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Item type:Publication, The Impact of Artificial Intelligence on Second Language Acquisition Experiences(2026)Zambrano JhonArtificial intelligenceArtificial intelligencein educationArtificial intelligence in education has transformed foreign language learning, but also raises pedagogical, ethical, and technical challenges, including data privacy, algorithmic transparency, equitable access, and shifting teacher roles. This study examines how students perceive the use of adaptive personalizationAdaptive personalization tools supported by intelligent technologies in second languageSecond language learning. It focuses on student experiences with digital platforms that automatically adjust content difficulty, learning pace, and feedback according to individual progress and performance. The research seeks to provide empirical evidence on both the educational potential and current limitations of such systems. A mixed-method approach was applied. Quantitative data were collected through structured questionnaires measuring user satisfactionUser satisfaction, perceived effectivenessEffectiveness of learning, motivation, and self-regulation. Qualitative insights were gathered through open-ended responses, allowing participants to share detailed perspectives on their interaction with these adaptive systems. The study involved university students participating in technology-assisted language learning programs, offering a representative context for analyzing emerging practices in higher educationHigher education. The findings indicate that students generally view these adaptive systems as effective in fostering personalized learningPersonalized learning pathways, enhancing motivation, and enabling timely feedback. Many participants emphasized the advantage of progressing at their own pace while receiving immediate support when facing difficulties. Overall, results show a positive impact on learner engagement and autonomy, although limitations persist regarding the handling of complex language skills and the reduction of human interaction. Nevertheless, some concerns emerged regarding the limited flexibility of these systems in addressing complex language aspects, occasional reduction of human interaction, and potential dependency on automated guidance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.24 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Risks and Ethical Challenges of Emotional Intelligence in Conversational AgentsThe development of emotionally intelligent conversational agents has attracted growing interest due to their potential to enhance human–machine interaction. These systems aim to simulate empathy by recognizing and responding to human emotions, enabling more fluid, personalized, and engaging communication. Yet, this simulated empathy raises significant technical, ethical, and social concerns, particularly in domains such as healthcare, education, and commerce, where emotional influence can shape decision-making and user well-being. This article presents a narrative review that critically examines the integration of emotional intelligenceEmotional intelligence into conversational AI. It draws on interdisciplinary literature in artificial intelligenceArtificial intelligence, affective computing, and ethicsEthics, reviewing peer-reviewed sources published between 2015 and 2024. The analysis applied a thematic approach to identify recurrent patterns, conceptual tensions, and sector-specific risks. Findings show that while advances in voice analysis, natural language processing, and deep learning have improved emotion detection, important limitations persist in multicultural and linguistically diverse contexts. These gaps risk misinterpretations, inappropriate responses, or discriminatory interactions. Moreover, users may mistakenly interpret emotionally tailored responses as genuine empathy, fostering emotional confusion or dependence. The potential for manipulative or persuasive uses further complicates their ethical deployment. This study provides a novel contribution by explicitly linking simulated empathy with risks of anthropomorphization, autonomy loss, and regulatory gaps, thereby bridging technical advances with their socio-ethical implications. It highlights practical challenges for applied contexts such as clinical support, education, and digital services, offering insights for both researchers and practitioners. Ethical principles, inclusive design, and regulatory frameworks are needed to ensure that emotionally intelligent AIArtificial intelligence supports rather than exploits human emotional experience. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.6 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Integrating Automation and Artificial Intelligence into Educational Practice(2026)7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Natural Language Processing Applied to Emotion Analysis for Continuous Improvement in Industrial EnvironmentsThe objective of this study was to analyze emotions expressed in natural language within Ecuadorian industrial environments using natural language processing (NLP) techniques. A sample of 150 anonymized texts was used, extracted from workplace climate surveys, satisfaction forms, operational reports, and digital suggestion boxes from companies in the manufacturing, food, logistics, health, education, and technology sectors. The texts were processed with an NLP pipeline using the spaCy library for cleaning, tokenization, and lemmatization, and semantically represented pre-trained models such as multilingual BERT and Emotion BERT. Supervised classification identified six emotions: joy, sadness, anger, fear, surprise, and neutrality. Statistical analysis revealed that the most frequent emotion was neutrality (34% of the total), followed by joy (21%), sadness (18%), anger (12%), fear (10%), and surprise (5%). At the sectoral level, logistics was the sector with the highest proportion of joy (28%), followed by food (24%) and manufacturing (12%). Manufacturing, on the other hand, had the highest proportions of sadness (20%) and anger (18%). The temporal analysis of positive sentiment between January and June 2025 showed a sustained increase in the technology sector, which rose from 62% to 77%. The healthcare sector showed an oscillating curve, falling from 58% to 56% in March and recovering to 63% in June. Education showed a cyclical pattern between 49% and 54%, related to its institutional calendar. In contrast, manufacturing remained stable but low, fluctuating between 40% and 42%. These results show that PLN allows us to capture structural emotional differences between sectors, and that these emotions can be correlated with internal dynamics of recognition, workload, or participation. It is concluded that automated emotional analysis is a useful tool for monitoring the organizational climate, anticipating psychosocial risks, and designing tailored intervention strategies. Its systematic application is recommended in organizations with digitized internal communication structures, especially in sectors with high turnover or emotional vulnerability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.11 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Influence of Artificial Intelligence in the Academic Field Within the Context of Higher Education in Ecuador(2026)17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Attitudes Toward Artificial Intelligence in Urban Ecuadorian PopulationsArtificial intelligenceArtificial intelligence is reshaping how individuals interact with digital systems, influencing education, work, and daily life. Understanding how people perceive and accept intelligent technologies is essential for designing adaptive, human-centered solutions that align with diverse expectations. Although AIArtificial intelligence use is expanding in Latin AmericaLatin America, empirical studies on public attitudes in the region remain scarce. This study examined behavioral patterns among 574 residents of Quito, Ecuador, focusing on how age and occupation influence acceptance, caution, or resistance toward AI. A previously validated attitudinal questionnaire was applied, and statistical analyses assessed both response consistency and the structure of public perceptions. Results showed that younger individuals, especially those aged 18–24, expressed more favorable views of AI than adults aged 25–56. While effect sizes were modest, the trend was consistent. More prominently, students demonstrated higher acceptance than artisans, with a moderate difference in group averages. These findings indicate that generational exposure and occupational context are closely tied to how individuals interpret and engage with emerging technologies. Structural analysis revealed inconsistencies in how attitudes are internally configured, with the overall model falling short of standard expectations for coherence. This suggests the need to refine attitudinal dimensions in future research. Beyond statistical outcomes, the Quito case highlights how urban environments, marked by digital infrastructures alongside persistent inequalities, shape public attitudes toward AI. These insights underscore the importance of sociocultural context in global debates on digital inclusion and provide practical guidance for designing inclusive and responsible intelligent systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.8 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Student Perceptions of an AI-Based Assistant for Formative Feedback in Higher Education(2026); Miguel Ángel Uribe-LaverdeThe integration of artificial intelligence (AI) in higher educationHigher education is transforming assessment and feedback practices, yet empirical evidence from Latin America remains scarce. This study examines students’ perceptions of an AI-based assistant (ChatGPT) for formative feedbackFormative feedback and assessment in an undergraduate instructional design course in Ecuador. Using a mixed-methods design, results show high levels of Perceived Usefulness, Ease of Use, and Motivational Value, while concerns emerged regarding transparencyTransparency, privacy, and equitable access. Students valued the immediacy and objectivity of AI-generated feedback but emphasized the need for clearer grading criteria and continued human mediation. These findings provide one of the first regional contributions to understanding the role of AI-based assistants in higher educationHigher education, underscoring their potential to complement traditional feedback in resource-constrained environments while highlighting ethical and practical challenges that must be addressed for equitable adoption. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.8 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A comprehensive framework for integrating modern educational technologies with problem-based learning in medical education(2025); Monserrat Vanessa Romero-DuranProblem-Based Learning (PBL) has evolved from its traditional roots into a sophisticated pedagogical approach enhanced by advanced digital technologies, including artificial intelligence as a subset of these digital innovations. This comprehensive framework provides medical educators with evidence-based guidance for implementing technology-enhanced PBL methodology, incorporating both traditional principles and modern technological tools. We synthesize current literature from 2019 to 2025, analyzing research findings to create actionable recommendations for educators seeking to implement or improve their PBL programs. Recent studies demonstrate significant improvements through technology integration: 34% enhancement in diagnostic accuracy (Yang et al. in J Pharm Educ Pract 12:112–120, 2024), 28% better knowledge retention (Yan et al. in BMC Med Educ 23:456, 2023), and 42% increase in student engagement (Matsuda and Izumi in Med Educ Online 29:2345, 678, 2024). The integration of virtual patients, simulation-based learning, and adaptive systems shows promising results in enhancing traditional PBL methodologies while maintaining core pedagogical principles. Our proposed framework addresses implementation planning, role definitions, assessment strategies, and quality assurance mechanisms that medical educators can immediately apply across diverse cultural and institutional contexts. © The Author(s) 2025.14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Artificial Intelligence in Marketing: A Bibliometric StudyNowadays, the use of artificial intelligence (AI) is revolutionizing and transforming businesses. In the field of marketing, it has enabled the optimization of strategies and campaigns, content personalization, more precise segmentation, and maximization of planning results, thanks to its ability to process and analyze data. The research aims to provide a bibliometric approach to current knowledge on AI in marketing. The methodology involved a bibliometric review by obtaining indexed research papers from the SCOPUS database, which were then analyzed using the VOSviewer application. The results identified that countries such as the United States, India, and China have the highest scientific production on the subject. Additionally, it was revealed that the most relevant knowledge areas are engineering, management and business, and accounting. In this context, it is concluded that it is crucial for companies worldwide to observe the advancements made by these countries to replicate strategies according to their needs. Considering that AI, thanks to the internet, is accessible for all types of businesses, they only need to identify opportunities and key areas to apply AI tools and train their personnel.32 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Influence of Social Media and Artificial Intelligence on Cyberbullying for Decision-Making with Legal or Judicial Foundations in Ecuador(2025); Rocío Maciel ArellanoCyberbullying remains a pervasive issue globally and in Ecuador, fueled by the rapid evolution of the Internet, emerging trends in information and communication technologies (ICT), artificial intelligence (AI), and social networks. One of the primary contributing factors is the influence of social networks and AI, coupled with the absence of robust legal and judicial frameworks. The objective of this study is to propose a conceptual model for cybersecurity management in social networks. A deductive approach and exploratory research methods were used to analyze information from various official sources. The results include a mental map that identifies key stakeholders, a simulation designed to mitigate cyberbullying on social networks, and a conceptual model to address cyberbullying management. The study concludes that mitigating cyberbullying requires the implementation of appropriate AI tools and the development or improvement of cyberbullying laws in each country. Simulations demonstrated that in one scenario, the occurrence of cyberbullying could be reduced to an average of 25%, highlighting both the challenges and the potential of leveraging AI and updated legislation to combat this issue effectively.33