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This working paper, part of an ongoing national study, presents preliminary analysis of public service professionalism among state public administrators in many states on the basis of data already produced by a continuing survey research project. Information about the data source and sample profiles are provided. Additionally, the research objectives for the paper are listed, and the questionnaire that was used to assess the research objectives is provided. The paper addresses the following questions: (1) What are the public service value orientations of MPA (Masters in Public Administration) and CPM (Certified Public Administration) graduates who are currently employed as state administrators? (2) What are the professional behavioral dimensions of these administrators? (3) What are the orientations of these administrators toward public Administration education? and (4) Do administrators with MPA/CPM education significantly differ from state administrators without compatible training/education? Results of the analyses are reported under the following headings: Value Orientations of MPA and CPM Graduates; Professional Behavioral Attributes among MPA and CPM Graduates; Public Administration Professionalism among MPA and CPM Graduates; and the Differences between the General Sample, MPA, and CPM Graduates. Contains 21 tables and 105 references. (GLR)

This qualitative study attempted to answer the question of what constitutes a collegial environment. New faculty members (N=258) at five institutions were surveyed and 92 new faculty were interviewed. The study utilized a methodology of quantifying data from interviews, the Rasch analytic technique, in which the definition of collegiality was separated from the rating of how collegial an environment was considered to be, thereby providing a common definition of collegiality on which faculty could rate their institutions. The study found that no respondents rated their institutions as uncollegial, a few rated them as very collegial and most rated them as average. The characteristic of whether new or other faculty initiated interactions was not perceived as related to collegiality. No gender differences in perceived collegiality were found. By rank, instructors and new faculty at institutions with no ranks rank rated their institutions as more collegial than those who were either tenured on the tenure track. New faculty at 2-year institutions rated their institutions as more collegial than those at 4-year institutions. The collegial environment was characterized by intellectual support and a sense of community, with support of new faculty's scholarly endeavors and reciprocal interactions between faculty members. (PRW)

This paper considers the feasibility of linking a student data sample with the Schools and Staffing Survey (SASS) teacher and administrative data. The National Center for Education Statistics (NCES) has from time to time considered linking their student-based elementary and secondary surveys to the school- and teacher-based surveys. Speculation on the feasibility of linking datasets is of particular importance in the current climate of budgetary constraints and distrust of federal data collection. The rationale for linking a student data collection in SASS is discussed, and some options for collecting these data are explored, whether linking the National Assessment of Educational Progress to the SASS or linking a new National Education Longitudinal Study with SASS. The argument for attaching a longitudinal component to the SASS response rests on several premises. Doing this could measure the types of student data deemed most worthwhile, while satisfying the two criteria for sensible merger: producing some cost benefit and engendering an analytical payoff. Of the various options available, merging a new National Education Longitudinal Study and the SASS provides the most benefit to the whole educational policy community. (Contains six references.) (SLD)

This report presents an investigation by the American College Testing Program (ACT) of an alternative design for the National Assessment of Educational Progress (NAEP). The proposed design greatly simplifies the data collection and analysis procedures needed to produce assessment results and has the potential to produce results that are more timely and easier to interpret. The plan calls for developing individual NAEP forms, where each individual form represents, as closely as possible, the assessment questions from the domain of knowledge being measured by an NAEP construct. Sets of these forms could be administered, in random order, to students in the schools. This would replace the balanced incomplete block design (BIB) currently used. Assessments constructed under the BIB design do not closely represent, at least for the 1996 science assessment, the content framework. Enhanced procedures are also suggested for developing precise content and statistical specifications for individual forms and procedures for pretesting items. The basic scores that ACT suggests using for producing group assessment results are calculated by weighting item scores from multiple-choice and constructed-response items, where the weights are determined, a priori, by content specialists. These weights should relate more closely to the weighting intended by content specialists than do current NAEP weights. Scaling, equating, and score distribution estimation methods are described that rely on less stringent psychometric and statistical assumptions than do current procedures. Issues in sampling that include sample size requirements, sample design, and estimating standard errors are also examined, as are procedures for reporting score distributions that reflect group performance on content domains. The feasibility of using such domain scores to measure trends and to facilitate setting NAEP standards is explored. ACT recommends focusing on the design of assessments and the data collection methods rather than on complex analysis procedures. (Contains 18 tables, 9 figures, and 41 references.) (SLD)

This resource paper describes two recent studies and one report on special education costs and the methodology used in their analyses. Each study and its data source are summarized with a short discussion on the quality of the data and its usefulness and limitations in generating reliable cost estimates for special education. The paper summarizes information from the following three sources: (1) the examination of special education costs presented in the "12th Annual Report to Congress on the Implementation of the Education of the Handicapped Act," U.S. Department of Education (1990); (2) "Special Education: Views from America's Cities" prepared by the Council of the Great City Schools (1988); and (3) "Patterns in Special Education Delivery and Cost" prepared by Decision Resources Corporation (1988). A section on terminology and definitions is followed by a section which looks at each of the three sources for cost determination. A concluding discussion notes that the three reports draw different conclusions. A table compares results of the three studies for the 1985-86 school year. The paper stresses that distinguishing between the concepts of "total cost" versus "excess cost" is central to the correct use and interpretation of a cost ratio estimate. The Decision Resources Corporation report is seen as yielding the most accurate cost estimates and ratios. This study estimates "excess costs" incurred by the student with disabilities as ranging from 0.9 to 9.6 times the average per pupil expenditure, depending upon the student's special education program. The diversity of local conditions is seen as making any system for evaluating special education costs difficult. (DB)

During the past 6 years, under a contract from the National Center for Education Statistics, a Technical Review Panel has overseen and conducted a series of research studies addressing a range of validity questions relevant to the various uses and interpretations of the National Assessment of Educational Progress (NAEP). Study topics included: (1) the quality of NAEP data; (2) the number and character of NAEP scales; (3) the robustness of NAEP trend lines; (4) the trustworthiness of and interpretation of group comparisons; (5) the validity of interpretations of NAEP anchor points and achievement levels; (6) the linking of other test results to NAEP; (7) the effects of student motivation on performance; (8) the adequacy of NAEP data on student background and instructional experiences; and (9) what is understood from NAEP reports by educators and policy makers. This report describes the questions addressed by each study and summarizes the most important findings. In addition, general conclusions based on this body of research are presented and related to the major purposes of the NAEP. A general conclusion is that the evolving and growing range of uses to which NAEP is put will create the need for ongoing validation work of the sort illustrated by the Panel's studies. (Contains 61 references.) (Author/SLD)

This study investigated selected attitudinal and demographic factors, involvement, and philanthropic awareness of alumni donors and non-donors from a Research I, public university. A random sample of 500 alumni (250 donors and 250 non-donors) was selected from a population of 37,691, resulting in 371 (74 percent) usable surveys. Discriminant function analysis was applied to the data to determine if group membership for donor status (donor or non-donor) and group membership for donor level could be predicted. The study revealed that donor or non-donor status for alumni is predictable with a moderate-to-high degree of accuracy. The most powerful discriminating variables between alumni donors and non-donors within the population examined were: family income, perceived need for financial support, reading alumni publications, subsequent enrollment for graduate work, belonging to a special interest group, and involvement with the university as an alumnus. The most powerful discriminating variables between high- and low-donors within the population examined were: subsequent enrollment for graduate work, family income, perceived need for financial support, involvement with the university as an alumnus, participation in the Greek system or departmental club/organization, and religious preference. The study suggests that university development and alumni offices should work collaboratively in inviting alumni to participate in events that parallel activities reflective of alumni interests during their time as students. (Contains 17 references.) (GLR)

Student satisfaction surveys assess satisfaction with various facets of the university and includes key sets of questions on programs and services, university learning and social environment, university mission and values, educational preparation, transfer intent, general satisfaction, attitudes toward coursework, and student demographic information. Efforts at DePaul University (Illinois) in meeting student expectations of the educational experience are discussed including: (1) the methodology for successfully conducting student satisfaction surveys, (2) the implications of these surveys for institutional research, and (3) the strategies for maximizing the use of student satisfaction data. Specific topics discussed include DePaul University's experiences and efforts in survey development, sample selection, survey preparation and mailing, and data processing. Areas for continued improvement in conducting and utilizing these types of surveys are also examined. (Contains five references.) (GLR)

A study was done of ways to use data from the Cooperative Institutional Research Programs (CIRP) to provide information on policy questions related to international education. The CIRP survey is an annual project that provides participating institutions with the opportunity to use the database to explore questions concerning an institution's international activities. The study population included 1,403 entering freshmen at the Twin Cities campus of the University of Minnesota in the fall of 1991. The analysis focused on responses to three particular survey questions on international issues. Analysis of the student responses found that students for whom English was not their native language were frequently older and Asian-American. Students who spoke a language other than English at home were more likely to be female and Asian-American. Both students who were non-native English speakers and students who spoke a language other than English at home reported a lower parental income and had parents with lower levels of formal education. Students who placed personal importance on helping to promote racial understanding were more likely to be female, to speak a language other than English at home, and to be Asian-American. These students reported more hours during a typical week in high school were spent studying, volunteering, and participating in student clubs. They expected to take an active part in their college experience. The study concluded that institutions should consider ways in which they can do further analysis of the CIRP data. Included are a copy of the CIRP survey form and nine references. (JB)

This paper is part of series of the EDUCAUSE Center for Analysis and Research Campus Cyberinfrastructure (ECAR-CCI) Working Group. The topic of big data continues to receive a great deal of publicity because of its promise for opening new avenues of scholarly discovery and commercial opportunity. The ability to sift rapidly through massive amounts of data, for example, is resulting in new kinds of scientific discoveries and is making information about Internet-browsing habits more accessible and usable to the commercial sector. Understanding the issues associated with this topic is particularly important on our campuses, where the Internet plays a vital role in managing and providing access to big data sets for research and in helping generate big enterprise data sets from the day-to-day business of the university. This paper, the fourth in the series, examines current data-curation activities, discusses why they need to be extended to research big data, and, most importantly, focuses on why they are important and what purposes they are intended to serve. The emphasis is not on technical details, specific disciplinary standards, or best practices but rather on the contributions and limitations of various roles and activities during the data life cycle, particularly as they apply to research big data. [For the first paper in the series, "Big Data: Laying the Groundwork. ECAR Working Group Paper," see ED564458; for the second paper in the series, "Big Data in the Campus Landscape: Basic Infrastructure Support. ECAR Working Group Paper," see ED564457; and for the third paper in the series, "Big Data in the Campus Landscape: Security and Privacy. ECAR Working Group Paper," see ED564587.]

Given "T" joint observations on "K" variables, it is frequently useful to consider the weighted average or scaled score. L-scaling is introduced as a technique for determining the weights. The technique is so named because of its resemblance to the Leontief matrix of mathematical economics. L-scaling is compared to two widely-used procedures for data reduction, but no attempt is made to survey the voluminous literature on scaling methods. These methods are the first principal component method and the best weight function method. A robust L-scaling technique is described for use when the data matrix is contaminated by outliers. The discussion proceeds in terms of descriptive statistics since the various techniques have sampling properties that are either unknown or intractable. The technique is illustrated with a hypothetical example of 100 observations on three variables drawn from a pseudorandom-number generator. L-scaling is one method a researcher may apply when a sensitivity analysis, which compares the outcomes of several scaling methods, is desired. Four tables illustrate the study. (SLD)

Preferences for schools are important determinants of equitable access to high-quality education, effects of expanded choice on school improvement and school choice mechanism design. Standard methods for estimating consumer preferences are not applicable in education markets because students do not always get their first choice school. This review describes recently developed methods for using rich data from a school choice mechanism to estimate student preferences. Our objectives are to present a unifying framework for these methods and to help applied researchers decide which techniques to use. After laying out methodological issues, we provide an overview of empirical results obtained using these models and discuss some open questions.