Sistemas de recomendación en educación: una reseña de los mecanismos de recomendación en entornos de aprendizaje virtual (E-learning)

In recent years, new trends and methodologies have emerged that greatly favor the education sector. E-learning as an alternative to regular teaching and learning processes has transformed the educational dynamics thanks to the inclusion of MOOCs, personal learning environments, allowing the educational process to be carried out at a personalized level where the focus is on learning styles and the profile of the student. This article presents a review of current works around machine learning mechanisms to make recommendations in the educational environment, where it is found that besides the discovery of the student’s learning style, it is important to know their level of knowledge and learning speed, in addition to the tools used by the student to carry out their studies. Finally, the opportunity for implementation and research of these issues in Colombia is highlighted. Recientemente, han emergido nuevas tendencias y metodologías que han favorecido enormemente al sector educativo. El e-learning como alternativa a los procesos de enseñanza y aprendizaje regulares ha transformado las dinámicas educativas debido a la inclusión de los MOOC, entornos personales de aprendizaje, permitiendo que el proceso educativo sea llevado a cabo en un nivel personalizado en donde el foco esté puesto en los estilos de aprendizaje y el perfil del estudiante. Este artículo presenta una revisión de trabajos actuales alrededor de mecanismos de aprendizaje de máquina para hacer recomendaciones en el entorno educativo, en donde se encuentra que, aparte del descubrimiento del estilo de aprendizaje del estudiante, es importante conocer su nivel de conocimiento y su velocidad de aprendizaje, así como las herramientas usadas por el estudiante para llevar a cabo sus estudios. Finalmente, se hace énfasis en la oportunidad de implementar y seguir investigando estas cuestiones en Colombia.&nbsp

INVESTIGATING SITUATED LEARNING PRACTICE FOR ENGLISH LANGUAGE TEACHING IN HIGHER EDUCATION (ONLINE-BASED ENVIRONMENT)

In online-based contextual English language learning, learning must occur in its context, allowing English learners to seek and discover logical explanations for their knowledge via interaction with their non-physical and social distance environments. The purpose of the study is to explain and establish online-based situated learning in the English pedagogical context. The ethnography case study design employed the analysis with a collective case study type approach. The result exposed that situated learning affirmed to be implemented in online English learning contextual. Communities of practice implied a set of individuals with diverse interests and attitudes with similar purposes, and Skype, Zoom, Google Hangouts, Microsoft Teams were implied to be adaptable on this model. Authentic learning stresses actual activities that apply to real-world circumstances, and the model incorporated the Grammarly, Draftin, Scholastic Story Starters, Book Creator, and ReadWorks. The online language learning systematic model is designated to assess the quantity of material presented successfully in the course using online realistically, and it has Moodle, Google Classroom, Ispring Learn, and Microsoft Team. The last model finding is Task-Based Language Learning. Duolingo, Fabulingua, FluentU, and English Tools were the integrated online tools in the English pedagogical situated learning. Integrated and genuine situated learning of English language learning, online environments must allow English language learners to be competent performers with acquired information and collaborate on the essential communicative and technology literacy ability

Indicators for enhancing learners’ engagement in massive open online courses: A systematic review

Massive open online courses (MOOCs) have paved a new learning path for the 21st-century world. The potential to reach a massive geographically dispersed audience is one of the major advantages of MOOCs. Moreover, they can be offered on a self-paced and self-regulated basis and have become an integral part of lifelong learning, especially in workplaces. However, one persistent problem is the lack of learners’ engagement. A harmonisation of studies providing a holistic view into aggregating indicators for enhancing learners’ engagement in MOOCs is lacking. The coronavirus pandemic has accelerated MOOC adoption, and learners’ engagement in MOOCs has become even more essential for the success of this educational innovation. We examine the existing literature to derive indicators important for enhancing learners’ engagement in MOOC learning environments. Using a systematic approach, 83 empirical studies were examined, and 10 indicators were identified as important considerations for enhancing learners’ engagement while designing MOOCs—from initiatives for individual learners to platform and instructional design perspectives. We also present a table describing these indicators and offer a structured discussion on each one. We believe the results provide guidelines for MOOC designers and instructors, educational policymakers, higher education institutions, and MOOC engagement researchers.Peer reviewe