This study investigated pre-service mathematics teachers' (PST), who are going to teach middle grade mathematics (grade 5-8), understanding of inclusion relationships of quadrilaterals. In addition to describing PSTs' understanding of inclusion relations of quadrilaterals; it was also aimed to document the development of PSTs' understanding of…

This study examined how teachers read cases in a professional development academy for reading teachers. It drew on reading theory, particularly Tierney and Pearson's (1981) work on "text-based" and "reader-based" readings of traditional print-based text, to analyze conversations about cases where a specific focus on pedagogical…

Purpose of the Study: Missing data are a common problem encountered while implementing measurement instruments. Yet the extent to which reliability, validity, average discrimination and difficulty of the test results are affected by the missing data has not been studied much. Since it is inevitable that missing data have an impact on the…

Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a model based on temporal relationships of heterogeneous data as the basis for building predictive models. We show how within- and between-semester temporal patterns can provide insight into the…

School discipline and school safety are primary areas of concern for school administrators. This article summarizes the research literature regarding suspension in response to nonviolent and subjective offenses for racial/ethnic minorities. Steps that administrators can follow in applying a root cause analysis with a focus on school practices are…

We propose a general cognitive diagnosis model framework to diagnose mental disorders using item scores obtained from clinical measurement instruments. This framework can be used to validate the extent to which the items measure the specific disorders. The method is illustrated using data obtained with the Dutch version of Millon Clinical…

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…

Current developments in the statistics community suggest that modern statistics education should be structured holistically, that is, by allowing students to work with real data and to answer concrete statistical questions, but also by educating them about alternative frameworks, such as Bayesian inference. In this article, we describe how we…

The allocation of merit-based awards and need-based aid is important to both universities and students who wish to attend the universities. Current approaches tend to consider only institution-centric objectives (e.g. enrollment, revenue) and neglect student-centric objectives in their formulations of the problem. There is lack of consideration to…

Data Mining (DM) is one of the most offered courses in data analytics education. However, the design and delivery of DM courses present a number of challenges and issues that stem from the DM's interdisciplinary nature and the industry expectations to generate a broader range of skills from the analytics programs. In this research, we identified…