Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Education in Software Engineering traditionally focuses on techniques used in the classroom that generate stress and disinterest in the topics taught; therefore, a significant challenge to the use of more effective and motivating teaching methods to achieve student learning. Moreover, the lack of motivating teaching methods results in a lack of perception regarding the importance of artifacts that come together with software, such as documentation. Consequently, students prefer to focus only on development without paying attention to the necessary artifacts, so the maintenance and update of software in later stages are negatively affected. In response to this problem, the need arises to incorporate more dynamic and effective teaching approaches that encourage student participation and commitment. In this sense, Gamification is presented as an innovative solution that has gained increasing interest in Software Engineering and other fields of education. This research aims to provide the results of a case study in which Gamification has been used in teaching Software Engineering for the topic of software requirements within a master's software engineering course.

This study evaluated and compared the levels of artistic creativity among undergraduate university students enrolled in distance learning programs across five distinct programs at a local university. The assessment focused on four key components: Fluency, Flexibility, Originality, and Elaboration. The results revealed significant differences in creativity between the programs, with Social Work students demonstrating higher levels of creativity compared to those in Tourism, and Marketing students surpassing their counterparts in the Tourism program. However, no significant differences in creativity were observed among other program pairings. Notably, while all programs excelled in the aspect of ”Elaboration,” ”Fluency” displayed a lower performance in the swift generation of ideas.The findings underscored the potential influence of myths, beliefs, and dogmas on creativity, particularly among Theology students. Moreover, the visual expression styles employed by students in the Tourism program may not align with the kinesthetic nature of their career profiles. These findings emphasize the imperative for further research to explore these factors. In conclusion, this study highlights the significance of tailored approaches to nurture creativity within distinct undergraduate programs with distance learning components and the interplay of creative dimensions in professional preparation across various fields.

This article explores the trends in online learning and the influence of specific criteria in the selection of online courses among executives and entrepreneurs in the business sector. The use of artificial intelligence (AI) in online learning platforms has been a key factor in enhancing the personalization and adaptability of courses, resulting in higher student satisfaction and success. The study highlights the evolution and importance of online learning platforms, detailing their methods, popular courses, pricing, and flexibility, which contribute to their success in virtual education. Additionally, the integration of AI technologies has allowed for a deeper analysis of student interaction patterns, facilitating the identification of areas for improvement and the implementation of personalized interventions. The research underscores the need for continuous updates in both technological tools and educator skills to meet the growing demands of online education. The article concludes that virtual education has a scalable and continuously growing future, driven by its perceived benefits and the adoption of advanced technologies.

Bullying is a global problem that negatively affects students, their families, and communities.This study addresses the creation and evaluation of an artificial intelligence (AI)-basedchatbot to provide emotional support to student victims of bullying, using a combination ofexploratory and descriptive approaches. A chatbot was developed on the Telegram messagingplatform, integrating the ChatGPT API to improve response generation. A topic- and equitysensitive design was implemented, and conversation logging and harassment detectionfunctionality was enabled. The research focused on the technical functionality of the chatbotand its ability to provide emotional support and guidance. The chatbot proved to be capable ofproviding basic emotional support and guidance to users. The integration of ChatGPTenriched the consistency and contextualization of responses. Intuitive interaction wasachieved through Telegram, providing relevant and contextually appropriate responses.Although this research focused on the technical functionality of the chatbot, itsimplementation in students and data analysis of user interactions represent important futuresteps. The chatbot has the potential to empower victims of bullying and improve schoolsafety. In addition, this research contributes to the creation of a new tool for collecting andanalyzing data on bullying, improving early detection and prevention.

Inclusive education is a topic that has acquired relevance in last years with an extraordinary strong, and it’s because education in general, is crucial for the development of any country. However, most of higher education institutions aren’t prepared to attend real needs of teaching-learning process to each student in a personal way, this situation is more complex when college students have one or more kinds of learning deficit or belong to one or more vulnerable social groups. In other hand, college teachers play a very important role in teaching-learning process, but unfortunately most of them don’t have necessary digital skills to teach their students from an inclusive education perspective. Besides technological resources in higher education institutions, are designed and developed for regular students. This research has as main goal explain how a federated learning model trained with higher education data students helps to understand students’ characteristics to get a student profile and be able to provide each student with the most useful digital tools and contents as support to satisfy every kind of personal learning needs, to mitigate historical learning disadvantages of student with any kind of learning deficit.

Industry 4.0 is driving significant transformations, even in complex and uncertain industrial environments. This concept represents an innovation strategy aimed at redefining the manufacturing sector, enhancing global competitiveness through cost reduction, more agile processes, and superior product quality. Concurrently, Artificial Intelligence (AI) is at the forefront of a profound shift in organizational management and operations, reshaping professional routines and redefining society's interaction with technology. The increasing complexity of business environments, particularly the inherent challenges within industrial sectors, alongside continuous technological advancements, establishes AI as a critical tool not only for fostering innovation but also for optimizing efficiency and enhancing competitiveness across all organizational domains. In this context, this study introduces a structured model grounded in the theoretical exploration of Industry 4.0 maturity models to assess the current maturity levels of AI utilization in the industry. Thus, this work presents the development of a standard for measuring AI adoption levels in Industry 4.0. This index will illuminate companies’ readiness and proficiency in integrating AI into both daily operations and strategic processes. Through the continued application of this tool, companies will also gain insights into their growth across the evaluated domains.

Epidemiological studies have demonstrated a significant increase in the incidence of Autism Spectrum Disorder (ASD) in the population over the years. Estimates indicate that approximately 1% of children worldwide are diagnosed with autism, while in the United States, this ratio is 1 in every 36 children. Additionally, research suggests a growing interest in technology among autistic children, with the use of computing devices showing potential for the development of social and emotional skills. Digital technology is widely recognized for playing a crucial role in promoting social inclusion and improving the quality of life for people with disabilities. In this context, social networks offer a virtual environment for entertainment and interaction among various groups of individuals. This project aims to present a social network platform specifically developed for adolescents with Autism Spectrum Disorder. The project incorporates various accessibility concepts and strategies to promote interaction and socialisation among community members. Usability and accessibility evaluations were conducted in different ways. First, an initial usability test, conducted within the scope of the tool's development, involved two students and a professor in the field of HCI. Subsequently, the usability of the social network was evaluated by three specialists using Nielsen's heuristic evaluation technique, revealing few usability issues, as presented in this article. Furthermore, usability inspections were conducted using automated tools, identifying x issues, as described in the text. Finally, a test with an ASD specialist was conducted, whose considerations indicate good clinical use prospects for the tool, which are detailed in this article.

Time-series evaluation explores the way in which data differs over time and optimal prediction could determine the pathway wherein the data seems to be changing. Prediction of time-series might possess significant value for business development when one possess the access to existing information with time-constituent. Concurrently, DL (Deep Learning) algorithms are capable of offering promising solution to predict time-series due to their advantages in automatic temporal learning. With extensive usage of DL based models in varied areas like science, one might be tangled as to determine the suitable model to resolve the existing issues. Moreover, these methods might be used by existing works in various forms like hybrid. Hence, this study is instigated by an intention to afford a precise review about the recent DL based models to predict time-series. Hence, this study reviews the recent research works (2018-2023) related to the use of DL based models for effective time-series prediction in various areas. Further, a comparatively assessment is undertaken by considering the conventional DL models and varied applications of widely employed DL models for efficient prediction of time-series. Lastly, the research gaps are emphasized from conventional studies with future recommendations. This would support future researches in resolving the prevailing challenges in this area, thereby attempt to bring innovations for effective time-series prediction.

In the era of Industry 4.0, the success of the adoption of advanced technologies depends on how they are assimilated and incorporated into current production systems. This work focuses on analyzing the state of technological adoption in Small and Medium Enterprises (SMEs) in the metalworking sector in Argentina, analyzing the ICT products implemented in each of the functional areas of the company that maintain interaction with the people who operate them and identifying the knowledge and capabilities of real users for each functional area. For this purpose, an expanded InTICs®methodology was used to measure the degree of technological maturity of a productive company. The obtained results show that most of the companies surveyed present a medium level of technological maturity, with variations depending on their size. Microenterprises tend to register a basic level of maturity, while medium and large companies show greater adoption of advanced technologies. These results offer a detailed vision of the integration of Industry 4.0 technologies in Argentine metalworking SMEs, providing valuable information to identify users and the levels of interaction between people and the technologies they operate, as well as to analyze the required human capabilities and training strategies to promote digital transformation in this sector.

This paper extends previous work on usability evaluation heuristics for e-commerce platforms by conducting a detailed experimentation to validate and refine the proposed heuristic set. A group of international expert evaluators applied the new heuristics to an e-commerce platform, providing both individual assessments and qualitative feedback. The results revealed significant insights into the platform's usability, highlighting strengths and areas needing improvement. This process not only identified deficiencies but also allowed for the adjustment and optimization of the heuristic questions to better reflect user needs and expectations. The validated heuristics, which include 15 guidelines and 60 questions, provide a comprehensive evaluation framework, quantifying usability through a percentage score. The findings contribute to the ongoing enhancement of e-commerce platform usability and offer valuable knowledge for the usability and user experience research community.