A critical issue in using fine-grained gameplay data to measure learning processes is the development of indicators and the algorithms used to derive such indicators. Successful development--that is, developing traceable, interpretable, and sensitive-to-learning indicators--requires understanding the underlying theory, how the theory is…

Video has become a widespread tool for capturing naturalistic behavioral data. While mixed methods show great potential in understanding the active nature of children's interaction, only a few studies have developed mixed methods for video-based interaction research. This paper presents a mixed methods embodied interaction model appropriate for…

Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…

Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…

Interactive learning is a two-way learning method of learners independently by using computer and network technology. In the interactive relationships, interactive learning plays a role for learners to achieve the learning purpose, interactive learning has become an important effect of online learning, but it also has many problems that need to be…

Why we need better reports of teacher professional development interventions for finding out what works where: Worldwide, billions of dollars are invested yearly in the professional development of in-service teachers ($14 billion in the USA alone, as of 2014; Bill & Melinda Gates Foundation, 2014). This makes the question of what effects TPD…

Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…

Digital phenotyping is defined as the "moment-by-moment quantification of the individual level human phenotype in situ using data from personal digital devices". The passive data collected by smartphone devices, including GPS, accelerometer and communication logs, can provide insights on users' behaviors that could be related to various…

LearnSphere is a web-based data infrastructure designed to transform scientific discovery and innovation in education. It supports learning researchers in addressing a broad range of issues including cognitive, social, and motivational factors in learning, educational content analysis, and educational technology innovation. LearnSphere integrates…

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…

Play is considered an important aspect of Early Childhood Education and Care. However, the relationship between play and learning is often taken for granted both in research and praxis. In this article, we study our own research group's empirical work over a 40-year period, and how we have used the concepts of play and learning. We observed that…

Data infrastructures exist in a variety of formats. This article draws on the insights of senior personnel involved in developing a new data dashboard in one state jurisdiction in Australia. While literature on dashboards often focuses on the teachers and learners influenced by them, there is less attention to those involved in their development…

Understanding scientific phenomena requires learners to construct mental models of causal systems. Simulation-based discovery learning offers learners the opportunity to construct mental models and test them against the behavior of a simulation. The purpose of this study was to investigate sequential patterns of learner actions and utterances…

Purpose: The goal of this study is to explore how content creators engage in critical data literacies on TikTok, a social media site that encourages the creation and dissemination of user-created, short-form videos. Critical data literacies encompass the ability to reason with, critique, control, and repurpose data for creative uses. Existing work…

The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…