The success of online learning relies on college students' self-regulated learning. The common visualizations (e.g., presentation learning behaviors' frequency and duration) are widely used to enhance online self-regulated learning. But most college students still have difficulty in accurately understanding their learning patterns and…

This study presents a panoramic overview of research conducted between 2010 and 2020 on how the Personal Learning Environment (PLE) supports Self-Regulated Learning (SRL). We elaborate on why the PLE is suitable for SRL, discuss its research themes, explain how the PLE supports SRL and outline the available PLE platforms. The review method we used…

Self-regulated learning (SRL) strategies have been identified as a valuable component of digital game-based learning system (GBLS) activities. However, few studies have focused on the effects of information feedback on self-efficacy, SRL strategies, and perceived and actual learning effectiveness. Social cognitive and SRL theories describe the…

This article analyzes the relationship between self-regulated learning (SRL) and personal learning environments (PLE) in light of the educational academic literature of the decade 2010-2020. This study uses a systematized literature review followed by a qualitative analysis of the most cited literature to establish a narrative that highlights and…

The goal of ITS is to support learning content, activities, and resources, adapted to the specific needs of the individual learner and influenced by learner's motivation. One of the major challenges to the mainstream adoption of adaptive learning is the complexity and time involved in guiding the learning process. To tackle these problems, this…

Math anxiety can significantly impair student learning outcomes. This is often due to a lack of self-regulated learning (SRL), leading to a reliance on external guidance. This systematic literature review aimed to increase existing knowledge on the role of SRL in reducing students' mathematics anxiety and to assess its impact on improving learning…

Differentiated instruction emphasizes tailoring teaching methods to diverse learning styles, ensuring each student's unique needs are met and fostering a more inclusive and effective learning environment. This Spotlight will empower readers with tech advice for implementing effective accelerated learning; strategies for supporting students with…

Writing high-quality procedural texts is a challenging task for many learners. While example-based learning has shown promise as a feedback approach, a limitation arises when all learners receive the same content without considering their individual input or prior knowledge. Consequently, some learners struggle to grasp or relate to the feedback,…

This paper proposes a computer-aided teaching model using knowledge graph construction and learning path recommendation. It first creates a multimodal knowledge graph to illustrate complex relationships among knowledge. Learning elements and sequences are then used to form time sequences stored as directed graphs, supporting flexible path…

Academically talented students with autism, also known as twice-exceptional students with autism (2eASD), are increasingly identified in school. These students present challenges to educators who attempt to plan and implement successful instructional opportunities, as teachers' knowledge and use of evidence-based practices (EBPs) for students…

This study investigated the feasibility and effectiveness of using a flipped classroom (FC) approach to combine self-regulated learning (SRL) instruction and out-of-class eLearning activities in a two-year reading intervention program to facilitate students' learning of classical Chinese reading. A total of 352 junior secondary students from three…

Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…

Machine learning is a powerful method for predicting the outcomes of interactions with educational software, such as the grade a student is likely to receive. However, a predicted outcome alone provides little insight regarding how a student's experience should be personalized based on that outcome. In this paper, we explore a generalizable…

As generative AI tools are increasingly popular in today's teaching and learning process, challenges and opportunities occur at the same time. Self-directed learning has been regarded as a powerful learning ability that supports learners in informal learning contexts and its importance rises in salience when incorporating AI into learning. This…

This study analyses the effects of group differentiation by students' learning strategies of around 1200 students in 46 classes from eight secondary schools in the Netherlands. In an experimental setup with randomization at the class level, division of students over three groups per class (an instruction-independent group, an average group, and an…