Higher education is increasingly defined by data, indicators and metrics. The paper examines how English universities conceptualise and articulate their perspectives on 'teaching quality' in the context of the Teaching Excellence and Student Outcomes Framework (TEF) in the UK. By adopting a qualitative thematic analysis approach, the author…

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…

Much of learning analytics research has focused on factors influencing model generalizability of predictive models for academic performance. The degree of model generalizability across courses may depend on aspects, such as the similarity of the course setup, course material, the student cohort, or the teacher. Which of these contextual factors…

A small subset of education studies analyzes school data collected seasonally (separating the summer from the school year). At first, this work was primarily known for documenting learning loss in the summers, but scholars have since recognized that observing how inequality changes between summer and school periods provides leverage for…

Educational researchers have pointed to socioemotional dimensions of learning as important in gaining a more nuanced description of student engagement and learning. However, to date, research focused on the analysis of emotions has been narrow in its focus, centering on affect and sentiment analysis in isolation while neglecting how emotions…

The use of videos in teaching has gained impetus in recent years, especially after the increased attention towards remote learning. Understanding students' video-related behaviour through learning (and video) analytics can offer instructors significant potential to intervene and enhance course designs. Previous studies explored students' video…

Increasingly, data collection and analysis are core functions of higher education institutions. However, an EDUCAUSE QuickPoll revealed that just one in four (25%) of respondents believed the structure of data functions at their institution was ideal for their analytics needs, and only 16% of respondents indicated that their institutional data…

This study focuses on the problem that the process of building learning habits has not been clearly described. Therefore, we aim to extract the stages of learning habits from log data. We propose a data model to extract stages of learning habits based on the transtheoretical model and apply the model to the learning logs of self-directed extensive…

In the wake of the COVID-19 pandemic, educators and policymakers have scrambled to assess the impact on student learning. Popular metrics that have gained traction are the notions of "years of learning lost" or "months behind," which attempt to quantify the educational setbacks caused by the pandemic. The allure of these…

The planned systematized design of the use of serious games in the classroom is presented as a strategy to optimize learning. In this framework, Learning Analytics represents stealth assessment and follow-up method, and a way to personalize such games by simplifying their application for teachers. The aim of this research was to analyze the impact…

Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…

We examined how Learning Analytics literature represents participants from diverse societies by comparing the studies published with samples from WEIRD (Western, Industrialized, Rich, Democratic) nations versus non-WEIRD nations. By analyzing the Learning Analytics studies published during 2015-2019 (N = 360), we found that most of the studies…

Background: With the development of computational literacy, there has been a surge in both research and practice application of text-based and block-based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major…

Learning outcomes can be predicted with machine learning algorithms that assess students' online behavior data. However, there have been few generalized predictive models for a large number of blended courses in different disciplines and in different cohorts. In this study, we examined learning outcomes in terms of learning data in all of the…

Teacher networks and communities have played an important role in teacher professional development. In such contexts, teachers often receive extensive feedback from peers as part of social learning. However, many teachers have difficulty identifying essential information from a large amount of peer feedback, which may impede self-reflection and…