Clustering of educational data allows similar students to be grouped, in either crisp or fuzzy sets, based on their similarities. Standard approaches are well suited to identifying common student behaviors; however, by design, they put much less emphasis on less common behaviors or outliers. The approach presented in this paper employs fuzzing…

In this research, a combination of both quantitative and qualitative approaches is used to identify different market segments in the education industry. To solve the research problem, an exploratory approach to data mining is used and, using a series of interviews with experts, the factors affecting segmentation are identified. Then, using the…

Post-secondary education is expected to substantially contribute to the cognitive growth and professional achievement of students studying science, technology, engineering, and mathematics (STEM). Yet, there is limited understanding of how students studying STEM develop a professional identity. We used the lens of self-authorship to develop a…

User clustering algorithms have been introduced to analyze users' learning behaviors and help to provide personalized learning guides in traditional Web-based learning systems. However, the explicit and implicit coupled interactions, which means the correlations between user attributes generated from learning actions, are not considered in these…

Today Learning Management Systems (LMS) have become an integral part of learning mechanism of both learning institutes and industry. A Learning Object (LO) can be one of the atomic components of LMS. A large amount of research is conducted into identifying benchmarks for creating Learning Objects. Some of the major concerns associated with LO are…

Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…

Extension professionals often assess community needs to determine programs and target audiences. Data can be collected through surveys, focus group and individual interviews, meta-analysis, systematic observation, and other methods. Knowledge gaps are identified, and programs are designed to resolve the deficiencies. However, do Extension…

New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…

Mixed-format assessments are increasingly being used in large scale standardized assessments to measure a continuum of skills ranging from basic recall to higher order thinking skills. These assessments are usually comprised of a combination of (a) multiple-choice items which can be efficiently scored, have stable psychometric properties, and…

Annual "Profiles" reports are comprehensive digests of data on education management organizations. Analysis and interpretation of the data in this report are, for the most part, limited to describing general trends over time. The report is intended for a broad audience. Policymakers, educators, school district officials, and school board…

Surveillance video recording is becoming ubiquitous in daily life for public areas such as supermarkets, banks, and airports. The rate at which surveillance video is being generated has accelerated demand for machine understanding to enable better content-based search capabilities. Analyzing human activity is one of the key tasks to understand and…

In this paper, we present a data-based user modeling framework that uses both unsupervised and supervised classification to build student models for exploratory learning environments. We apply the framework to build student models for two different learning environments and using two different data sources (logged interface and eye-tracking data).…

A description is given of a general method for studying partitions. The main focus is with the analysis of relationships among several different partitions of the same items for the explorations as well as confirmation of structural relationships. A partition is defined as a set of mutually exclusive clusters of items; however, this paper deals…

This paper focuses on firm behaviour within business clusters and cluster-type environments. Using survey data to distinguish cluster members by the perceived degree of participation, the authors categorize them as leading, proactive or reactive players. They then examine the clustering behaviour of each of these categories. They find that (a)…

Compares two basic variants of the sorting method: single-sort and multiple sort. The nature of individual differences in sorting, as well as sex differences, were also investigated. Stimulus materials were the 15 mutually exclusive kinship terms selected by Wallace and Atkins (1960). (RC)