Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…

Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…

Purpose: The goal of this study is to explore how content creators engage in critical data literacies on TikTok, a social media site that encourages the creation and dissemination of user-created, short-form videos. Critical data literacies encompass the ability to reason with, critique, control, and repurpose data for creative uses. Existing work…

As data are 'numbers with context' (Cobb & Moore, 1997), contextual knowledge plays a prominent role in dealing with statistics. While insights about a specific context can further the depth of interpreting and evaluating outcomes of data analysis, research shows how it can also hinder relying on data especially if results differ from…

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…

Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…

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…

Amidst ongoing technological and social change, this article explores the implications for critical education that result from a data-driven model of digital governance. The article argues that traditional notions of critique which rely upon the deconstruction and analysis of texts are increasingly redundant in the age of datafication, where the…

The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining…

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 idea of data-based decision-making (DBDM) at the classroom level is that teachers use assessment data to adapt their instruction to students' individual needs and thus improve students' learning progress. In this study, we first investigate this theoretically assumed DBDM process, and second, we evaluate the effectiveness of teacher support on…

Collaborative learning provides learners with significant opportunities to collaborate on solving problems and creating better products. There has been a growing utilization of adaptive and intelligent systems to support productive learning while promoting collaborative practices. One of the core capabilities of these adaptive and intelligent…

As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…

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…

The growth of Learning Analytics (LA) as a research field has been extensively documented since its beginnings. This paper provides a broad overview of the publications that Latin American authors have published in the last years by performing a quantitative review of the literature (from 2011 to 2019). A total of 282 papers were collected and…