Facultad de Ciencias Sociales y Humanas
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Family functioning and social network addiction in college students of the city of Quito

2024 , Jirón Jiménez, Jonathan , Freire Muñoz, Irina , Iriarte Pérez, Luis

This research aims to analyze the relationship between family functioning and social network addiction in college students in the city of Quito. The research design is nonexperimental cross-sectional, with a quantitative method and a descriptive - correlative scope. Two data collection instruments are used: 1. Social Networks Addiction Questionnaire (ARS) and 2. Family Functioning Perception Questionnaire (FF-SIL). The sample consisted of 274 college students from the city of Quito. The results were 50% of moderately functional families, in addition to a higher prevalence of students with an 'obsession to be informed' and a 'need/obsession to be connected' with 51.8% and 42.3% respectively. Likewise, there is a statistically significant correlation, directly proportional between family functioning and the 'problem' dimension of social networks addiction.

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Classification Tools to Assess Critical Thinking in Automotive Engineering Students

2024 , Espinosa Pinos, Carlos Alberto , Amaluisa Rendón, Paulina Magally , Noemi Viviana Rodríguez Ortiz

Inadequate conflict resolution skills in automotive engineering students can have negative consequences in the workplace. The development of mathematical logical thinking can help students develop critical analysis skills, improve problem-solving ability, develop reasoning skills, and effective communication, enabling them to deal effectively with conflicts and find creative solutions. This research aims to identify predictors of problem-solving ability using classification algorithms. Methodology: In this study, three classification algo-rithms were applied and the KDD process was used to identify predictors of problem-solving ability. The data set includes 60 records of students from the automotive engineering program at Universidad Equinoccial in Quito, Ecuador, to whom three tools were applied: a sociodemographic card, a Shatnawi test related to mathematical logical thinking, and a Watson Glaser test on conflict resolution ability. Results: The best classification model is the K-nearest neighbors’ algorithm and its predictive ability is very good, with a true positive rate versus false positive rate AUC of 0.75, along with a good performance in classifying negative cases. The model can be improved with increased sampling, cross-validation, or hyper-parameter adjustment. Conclusion: Age and mathematical logical thinking are strongly associated with conflict resolution ability. In future research it is important to consider additional variables such as experience in problem-solving projects, technical knowledge and communication skills; to explore the use of more advanced machine learning algo-rhythms; to design specific educational interventions based on the development of mathematical logical thinking; or to compare conflict resolution ability between different engineering disciplines.

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Is Gender a Source of Measurement Variability in the General Self-Efficacy Scale? Psychometric Analysis in Ecuadorian Adults

2025 , Alexandra Salinas-Palma , Rodrigo Moreta-Herrera , Lascano Arias, Giovanni , Marco Mena-Freire , Guido Mascialino , Lucía Almeida-Márquez , Tomás Caycho-Rodríguez

To analyze whether gender is a source of variability in the General Self-Efficacy Scale (GSES) using Classical Test Theory (CTT) and Item Response Theory (IRT) in a sample of Ecuadorian adults. This is an instrumental study that assesses factorial validity and Measurement Equivalence (ME) across gender using CTT, while IRT is used to estimate item discrimination [a], difficulty [b], and differential item functioning (DIF). A total of 485 adults participated, with 44.9% male and 55.1% female, aged 18 to 53 years (M = 24.29; SD = 7.61). The unifactorial structure of the GSES was confirmed and measurement invariance was established at the thresholds (scalar) level across gender. Furthermore, there are no significant differences (p <.05) in the latent means of the groups. The item parameters for [a] and [b] were found to be adequate, with no evidence of gender-based DIF in the items. The GSES is a reliable scale for use in studies involving Ecuadorian adults, and gender does not significantly affect its measurement propertie

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Applying Classification Techniques in Machine Learning to Predict Job Satisfaction of University Professors: A Sociodemographic and Occupational Perspective

2024 , Espinosa Pinos, Carlos Alberto , Acosta Pérez, Paul Bladimir , Camila Alessandra Valarezo-Calero

This article investigates the factors that affect the job satisfaction of university teachers for which 400 teachers from 4 institutions (public and private) in Ecuador were stratified, resulting in a total of 1600 data points collected through online forms. The research was of a cross-sectional design and quantitative and used machine learning techniques of classification and prediction to analyze variables such as ethnic identity, field of knowledge, gender, number of children, job burnout, perceived stress, and occupational risk. The results indicate that the best classification model is neural networks with a precision of 0.7304; the most significant variables for predicting the job satisfaction of university teachers are: the number of children they have, scores related to perceived stress, professional risk, and burnout, province of the university at which the university teacher surveyed works, and city where the teacher works. This is in contrast to marital status, which does not contribute to its prediction. These findings highlight the need for inclusive policies and effective strategies to improve teacher well-being in the university academic environment.

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Psychometric properties of the Escala de Gravedad de Síntomas Revisada del Trastorno de Estrés Postraumático (EGS-R) in adults in Ecuador after the Covid-19 pandemic

2024 , Moreta-Herrera R. , Núñez-Núñez M. , Lascano Arias, Giovanni , Mascialino G. , Rodríguez-Lorenzana A.

Objective: This study aims to assess the validity of the Escala de Gravedad de Síntomas Revisada del Trastorno de Estrés Postraumático (EGS-R) among adults in Ecuador within the post-pandemic context of Covid-19. Methods: Descriptive and instrumental design. Participants: 537 participants from Ambato, Ecuador, comprising 44.1% men and 55.9% women, aged 18 to 65 years (M = 24.36; SD = 8.87). Among the participants, 64.6% had experienced Covid-19, while 35.4% had not. Results: The EGS-R exhibits a hierarchical factorial structure, demonstrating measurement equivalence between participants who experienced Covid-19 and those who did not. Significant differences emerged between the groups, with individuals who had contracted Covid-19 displaying a higher symptom burden, thereby establishing the discriminant validity of the measure. The scale also exhibits validity concerning other variables, such as stress perception, and demonstrates satisfactory internal consistency among its scores. Conclusions: The EGS-R proves to be a valuable tool for assessing adults in Ecuador for potential indicators of Posttraumatic Stress Disorder (PSTD) given the robust evidence of validity and reliability, affirming its utility and evaluative capacity in this population. © 2024

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Can artificial intelligence replace journalists? A theoretical approach

2025 , Londoño Proaño, Cristián , Buele, Jorge

In the digital age, journalism is facing significant transformations due to the impact of artificial intelligence, a technology that optimizes processes, but also poses ethical and technical dilemmas. This study addresses whether AI can replace journalists or whether it should be considered as a complementary tool that enhances their capabilities. The problem lies in the increasing automation of journalistic tasks and its impact on the quality, ethics and professional identity of the sector. The research justifies its relevance due to the need to understand the scope and limitations of this technology to guarantee ethical and contextualized journalism. The methodology adopted is qualitative and based on documentary analysis. Academic studies, technical reports, and case studies were reviewed to evaluate the use of AI in newsrooms, highlighting its capabilities in automation, personalization, and data analysis, along with its ethical and operational limitations. Among the main results, it is identified that artificial intelligence is effective for tasks such as automated news generation and massive data analysis, but its inability to perform critical analysis and ethical decisions limits it as a complete substitute for the journalist. Likewise, their dependence on trained data perpetuates biases that can compromise the credibility of information. This study highlights that artificial intelligence should be conceived as a support for the journalist, enhancing creativity and analytical depth without compromising the essential values of the profession. It also underscores the importance of a synergistic collaboration between technology and journalists, including regulation and training to take advantage of it ethically and effectively.

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Transformations in academic work and faculty perceptions of artificial intelligence in higher education

2025 , Buele, Jorge , Llerena Aguirre, Leonel

Technologies based on artificial intelligence are transforming teaching practices in higher education. However, many university faculty members still face difficulties in incorporating these tools in a critical, ethical, and pedagogically meaningful way. This review addresses the issue of limited artificial intelligence literacy among educators and the main obstacles to its adoption. The objective was to analyze the perceptions, resistance, and training needs of faculty members in the face of the growing presence of artificial intelligence in educational contexts. To this end, a narrative review was conducted, drawing on recent articles from Scopus and other academic sources, prioritizing empirical studies and reviews that explore the relationship between intelligent systems, university teaching, and the transformation of academic work. Out of 757 records initially retrieved, nine empirical studies met the inclusion criteria. The most frequently examined tools were generative artificial intelligence systems (e.g., ChatGPT), chatbots, and recommendation algorithms. Methodologically, most studies employed survey-based designs and thematic qualitative analysis. The main findings reveal a persistent ambivalence: faculty members acknowledge the usefulness of such technologies, but also express ethical concerns, technical insecurity, and fear of professional displacement. The most common barriers include lack of training, limited institutional support, and the absence of clear policies. A shift in the teaching role is observed, with greater emphasis on mediation, supervision, and critical analysis of output generated by artificial intelligence applications. Additionally, ethical debates are emerging around algorithmic transparency, data privacy, and institutional responsibility. Effective integration in higher education demands not only technical proficiency but also ethical grounding, regulatory support, and critical pedagogical development. This review was registered in Open Science Framework (OSF): 10.17605/OSF.IO/H53TC.

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Occupational Risks: A Comparative Study of the Most Common Indicators in Uruguay, Cuba and Ecuador

2023 , Acosta Pérez, Paul Bladimir , Espinosa Pinos, Carlos Alberto , Acuña Mayorga, José Miguel , Lascano Arias, Giovanni

Efficiency and effectiveness in daily work activities demand the control of processes, those elements that can affect the health of employees known as occupational risks. The objective of this study was to identify indicators of more frequent labor risks in the countries of Uruguay, Cuba and Ecuador, for which a bibliographic compilation was carried out, as well as a descriptive analysis of the indicators of occupational risk. The results show that the countries analyzed coincide as the highest index of risks to manufacturing industries. It is concluded that the international regulations and conventions that govern safety have been accepted by the different countries that make them up, mainly in the statistical registry of accidents, reports, affiliates among others. Finally, policies aimed at the prevention, detection, monitoring and eradication of occupational risks in the workplace must be established. © 2023 IEEE.

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The Podcast as an Educational Tool: The Case of Motivo de Consulta

2025 , Londoño Proaño, Cristián , Freire Muñoz, Irina , Iriarte Pérez, Luis

The podcast has become an innovative educational tool that allows the dissemination of knowledge in an accessible and flexible way. In this context, the present study aims to analyze how the podcast Motivo de Consulta contributes to psychology education by transmitting knowledge about mental health in academic and professional contexts. The research follows an exploratory and empirical approach with a qualitative design, developed in several phases: first, a survey was applied to 100 people to identify their learning needs; Subsequently, these results were contrasted with a review of scientific literature to select the topics of the podcast; then, ten episodes were designed, produced and broadcast on Spotify with interviews with psychology experts; Finally, a content analysis was carried out to evaluate the alignment of the podcast with contemporary pedagogical principles. The results showed that the podcast not only addresses the concerns of the public, but also facilitates the appropriation of knowledge through a dynamic and interactive format. It is concluded that Motivo de Consulta is an effective educational strategy that complements traditional teaching methods and promotes autonomous and meaningful learning in psychology training.

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Digital Competency Enhancement in Personnel Training and Development: A Literature Review of Current Trends and Challenges

2024 , Taruchaín Pozo, Fernando , Avilés-Castillo, Fátima

In a perpetually advancing technological landscape, workforce training and development centered around digital competency and computer science principles are critical for ensuring the organizational resilience and competitiveness. This study undertakes a bibliographic analysis of technology-focused personnel training and development, aspiring to identify the strategies implemented, benefits perceived, and challenges emerging in this digital era. Three foundational research questions are outlined: What strategies are employed in technology-focused continuous training? What benefits do workers acquire after technology-centric training? And what are the prevalent challenges in digital skills training? A literature search approach was deployed to answer these queries, executing a meticulous analysis of 33 significant scientific papers. The results indicate a burgeoning trend towards virtual, technology-driven training, and the usage of practical simulations in training. It was also confirmed that continuous technology-focused training creates positive impacts on both work performance and worker attitudes. However, challenges like resistance to change and technological limitations persist in certain organizations.

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