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…

Curriculum maps have long served as useful guides in the careful design of a curriculum's pedagogical aims and where they are to be achieved, however such a map cannot indicate how students are actually moving through the curriculum. This article discusses traffic models. When employed in the study of courses drawn from multiple departments,…

We provide an overview of existing and emerging ways that institutional researchers can leverage National Student Clearinghouse data to expand a culture of data-driven decision-making across campus, with a focus on examples from the field.

As technology has become ubiquitous in learning contexts, there has been an explosion in the amount of learning data. This creates opportunities to draw on the decades of learner modelling research from Artificial Intelligence in Education and more recent research on Personal Informatics. We use these bodies of research to introduce a conceptual…

This response to Neil Selwyn's paper, 'What's the problem with learning analytics?', relates his work to the ethical challenges associated with learning analytics and proposes six ethical challenges for the field.

Cronbach's alpha is the most frequently used measure to investigate the reliability of measurement instruments. Despite its frequent use, many warn for misinterpretations of alpha. These claims about regular misunderstandings, however, are not based on empirical data. To understand how common such beliefs are, we conducted a survey study to test…

Cohen's kappa coefficient is commonly used for assessing agreement between classifications of two raters on a nominal scale. Three variants of Cohen's kappa that can handle missing data are presented. Data are considered missing if one or both ratings of a unit are missing. We study how well the variants estimate the kappa value for complete data…

Past research indicates that individuals respond adaptively to contextual factors in multiattribute choice tasks. Yet it remains unclear how this adaptation is cognitively governed. In this article, empirically testable implementations of two prominent competing theoretical frameworks are developed and compared across two multiattribute choice…

In the changing landscape of libraries and the roles of librarians, the area of Research Data Management (RDM) is emerging with new opportunities and challenges. This literature review identifies the current levels of publication that deal with the relationship of the librarian and their role in the research data management process and provides an…

In fiscal year 2017, The Ohio State University Libraries in Columbus piloted the purchase of research data sets to explore how to integrate this format into the standard workflows of the collections strategist and electronic resources officer. The pilot project had few restrictions except that one-time money must be used and purchases must be…