This paper presents an analysis of learning analytics practices which aimed to achieve personalised learning. It addresses the need for a systematic analysis of the increasing amount of practices of learning analytics which are targeted at personalised learning. The paper summarises and highlights the characteristics and trends in relevant…

Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…

The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…

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…

The availability of large-scale learning data presents unprecedented opportunities for investigating student learning processes. However, it is challenging for instructors to fully make sense of this data and effectively support their teaching practices. This study introduces LearningViz, an interactive learning analytics dashboard to help…

Educational data mining involves the application of data mining techniques to student activity. However, in the context of computer programming, many data mining techniques can not be applied because they require vector-shaped input, whereas computer programs have the form of syntax trees. In this paper, we present ast2vec, a neural network that…

This collection focuses on the role of higher education institutions concerning datafication as a complex phenomenon. It explores how the universities can develop data literac(ies) shaping tomorrow skills and "formae mentis" to face the most deleterious effects of datafication, but also to engage in creative and constructive ways with…

Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…

Data--their collection, analysis and use--have always been part of education, used to inform policy, strategy, operations, resource allocation, and, in the past, teaching and learning. Recently, with the emergence of learning analytics, the collection, measurement, analysis and use of student data have become an increasingly important research…

This study presents a systematic review of the literature on the predicting student retention in higher education through machine learning algorithms based on measures such as dropout risk, attrition risk, and completion risk. A systematic review methodology was employed comprised of review protocol, requirements for study selection, and analysis…

In the higher education context, an increasing concern on the technical or instrumental approach permeates attention to academics' data literacies and faculty development. The need for data literacy to deal specifically with the rise of learning analytics in higher education has been raised by some authors, though in spite of some focus on the…

For this 14th iteration of the International Conference on Educational Data Mining (EDM 2021), the conference was held completely online. EDM is organized under the auspices of the International Educational Data Mining Society and was meant to happen in Paris, France. The official theme of this year's conference was Shifting Landscape of…

Determining whether a state's young people are on track for a life with opportunity is a critical -- but diffcult -- task for governors and state leaders. States can be both awash in data and unable to easily access and use that data to inform policy. State longitudinal data systems that meaningfully connect workforce, higher education, K-12, and…

Determining whether a state's young people are on track for a life of opportunity is a difficult task for governors and state leaders. States can be both awash in data and unable to easily access and use that data to inform policy. State longitudinal data systems that meaningfully connect workforce, higher education, K-12, and early childhood…

The purpose of this research is to examine the research that has been done on MOOCs by applying data mining and analytic approaches and to depict the current state of MOOC research. The text mining revealed four broad themes: (I) MOOCs as a mainstreaming learning model in HE, (II) motivation and engagement issues in MOOCs, (III) assessment issues…