Graph data, especially large graph data, come up in many domains, such as social networks, the map of science, biological data, and even knitting! This presents a problem when we consider visualizing these structures. Layouts must be chosen carefully so that the structure of the graph is visible. Some graphs are large enough and connected enough…

There is a significant amount of data available about students and their learning activities in many educational systems today. However, these datasets are frequently spread across several different digital services, making it challenging to use them strategically. In addition, there are no established standards for collecting, processing,…

Ithaka S+R's Research Support Services program's most recent project, "Supporting Big Data Research," focused specifically on the rapidly emerging use of big data in research across disciplines and fields. As part of this study, they partnered with librarians from more than 20 colleges and universities, who then conducted over 200…

Research into self-regulated learning has traditionally relied upon self-reported data. While there is a rich body of literature that has extracted invaluable information from such sources, it suffers from a number of shortcomings. For instance, it has been shown that surveys often provide insight into students' perceptions about learning rather…

The main challenges commonly associated with acquiring practical network engineering skills are the requirements for access to specialised and up-to-date network equipment, as well as the high costs associated with obtaining and maintaining this equipment. The PT Anywhere initiative addresses these challenges by offering a mobile environment for…

This article describes the crossroads between learning analytics and learner engagement. The authors do this by describing specific challenges of using analytics to support student engagement from three distinct perspectives: pedagogical considerations, technological issues, and interface design concerns. While engaging online learners presents a…

Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…

This study uses a sequential, mixed method, action research, quantitative to qualitative research design. The purpose of this study was to develop a useful standardized hiring process at a state medical college that brings clarity to the hiring process and policies. Two conceptual frameworks guided the innovations in this study--communities of…