This study provides an overview of research on teachers' use of artificial intelligence (AI)
applications and machine learning methods to analyze teachers' data. Our analysis showed …

Learning sciences are embracing the significant role technologies can play to better detect,
diagnose, and act upon self-regulated learning (SRL). The field of SRL is challenged with …

Artificial intelligence (AI) has generated a plethora of new opportunities, potential and
challenges for understanding and supporting learning. In this paper, we position human and …

In this paper, we argue that a particular set of issues mars traditional assessment practices.
They may be difficult for educators to design and implement; only provide discrete snapshots …

The effects of technology acceptance and innovation diffusion behaviors on information and
communications technology-enabled teaching/learning systems (ITLS) adoption attract …

Early socio-cognitive conceptions of self-regulated learning (SRL) emphasized individual,
cognitive-constructive aspects involved in cognition, behavior, and motivation, as well as …

This study utilized multimodal learning analytics and AI-based methods to examine the
patterns of the socially shared regulation of collaborative learning (CL). The study involved …

Hybrid systems combining artificial and human intelligence hold great promise for training
human skills. In this paper, I position the concept of Hybrid Human-AI Regulation and …

We present a systematic literature review of data-driven self-regulated learning (SRL) that
emphasises the methodological importance of temporality and sequence, as opposed to …

The new educational models such as smart learning environments use of digital and context‐
aware devices to facilitate the learning process. In this new educational scenario, a huge …