Data are fundamental to Learning Analytics (LA) research and practice. However, the ethical use of data, particularly in terms of respecting learners' privacy rights, is a potential barrier that could hinder the widespread adoption of LA in the education industry. Despite the policies and guidelines of privacy protection being available worldwide,…

This article presents methods for using extant data to improve the properties of estimators of the standardized mean difference (SMD) effect size. Because samples recruited into education research studies are often more homogeneous than the populations of policy interest, the variation in educational outcomes can be smaller in these samples than…

To improve and facilitate the acquisition of learning outcomes, teachers often use innovative teaching methods such as gamification to keep students' attention and increase their motivation. In recent years, the use of educational data mining (EDM) methods to explore academic topics has increased. With the expansion of EDM, a gap in the literature…

Multivariate Functional Principal Component Analysis (MFPCA) is a valuable tool for exploring relationships and identifying shared patterns of variation in multivariate functional data. However, interpreting these functional principal components (PCs) can sometimes be challenging due to issues such as roughness and sparsity. In this dissertation,…

Big Data offers opportunities and challenges in all aspects of human life. In relation to research ethics, Big Data represents a normative difference in degree rather than a difference in kind. Data are more messy, rapid, difficult to predict, and difficult to identify owners; but the principles of informed consent, confidentiality, and prevention…

Data- driven decision making DDDM in school settings is often guided and influenced by various sources of data that assist in improving students' outcomes. School principals as the main educational leaders, play a pivotal role in DDDM using the available school data. Semi-structured interviews with 24 school principals were conducted to…

The purpose of this invited paper is to show the learning disabilities field what LDbase is, why it's important for the field, what it offers the field, and examples of how you can leverage LDbase in your own work.

Multi-lab projects are large scale collaborations between participating data collection sites that gather empirical evidence and (usually) analyze that evidence using meta-analyses. They are a valuable form of scientific collaboration, produce outstanding data sets and are a great resource for third-party researchers. Their data may be reanalyzed…

This chapter introduces the learning analytics as a catalyst to transform data utilization and bolster support for the scholarship of teaching and learning.

This dissertation examines the role of digitalization in new venture internationalization in three studies: a systematic literature review, a quantitative study, and a qualitative study. The systematic literature review synthesizes existing literature in the research domains of digitalization and international opportunity recognition, as well as…

Eye tracking has taken hold in second language acquisition (SLA) and bilingualism as a valuable technique for researching cognitive processes, yet a comprehensive picture of reporting practices is still lacking. Our systematic review addressed this gap. We synthesized 145 empirical eye-tracking studies, coding for 58 reporting features and…

We are at a critical moment for assessment in schools. Teachers are called to navigate advances in classroom assessment research, top-down assessment policies, and lingering effects of the COVID-19 pandemic on teaching and learning. Embedded in this context are also systemic challenges to teachers' assessment practice. This paper analyses these…

Misleading data visualizations have become a significant issue in our information-rich world due to their negative impact on informed decision-making. Consequently, it is crucial to understand the factors that make viewers vulnerable to misleading data visualizations and to explore effective instructional supports that can help viewers combat the…

Data mining has been successfully and widely utilized in educational information systems, and an important research field has been formed, which is educational data mining. Process mining inherits the characteristics of data mining which can not only use historical data in the system to analyze learning behavior and predict academic performance,…

This paper scrutinizes the increasing trend of using international large-scale assessment (ILSA) data for causal inferences in educational research, arguing that such inferences are often tenuous. We explore the complexities of causality within ILSAs, highlighting the methodological constraints that challenge the validity of causal claims derived…