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

Dyslexia is a learning difficulty that affects reading and writing and has been studied in search of novel tools for detection and treatment. This article analyzes the applicability of Artificial Intelligence to the management of dyslexia cases in university settings, through a systematic review focused on the contributions of scientific literature on assessment/diagnosis and intervention processes. Through searches in Scopus and Web of Science, empirical studies were selected considering the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols method. The results show that Artificial Intelligence is effective in the detection of dyslexia through eye movement analysis and neuroimaging, allowing early diagnosis. However, research has mainly focused on assessment and diagnosis, while its application in interventions requires further study. In conclusion, Artificial Intelligence has the potential to improve accessibility and personalization in the treatment of dyslexia, contributing to the transformation of university educational processes in students suffering from this condition.

El auge de las nuevas tecnologías de información y comunicación y el uso generalizado de las redes sociales, están generando un replanteamiento constante de los modelos de enseñanza en instituciones universitarias. Esta investigación persigue dos objetivos, por un lado, desarrollar la capacidad de los estudiantes para adquirir conceptos a través de la lectura extensiva de historias de vida y, por otro, introducir a los estudiantes en el diseño y realización de historias de vida y entrevistas como parte de su formación socio-práctica. En esta investigación se optó por utilizar la entrevista y la historia de vida como herramientas pedagógicas, interconectándolas a través de las tecnologías de información y comunicación, con el uso de la red social conocida como TikTok, todo ello aplicado al Grado en Trabajo Social en la Universidad Pablo de Olavide y la Universidad de Málaga en España. Los resultados obtenidos esperan generar un debate en profundidad sobre el potencial pedagógico de los métodos narrativos en combinación con el uso de las tecnologías de información y comunicación y las redes sociales, así como servir de guía al profesorado de Trabajo Social para el buen uso de estas tecnologías y las redes sociales como herramientas activas para la educación.

The tourism industry stands out as a significant source of revenue. Beyond driving economic growth and job creation, tourism also plays a key role in stimulating infrastructures development and promoting services tourist. This study aimed to forecast tourist arrivals in Panama using ARIMA models. Monthly data on tourist arrivals to Panama were collected. The results show that the ARIMA model provides reasonable and useful forecasts for tourist arrivals in Panama, with an acceptable level of accuracy. Therefore, in conclusion, the results of this study become significant for the strategic planning of tourism in Panama, in response to the dynamics of this important sector of the national economy.

X has become the online platform for political debate adopted by presidential candidates to position their personal brands and disseminate political ideals. In Colombia, during the presidential campaign that took place both before the COVID-19 pandemic, extreme political positions were observed between the right- and left-wing candidates, Iván Duque and Gustavo Petro. This research analyzes the thematic content of their published tweets during the 2018 presidential election campaign and subsequently within the context of first year of the COVID-19 pandemic, in 2020, to carefully examine and compare viewpoints. A total of 9,395 tweets and 311,654 words from the official X accounts were scrutinized. The methodology used - non-experimental, while following a descriptive, quantitative approach - was based on a computerized content analysis operated by topic modeling, that does not include information on the interaction with the followers. The results, however, show a marked difference in thematic axis points between right and left where, on the one hand, the leaders studied published content related to government proposals and solutions, while on the other hand, there was evidence of a polarization strategy that sought to discredit the opposing candidate by strengthening his own position as primary interlocutor.

Traditional film criticism has found a new space for dissemination on YouTube, where, in addition to its own characteristics, it has added the interaction and active participation of users, generating new audiovisual content, with a more entertaining language, but without forgetting the usual features of the genre. The data were obtained from the content analysis of the four Spanish-language film review channels with the most activity and the largest number of followers. This platform, where the critic demonstrates a deep knowledge of the subject, favours closeness with the public through an innovative audiovisual format that fills the existing gap in traditional television about film in general and about criticism in particular.

Film exhibition and distribution platforms currently lead the exhibition market. Film festivals hosted on these platforms provide students with their first opportunities for professional evaluation, allowing them to put their acquired skills to the test through public competition and expert review. This study examines the characteristics of European university film festivals, using the distribution platform FilmFreeway’s database as the main source of information. The analysis is both quantitative (focusing on festival locations, sample boundaries, and general data) and qualitative (addressing jury committees, their structure, and award processes). In this phase, in-depth interviews were also conducted to strengthen the comparative analysis. Initial findings show that few festivals are organized and targeted exclusively at university students. These festivals tend to be general in focus, international in scope, and centered on short films. They typically include two evaluation phases: selection, in which the organizing team is actively involved; and judging, carried out by industry professionals who are not part of the organizing team.

Prejudices and xenophobic attitudes are cognitive schemas that frame emotions and behaviours. They emerge most profusely in the digital media ecosystem and are articulated as hate speech, primarily through comments on social media attracted by photographs. Thus, this study aimed to explore the association between the emotional response to images depicting racialised and non-racialised individuals and the likelihood of negative messages in virtual settings, such as social media. For this purpose, 103 Spanish participants (age X = 40.32) were recruited through Mechanical Turk (MTurk) and shown 46 images, together with pictographic scales for assessing emotional response (Self-Assessment Manikin). The likelihood of writing a comment and its valence were also queried. The results revealed significant differences across categories in emotional response and in the possibility of posting a negative comment, with images of racialised individuals having the highest values. The emotional pattern of those who indicated a high likelihood of negative comments was identified as fear of negative images of racialised individuals and hate for positive ones. These results contribute to the emotional characterisation of perpetrators of hate speech in digital and social media, specifically those related to xenophobic attitudes.

This article analyzes the level of emotivism in the digital political debate on Facebook during the 2023 General Elections based on official and verified accounts of parties, political leaders, media, and users. For this, 34,968 Facebook messages were downloaded during the official electoral campaign period and classified into three groups of agents: connective parties, media, and other connective action actors. Big data techniques were used to analyze the messages, and the NRC Emotion Lexicon was applied to measure the emotions present. The findings show high affective congruence because the messages have low emotional content. The presence of the emotion “love” in the reactions amounts to almost half. This may indicate irony and user discontent toward the messages posted during the electoral process. In cases of low affective attunement, the over-dimensionality of “love” stands out. These results are relevant from the emotivist perspective because they shed light on emotions in this type of debate that mobilizes public opinion and, at times, other negative dynamics that move away from the democratic ideal.