Artificial intelligence (AI) has been hailed for its potential to revolutionize teaching and
learning practices. Undoubtedly, there has been development, but has it transferred to a …

Abstract Self-Regulated Learning (SRL) is related to increased learning performance.
Scaffolding learners in their SRL activities in a computer-based learning environment can …

Background Adaptive systems serve to personalize interventions or training based on the
user's needs and performance. The adaptation techniques rely on an underlying engine …

Scaffolds that support self‐regulated learning (SRL) have been found to improve learning
outcomes. The effects of scaffolds can differ depending on how learners use them and how …

Personalized learning (PL) aspires to provide an alternative to the one-size-fits-all approach
in education. Technology-based PL solutions have shown notable effectiveness in …

Self-regulated learning (SRL) is the ability to regulate cognitive, metacognitive, motivational,
and emotional states while learning and is posited to be a strong predictor of academic …

Self-regulation is an essential skill for lifelong learning. Research has shown that self-
regulated learning (SRL) leads to greater academic achievement and sustainable …

Makerspaces persist as formal and informal spaces of learning for youth, promoting
continued interest in studying how design can support the variety of learning opportunities …

Recent advances in generative artificial intelligence (AI) and multimodal learning analytics
(MMLA) have allowed for new and creative ways of leveraging AI to support K12 students' …

Background Self‐regulated learning (SRL) is a predictive variable in students' academic
performance, especially in virtual reality (VR) environments, which lack monitoring and …