks, ensuring valid and reliable metrics that can drive a more equitable and inclusive education.
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Authors:
Federico Larroca, Gonzalo Belcredi, Romina García Camargo, Gastón García González, Lucas Inglés, Camilo Mariño, Martín Randall
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.
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Authors:
María de Los Ángeles Martínez-Mercado, Gisela Elízabeth López-Bustamante, Azucena Minerva García-León, Elva Patricia Puente-Aguilar, Daniela del Carmen Bacre-Guzmán
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.
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Authors:
María-Carmen Ricoy, Natalia Varela-García, Joseba Delgado-Parada
Abstract:
Artificial Intelligence (AI) has recently risen in the educational field. However, studies showing the use of AI by school counselors are scarce, despite the benefits these tools can offer, especially with vulnerable groups. This study aims to analyze the perception of school counselors regarding AI. For this purpose, we analyzed the applications of AI, the challenges, training needs, and changes in their role as school counselors. This research is framed within the qualitative methodology through content analysis. For the data collection, an open-ended questionnaire was used with a sample of 20 school counselors from secondary schools. As main results and conclusions, it should be noted that the participants emphasize the help of AI in streamlining bureaucratic tasks in the school context, the personalization in vocational guidance, and the creation of materials to address student diversity, for example, with vulnerable groups. They identify challenges associated with human disconnection, lack of data privacy, and the need for training, essentially from a technical perspective. However, school counselors are still unclear about the changes in their roles and responsibilities derived from AI use. Some of them consider that AI will not entail relevant changes, while others anticipate the need for data interpretation and technological supervision. The findings of this study emphasize the need for further research on the benefits and risks of AI in school counseling for secondary education.
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Authors:
Ivanilse Calderon, Ana Carolina Oran, Williamson Silva, Eduardo Feitosa
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.
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Authors:
Siria Yahaira Valenzuela-Arvizu, Hugo Alexander Rozo-García, María Soledad Ramírez-Montoya
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.
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Authors:
Juárez-Hernández Julia Guadalupe, Fragoso-Díaz Olivia Graciela, Álvarez-Rodríguez Francisco Javier, Rojas-Pérez Juan Carlos
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.
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Authors:
Bing Yu, Jing Gong, Yumei Shan
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
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