Based on our experience developing and delivering a highly successful data visualization course within a Master of Science in Business Analytics program, we present a taxonomy for data visualization courses and recommend content and pedagogical features for each type of data visualization course therein. We also discuss the interdependence between…

Students' knowledge of data analysis determines the quality of the research they report but they tend to perceive courses on statistics or data analysis as challenging and unappealing. The present study aimed to investigate the correlation between biology education students' attitudes toward statistics and their proficiency in determining various…

The purpose of this study was to develop and measure the usability of the software prototype of formative assessment in the LMS. This study was applied in terms of research objective and mixed method (qualitative-quantitative) in terms of data collection in which an exploratory sequential mixed methods design was used. In addition, in order to…

This paper interrogates whether technical democracy is well-suited to contend with possible technical controversies, including the increasing prevalence of EdTech in public schooling. Drawing across Habermasian 'deliberative democracy' that seeks consensus-derived resolution, as well as more agonistic approaches that embrace conflict as the means…

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…

The massive amount of text related to education provides rich information to support education in many aspects. In the meantime, the vast yet increasing volume of text makes it impossible to analyze manually. Text mining is a powerful tool to automatically analyze large-scaled texts and generate insights from the texts. However, many educational…

Background: Intercoder reliability is a statistic commonly reported by researchers to demonstrate the rigour of coding procedures during data analysis. Its importance is debatable in the analysis of qualitative interview data. It raises a question on whether researchers should identify the same codes and themes in a transcript or they should…

To examine the similarities and differences between two closely related yet distinct fields -- Educational Data Mining (EDM) and Learning Analytics (LA) -- this study conducted a literature review of the empirical studies published in both fields. We synthesized 492 LA and 194 EDM articles published during 2015-2019. We compared the similarities…

Drawing on insights from philosophy and theology, we explore the relationship between religion, data and global education policy through an analysis of the career of Sir Michael Barber, widely regarded as an authority on the reform of public services and an influential policy entrepreneur. The analysis provides a novel perspective which…

The perceived importance of data in society has led to a surge in interest towards data science education. This article seeks to build on existing literature concerned with the sociopolitical, cultural, and ethical dimensions of data science education by considering the salience of two interrelated concepts discussed in Asian and Asian American…

Agent-based models (ABMs) often rely on psychometric constructs such as 'opinions', 'stubbornness', 'happiness', etc. The measurement process for these constructs is quite different from the one used in physics as there is no standardized unit of measurement for opinion or happiness. Consequently, measurements are usually affected by 'psychometric…

Data mining approaches have been widely used to estimate student performance in online education. Various Machine Learning (ML) based data mining techniques have been developed to evaluate student performance accurately. However, they face specific issues in implementation. Hence, a novel hybrid Elman Neural with Apriori Mining (ENAM) approach was…

This article aims to clarify fundamental aspects of the process of assigning fuzzy scores to conditions based on family resemblance (FR) structures by considering prototype and set theories. Prototype theory and set theory consider FR structures from two different angles. Specifically, set theory links the conceptualization of FR to the idea of…

State postsecondary education data systems are vital assets for policymakers, researchers, and the public. The State Higher Education Executive Officers Association's (SHEEO) Communities of Practice project builds upon SHEEO's efforts to measure the capacity and effective use of state postsecondary data systems and provides states with…

Implementing supported and customized employment in all their components is essential for supporting job seekers with disabilities to achieve their career goals. We asked 42 employment consultants in nine employment programs to respond daily to three quick questions about their employment support activities, for 6 months. Through monthly coaching,…