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    Application of the Tití App Technological Tool in Reading and Writing Comprehension
    (2025)
    Pérez Pérez, Paulina  
    ;
    Caicedo, Andrés  
    Education at its various levels seeks to foster social change among all stakeholders, particularly students and teachers. In primary school, persistent learning difficulties have been identified, most of which are linked to mastering literacy skills - an essential foundation for educational progress. The interactive tool TitíApp, designed to correct errors such as omissions, substitutions, and rotations, has proved effective in enhancing children's reading abilities. This application not only supports the teaching - learning process but also helps narrow the digital divide across different sectors. The aim of this study was to compare children's reading competencies before and after using TitíApp. A pre and post-assessment methodology was employed with the Toro and Cervera Reading-Writing Analysis Test, applied in accordance with ethical standards for minors. The sample comprised 234 students from public and private schools in Pichincha Province. Findings revealed a reduction in errors when reading letters, syllables, and words, as well as an overall improvement in reading comprehension. The discussion highlights the growing positive impact of technological tools in education, noting that Tití App was particularly effective in improving students' reading fluency and comprehension. Ultimately, the use of this tool offers an engaging and effective means of restoring reading skills while reflecting a culturally grounded approach within the Ecuadorian context. © 2025 IEEE.
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    Proposal of a theoretical-practical evaluation model for the accreditation of university courses in Ecuador
    (2024)
    Dillon Pérez, Francisco  
    ;
    Rojas, David  
    ;
    Espinosa, Diana
    ;
    Jiménez, Silvia Aguirre
    The objective of this research work was to design a theoretical-practical model for evaluating university courses for accreditation purposes. The paradigm used was mixed (quali-quantitative) of a descriptive, explanatory, exploratory and correlational type; interpretive in nature and focused on action research. Furthermore, to support the construction of the proposed model, bibliographic, documentary and field analysis processes were used. One of the main conclusions obtained because of the research process has allowed us to determine that the approach of this model could help improve the designs of the different academic careers and programs at a macro, meso and micro curricular level for accreditation purposes, also allowing in this way, comply with the evaluation parameters established by the Ecuadorian university higher education control bodies.
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    Validation of a teaching model instrument for university education in Ecuador through an artificial intelligence algorithm
    (2025)
    Jenniffer Sobeida Moreira-Choez
    ;
    Tibisay Milene Lamus de Rodríguez
    ;
    Núñez-Naranjo, Aracelly Fernanda  
    ;
    Ángel Ramón Sabando-García
    ;
    María Belén Reinoso-Ávalos
    Introduction: In the context of university education in Ecuador, the application of Artificial Intelligence (AI) for the assessment and adaptation of teaching models marks significant progress toward enhancing educational quality. The integration of AI into pedagogical processes is increasingly recognized as a strategic component for fostering innovation and improving instructional outcomes in higher education. Methods: This study focused on the validation of an AI-based instrument, specifically designed for the evaluation and adaptation of pedagogical strategies in the Ecuadorian university environment. A quantitative methodology was adopted, employing multivariate statistical analyses and structural equation modeling (SEM) to examine the internal consistency, construct validity, and interrelations among various didactic dimensions. The instrument was applied to a statistically representative sample of university professors across both undergraduate and graduate levels. Results: The statistical analysis demonstrated high levels of internal consistency and discriminative validity among the constructs representing different teaching models. The confirmatory factor analysis and SEM procedures verified the adequacy of the theoretical structure and the robustness of the proposed measurement model. Coefficients obtained for reliability and model fit met or exceeded established thresholds in educational research. Discussion: The findings confirm the empirical soundness of the AI-based instrument and support the feasibility of using such tools to assess and enhance teaching models in higher education. These results underscore the importance of adopting innovative, data-driven methodologies that respond to the demands of contemporary educational environments. Furthermore, the use of AI in the validation process enables a more precise interpretation of educational information, reinforcing the relevance of AI-supported models in optimizing teaching and learning processes.
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