The purpose of this study is to examine the effect of randomized versus nonrandomized data using an Excel case study project to measure students' academic performance. Specifically, the study examines whether randomized data strengthens students' analytical, problem-solving, and Excel skills while manipulating and analyzing accounting data. The…

The Welsh Baccalaureate qualification has been adopted by most secondary schools within Wales. In years 12 and 13 (ages 16-18), 50% of the qualification requires students to collect primary data and also conduct secondary data analysis to write a 5000 word investigative report. To help teachers develop effective teaching strategies and resources,…

It is important for policymakers and managers of higher education institutions knowing how well their universities are operating. This article aimed to show that data envelopment analysis (DEA) can be an excellent benchmarking instrument in higher education. First, by using several inputs and outputs at the institutional level, DEA can identify…

This article is the third installment in a series regarding the conduct, dissemination, and consumption of large-scale secondary research. See Part 1 on conducting secondary analysis (Sullivan et al., 2020) (EJ1239445) and Part 2 on practitioners' use of this research (Kulkarni et al., 2020) (EJ1248185). The purpose in this final installment is to…

States' commitments to tackling long standing inequities have been stifled by missing data, long delays, insufficient data-analysis tools, and the excessive reporting burden placed on states and institutions. If states hope to achieve their completion and equity goals, they need access to data that does not leave them guessing--so they can…

We introduce DeepPerfEmb, or DPE, a new deep-learning model that captures dense representations of students' online behaviour and meta-data about students and educational content. The model uses these representations to predict student performance. We evaluate DPE on standard datasets from the literature, showing superior performance to the…

Effectively estimating student enrollment and recruiting students is critical to the success of any university. However, despite having an abundance of data and researchers at the forefront of data science, traditional universities are not fully leveraging machine learning and data mining approaches to improve their enrollment management…

Massive online Open Courses (MOOCs) make extensive use of videos. Students interact with them by pausing, seeking forward or backward, replaying segments, etc. We can reasonably assume that students have different patterns of video interactions, but it remains hard to compare student video interactions. Some methods were developed, such as Markov…

Purpose: This report highlights ways in which race-based data can be used to combat systemic racism in matters relating to academic and non-academic and student misconduct. Methods: Information synthesis of available information relating to race-based data and student conduct. Results: A summary and synthesis of how and why race-based data can be…

The purpose of this study was to evaluate the relationship of pre-entrance factors and the success of students in an Associate of Applied Science (A.A.S.) degree nursing program at a community college in East Tennessee. The criterion variable was success in the nursing program. Success was defined as academic success in all nursing courses and…

This article demonstrates how a digital environment offers new opportunities for transforming qualitative data into quantitative data in order to use data mining and information visualization for mixed methods research. The digital approach to mixed methods research is illustrated by a framework which combines qualitative methods of multimodal…

Purpose: The primary goal of this commentary was to consider the future directions that researchers dealing with levels and regulation of strategies and with approaches to learning may wish to pursue in the years to come. Procedure: In order to accomplish this goal, the first step was to look for any common ground shared by authors contributing to…

In 2012, this author published a paper describing a method for using the raw data from Web of Science to examine the journals cited by any given group of researchers and then compare that list to lists of 'top journals' of similar disciplines. It was not a straightforward method to use and required a great deal of effort and spreadsheet work by a…

This article presents the use of the qualitative research method and the challenges that this form of research imposes along with the increasingly systematic reluctance experienced by doctoral students and their chairs. Increasingly, doctoral students are opting for the qualitative approach over that of the traditional quantitative methodology.…

Learning Analytics (LA) is an emerging field in which sophisticated analytic tools are used to improve learning and education. It draws from, and is closely tied to, a series of other fields of study like business intelligence, web analytics, academic analytics, educational data mining, and action analytics. The main objective of this research…