Recommender systems have become one of the main tools for personalized content filtering
in the educational domain. Those who support teaching and learning activities, particularly …

In personalized learning, each student gets a customized learning plan according to their
pace of learning, instructional preferences, learning objects, etc. Hence the content …

User control and human-AI collaboration are two related directions of research in the
modern stream of work on human-centered AI. The field of AI in education was an early …

Recommender systems in e-learning domain play an important role in assisting the learners
to find useful and relevant learning materials that meet their learning needs. Personalized …

This article is a comprehensive literature review of student-facing learning analytics
reporting systems that track learning analytics data and report it directly to students. This …

El objetivo del presente artículo es analizar cómo se han transformado las estrategias
pedagógicas en la educación superior con la inserción de las Tecnologías de la …

From the perspective of Learning and Educational Technologies, academic advising has
been one of the most overlooked aspects of academic support systems, despite being …

In e-learning recommender systems, interpersonal information between learners is very
scarce, which makes it difficult to apply collaborative filtering (CF) techniques to achieve …

We conducted a literature review on systems that track learning analytics data (eg, resource
use, time spent, assessment data, etc.) and provide a report back to students in the form of …

In e-learning, most content-based (CB) recommender systems provide recommendations
depending on matching rules between learners and learning objects (LOs). Such learner …