After being sued for inequity and inadequacy in school funding, many states in the US have reformed their education aid formulas but have still faced many criticisms. Using Connecticut as an example, this paper shows how to design a more equitable and adequate aid formula with tools to win broad support from communities and lawmakers. It develops…

Educational data science is an emerging transdisciplinary field formed from an amalgamation of data science and elements of biological, psychological and neuroscientific knowledge about learning, or learning science. This article conceptualises educational data science as a biopolitical strategy focused on the evaluation and management of the…

With the development of online learning, LMSs accumulated huge amounts of students' interaction data. Unfortunately, with the support of LMSs data, few researchers put a sight on interaction research in MPOCs. Particularly, comparing interaction activity patterns of different achievement student groups and in different course processes in MPOCs…

There has been an ongoing debate of which physical labs or virtual labs are better. To resolve this issue, a remote lab provides an online lab that can do real experiments to obtain real data from a distant physical lab. Instead of relying on a remote lab, this article suggests that students collect experimental data locally with low-cost data…

This thematic content analysis done about teaching biotechnology which is researched in Turkey is conducted with 64 articles, from a total of 45 magazines published in Turkey from 2003 to 2018. An analysis of the research trends of Turkish researchers based on teaching biotechnology. In this research, it has been tried to guide the researchers by…

As organizations become increasingly dependent on marketing analytics, universities are adapting their curricula to equip students with skills necessary to operate in data-rich environments. We describe six competencies that students need to become proficient with analytics: (1) assessing data quality, (2) understanding measurement, (3) managing…

We examine the American landscape of higher education quantitative research concerning how gender and sex demographic information is collected. We use a directed content analysis to examine the prevalence and operationalization of gender and sex among widely used higher education survey instruments. Our findings illuminate a seemingly haphazard…

Blended learning (BL) is a popular e-Learning model in higher education that has the potential to take advantage of learning analytics (LA) to support student learning. This study utilized LA to investigate fourth-year undergraduates' (n = 157) use of self-regulated learning (SRL) within the online components of a previously unexamined BL…

This feature focuses on the five areas an institution needs to know before implementing holistic measures. These include: what does a holistic review entail, how to be legally complaint, Sedlacek's noncognitive variables, applying student success measures, and the vital importance of training.

Approaches to synthesizing qualitative data have, to date, largely focused on integrating the findings from published reports. However, developments in text mining software offer the potential for efficient analysis of large pooled primary qualitative datasets. This case study aimed to (a) provide a step-by-step guide to using one software…

This study compared the quality of survey data collected from Mechanical Turk (MTurk) workers and college students. Three groups of participants completed the same survey. "MTurk" respondents completed the survey as paid workers using the Mechanical Turk crowdsourcing platform. "Student Online" respondents also completed the…

In the domain of programming, a growing number of algorithms automatically generate data-driven, next-step hints that suggest how students should edit their code to resolve errors and make progress. While these hints have the potential to improve learning if done well, few evaluations have directly assessed or compared the quality of different…

Reporting requirements for capturing data on the delivery of Supplemental Nutrition Assistance Program Education (SNAP-Ed) have evolved. University of Minnesota (U of M) Extension developed the SNAP Education Evaluation and Database System (SEEDS) to capture unduplicated participant information for SNAP-Ed programming conducted by U of M Extension…

"Data science" is a discipline that provides principles, methodology, and guidelines for the analysis of data for tools, values, or insights. Driven by a huge workforce demand, many academic institutions have started to offer degrees in data science, with many at the graduate, and a few at the undergraduate level. Curricula may differ at…

Many empirical economists say that the teaching of econometrics is unbalanced, and students are not well-prepared for the serious problems they will encounter with real data. Here, the author considers the problem of noisy data, which is present in most econometric studies, but receives far too little attention. Most econometric studies are done…