The accounting profession is undergoing a radical change that supplants many historical accounting duties by requiring technical skills to be added to the accountant's tool chest. Stakeholders are increasingly adopting disruptive technologies, including data analytics, blockchain, artificial intelligence, and cloud computing. We reviewed 185…

Visual analysis is the predominant method of analysis in single-case research (SCR). However, most research suggests that agreement between visual analysts is poor, which may be due to a lack of clear guidelines and criteria for visual analysis, as well as variability in how individuals are trained. We developed a survey containing questions about…

Statistical Analysis Software (SAS) is a widely used tool for data management analysis across a variety of fields. The procedure for item response theory (PROC IRT) is one to perform unidimensional and multidimensional item response theory (IRT) analysis for dichotomous and polytomous data. This review provides a summary of the features of PROC…

Purpose: The analysis of Ecological Momentary Assessment (EMA) data can be difficult to conceptualize due to the complexity of how the data are collected. The goal of this tutorial is to provide an overview of statistical considerations for analyzing observational data arising from EMA studies. Method: EMA data are collected in a variety of ways,…

The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery (SD) approach based on MapReduce. The proposed SD approach, which is an extension of the well-known FP-Growth algorithm, considers emerging parallel methodologies like MapReduce to be able to cope…

The nature of teaching and learning has evolved over the years, especially as technology has evolved. Innovative application of educational analytics has gained momentum. Indeed, predictive analytics have become increasingly salient in education. Considering the prevalence of learner-system interaction data and the potential value of such data, it…

This paper showcases how a reflexive practice, that includes arts-based activities, deepened understandings experienced by a doctoral student of psychology while completing the data analysis section of a metasynthesis. The metasynthesis focused on qualitative studies, examining the mental and spiritual care of persons living with diabetic foot…

This article presents a project that uses a business context to introduce students to a multiphase approach to analytics while relying primarily on an introductory Excel course for prerequisite knowledge. A range of analytics techniques--including Excel Pivot tables and charts, regression trend lines, and linear programming--are combined into an…

Educational institutions are creating a considerable amount of data regarding students, faculty and related organs. This data is an essential asset for academic institutions as it has valuable insights, knowledge and intelligence for the policymakers. Students are the fundamental entities and primary source of data creation in any educational…

With the prevalence of missing data in social science research, it is necessary to use methods for handling missing data. One framework in which data with missing values can still be used for parameter estimation is the Bayesian framework. In this tutorial, different missing data mechanisms including Missing Completely at Random, Missing at…

Education has been one of the areas most affected by the consequences of the COVID-19 pandemic since December 2019. This bibliometric review presents "the big picture" of the knowledge production on educational research conducted between January 1, 2020, and October 31, 2021. For this purpose, the current status of the related knowledge…

Introduction: Interrupted Time Series (ITS) studies may be used to assess the impact of an interruption, such as an intervention or exposure. The data from such studies are particularly amenable to visual display and, when clearly depicted, can readily show the short- and long-term impact of an interruption. Further, well-constructed graphs allow…

Diagnostic test accuracy (DTA) systematic reviews are conducted to summarize evidence on the accuracy of a diagnostic test including a critical evaluation of the primary studies. Where appropriate, the evidence is meta-analyzed to obtain pooled estimates of effectiveness. In this study, we reviewed and critiqued three DTA guidance documents with…

The purpose of this research note is to introduce a latent growth curve reconstruction approach based on the Tabu search algorithm. The approach algorithmically enables researchers to optimally determine at both the individual and the group levels the order of the polynomial needed to represent the latent growth curve model. The procedure is…

This paper presents the R Analyzer for Large-Scale Assessments (RALSA), a newly developed R package for analyzing data from studies using complex sampling and assessment designs. Such studies are, for example, the IEA's Trends in International Mathematics and Science Study and the OECD's Programme for International Student Assessment. The package…