Background: Learning analytics (LA) collects, analyses, and reports data from the learning environment, to provide evidence of the effects of a particular learning design. Learning design (LD) outlines the conceptual framework for a meaningful interpretation of Learning analytics data. Objectives: The study aims to identify the most relevant…

The increased adoption of online learning environments has resulted in the availability of vast amounts of educational log data, which raises questions that could be answered by a thorough and accurate examination of students' online learning behaviours. Event logs describe something that occurred on a platform and provide multiple dimensions that…

There is a growing interest in the research and use of automated feedback dashboards that display classroom analytics; yet little is known about the detailed processes instructors use to make sense of these tools, and to determine the impact on their teaching practices. This research was conducted at a public Midwestern university within the…

Technology-based, open-ended learning environments (OELEs) can capture detailed information of students' interactions as they work through a task or solve a problem embedded in the environment. This information, in the form of log data, has the potential to provide important insights about the practices adopted by students for scientific inquiry…

This study focuses on the problem that the process of building learning habits has not been clearly described. Therefore, we aim to extract the stages of learning habits from log data. We propose a data model to extract stages of learning habits based on the transtheoretical model and apply the model to the learning logs of self-directed extensive…

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…

Data analysis and interpretation has always played a fundamental role in the scientific curricula of high school students. The spread of digitalization has further increased the number of learning environments whereby this topic can be effectively taught: as a matter of fact, the ever-growing diffusion of data science across diverse sectors of…

Learning analytics dashboards have been developed to facilitate teacher guidance in computer-supported collaborative learning (CSCL). As yet, little is known about how teachers interpret dashboard information to facilitate guidance in their teaching practice. This study examined teachers' behavior patterns in interpreting information from…

Student wellbeing has been foregrounded during the recent Covid-19 pandemic but this is broad brush and contested with different models being followed across the sector. One aspect of concern is the extent to which access to the technology institutions require students to use contributes to additional stress. A student survey (n=30) in one UK HEI…

Although an increasing number of ethical data science and AI courses is available, with many focusing specifically on technology and computer ethics, pedagogical approaches employed in these courses rely exclusively on texts rather than on algorithmic development or data analysis. In this paper we recount a recent experience in developing and…

Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12…

Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…

Driven by the increased availability of Learning Management System data, this study explored its value and sought understanding of student behaviour through the information contained in activity level log data. Specifically, this study examined analytics data to understand students' engagement with online videos. Learning analytics data from the…

Recent research on learning analytics dashboards has focused on designing user interfaces that offer various forms of "visualization guidance" (often referring to notions such as "data storytelling" or "narrative visualization") to teachers (e.g., emphasizing data points or trends with colour and adding annotations),…

Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…