Higher education institutions (HEIs) implementing learning analytics (LA) use student data to improve the learning experience. The problem for LA implementation originates from individuals responsible for analytic programs from different institutional departments and the lack of a framework for communication and productive dialogue about usages of…

The purpose of this work is to identify contextual variables that help to explain the occupational aspirations of Spanish 15-year-old students. This is done by performing a secondary analysis of the PISA2018 test. Data have been analysed using decision trees introducing the students' expected occupational status as a dependent variable (DV), and…

Data infrastructures exist in a variety of formats. This article draws on the insights of senior personnel involved in developing a new data dashboard in one state jurisdiction in Australia. While literature on dashboards often focuses on the teachers and learners influenced by them, there is less attention to those involved in their development…

This review explores how artificial intelligence (AI henceforth) can reshape education through insights from situated learning literature. The objective was to critically examine opportunities and challenges of situated learning, and how AI could augment strengths while overcoming obstacles. A systematic review using the PRISMA method analyzed 60…

It is widely documented that higher education institutional responses to the COVID-19 pandemic accelerated not only the adoption of educational technologies, but also associated socio-technical controversies. Critically, while these cloud-based platforms are capturing huge datasets, and generating new kinds of learning analytics, there are few…

Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…

In this study, we explore the application of process mining techniques on assessment log data to explore problem-solving strategies in Algebra. By analyzing sequences of student activities, we demonstrate the significant potential of process mining in identifying problem-solving strategies that lead to successful and unsuccessful outcomes. Our…

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…

This systematic literature review investigates the fairness of machine learning algorithms in educational settings, focusing on recent studies and their proposed solutions to address biases. Applications analyzed include student dropout prediction, performance prediction, forum post classification, and recommender systems. We identify common…

Randomized A/B tests within online learning platforms enable us to draw unbiased causal estimators. However, precise estimates of treatment effects can be challenging due to minimal participation, resulting in underpowered A/B tests. Recent advancements indicate that leveraging auxiliary information from detailed logs and employing design-based…

Understanding students' privacy concerns is an essential first step toward effective privacy-enhancing practices in learning analytics (LA). In this study, we develop and validate a model to explore the students' privacy concerns (SPICE) regarding LA practice in higher education. The SPICE model considers "privacy concerns" as a central…

Student engagement is consistently identified as a key predictor of learner outcomes within the online learning environment. However, there is limited guidance about using proactive strategies to improve engagement for low and non-engaged students: for example by specifically employing course learning analytics (CLA) and nudging strategies in…

Learning analytics dashboards have been developed to facilitate teacher guidance in computer-supported collaborative learning (CSCL). As yet, little is known about how teachers interpret dashboard information to facilitate guidance in their teaching practice. This study examined teachers' behavior patterns in interpreting information from…

Lecture capture is popular within Higher Education, but previous research suggests that students do not always optimally select content to review, nor do they make the most of specific functions. In the current study conducted in the 2019/20 academic year, we used a repeated-measures crossover design to establish the effects of transcripts with…

In this paper, an empirical comparison of three state-of-the-art classifier methods (artificial immune recognition systems, Lazy-K Star, and random tree) to predict teachers' ability to adapt in a classroom environment is carried out. Two educational databases are used for this task. First, measures collected in an academic context, especially…