This research study provides an examination of the relatively new fields of Data Analytics and Data Science. We compare word rates in Data Analytics and Data Science documents to determine which concepts are mentioned most often. The most frequent concept in both fields is "data." The word rate for "data" is more than twice the…

Mixed methods, cross-cultural designs are a special case of the more general, mixed methods between-groups designs. The defining feature of mixed methods is the principled integration of qualitative and quantitative approaches, and cross-cultural comparison is premised on the systematic collection and analysis of data from two or more cultural…

Latent change score models (LCSMs) proposed by McArdle (McArdle, 2000, 2009; McArdle & Nesselroade, 1994) offer a powerful tool for longitudinal data analysis. They are becoming increasingly popular in social and behavioral research (e.g., Gerstorf et al., 2007; Ghisletta & Lindenberger, 2005; King et al., 2006; Raz et al., 2008). Although…

Purpose: From the standpoint of a novice researcher, the author has examined how blogging as a literacy practice enables one to explore and understand self in relation to analysing data and making meaning. The purpose of this paper is to discuss how blogging can be used as a reflective and critical tool and explore the notion of blogging as…

Educational Data Mining (EDM) is an important tool in the field of classification of educational data that helps researchers and education planners analyse and model available educational data for specific needs such as developing educational strategies. Trends International Mathematics and Science Study (TIMSS) which is a notable study in…

As we become increasingly acquainted with the rich opportunities that analytics systems can provide, there is a commensurate need to consider the extent to which analytics tools are effectively integrated, with proper training, into the day-to-day functioning of higher education professionals. This chapter explores the extent to which predictive…

The primary objective of the study is to examine the level of awareness and usage of data triangulation among under and post graduates in the tertiary institution. A descriptive survey was adopted and data collected from a sample of 114 selected randomly. A self-developed and validated instrument was used to collect data. Data collected were…

Multiple imputation is a popular method for addressing data that are presumed to be missing at random. To obtain accurate results, one's imputation model must be congenial to (appropriate for) one's intended analysis model. This article reviews and demonstrates two recent software packages, Blimp and jomo, to multiply impute data in a manner…

Dual enrollment is a complex policy issue and is increasingly of interest to state policymakers. Adequate data and data systems are critical to informing dual enrollment policy, yet the data at the federal level and many state data systems suffer from common challenges and lack the capacity to address dual enrollment policy. We review the…

Most literature related to Benford's Law discusses what the law can be used for and how it works but fails to address effective methods and procedures for teaching the law to students. This article examines existing information resources to determine the most effective methods and procedures used to explain this Law to those who have no experience…

The challenge in data analysis often lies in accounting for the multidimensionality and complexity of the data while simultaneously discovering patterns. Integrating and consolidating different types of data during analysis can broaden the perspective and permit obtaining complementary views. This methodological research study on data collection…

This editorial introduces a special section of the "Journal of Learning Analytics," for which Neil Selwyn's keynote address to LAK '18 has been written up as an article, "What's the problem with learning analytics?" His claims and arguments are engaged in commentaries from Alfred Essa, Rebecca Ferguson, Paul Prinsloo, and…

Analysis of keystroke logging data is of increasing interest, as evident from a substantial amount of recent research on the topic. Some of the research on keystroke logging data has focused on the prediction of essay scores from keystroke logging features, but linear regression is the only prediction method that has been used in this research.…

Activity Theory (AT) is increasingly employed as a lens to guide data analysis in information systems (IS) studies. The theory is also applied to assess and evaluate information systems and technologies (IS/IT) in organisations. Even though its popularity continues to increase in both business and academic domains, there is no formal or assessment…

Scores estimated from multidimensional item response theory (IRT) models are not necessarily comparable across dimensions. In this article, the concept of aligned dimensions is formalized in the context of Rasch models, and two methods are described--delta dimensional alignment (DDA) and logistic regression alignment (LRA)--to transform estimated…