Self-regulated learning (SRL) theory comprises cognitive, metacognitive, and affective aspects that enable learners to autonomously manage their learning processes. This article presents a systematic literature review on the measurement of SRL in digital platforms, that compiles the 53 most relevant empirical studies published between 2015 and…

Analyzing qualitative data from learning processes is considered "messy" and time consuming (Chi in J Learn Sci 6(3):271-315, 1997). It is often challenging to summarize and synthesize such data in a manner that conveys the richness and complexity of learning processes in a clear and concise manner. Moreover, qualitative data often…

Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…

In massive open online courses (MOOCs), learners can interact with each other using discussion boards. Automatically inferring the states or needs of learners from their posts is of interest to instructors, who are faced with a high attrition in MOOCs. Machine learning has previously been successfully used to identify states such as confusion or…

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…

The importance of temporality in learning has been long established, but it is only recently that serious attention has begun to be paid to the precise identification, measurement, and analysis of the temporal features of learning. From 2009 to 2016, a series of temporality workshops explored temporal concepts and data types, analysis methods for…

Founded on the need to help university students develop a greater academic metacognitive capacity, student-facing learning analytics are considered useful tools for making students overtly aware of their own learning processes, helping students to develop control over their learning, and subsequently supporting more effective learning. However,…

The goal of this study is to identify major research trends and focus in the field of educational research. To this end, 22,000 titles consisting of PhD dissertations, journal papers and conference proceedings were retrieved from the ERIC (Education Resources Information Center - https://eric.ed.gov/?) database in the period from 2009 to 2018. A…

This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…

This paper investigates the intersection of big data and philosophy of education by considering big data's potential for addressing learning via a holistic process of coming-to-know. Learning, in this sense, cannot be reduced to the difference between a pre- and post-test, for example, as it is constituted at least as much by qualities of…

This chapter explores lessons learned from two different learning analytics efforts at a large, public, multicampus university--one internally developed and one vended platform. It raises questions about how to best use analytics to support students while keeping students responsible for their own learning and success.

This chapter describes an open learning analytics system focused on learning process measures and designed to engage instructors and students in an evidence-informed decision-making process to improve learning.

A prominent goal of colleges and universities today is to enact data-driven teaching and learning. Faculty clearly play a key role, and yet they tend to have limited time, a lack of training in assessment or education research, and few incentives for engaging in this work. We describe a framework designed to address the practical and cultural…

This systematic review is built on the seminal work by the New London Group in 1996. Few endeavours have synthesized findings of empirical studies pertaining to the effects and challenges of multiliteracies practices in various schooling and geographical contexts. Through a five-point Likert scale and a deductive and inductive thematic analysis,…

Within educational data mining, many statistical models capture the learning of students working individually. However, not much work has been done to extend these statistical models of individual learning to a collaborative setting, despite the effectiveness of collaborative learning activities. We extend a widely used model (the additive factors…