Learning analytics systems are software designed to aggregate student data to be analyzed for the purpose of delivering information to students, with the goal of increasing student success, academic goal completion, and retention. Despite being identified as stakeholders and beneficiaries of learning analytics, student perceptions make up a small…

Design science research (DSR) is one of important research paradigms in information systems (IS) that focus on addressing business problems by building and implementing design artifacts. Recently, predictive analytics has become one major stream of DSR thanks to the improvement of computational power and methods and the increase in available…

Spatial analytics receive increased attention in educational data mining. A critical issue in stop detection (i.e., the automatic extraction of timestamped and located stops in the movement of individuals) is a lack of validation of stop accuracy to represent phenomena of interest. Next to a radius that an actor does not exceed for a certain…

Game-based assessment (GBA), a specific application of games for learning, has been recognized as an alternative form of assessment. While there is a substantive body of literature that supports the educational benefits of GBA, limited work investigates the validity and generalizability of such systems. In this paper, we describe applications of…

This research examines the effect of having a tracking technology in a learning management system (LMS) that reports the effect of perceiving other students' interactions on a learner's intention to keep using LMS in the future. The main underlying theory is herd behaviour theory which argues that crowd behaviour affects the perceptions of the…

Transparency and trustworthiness are among the key requirements for the ethical use of learning analytics (LA) and artificial intelligence (AI) in the context of social inclusion and equity. However, research on these issues pertaining to users is lacking, leaving it unclear as to how transparent and trustworthy current LA tools are for their…

Background: The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.…

Technology integration and learning analytics offer insights to improve educational experiences and outcomes. In advancing these efforts, laws and policies govern these environments placing protections, standards, and developmental opportunities for higher education, students, faculty, and even the nation-state. Nonetheless, evidence of…

In this study, we have proposed and implemented a sequential data analytics (SDA)-driven methodological framework to design adaptivity for digital game-based learning (DGBL). The goal of this framework is to facilitate children's personalized learning experiences for K-5 computing education. Although DGBL experiences can be beneficial, young…

The interactive learning is a continuous process, which is full of a large number of learning interaction activities. The data generated between learners and learning interaction activities can reflect the online learning behaviors. Through the correlation analysis among learning interaction activities, this paper discusses the potential…

Virtual learning environments give students more autonomy over their learning than traditional face-to-face classes and require that students adapt the ways they consume and assimilate new information. One theory of this process is self-regulated learning, which is illustrated in Efklides' Metacognitive and Affective model of Self-Regulated…

Educational Data Mining (EDM) is an emerging field that aims to better understand students' behavior patterns and learning environments by employing statistical and machine learning methods to analyze large repositories of educational data. Analysis of variable data in the early stages of a course might be used to develop a comprehensive…

Background: Measurement of students' self-regulation skills is an active topic in education research, as effective assessment helps devising support interventions to foster academic achievement. Measures based on event tracing usually require large amounts of data (e.g., MOOCs and large courses), while aptitude measures are often qualitative and…

Purpose: This paper aims to address research gaps around third party data flows in education by investigating governance practices in higher education with respect to learning management system (LMS) ecosystems. The authors answer the following research questions: How are LMS and plugins/learning tools interoperability (LTI) governed at higher…

Aim/Purpose: This article proposes a framework based on a sequential explanatory mixed-methods design in the learning analytics domain to enhance the models used to support the success of the learning process and the learner. The framework consists of three main phases: (1) quantitative data analysis; (2) qualitative data analysis; and (3)…