Self-regulated learning (SRL) theory comprises cognitive, metacognitive, and affective aspects that enable learners to autonomously manage their learning processes. This article presents a systematic literature review on the measurement of SRL in digital platforms, that compiles the 53 most relevant empirical studies published between 2015 and…

Replicating research studies is considered one way of establishing validity and confidence of findings in a field of study. In this paper, we introduce a replication framework for classifying studies conducted in the area of educational technology as a possible guide to conducting and reporting replication studies in the field. The paper includes…

Even though instructional videos are often used in many areas covering a wide range of studies and applications, the lack of a common approach for the definition and classification of instructional videos results in the use of several different models for these purposes. In order to develop such a common approach, there remains the need to build a…

More and more teachers create video explanations for their instruction. Whether or not they are effective for learning depends on the videos' instructional quality. Reliable measures to assess the quality of video explanations, however, are still rare, especially for videos created by (preservice) teachers. We developed such a measure in a…

The rapid development of digital technology and its pervasiveness in everyday life requires everybody to develop the skills necessary to engage with such technology for one's mundane tasks and communication needs. The first steps towards developing these skills can be particularly challenging for older adults, who might need to fundamentally adapt…

With the advent of physiological computing systems, new avenues are emerging for the field of learning analytics related to the potential integration of physiological data. To this end, we developed a physiological computing infrastructure to collect physiological data, surveys, and browsing behavior data to capture students' learning journey in…

Exploring the relationship between student ability and test-taking effort is an important area of study, offering insights into their approach to educational assessments. Previous research shows this relationship, yet there is a scarcity of research comparing the test-taking effort of students. In addition, researchers have frequently employed…

Predicting the students' performance has become a challenging task due to the increasing amount of data in educational systems. In keeping with this, identifying the factors affecting the students' performance in higher education, especially by using predictive data mining techniques, is still in short supply. This field of research is usually…

The demand for in-depth studies on educational data presupposes the application of technologies that allow data analysis of vast quantities, and subsequently, drawing relevant information and knowledge. The research objective herein is to employ data mining techniques on PISA databases to identify potential patterns that may explain the…

This research focuses on developing and implementing a continuous Naïve Bayesian classifier for GEAR courses at Rio Salado Community College. Previous implementation efforts of a discrete version did not predict as well, 70%, and had deployment issues. This predictive model has higher prediction, over 90%, accuracy for both at-risk and successful…