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Appendix B
Basic Design Parameters Of A Longitudinal Tracking System For Doctoral Students
Introduction
In his 1988 report, Peter Ewell introduced some basic principles and techniques that institutions might use to construct a student tracking system, focusing on the need to collect accurate and detailed institution-specific information on student retention, persistence, and enrollment behavior using a ''cohort tracking" model. The output of the longitudinal student record system can be a set of reports for institutional and external use.
Although it is beyond the purview of this study to introduce a specific student tracking system for doctoral-granting institutions, it is possible to draw from Ewell and others1 in describing the general features of a longitudinal tracking record for students enrolled in Ph.D. programs in the sciences and humanities which individual institutions might modify. The purpose of this section is to outline the key features of a system for tracking.
Purpose Of The Tracking System
The purpose of a longitudinal tracking system for graduate students is to construct a data base that provides a comprehensive picture of student progress through advanced degree work. The system should permit the analysis of variables contributing to successful and unsuccessful completion of doctoral studies. The cohort survival model (Ewell 1988; Zwick 1991; Bowen and Rudenstine 1992) lends itself to this type of analysis, but it requires the construction of discrete files for entering cohorts of students. These files are the heart of the tracking system.
Data To Be Collected
The first issue in constructing a longitudinal tracking system is the definition of who will be included in the system. At the graduate level, a tracking system might (1) include all students admitted to and enrolled for credit in Ph.D. granting programs, (2)
1
Other institutional researchers whose work has the potential to contribute to the design of a longitudinal student tracking system include Glover and Wilcox (1992), Nerad and Cerny (1991), Ehrenberg (1991), Tinto (1991), Tuckman, Coyle, and Bae (1989), and Zwick and Braun (1988).
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track students over all terms whether they are enrolled or not, and (3) exclude students explicitly enrolled in terminal master's degree programs.
A cohort of students consists of all those who first enroll in a degree program on a given date. At any future date, this cohort can be divided into four types of students:
(1)
those who have completed the degree;
(2)
those who have officially left the program without completing;
(3)
those who are still enrolled in the program; and
(4)
those who have "stopped out" and may return.
Over time, students move from groups (3) and (4) into groups (1) and (2). At some arbitrary date (e.g., eight years later), completion and attrition rates can be calculated based on the number of students in groups (1) and (2). Unfortunately, students at some institutions may remain indefinitely in groups (3) and (4), and researchers will need to decide whether to create a third category for these "noncompleters" or include them in the attrition rate.
Comprehensive tracking of graduate students will occur across a number of diverse graduate unit (e.g., programs, departments, colleges) within an institution. To design and mount an effective student tracking system at the doctoral level, an institutionally based committee or graduate office would be needed to provide data managers with specific information about important differences in the graduate programs that must be reflected in longitudinal student records. For example, does the doctoral program include a master's degree requirement on the way to the doctorate?
The data elements actually included in a longitudinal tracking system will include a minimal set of information about a student as well as optional information. Some elements will be determined by institutional information needs as well as reporting requirements imposed by external agencies, such as state and federal governments. The elements listed in the text box on the following page are offered for purposes of illustration without regard to other reporting requirements.2
Reports
A longitudinal tracking system can be used to develop several types of reports. Through manipulation of the data set, cohort analyses can be conducted, yielding the following types of derived measures:
number of students in a cohort
number/percent of students earning master's degrees by a particular semester
number/percent of students admitted to doctoral candidacy in a particular semester
number/percent of students in attendance in a semester (full-time or part-time or terminated)
In addition, the data base can be used to develop prescriptive reports which assist planners and institutional researchers to document variables contributing to attrition, such as the nature and timing of student
2
Coker and Feidel (1991) report that increasing emphasis on the assessment of institutional effectiveness has stimulated many campuses to examine existing data sources, surveys, and reports before proceeding to develop new measures.
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FIXED DATA ELEMENTS
Admissions Characteristics
name of student
student ID number
baccalaureate institution
year of baccalaureate
undergraduate grade point average
GRE (verbal, quantitative, subject) scores
entry semester into Ph.D. program
transfer student (from)
Demographic Characteristics
gender
race/ethnic identification
date of birth
physical disabilities
VARIABLE DATA ELEMENTS
Demographic Characteristics
citizenship
number of dependents
marital status
Enrollment Characteristics by Semester
credits completed
grade point average
type of student support
attendance status (full-time, part-time, on leave)
Degree Program Characteristics by Semester
field/subfield
department/academic unit
advisor
probationary status (if applicable)
master's degree awarded (optional)
admitted to candidacy
dissertation committee (chair and members)
doctoral degree awarded
support; family status; race or gender; access to faculty as advisors and/or dissertation committee chairs; and antecedent variables, such as the type/prestige of the baccalaureate institution.
References
Bowen, William G., and Neil L. Rudenstine 1992 In Pursuit of the Ph.D. Princeton, NJ: Princeton University Press.
Coker, D., and J. Feidel 1991 "The Data Collection Matrix Model." Research in Higher Education 32(1):71-81.
Ehrenberg, Ronald G. 1991 "Academic Labor Supply." In Economic Challenges in Higher Education, Part 2, edited by Charles T. Clotfelter, Ronald G. Ehrenberg, Malcolm Getz, and John J. Siegfried. Chicago, IL: University of Chicago Press.
Ewell, Peter 1988 Establishing a Longitudinal Student Tracking System: An Implementation Handbook. Boulder, CO: National Center for Higher Education.
Glover, Robert H., and Jerry Wilcox 1992 "An Interactive Model for Studying Student Retention." AIR Professional File 44 (Spring).
Nerad, Maresi, and Joseph Cerny 1991 "From Facts to Action: Expanding the Educational Role of the Graduate Division. Communicator (May Special Edition). Washington, DC: Council of Graduate Schools.
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Tinto, Vincent 1991 "Toward a Theory of Graduate Persistence." Paper presented at the annual meeting of the American Educational Research Association, Chicago, Illinois.
Tuckman, Howard P., Susan Coyle, and Yupin Bae 1989 "The Lengthening of Time to Completion of the Doctorate Degree." Research in Higher Education 30:503-16.
Zwick, Rebecca 1991 An Analysis of Graduate School Careers in Three Universities: Differences in Attainment Patterns Across Academic Programs and Demographic Groups. Princeton, NJ: Educational Testing Service.
Zwick, Rebecca, and Henry I. Braun 1988 Methods for Analyzing the Attainment of Graduate School Milestones: A Case Study. GRE Board Professional Report No. 86-3P. Princeton, NJ: Educational Testing Service.
Representative terms from entire chapter:
student tracking
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