The emergence of big data in educational contexts has led to new data-driven approaches to support informed decision making and efforts to improve educational effectiveness. Digital traces of student behavior promise more scalable and finer-grained understanding and support of learning processes, which were previously too costly to obtain with…

With the development of online learning, LMSs accumulated huge amounts of students' interaction data. Unfortunately, with the support of LMSs data, few researchers put a sight on interaction research in MPOCs. Particularly, comparing interaction activity patterns of different achievement student groups and in different course processes in MPOCs…

Blended learning (BL) is a popular e-Learning model in higher education that has the potential to take advantage of learning analytics (LA) to support student learning. This study utilized LA to investigate fourth-year undergraduates' (n = 157) use of self-regulated learning (SRL) within the online components of a previously unexamined BL…

This article examines the effects of incorporating information and communication technologies in schools in terms of distributive justice. To do so, four issues that are central to educational justice are discussed: scarcity of resources, the positional nature of education, peer effects, and biases in educational decision-making. The discussion…

Various types of structured data collected by learning management systems such as Moodle have been used to improve student learning outcomes. Learning analytics refers to an assortment of data analysis methods used for this task. These methods typically do not consider unstructured data such as blogs, discussions, e-mail, and course messages.…

This profile describes the AIChE Concept Warehouse (CW) website, a community developed, web-based tool to decrease instructional barriers and to help faculty implement concept-based active learning in class. The CW provides three distinct but complementary functions: (a) a content repository, (b) an audience response system and learning management…

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…

Privacy and surveillance are pervasive words not only in higher education but also in many areas in our life. We use and hear them often while shopping online, reading the news, or checking the policies and terms of websites. In this study, I highlight the challenges of data collection and surveillance in education, specifically, in online…

Extensive research in learning science has established the importance of time management in online learning. Recently, learning analytics (LA) has shed further lights on the temporal characteristics of learning by allowing researchers to capture authentic digital footprints of student learning behaviours. Nonetheless, students' timing of…

Persistence in learning processes is perceived as a central value; therefore, dropouts from studies are a prime concern for educators. This study focuses on the quantitative analysis of data accumulated on 362 students in three academic course website log files in the disciplines of mathematics and statistics, in order to examine whether student…

Learning analytics can be used to enhance student engagement and performance in online courses. Using learning analytics, instructors can collect and analyze data about students and improve the design and delivery of instruction to make it more meaningful for them. In this paper, the authors review different categories of online assessments and…

Learning technologies are now commonplace in education, and generate large volumes of educational data. Scholars have argued that analytics can and should be employed to optimize learning and learning environments. This article explores what is really meant by "analytics", describes the current best-known examples of institutional…

Purpose: The purpose of this paper is to demonstrate the utility of combining event-centred and variable-centred approaches when analysing big data for higher education institutions. It uses a large, university-wide data set to demonstrate the methodology for this analysis by using the case study method. It presents empirical findings about…

In the 21st century, attainment of a college degree is more important than ever to achieve economic self-sufficiency, employment, and an adequate standard of living. Projections suggest that by 2020, 65% of jobs available in the U.S. will require postsecondary education. This reality creates an unprecedented demand for higher education, and…

This paper details the anticipated impact of synthetic "big" data on learning analytics (LA) infrastructures, with a particular focus on data governance, the acceleration of service development, and the benchmarking of predictive models. By reviewing two cases, one at the sector-wide level (the Jisc learning analytics architecture) and…