Multimodal learning analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across…

A problem exists in NC Montessori schools with effective data analysis for specific learning disabilities (SLD) placement. The purpose of this study was to identify administrators' and teachers' perceptions of data collection and analysis within multitiered systems of support (MTSS) in a Montessori school. Fixsen's implementation science theory…

This paper reports on systematic literature review that examined learning theories and data collection and analysis methods used to study game-based learning in research on educational digital games for K-12 populations. Through electronic database, hand, and ancestral searches, we identified 25 empirical studies (29 educational games) published…

With the growth of tech-driven instructional possibilities, school systems have an increasingly urgent responsibility for schools to continuously assess and improve student data-protection practices. Attai, a project director for the Consortium for School Networking, outlines a program designed to help education leaders master the fundamentals of…

A major problem an instructor experiences is the systematic monitoring of students' academic progress in a course. The moment the students, with unsatisfactory academic progress, are identified the instructor can take measures to offer additional support to the struggling students. The fact is that the modern-day educational institutes tend to…

Online education is growing because of its benefits and advantages that students enjoy. Educational technologies (e.g., learning analytics, student modelling, and intelligent tutoring systems) bring great potential to online education. Many online courses, particularly in self-paced online learning (SPOL), face some inherent barriers such as…

Ethics is a prominent topic in learning analytics that has been commented on from conceptual viewpoints. For a broad range of emerging technologies, systematic literature reviews have proven fruitful by pinpointing research directions, knowledge gaps, and future research work guidance. With these outcomes in mind, we conducted a systematic…

Passive data from a tracking application (or "meter") installed on participants' devices to register the URLs visited have great potential for studying people's online activities. However, given privacy concerns, obtaining cooperation installing a meter can be difficult and lead to selection bias. Therefore, in this article, we address…

Developmental scientists are often interested in subgroups of people who share commonalities in aspects of development; these subgroups often cannot be captured directly but instead must be inferred from other information. Mixture models can be used in these situations. Two specific types of mixture models, latent profile transition analyses and…

Increasingly surveys are using interviewers to collect objective health measures, also known as biomeasures, to replace or supplement traditional self-reported health measures. However, the extent to which interviewers affect the (im)precision of biomeasurements is largely unknown. This article investigates interviewer effects on several…

Digital transformation (Dx) refers to a series of deep and coordinated culture, workforce, and technology shifts that enable new educational and operating models and transform an institution's business model, strategic directions, and value proposition. Dx initiatives on many campuses are anchored in student success goals. As a result of this…

Research based on educational data mining conducted at academic institutions is often limited by the institutional policy with regard to the type of learning management system and the detail level of its activity reports. Often, researchers deal with only raw data. Such data normally contain numerous fictitious user activities that can create a…

Collecting biological data in representative surveys is becoming more common due to their potential to inform research and policy. Nevertheless, using nurses to collect these data can lead to unintended effects. In this paper, we investigate how nurses influence the non-response process by looking at five waves of data coming from two surveys in…

Understanding the processes in education, such as the student learning behavior within a specific course, is a key to continuous course improvement. In online learning systems, students' learning can be tracked and examined based on data collected by the systems themselves. However, it is non-trivial to decide how to extract the desired students'…

A course-level early final study status prediction task is to predict as soon as possible the final success of each student after studying a course. It is significant because each successful course accomplishment is required for a degree. Further, early predictions provide enough time to make necessary changes for ultimate success. This article…