This paper demonstrates a dynamic, collaborative, and dialogic strategy for guiding students (and experienced researcher teams) through rudimentary forms of visual analysis using draw-and-write datasets. The approach identifies five sequential stages of the visual analysis process and further delineates twenty activities therein. Akin to the…

Understanding human judgement and decision making during visual inspection of data is of both practical and theoretical interest. While visualizing data is a commonly employed mechanism to support complex cognitive processes such as inference, judgement, and decision making, the process of supporting and scaffolding cognition through effective…

In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…

This chapter identifies some of the challenges surrounding data collection and analysis regarding development students, including testing and identifying academic needs, placement determination, and measuring student outcomes.

This dissertation explores the use of Customer Relationship Management (CRM) technologies and processes in a large Midwestern undergraduate public Institution of Higher Education. CRM systems and processes have operated in business and industry for some time, but only more recently are CRM systems being adopted and used for undergraduate student…

This report presents school-level finance data on expenditures by function from the School-Level Finance Survey (SLFS). The SLFS is an extension of two existing collections being conducted by the National Center for Education Statistics (NCES) in collaboration with the Census Bureau: the School District Finance Survey (F-33) and the state-level…

Qualitative classroom data from video recordings and students' written work can play important roles in improving mathematics instruction. In order to take full advantage of these data sources, it is helpful to have a strong analytic lens to orient one's reflections on the data. One promising analytic lens is the National Research Council's five…

Programmatic text analysis can be used to understand patterns and reveal trends in data that would otherwise be difficult or impossible to uncover with manual coding methods. This work uses programmatic text analysis, specifically term frequency counts, to study nearly 10,000 chemistry thesis and dissertation titles from 1911-2015. The thesis and…

These pages aim to explain and interpret why the late Mika Seppälä, a conformal geometer, proposed to model student study behaviour using concepts from conformal geometry, such as Riemann surfaces and Strebel differentials. Over many years Mika Seppälä taught online calculus courses to students at Florida State University in the United States, as…

Scholarly personal narrative (SPN) extends the available methodologies by which researchers conduct the Scholarship of Teaching and Learning (SoTL). In this article, the authors define SPN, which interprets personal experience through scholarly frameworks, leveraging the power of reflective practice to understand the interpersonal dynamics of both…

This paper presents a critical analysis, from the point of view of a statistician, of the methodology used by Hattie in "Visible Learning," and explains why it must absolutely be called pseudoscience. We first discuss what appears to be the intentions of Hattie's approach. Then we describe the major mistakes in "Visible…

Quality in higher education is an attractive and important field not only for higher education institutions but also for their stakeholders. However, the research field is very complex due to the overlapping and interlinking of its topics. Over the years, an enormous amount of studies has been devoted to exploring different topics. Nevertheless,…

Inherent in applied developmental sciences is the threat to validity and generalizability due to missing data as a result of participant drop-out. The current paper provides an overview of how attrition should be reported, which tests can examine the potential of bias due to attrition (e.g., t-tests, logistic regression, Little's MCAR test,…

Polar coordinate analysis is a powerful data reduction technique based on the Zsum statistic, which is calculated from adjusted residuals obtained by lag sequential analysis. Its use has been greatly simplified since the addition of a module in the free software program HOISAN for performing the necessary computations and producing…

Exposing eLearning objects on the Web of Data leads to sharing and reusing of educational resources and improves the interoperability of data on the Web. Furthermore, it enriches e-learning content, as it is connected to other valuable resources using the Linked Data principles. This paper describes a study performed on the Organic.Edunet…