Using Bad News to Make Good Decisions

Along the way, a number of personnel, organizational, and technical problems were encountered, and many were resolved. What did became clear is that using data to inform decision making is an evolving process that can provide a solid basis for continuous program improvements.

A Case Study

We know that a nationwide shortage of highly qualified teachers exists, and not enough people are becoming teachers. We also know there are increasing demands for institutions to demonstrate a system of accountability through program assessment. As stated by the State Higher Education Executive Officers (2005), “The National Commission on Accountability in Higher Education believes improved accountability for better results is imperative, but how to improve accountability in higher education is not so obvious” (p. 4). Also, many teacher preparation programs are not accredited, and of the 1,300 teacher preparation programs that existed in 1999, only 38 percent were accredited through the National Council for the Accreditation of Teacher Education (NCATE) (The CEO Forum on Education & Technology, 2000, p. 3). While examining the effectiveness of the Teacher Education program assessment at the case institution, three convergent themes emerged.

Institutional Research Using Data Mining

The aim of this chapter is to explore the application of data mining for analyzing academic performance in connection with the participatory behavior of the students enrolled in an online two-year Master degree program in project management. The main data sources were the operational database with the students’ records and the log files and statistics provided by the e-learning platform. One hundred eighty-one enrolled students, and more than 150 distinct characteristics/ variables per student were used. Due to the large number of variables, an exploratory data analysis through data mining was chosen, and a model-based discovery approach was designed and executed in Weka environment. The association rules, clustering, and classification were applied in order to identify the factors explaining the students’ performance and the relationship between academic performance and behavior in the virtual learning environment. Data mining has revealed interesting patterns in data. These patterns indicate that academic performance is related to the intensity of the student activities in virtual environment. If the student understands how to work and she/he is motivated to communicate with others, then he might have a good academic performance. Based on clustering analysis, different student profiles were discovered, explaining the academic performance. The results are very encouraging and suggest several future developments.

The Dean of Information

The author focuses on the institutional researcher as an institutional leader, over and above providing traditional reporting and support. IR practitioners hold authority over the institution’s data. Leadership and social psychological theory can explain their effectiveness. The author combines effective leadership theory with the Theory of Planned Behavior to produce framework for IR leadership. This framework should help the IR professional be more than a data custodian. It should help the IR professional adopt both a transformative and facilitative leadership stance as needed, in order to help the institution reach its goals.

Measuring Diversity at a Historically Black College of Dentistry

There are several excellent indices available to quantify diversity within a student body. Richness and evenness can be studied using Simpson’s Index with its associated Reciprocal Index, and with Shannon-Weiner’s Index “H” and Index “E”. Lieberson provides the means to measure isolation and interaction, and Dissimilarity works well to identify segregated communities. Results using these indices show that the Historically Black College of Dentistry is a culturally vibrant and diverse academic and social environment. White students at the Historically Black College of Dentistry are more likely to enjoy interaction with other Whites than will Historically Black and Hispanic students at all other dental schools, except at the other Medical College, the only other HBCU with a dental school. Overall, there was no statistical diversity difference between the Historically Black College of Dentistry and all other dental schools over the 10 year study period. Statistically significant correlations between each index provided a framework for using each index in prediction modeling. Recent methods to manage multi-collinearity, such as extracting unstandardized residuals to use as adjusted coefficients add promise that all indices can be used in future diversity studies.

Developing a Quality Distance Learning Program in a Comprehensive Community College

Community colleges offer a variety of distance learning opportunities and continue to invest in technologies that better serve their students. This case study focuses on the experiences of Big State Community College and its progression from a few faculty teaching online courses to a distance learning program that supports greater than 25% of institutional enrollments. It explores the challenges of ensuring that Big State Community College’s evolving distance learning program promotes student success and is of a quality that reflects positively on the institution.

Using Geospatial Information Systems for Strategic Planning and Institutional Research

This chapter will address the use of Geospatial Information Systems (GIS) for institutional research and strategic planning departments. Throughout the chapter GIS will be examined for its applied purposes as well as answering basic research questions. This chapter will provide examples on how GIS can be used to answer certain questions and provide analysis to research. By using GIS, institutional research and strategic planning offices can use location as a variable to obtain answers on certain types of questions that can be useful to university administrators and government officials attempting to construct policies and procedures for their institutions. GIS can also be used by institutional research and strategic planning departments for requests from upper administrators in colleges and universities as well as external requests.

African Americans and Planned Resilience

The purpose of the current study is to examine secondary school factors that predict the performance and persistence of African American students at postsecondary institutions. Ajzen’s (1991) Theory of Planned Behavior (TPB), used as the theoretical framework of this study, suggests that intentions, driven by attitudes and beliefs, can predict behavior. This theory was adapted to include resilience, a theory that focuses on student assets, rather than deficits. This theory focuses on how children overcome risk factors like poverty and poor schools to reach agreed upon measures of success.

A Million Ghosts

On the surface, West Point’s long line of cadet moral development may not seem obvious. Perhaps notable alumni, its history in educating engineers, or maybe even its architecture are commonly thought of first. However, upon closer examination and consideration of the Academy’s dynamic curricular and extracurricular structure we find, throughout its history, that the moral and character education and development of its cadets is the foundation upon which engineers are taught and buildings are constructed.

Principles for the Analysis of Large Complex Secondary Databases in Educational Settings

A primary feature of institutional research work is prediction. When statistics are used as the primary analysis tool, much of this work depends upon ordinary least squares regression, which assumes that data have one level. However, much of the data in educational research, in general, and in higher education research, in particular, is multilevel or nested. This chapter explores multilevel data analysis, with a focus on exploring issues associated with sampling, weighting, design effects, and analysis of data. Additionally, it emphasizes the importance of considering contextual effects using as a reference large secondary datasets. The chapter will also explore opportunities and challenges presented by these types of data.