enseñanza en línea e híbrida

En este trabajo se reporta el avance de una pequeña investigación que tiene como propósito indagar qué tipo de estrategias de aprendizaje utilizan los estudiantes de un curso en línea para aprender a aprender y cuáles necesitan usar para convertirse en estudiantes exitosos, lo que nos dará una pauta para saber de qué manera orientar su aprendizaje para lograr estudiantes estratégicos capaces de regular, monitorear y evaluar su propio aprendizaje y tomar medidas cuando se den cuenta de que su aprovechamiento no está dando los resultados que esperaban.

Tecnología educativa y autonomía en el aprendizaje de lenguas extranjeras: una revisión bibliográfica y prospectivas

Spyridon Vassis (2025)

Decires

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: tecnología educativa

Resumen:

Se presenta una revisión bibliográfica sobre el impacto de la tecnología educativa en el aprendizaje de lenguas extranjeras con énfasis en el desarrollo de la autonomía de la comunidad estudiantil. A través de esta revisión se examinan las estrategias y herramientas tecnológicas que han demostrado ser efectivas en diversos contextos educativos, como cursos semipresenciales, aplicaciones móviles y plataformas de aprendizaje en línea. Los resultados de los estudios examinados evidencian que el uso de tecnologías digitales facilita la autonomía del aprendizaje, mejora las competencias lingüísticas y fomenta la motivación entre los grupos de estudiantes.

Se destacan diversos enfoques...

Reconceptualizing community of inquiry in the age of generative artificial intelligence

Shen Ba, Dragan Gašević, Cher-Ping Lim (2026)

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Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

The Community of Inquiry (CoI) framework is widely used to guide and explain learning in online and blended environments. However, generative artificial intelligence (GenAI) challenges a key assumption in CoI research and practice: that indicators of presence can be attributed primarily to human learners, instructors, and their interactions. GenAI can produce fluent discourse that resembles strong cognitive, social, or teaching presence. Yet such discourse may not reflect learners' thinking, relationships, or regulatory intentions. To date, research often frames GenAI as a tool, a dialogic partner, or a possible fourth presence. These views, however, do not fully capture GenAI's pervasive...

Augmenting assessment with AI coding of online student discourse: A question of reliability

Kamila Misiejuk, Rogers Kaliisa, Jennifer Scianna (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Currently, many generative Artificial Intelligence (AI) tools are being integrated into the educational technology landscape for instructors. Our paper examines the potential and challenges of using Large Language Models (LLMs) to code student-generated content in online discussions based on intended learning outcomes and how instructors could use this to assess the intended and enacted learning design. If instructors were to rely on LLMs as a means of assessment, the reliability of these models to code the data accurately is crucial. Employing a diverse set of LLMs from the GPT family and prompting techniques on an asynchronous online discussion dataset from a blended-learning bachelor-...

A systematic review of ontology use in E-Learning recommender system

Nur W. Rahayu, Ridi Ferdiana, Sri S. Kusumawardani (2022)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

Ontology and knowledge-based systems typically provide e-learning recommender systems. However, ontology use in such systems is not well studied in systematic detail. Therefore, this research examines the development and evaluation of ontology-based recommender systems. The study also discusses technical ontology use and the recommendation process. We identified multidisciplinary ontology-based recommender systems in 28 journal articles. These systems combined ontology with artificial intelligence, computing technology, education, education psychology, and social sciences. Student models and learning objects remain the primary ontology use, followed by feedback, assessments, and context...

Does intrinsic motivation mediate perceived artificial intelligence (AI) learning and computational thinking of students during the COVID-19 pandemic?

José Luis Martín-Núñez, Anil Yasin Ar, Rodrigo Pérez Fernández (2023)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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The concept of Artificial Intelligence (AI), born as the possibility of simulating the human brain's learning capabilities, quickly evolves into one of the educational technology concepts that provide tools for students to better themselves in a plethora of areas. Unlike the previous educational technology iterations, which are limited to instrumental use for providing platforms to build learning applications, AI has proposed a unique education laboratory by enabling students to explore an instrument that functions as a dynamic system of computational concepts. However, the extent of the implications of AI adaptation in modern education is yet to be explored. Motivated to fill the...

How does students' perception of ChatGPT shape online learning engagement and performance?

Mahboobeh Mehrvarz, Ghasem Salimi, Samaneh Abdoli (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Artiicial intelligence technologies, such as ChatGPT, Bert, LaMDA, and T5 have become deeply integrated into universities, influencing numerous functions within higher education and various aspects of students' lives. This article examined how students' perceptions of ChatGPT influence their engagement and performance in online learning, focusing on the mediating role of engagement. The perception of ChatGPT involves a student's understanding of, willingness to utilize, and concerns regarding the technology. These interconnected factors can influence students' online learning engagement with the software and, consequently, affect their academic performance. The study used self-reported data...

Learners’ web navigation behaviour beyond learning management systems: A way into addressing procrastination in online learning?

Eduard Pogorskiy, Jens F. Beckmann (2022)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

The attractiveness of online games, social media, and mobile apps is frequently considered a challenge for online learners. Procrastinatory behaviour is often associated with a relative lack of self-regulatory skills that would otherwise help learners to resist distractions and to progress in learning. This paper reports a pilot study, conducted with 49 online learners, in which we describe the use of a virtual learning assistant as a tool for collecting online learners' web navigation behaviour. As this virtual learning assistant operates as an extension to the Chrome web browser, it is possible that data collection is achieved independently of, and beyond specific learning management...

Sequential, typological, and academic dynamics of self-regulated learners: Learning analytics of an undergraduate chemistry online course

Ken-Zen Chen, Shao-Chi Li (2021)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

This research explored the typologies of self-regulated learners in an asynchronous online Chemistry I (OCI) course of an undergraduate active learning program. Student readiness and capability regarding self-regulated learning (SRL), the activity logs in the learning management system, and academic achievement were collected to investigate behavioral sequences of different typologies of learning self-regulation. Seventeen students who took OCI in the 2019 school year were recruited for the study. Through learning analytics for the 3965 behavioral codes, the study generated three key results. First, hierarchical cluster analysis classified two typologies of self-regulated online learners:...

AI-based learning content generation and learning pathway augmentation to increase learner engagement

Chaitali Diwan, Srinath Srinivasa, Gandharv Suri (2023)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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Retaining learner engagement is a major challenge in online learning environments, which is even more intensified with learning spaces increasingly built by combining resources from multiple independent sources. Narrative-centric learning experience has been found to improve learner engagement by several researchers. Towards this end, we propose an AI-based approach that generates auxiliary learning content called narrative fragments which are interspersed into the learning pathways to create interactive learning narratives. The proposed approach consists of the automatic generation of two types of narrative fragments– overviews of the learning pathway segments and reflection...