The system architecture of big data in massive open online courses (BD-MOOCs System Architecture) is composed of six components. The first component was comprised of big data tools and technologies such as Hadoop, YARN, HDFS, Spark, Hive, Sqoop, and Flume. The second component was educational data science, which is composed of the following four…

In science and engineering education, remote laboratories are designed to bring ubiquity to experimental scenarios, by having real laboratories operated through the Internet. Despite that remote laboratories enable the collection of students' work data, the educational use of these data is still underdeveloped. Learning analytics dashboards are…

Purpose: Course evaluations are formative and are used to evaluate learnings of the students for a course. Anomalies in the evaluation process can lead to a faulty educational outcome. Learning analytics and educational data mining provide a set of techniques that can be conveniently applied to extensive data collected as part of the evaluation…

Most children first enter social groups of peers in preschool. In this context, children use movement as a social tool, resulting in distinctive proximity patterns in space and synchrony with others over time. However, the social implications of children's movements with peers in space and time are difficult to determine due to the difficulty of…

This research investigated the potential of learning analytics (LA) as a tool for identifying and evaluating K-12 student behaviors associated with active learning when using video learning objects within an online learning environment (OLE). The study focused on the application of LA for evaluating K-12 student engagement in videobased…

Education researchers are deeply interested in understanding the way students organize their knowledge. Card sort tasks, which require students to group concepts, are one mechanism to infer a student's organizational strategy. However, the limited resolution of card sort tasks means they necessarily miss some of the nuance in a student's strategy.…

Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…

Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to…

History teaching from early educational stages not only should assess the student's ability to memorise historical content, but also their ability to think historically. Traditional summative tests do not enable teachers to continuously monitor the progress of students. This study evaluates the effect in history learning of incorporating learning…

Background: Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved…

Understanding the trends and developments in artificial intelligence research in science education, which has rapidly advanced in recent years, is crucial for technological innovations and applications in education. Therefore, this study examines research on artificial intelligence in science education conducted between 2019 and 2023 (the last…

The rise of precision education has encouraged teachers to use intelligent diagnostic systems to understand students' learning processes and provide immediate guidance to prevent students from giving up when facing learning difficulties. However, current research on precision education rarely employs multimodal learning analytics approaches to…

Researchers in learning analytics have created indicators with learners' trace data as a proxy for studying learner behaviour in a college course. Student Approaches to Learning (SAL) is one of the theories used to explain these behaviours, distinguishing between deep, surface, and organized study. In Latin America, researchers have demonstrated…

This paper discusses how Orff's music education system is combined with the localized teaching mode under the background of globalization, especially with the support of big data analysis to realize the innovation of music education. Orff's music education has attracted worldwide attention for its openness, diversity and innovation. In China, its…

Learning analytics promise significant benefit to online education providers through improved, better-targeted student services. Much has been written about the potential of analytics and how they might be technically implemented, and various ethical considerations are published highlighting the significant potential risk of gathering,…