Analyses of student data in post-secondary education should be sensitive to the fact that there are many different topics of study. These different areas will interest different kinds of students, and entail different experiences and learning activities. However, it can be challenging to identify the distinct academic themes that students might…

The usage of data mining has dramatically increased over the past few years and the education sector is leveraging this field in order to analyze and gain intuitive knowledge in terms of the vast accumulated data within its confines. The primary objective of this study is to compare the results of different classification techniques such as Naïve…

Attributes of teaching and learning contexts provide rich information about how students participate in learning activities. By tracking and analyzing snapshots of these attributes captured continuously throughout the duration of the learning activities, teachers can identify individual students who need special attention and apply different…

Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…

The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In this paper, we present three attempts to improve upon current affect detectors. The first…

Introduction: Star and Bowker describe the residual as what does not fit into a category system and as an inevitable byproduct of classification. In this project, we explore what happens when we attempt to give prominence to the residual instead of minimizing it. Methods: The three authors created three "transformations" of a small…

The monitoring and support of university freshmen is considered very important at many educational institutions. In this paper we describe the results of the educational data mining case study aimed at predicting the Electrical Engineering (EE) students drop out after the first semester of their studies or even before they enter the study program…

This paper concerns the construction of a bibliography of written materials about Aboriginal science and technology drawn from books, theses, dissertations, scientific and non-scientific journals, conference papers and newspapers etc: in fact, articles about the science and technology that relate in some way to Aborigines, from whatever source,…

Professionals responsible for educational research, evaluation, and statistics have sought to provide timely and useful information to decision makers. Regardless of the evaluation model, research design, or statistical methodology employed, informing the decision making process with quality, reliable data is a basic goal. The definition of…

Describes a preliminary research project that applies Personal Construct Theory to user perceptions of photographs. While some problems associated with Repertory Grids for subject content analysis are identified, findings indicate they provide a useful method for collecting unbiased data about what users see in visual images and for comparing user…

This paper reviews objectives, methodology, and data analysis procedures of a study concerning educational innovation. This research, part of the Procedures for Adopting Educational Innovations (PAEI) Program at the University of Texas at Austin, was undertaken to study interventions and their effects. It was considered a first step in determining…

This paper discusses the policy environment in which data on race and ethnicity of college applicants are collected through a history of the federal collection of racial data, the current status of racial data collection, and the processes that led to current and proposed data collection requirements. The impact of recent changes in reporting…

Q-technique factor analysis identifies clusters or factors of people, rather than of variables, and has proven very popular, especially with regard to testing typology theories. The present study investigated the utility of three different protocols for obtaining data for Q-technique studies. These three protocols were: (1) a conventional ipsative…

The Milwaukee (Wisconsin) Public Schools (MPS) recently implemented a new, state-designed accounting system, called the Wisconsin Elementary and Secondary School Accounting System (WESSAS), based on guidelines proposed in the U.S. Office of Education's Handbook II. This report describes and discusses that implementation and provides numerous…