This study addresses the need to integrate ethical, human-centered principles into user experience (UX) design for generative AI (GenAI)-based assistants. Acknowledging the ethical and societal challenges posed by the democratization of GenAI, this study developed a set of six UX design guidelines and 37 recommendations to guide development teams in creating GenAI assistants. A card-based toolkit was designed to encapsulate these guidelines, applying color theory and Gestalt principles to enhance usability and understanding. The design science research methodology (DSRM) was followed, and the toolkit was validated through a hands-on workshop with software and UX professionals, assessing usability, user experience, and utility. The quantitative results indicated the high internal consistency and effectiveness of the toolkit, while the qualitative analysis highlighted its capacity to foster collaboration and address GenAI-specific challenges. This study concludes that the toolkit improves usability and utility in UX design for GenAI-based assistants, though it identifies areas for future enhancement and the need for further validation across varied contexts.

This study characterizes Inclusive Interactive Multimedia Experiences (IIMEs) within school contexts by integrating learning analytics to enable personalized student monitoring and evaluation. By analyzing regulatory documents and multimedia systems (MS) development methodologies, this paper provides comprehensive guidance for IIME pre-production, focusing on learning objectives, activities, responsible design, and inclusion. The research presents a detailed framework for IIME development. It addresses the integration of digital media, interaction modalities, sensory systems, and emotional engagement. Furthermore, it examines the technological mediation necessary to deliver a holistic multimedia experience, prioritizing accessibility and cultural sensitivity. A case study conducted at Rafael Navia Varón School in Cali, Colombia, demonstrates the practical application of the proposed framework through the development of Decisiones Cruciales, an IIME designed to address bullying and cyberbullying via interactive storytelling. This IIME uses learning analytics to provide teachers with detailed metrics on student performance and socio-emotional competencies. The findings from the students’ analysis highlight their engagement and the educational impact of the IIME, particularly in fostering empathy and communication skills. The results underscore the potential of IIMEs to advance inclusive education by delivering adaptive and culturally relevant content. This study contributes to the academic literature by offering practical guidelines for designing and implementing IIMEs that align with universal accessibility and responsible design principles, ultimately promoting an equitable and effective educational environment.

Interactive multimedia experiences are interesting for students because they stimulate several of their senses, provide assorted styles of interaction, and the user can modify the development of the experience thanks to the interactions with it, among other benefits. Moreover, this interaction produces data that can be used to improve the teaching-learning process of students using Learning Analytics techniques. In this sense, this paper presents a review of the state of the art on the impact of Learning Analytics in the development of multimedia technologies and evolution in the design process in the context of elementary education. A systematic literature review methodology has been applied to carry out this research. The results show the need for a well-defined process and a series of specific guidelines to include Learning Analytics in the solutions for this context.

In this paper, we give an extension of the functional regression concurrent model to the case of spatially correlated errors. We propose estimating the spatial correlation structure by using functional geostatistics. The estimation of the regression parameters is carried out by feasible generalized least squares. This modeling approach is motivated by the problem of validating rainfall data retrieved from satellite sensors. In this sense, we use the methodology to study the relationship between satellite and ground rainfall time series recorded in 82 weather stations from Department of Valle del Cauca, Colombia. The model obtained allows predicting pentadal rainfall curves in many sites of the region of interest by using as input the satellite information. A residual analysis shows a good performance of the methodology proposed.

Interactive multimedia experiences (IME) can be a pedagogical resource that has a strong potential to enhance learning experiences in early childhood. Learning analytics (LA) has become an important tool that allows us to understand more clearly how these multimedia experiences can contribute to the learning processes of these students. This article proposes a work route that defines a set of activities and techniques, as well as a flow for their application, by taking into consideration the importance of including LA guidelines when designing IMEs for elementary education. The work route’s graphical representation is inspired by the foundations of the Essence standard’s graphical notation language. The guidelines are grouped into five categories, namely (i) a data analytics dashboard, (ii) student data, (iii) teacher data, (iv) learning activity data, and (v) student progress data. The guidelines were validated through two approaches. The first involved a case study, where the guidelines were applied to an IME called Coco Shapes, which was aimed at transition students at the Colegio La Fontaine in Cali (Colombia), and the second involved the judgments of experts who examined the usefulness and clarity of the guidelines. The results from these approaches allowed us to obtain precise and effective feedback regarding the hypothesis under study. Our findings provide promising evidence of the value of our guidelines, which were included in the design of an IME and contributed to the greater personalized monitoring available to teachers to evaluate student learning.

Artificial intelligence (AI), particularly Generative AI (GenAI), is reshaping higher education by transforming how students learn and engage with information. This study explores the role of GenAI assistants in fostering critical thinking, a core competency for navigating an era of rapid technological change. Conducted with students from the Multimedia Design course at the Universidad Autónoma de Occidente, Colombia, the research compared two versions of the GenAI assistant: a standard model and one configured with Hegelian dialectics to stimulate reflective dialogue. While quantitative results showed no statistically significant differences between groups, qualitative insights revealed that the dialectical assistant promoted deeper analytical and evaluative thinking. The study underscores the need for sustainable process models in teacher training to integrate GenAI responsibly, ensuring balanced skill development, ethical awareness, and long-term cognitive growth.