A
Conference Agenda and Attendees
TEACHER SUPPLY, DEMAND, AND QUALITY CONFERENCE ON POLICY ISSUES, MODELS, AND DATA BASES
March 21–23, 1991
National Academy of Sciences/National Research Council
2001 Wisconsin Avenue, N.W. — Green Building
Washington, D.C.
AGENDA |
||
Thursday, March 21, 1991 Green Building, Room 130 |
||
6:00 |
Reception |
|
7:00 |
Dinner |
|
8:00 |
Opening Session |
Lee Shulman, Chair |
|
Welcome |
Emerson Elliott |
|
After dinner speaker |
Albert Shanker |
Friday, March 22, 1991 Green Building, Room 130 |
||
8:30 a.m. |
Continental breakfast |
|
9:00 |
Opening remarks |
Lee Shulman, Chair |
9:05 |
The OERI Perspective on Teacher Supply, Demand, and Quality |
Christopher Cross |
9:20 |
What NCES Hopes to Learn from the Conference |
Paul Planchon |
9:30 |
Paper: On the Problem of Improving Teacher Quality While Balancing Supply and Demand |
Mary Kennedy |
|
Invited discussants |
James Stedman Arthur Wise |
|
Open discussion |
|
12:00 |
Luncheon |
|
1:00 p.m. |
Paper: The State of the Art in Projecting Teacher Supply, Demand, and Quality |
Stephen Barro |
|
Invited discussants |
Gus Haggstrom Ronald Kutscher |
|
Open discussion |
|
3:15 |
Paper: National Data Bases Relevant to Teacher Supply, Demand, and Quality Models and Projection Methods |
Ross Brewer Stephen Coelen James Wilson |
|
Invited discussants |
Alan Fechter Thomas Hilton |
|
Open discussion |
|
5:30 |
Adjourn |
|
Saturday, March 23, 1991 Green Building, Room 130 |
||
8:30 a.m. |
Continental breakfast |
|
9:00 |
Opening remarks |
Lee Shulman, Chair |
9:05 |
Panel on State Data |
|
|
Who Will Teach? |
Richard Murnane |
|
Developing a Regional Database for the Northeast: Problems, Products, and Prospects |
James Wilson |
|
A Cooperative Project to Develop Teacher Supply/Demand Information in the Southern States |
Robert Stoltz |
|
State Data on Teacher Quality, Supply, and Demand |
Rolf Blank |
|
Open discussion |
|
11:30 |
Summary of Conference Findings |
Lee Shulman |
12:00 noon |
Roundtable Discussion of Important Next Steps |
|
12:55 p.m. |
Last Word |
Dorothy Gilford |
1:00 |
Adjourn Buffet Luncheon |
|
ATTENDEES
Chair
Lee S. Shulman. Charles E. Ducommun Professor of Education, School of Education, Stanford University
Speakers and Discussants
Stephen M. Barro, President, SMB Economic Research, Inc.
Rolf K. Blank, Project Director, Science/Mathematics Indicators Project, Council of Chief State School Officers
W. Ross Brewer, Director of Planning and Policy Development, Vermont Department of Education
Stephen P. Coelen, Director, Massachusetts Institute for Social and Economic Research (MISER) and Data and Decision Analysis, Inc.
Christopher T. Cross, Assistant Secretary, Office of Educational Research and Improvement
Emerson J. Elliott. Acting Commissioner, National Center for Education Statistics
Alan Fechter, Executive Director, Office of Scientific and Engineering Personnel, National Academy of Sciences/National Research Council
Gus W. Haggstrom, Senior Statistician, Economics Department, The RAND Corporation
Thomas L. Hilton, Senior Research Scientist, Educational Testing Service
Mary M. Kennedy, Professor of Education and Director, National Center for Research on Teacher Education, Michigan State University
Ronald E. Kutscher, Associate Commissioner, Office of Employment Projections. Bureau of Labor Statistics
Richard J. Murnane, Professor, Graduate School of Education, Harvard University
Paul Planchon, Associate Commissioner, Elementary/Secondary Education Statistics Division, National Center for Education Statistics
James B. Stedman, Specialist in Social Legislation, Education and Public Welfare Division. Congressional Research Service, Library of Congress
Robert P. Stoltz, Vice President and Director for Education Policy, Southern Regional Education Board
James M. Wilson, Senior Project Analyst, Massachusetts Institute for Social and Economic Research (MISER) and Data and Decision Analysis, Inc.
Arthur E. Wise, President, National Council for Accreditation of Teacher Education
Invited Participants
Susan Ahmed, Mathematical Statistician, Statistical Standards and Methodology Division, National Center for Education Statistics
Nabeel Alsalam, Chief, Indicators and Reports Branch, Data Development Division, National Center for Education Statistics
Elizabeth Ashburn, Schools and School Professionals Division. Office of Research, Office of Educational Research and Improvement
Sharon Bobbitt, Statistician, Elementary/Secondary Education Statistics Division, National Center for Education Statistics
Teresa Bunsen, Project Officer, Division of Personnel Preparation, Office of Special Education Programs
John G. Chapman, Program Analyst, Office of Planning, Budget, and Evaluation, U.S. Department of Education
Joseph Conaty, Education Research Specialist, Office of Research, Office of Educational Research and Improvement
Lynne Cook, Director, National Clearinghouse for Professions in Special Education
C. Emily Feistritzer, President, Feistritzer Publications and Director, National Center for Education Information
David Florio, Director of Policy Studies, Office of the Assistant Secretary, Office of Educational Research and Improvement
Debra Gerald, Mathematical Statistician, Statistical Standards and Methodology Division, National Center for Education Statistics
Milton Goldberg, Director, Office of Research, Office of Educational Research and Improvement
Jewell Gould, Director of Research, American Federation of Teachers
Jeanne E. Griffith, Associate Commissioner, Data Development Division, National Center for Education Statistics
David W. Grissmer, Deputy Director, Defense Manpower Research Center, The RAND Corporation
Ron Hall, Acting Associate Commissioner, Postsecondary Education Statistics Division, National Center for Education Statistics
Suzann R. Harrison, Executive Secretary, Georgia Professional Standards Commission
David Haselkorn, President, Recruiting New Teachers, Inc.
Terrence L. Hibpshman, Manager, Research Branch, Division of Research, Kentucky Department of Education
Edward Hurley, Research Specialist, National Education Association
Joseph S. Johnston, Jr., Vice President for Programs, Association of American Colleges
Daniel Levine, Study Director, Committee on Postsecondary Education and Training for the Workplace, National Academy of Sciences / National Research Council
Paul Lauritzen, Professor of Special Education, University of Wisconsin
David Mandel, Vice President for Policy Development, National Board of Professional Teachers
Marilyn M. McMillen, Statistician, Elementary/Secondary Education Statistics Division, National Center for Education Statistics
Jeffrey Owings, Chief, Longitudinal and Household Studies Branch, Elementary/Secondary Education Statistics Division, National Center for Education Statistics
John Ralph, Chief, Policy and Review Branch, Data Development Division, National Center for Education Statistics
Mary Rollefson, Acting Chief, Special Surveys and Analysis Branch, National Center for Education Statistics
Paul M. Siegel, Senior Education Analyst, Population Division, Bureau of the Census
John J. Stiglmeier. Director, Information Center on Education, New York State Education Department
Peter Stowe, Statistician, Postsecondary Education Statistics Division, National Center for Education Statistics
Miron L. Straf, Director, Committee on National Statistics, National Academy of Sciences/National Research Council
Larry E. Suter, Program Director, Assessments and Indicators, Office of Studies and Program Assessment, Directorate for Education and Human Resources, National Science Foundation
Bayla White, Senior Budget Examiner, Office of Management and Budget
Staff
Dorothy M. Gilford, Project Director, Conference on Teacher Supply, Demand, and Quality
Laura Lathrop, Research Assistant
Jane Phillips, Administrative Assistant
Consultant:
Erling E. Boe, Professor, Graduate School of Education, University of Pennsylvania
B
National Data Bases Related to Teacher Supply, Demand, and Quality
The American Freshman
Association of American Colleges Curriculum Database
Common Core of Data
Current Population Survey
Graduate Record Examination (GRE)
High School and Beyond (HS&B)
Integrated Postsecondary Education Data System (IPEDS)
Longitudinal Study of American Youth (LSAY)
National Assessment of Educational Progress (NAEP)
National Education Longitudinal Study of 1988 (NELS-88)
The National Longitudinal Study (NLS-72)
National Surveys of Science and Mathematics Education
The Private School Survey
Schools and Staffing Survey (SASS) and Teacher Follow-up Survey (TFS)
Status of the American Public School Teacher
Surveys of Recent College Graduates
THE AMERICAN FRESHMAN
The American Freshman survey is conducted annually by the Cooperative Institutional Research Program (CIRP). of the University of California at Los Angeles (UCLA). CIRP and UCLA's Higher Education Research Institute survey all incoming freshmen in full-time study in a sample of
These summaries rely heavily on descriptions in Precollege Science and Mathematics Teachers (Dorothy M. Gilford and Ellen Tenenbaum, Editors, National Academy Press, Washington, D.C., 1990) and on material provided by various sponsors of data bases.
colleges and universities. The data are stratified by type of college, public or private control, and selectivity. Longitudinal follow-up studies are conducted each summer to track students two and four years after college entry. Freshman surveys typically involve 300,000 students at 600 institutions; follow-ups are done with probability samples of 25,000 students from each cohort.
The 40-question survey instrument solicits data on high school background, including SAT or ACT scores and grade point average, intended major and educational goals, career plans, financial arrangements, and attitudes. Personal data include race/ethnicity, sex, and parents' income and occupations. Data from The American Freshman can illuminate the beginning stage of the supply pipeline—choosing a major and a career plan. The survey includes education as one of the ''Probable Major Fields of Study.'' This broad category has a number of subcategories, including levels of education, subject matter, and special education. The longitudinal survey can provide some information about the stability of the early preference for teaching as an occupation. Questionnaire data, such as SAT scores and number of honors courses taken in high school, can be used to provide some measure of the qualifications aspects of quality.
Contact: |
Alexander W. Astin Higher Education Research Institute Graduate school of Education University of California 405 Hilgard Avenue Los Angeles, California 90024-1521 310/825-1925 |
ASSOCIATION OF AMERICAN COLLEGES CURRICULUM DATABASE
The Association of American Colleges (AAC) expanded what began as a small study in 1985–86 and 1987–88 to a large study that collected transcript data on all spring 1991 graduates from 200 institutions. These data provide the foundation for a curriculum database (CDB). To identify changes and trends, the AAC plans to collect and process such data every two years.
Of the 200 participating institutions, 100 were "friends" of the AAC and 100 were a stratified probability sample of 1,360 B.A.-granting institutions, which can provide national estimates. Twenty-four strata were used based on classifying the sampling frame by: control (public/private): type (liberal arts/comprehensive/doctoral/research); and geographic location (east/ middle/west). The CDB does not use a questionnaire but takes electronic transcript and student record data.
Student data collected include: major/school, gender, ethnicity, date of birth, GPA, scores on the SAT and ACT, advanced placement credits, trans-
fer credits, and transfer level (when applicable). In addition, data were collected on all course enrollments, including the year, term, campus, grade, and credits of each course. Each institution was asked to map its curriculum to clarify the field or discipline to which courses and majors belonged.
The CDB will provide information on course background as well as student variables that will be useful in longitudinal analysis of teacher preparation.
Contact: |
Joseph S. Johnston, Jr. Association of American Colleges 1818 R Street, N.W. Washington, D.C. 20009 202/387-3760 |
COMMON CORE OF DATA
The Common Core of Data (CCD) is a comprehensive, annual, national statistical data base for all public elementary and secondary schools and school districts. CCD is conducted by the National Center for Education Statistics, and the data base contains data that are comparable across states.
The CCD is comprised of five surveys that are sent to state departments of education. These five data sets can be used separately or in conjunction with one another in addressing issues of teacher supply and demand.
The data collected by the CCD surveys include three categories of information: general descriptive information on schools and school districts and state-level information on students and staff, and finances.
The information on students and staff includes enrollment by grade and race, full-time equivalent staff by major employment, and high school graduates and completers in the previous year.
Contact: |
John Sietsema Elementary and Secondary Education Statistics Division National Center for Education Statistics 555 New Jersey Avenue, N.W. Washington, D.C. 20208-5651 202/219-1335 |
CURRENT POPULATION SURVEY
The Current Population Survey (CPS) is a continuing cross-sectional survey of a sample of U.S. households. The Bureau of Labor Statistics provides the major funding for the survey. It is conducted monthly by the Census Bureau and collects data on labor force status. The CPS surveys people age 15 or older on their employment status in the week prior to the
survey. In most months the survey includes supplemental questions on such topics as income and work experience. Four of the monthly supplements collect data relevant to teacher supply, demand, and quality. The January supplement asks questions about skills improvement and training since obtaining their current (last) job, and the March supplement focuses on labor market information, migration patterns that can be used for planning schools, and income. The May supplement obtains information on multiple job holders. including information on hours worked at the main and second job and the reason for working a second job. The October supplement focuses on enrollment in formal schools, full-and part-time status in school, level of schooling, and tuition. It also includes questions about enrollment in business, vocational, technical, and correspondence courses. The October supplement is particularly useful in tracking trends in school enrollment, dropout rates, and relationships between educational attainment and labor force activity.
The sample design involves two stages. In the first stage the nation is divided into primary sampling units (PSUs). PSUs are comprised of larger counties and independent cities and groups of smaller counties. The larger PSUs are selected with certainty for the samples, while the smaller PSUs are grouped into strata and subsampled. In the second stage of sampling, clusters of two to four households are selected for interviewing from address lists developed by the Census Bureau. The CPS sample is designed to be state-representative for annual average data for most states.
Currently, the CPS sample includes about 60,000 eligible housing units, with 2,500 eligible housing units containing at least one adult Hispanic included in the March supplement. Information is collected for all the residents at each unit. The census rotates housing units into and out of the survey, replacing one-eighth of the sample each month. Each household is in the sample for 4 months, out for 8 months, and then in for 4 months, so that longitudinal data can be obtained for consecutive March or October supplements.
The Census Bureau plans to redesign the CPS samples based on the 1990 census. The newly designed samples will be implemented around 1994–1995. In addition, the Census Bureau expects to introduce an improved labor force questionnaire in the mid-1990s and to complete a new processing system that will take advantage of the quasi-longitudinal nature of the survey.
Contact: |
Ronald R. Tucker Current Population Survey Branch Demographic Surveys Division Bureau of the Census Washington, D.C. 20233 301/763-2773 |
GRADUATE RECORD EXAMINATION
The Graduate Record Examinations (GRE) include a General Test and Subject Tests in 16 subject areas. The GRE General Test measures verbal, quantitative, and analytical abilities. The Subject Tests measure knowledge and understanding of subject matter in specific fields. The GRE scores provide those graduate schools and fellowship sponsors who require the GRE with a common measure for comparing the qualifications of applicants from a variety of backgrounds.
In addition to test scores, GRE takers are requested to provide background information, including information on the major field of undergraduate study and of intended graduate study. It is possible to relate intended graduate majors to intended undergraduate majors (from the SAT of the same student) to develop a system of predicting graduate school enrollment by major. GRE scores are also useful as an indicator of the cognitive ability of students choosing graduate work in education relative to those in other fields.
Contact: |
Charlotte V. Kuh Graduate Record Examinations Educational Testing Service P.O. Box 6000 Princeton, New Jersey 08541-6000 609/951-6506 |
HIGH SCHOOL AND BEYOND
High School and Beyond (HS&B) is a national longitudinal survey of high school seniors and sophomores conducted by the National Center for Education Statistics. A probability sample of 1,015 public and private high schools was selected with 36 seniors and 36 sophomores in each of the schools. A total of about 30,000 sophomores and 28,000 seniors participated in the base-year survey. The base-year data were collected in 1980, with follow-ups in 1982, 1984, and 1986, and another is planned for 1992. In addition, data from their parents and teachers and high school and postsecondary education transcripts were included. Currently the sample contains 14,825 participants from the 1980 sophomore cohort and 11,995 participants from the 1980 senior cohort.
The purpose of the survey is to observe the educational, occupational, and family development of young people as they pass through high school and college and take on adult roles. Data obtained can also help researchers understand the new graduate component of the supply pool and the incentives to which they respond.
The 1980 and 1982 surveys consisted of questionnaire data (on background characteristics, attitudes, postsecondary educational and career plans, and activities related to education, career, and family development). Cognitive tests developed for the sophomore cohort by the Educational Testing Service were administered in 1980 and 1982. The tests were designed to measure cognitive growth in three domains: verbal, mathematics, and science.
The 1984 and 1986 follow-up surveys contain similarly detailed questions concerning college courses and experiences, jobs (including salaries), attitudes, and marriage and family formation. An analysis file is being prepared containing transcripts and student responses for students indicating that they plan to become teachers.
The Administrator and Teacher Survey (ATS), which was given to a sample of High School and Beyond school staff in 1984, can be used for research on teacher supply, demand, and quality. It was designed to explore findings from "effective schools" research with a broadly representative sample. The effective schools literature identifies characteristics of schools in which students perform at higher levels than would be expected from their background and other factors. Prior to the ATS, measures of those characteristics were not available on any large national data set. The ATS provides measures of staff goals, school environment, school leadership, and other processes believed important.
A total of 457 public and private high schools (approximately half of the 1,015 High School and Beyond schools) were sampled for the ATS; separate questionnaires were prepared for principals, teachers, vocational education coordinators, heads of guidance, and community service coordinators. Up to 30 teachers in each of the 457 schools responded to the teacher questionnaire; only one respondent per school completed the other surveys. Respondents include 402 principals and 10,370 teachers.
The ATS was designed to measure school goals and processes that the effective schools literature indicates are important in achieving effective education. Questionnaire items describe staff goals, pedagogic practices, interpersonal staff relations, teacher workload, staff attitudes, availability and use of services, planning processes, hiring practices, optional programs designed to produce educational excellence, and linkage to local employers, parents, and the community.
The ATS asked teachers a number of quality-related questions concerning school environment, in-service experience, interruptions, autonomy, absenteeism, parent contact, hours spent teaching and nonteaching, and time use and practices in a typical class. The respondent's educational background and subject preparation, certification and salary data were also asked. NCES has not issued publications based on the ATS, but the data are available on tape and a code book is available.
Contact: |
Aurora D'Amico Postsecondary Education Statistics Division National Center for Education Statistics 555 New Jersey Avenue, N.W. Washington, D.C. 20208 202/219-1365 |
INTEGRATED POSTSECONDARY EDUCATION DATA SYSTEM
The Integrated Postsecondary Education Data System (IPEDS), sponsored by the National Center for Education Statistics, is a single, comprehensive system that includes all identified institutions whose primary purpose is to provide postsecondary education. It includes programs whose purpose is academic, vocational, and continuing professional education. It excludes avocational and adult basic education programs. It includes the following types of institutions: baccalaureate or higher degree-granting institutions, 2-year award institutions, and less-than-2-year institutions. These three categories are further disaggregated by control (public, private nonprofit, and private for-profit), resulting in nine institutional categories.
Data are collected from approximately 10,500 postsecondary institutions. IPEDS has been designed to produce national, state, and institutional-level data for most postsecondary students. IPEDS collects data on fall enrollment (including enrollment in teacher training programs) including full and part-time enrollment by sex, racial, and ethnic data; age distributions (odd-numbered years): and residence status of first-time degree-seeking students (even-numbered years). In odd-numbered years, IPEDS also collects data on fall enrollment in occupationally specific programs by sex and race/ethnicity. It also collects degree-completion data by field or discipline, race/ethnicity, and sex. Specialized but compatible reporting formats have been developed for the different sectors of postsecondary education providers.
Contact: |
William H. Freund Postsecondary Education Statistics Division National Center for Education Statistics 555 New Jersey Avenue, N.W. Washington, D.C. 20208-5652 202/219-1373 |
LONGITUDINAL STUDY OF AMERICAN YOUTH
The Longitudinal Study of American Youth (LSAY) is a longitudinal study conducted by the Public Opinion Laboratory at Northern Illinois Uni-
versity, sponsored by the National Science Foundation. The study began in fall 1987 with two national cohorts, one of approximately 3,000 seventh graders and the other of approximately 3,000 tenth graders. Thus, when the two cohorts are linked, complete data from the seventh grade to the twelfth grade are available.
Although the LSAY focuses on the development of competence in mathematics and science, the data base is comprehensive and permits a broad range of investigation of educational development. Background data are collected from parents, science and mathematics teachers, and principals as well as students. Student and teacher data are collected annually, in both the fall and spring, allowing student data to be linked to particular teachers, textbooks, and syllabi.
The data are good for studying the dynamics of teacher quality as well as the antecedents of career choice. Public release files as well as a User's Manual and data tape for the science and mathematics achievement test item data are available from the project by request.
Contact: |
Jon D. Miller Longitudinal Study of American Youth Northern Illinois University DeKalb, Illinois 60115-2854 815/753-0952 |
NATIONAL ASSESSMENT OF EDUCATIONAL PROGRESS
The National Assessment of Educational Progress (NAEP) is a congressionally mandated study to continuously monitor the knowledge, skills, and performance of the nation's children and youth, directed and funded by the National Center for Education Statistics. The assessment is currently administered for NCES by the Educational Testing Service. It is referred to as The Nation's Report Card, the National Assessment of Educational Progress. Approximately 120,000 precollege students are randomly selected for the national assessment every two years. NAEP is required to provide objective data about student performance at national and regional levels.
Prior to 1990, NAEP was required to assess reading, mathematics, and science at least once every 5 years. Under current legislation, assessments in reading and mathematics are required at least every 2 years, in science and writing at least every 4 years, and in history or geography and other subjects selected by the National Assessment Governing Board at least every 6 years.
To comply with the legislation, NAEP has surveyed the educational accomplishments of 9-, 13-, and 17-year-old students in 11 subject areas, starting in 1969–70. NAEP first identifies counties as primary sampling
units through a stratified sampling plan. Then for each age level, public and private schools are selected by a stratified sampling plan. Finally, within each school groups of students are selected to participate in NAEP. Student samples include both age-and grade-representative populations. A variation of matrix sampling (Balanced Incomplete Block Spiraling) is used in packaging and administering assessment booklets. In the 1990 assessment, data were collected from a national probability sample of over 45,000 students per age/grade or a total of about 146,000 students in nearly 2,100 schools, as well as their principals and a sample of their teachers. In 1990 representative state-level data were produced for the first time for participating states from the trial state assessment in mathematics at the eighth grade level.
Assessments are given in fall, winter, and spring, measuring achievement and gathering information on attitudes and classroom practices as students perceive them. The nonachievement measures (attitudes toward science or math, homework and grades, and home environment) are obtained through a companion background questionnaire.
Over the past three assessment cycles NAEP has developed scales for the subjects assessed. These scales allow NAEP to compare results across ages and across assessments. In addition, the scaling scores allow NAEP to report the proportion of students at different proficiency levels in various subject areas.
NAEP Teacher Questionnaire
In 1984, NAEP began collecting data on teacher attributes, as reported by teachers of the students participating in the NAEP assessments. At grades 7 and 11, teachers are identifiable by subject (e.g., mathematics, science). The 1986 assessment, for example, gathered information from 325 seventh grade science teachers and 289 eleventh grade science teachers who responded.
The teacher questionnaire asked for data on general demographic characteristics, certification, educational preparation, and teaching experience at various grade levels. These help to illuminate aspects of teacher qualifications. School environment indicators asked on the questionnaire include classroom activities and practices, homework, laboratory and other instructional resources, and autonomy. The questionnaire asks whether the respondent would become a teacher if he or she could start over again. Continuing education is touched on in one item, although not in detail. There are no questions tracing the teacher's career path, salary, or other nonteaching work. Thus, the NAEP teacher survey may provide some quality-related information, but little on demand or supply.
Contact: |
Kent Ashworth Educational Testing Service Princeton, New Jersey 08541 1/800/223-0267 |
|
Gary W. Phillips Education Assessment Division National Center for Education Statistics 555 New Jersey Avenue, N.W. Washington, D.C. 20208-5653 202/219-1761 |
NATIONAL EDUCATION LONGITUDINAL STUDY OF 1988
The National Education Longitudinal Study of 1988 (NELS:88) is an education longitudinal study sponsored by the National Center for Education Statistics and designed to provide trend data about critical transitions experienced by young people as they develop, attend school, and embark on their careers. By initially focusing in 1988 on eighth graders and their schools, teachers, and parents, then by following up that cohort at two-year intervals, the NELS:88 data will be used to address such issues as persistence and dropping out of high school, transition from eighth grade to high school, tracking, and features of effective schools.
For the base-year survey conducted in spring 1988, a nationally representative sample of 1,000 schools (800 public and 200 private) was drawn. Within this school sample, 26,000 eighth grade students, 6,000 eighth grade teachers, and 24,000 parents were surveyed. Thus, the four major component surveys for the base year were directed at students, parents, school administrators, and teachers.
Students were asked about school work, aspirations, and social relations. They also took cognitive tests in four achievement areas: reading and vocabulary, mathematics, science, and social studies. The parent survey gauged parental aspirations for their children, commitment of resources to their children's education, and other family characteristics relevant to educational achievement. Analysis of these data may suggest young people's levels of interest and their parents' commitment to pursuing science/mathematics fields in the future.
School principals provided information about the teaching staff, student body, school policies and offerings, and courses required for eighth graders. For example, for science and for mathematics, the principal was to note whether a full year, a half year, less than a half year, or no specified amount is required. Whether a gifted-talented program is offered is also noted, by subject. School environment items, and particularly discipline indicators, are included. Staffing questions are general and not broken down by sub-
ject. From this survey, data on 8th grade mathematics or science required might inform demand in a general way. Course-taking data might inform preparation for high school mathematics and science. Indicators of quality of education offered at the eighth-grade level are somewhat more evident.
Teacher data include academic background and certification information, class size, time use, instructional materials used, laboratory use, and school environment information. The teacher questionnaire thus can shed light on a number of indicators of quality of education offered at the eighth-grade level by subject.
The science and mathematics teachers who participated in NELS:88 also participated in a National Science Foundation study, the NSF Teacher Transcript Study, under contract with Westat, Inc., in 1988. This study collected postsecondary education transcripts on a national basis for use in assessing the relationship between teacher qualifications and student achievement.
The NELS:88 First Follow-up, sponsored by the National Science Foundation as well as the National Center for Education Statistics, was conducted between February and May 1990. The follow-up survey included student, school administrator, teacher, and dropout questionnaires. Students took cognitive tests in reading, science, social science, and math. Selected teachers of each sampled student provided information about class size, the student's study habits and performance, instructional practices in the student's classes, teacher qualifications including how prepared the teacher feels to teach the subject matter in the course, and how satisfied they are with their teaching job, and whether or not they would become a teacher again. In 1992 the NCES plans a Second Follow-up Survey to survey this eighth-grade cohort, now in twelfth grade, again. In the 1992 survey, parent questionnaires will be used in addition to the student, school administrator, teacher, and dropout questionnaires.
Contact: |
Jeffrey A. Owings Elementary and Secondary Education Statistics Division National Center for Education Statistics 555 New Jersey Avenue, N.W. Washington, D.C. 20208-5651 202/219-1777 |
THE NATIONAL LONGITUDINAL STUDY
The National Longitudinal Study (NLS-72), conducted by NCES and administered by the National Opinion Research Center, studies the high school class of 1972 in the form of a sample of 23,000 high school seniors (1972) enrolled in 1,318 high schools. Follow-ups were conducted in 1973–74, 1974–75, 1976–77, and 1979–80. A fifth follow-up was conducted on a
subsample in 1986, with approximately 13,000 responding at this point they were about 32 years old. In each follow-up, data were collected on high school experiences, background, opinions, and attitudes, and future plans. Participants took achievement tests in the first survey. Follow-ups traced their college, postgraduate, and work experiences, including salaries. Reasons for leaving schools or jobs were also asked. In addition, respondents included data on marriage and family formation and military service.
A Teaching Supplement Questionnaire was sent to all respondents to the fifth follow-up survey (1986) who indicated they had teaching experience or had been trained for precollege teaching. In addition, persons with mathematics, science or engineering backgrounds (with 2-year, 4-year, or graduate degrees in those fields) were drawn into the sample. A total of 1,147 eligible individuals responded. Of these, 109 indicated they actually had no teaching experience, degree in education, or certification to teach. This left 1,038 completed teaching supplements to analyze, drawing on the wealth of previous NLS data on these individuals.
This sample of current and former teachers (and some who never became teachers) were asked about career paths, salaries in teaching and non-teaching positions, certification, continuing education, family formation, reasons for entry into teaching and attrition, and nonteaching jobs. This detailed information can be analyzed by subject area.
The data have been analyzed at NCES and by Heyns (1988) and contribute to knowledge of the characteristics of the supply pool, patterns of entry, exit, and reentry, and the role of salary and other incentives.
Contact: |
Aurora D'Amico Postsecondary Education Statistics Division National Center for Education Statistics 555 New Jersey Avenue, N.W. Washington, D.C. 20208-5652 202/219-1365 |
NATIONAL SURVEYS OF SCIENCE AND MATHEMATICS EDUCATION
The 1977 and 1985 surveys were sponsored by the National Science Foundation and conducted by Iris Weiss of Research Triangle Institute. They involved a national probability sample of schools, principals, and teachers in grades K–12. The 1985 survey covered 425 public and private schools. From these schools a sample of 6,000 teachers was selected. The sample was stratified by grades K–6, 7–9, and 10–12. For grades 10–12 the sample was also stratified by subject to avoid the oversampling of biology. Of the teachers sampled, 2,300 were teaching at the grade 10–12 level. The survey
used five different forms, one each for principals, elementary math teachers, elementary science teachers, secondary school math teachers, and secondary school science teachers. Response rates were generally high; for example, the response rate from principals was 86 percent.
Principals in schools selected for the grade 10–12 sample were asked to check the types and number of science and mathematics courses taught by each teacher: biology/life sciences, chemistry, physics, earth/space science, ''other mathematics/computer science.'' They were also asked to evaluate teachers' competence. Principals also reported whether they had difficulty hiring fully qualified teachers for vacancies, by subject.
The survey requested science and mathematics course offerings and enrollment (by race, ethnicity, and sex), and information about science labs and equipment, instructional techniques, and teacher training. Information on achievement was not requested.
Teachers supplied in-depth information on curriculum and instruction in a single, randomly selected class. Time spent in instruction, lab, and amount of homework given are among the types of practices for which data were collected.
In addition, information on the demographics, salary, attitudes, assignment of teachers, and data on the detailed educational background of each teacher were requested. Information about advanced degrees earned, certification, and subject-matter courses taken, to compare with standards of the NSTA and NCTM, and teaching experience were also included. Teachers were also asked if they feel inadequately qualified to teach in one or more courses.
The next surveys will be conducted by Horizon Research, Inc., with data collection in the 1992–93 academic year and questionnaires in the spring of 1993. The report publication will be in 1993–94.
Most of the teacher data from the National Survey of Science and Mathematics Education are related to aspects of quality. The course offerings and enrollment data in the school-level data supplied by principals provides some indicators of demand.
Contact: |
Iris Weiss Horizon Research, Inc. 111 Cloister Court, Suite 220 Chapel Hill, NC 27514 919/489-1725 |
|
Jennifer McNeill Research Triangle Institute P.O. Box 12194 Research Triangle Park, North Carolina 27709 1/800/334-8571 |
THE PRIVATE SCHOOL SURVEY
The Private School Survey, first conducted by the National Center for Education Statistics in 1989–90, collects data on private elementary and secondary schools. The survey reflects an increasing concern with alternatives in education. It will build a data base for private schools, generate biennial data on the total number of private schools, teachers, and students, and produce early estimates of private school characteristics.
The target population for the universe survey consisted of all private schools in the United States that meet NCES criteria of a school. The survey universe is comprised of private schools from a variety of sources. Periodically this list of schools is updated by matching it with other lists provided by private school associations, state departments of education, and other lists.
The early estimates portion of the survey is conducted with a sample of 1,200 schools selected from the list and area frame operations. The selected schools are stratified by affiliation (Catholic, other religious, and nonsectarian) and by grade level (elementary, secondary, combined). Schools will also be sorted by region and enrollment. Survey questions include information on religious orientation, level and size of school, length of school day and school year, total enrollment, number of high school graduates, number of teachers, location and year of beginning operation, and program emphasis. The early estimates section includes number of schools, teachers, students, and high school graduates.
Contact: |
Elizabeth Gerald Elementary and Secondary Education Statistics Division National Center for Education Statistics 555 New Jersey Avenue, N.W. Washington, D.C. 20208-5651 202/219-1334 |
SCHOOLS AND STAFFING SURVEY AND TEACHER FOLLOW-UP SURVEY
Prime sources of data about teacher supply, demand, and quality are the Schools and Staffing Survey (SASS) and its longitudinal component the Teacher Follow-up Survey (TFS), both conducted by the National Center for Education Statistics. SASS was first administered during the 1987-88 school year, again in 1990–91, and is scheduled to be conducted every three years thereafter. In addition, one year after each SASS is administered, a subsample of SASS teachers is selected for the TFS. Data generated by SASS and TFS serve the following five purposes: (a) to profile the nation's
teaching force; (b) to improve estimates and projections of teacher supply and demand by teaching field, sector, level, and geographic location; (c) to allow analyses of teacher mobility and turnover; (d) to enhance assessment of teacher quality and qualifications; and (e) to provide more complete information on school policies and programs, administrator characteristics, and working conditions. Accordingly. SASS includes a great deal of information about representative samples of teachers, school administrators, and schools from each state and from the nation as a whole.
Schools and Staffing Survey
The 1987–88 SASS was composed of four basic questionnaires, with minor variations for units in the public and private sectors, with content as summarized below:
SASS 1A—Teacher Demand and Shortage Questionnaire for Public School Districts (SASS 1B is the parallel private school form). District enrollment, hiring and retirement policies, and staff data. Number of teaching positions, by level and field, that are filled or remain unfilled. New hires, layoffs, salaries, benefits. High school graduation requirements by field.
SASS 2—School Administrator Questionnaire (public and private). Training, experience, and professional background of principals. School problems, including teacher absenteeism. Influence of teachers/principal/district on curriculum and on hiring. Methods of dealing with unfilled vacancies.
SASS 3A—Public School Questionnaire (SASS 3B is the parallel private school form). Teacher-student ratio, student characteristics, staffing patterns, and teacher turnover (entry, attrition). Supply sources of new entrants and destinations of leavers. Some data can be analyzed by academic subject area.
SASS 4A—Public School Teachers Questionnaire (SASS 4B is the parallel private school form). Education and training, current assignment, continuing education, job mobility, working conditions, career choices. Division of time, courses taught. Achievement level of students. Salary, other income. Opinions on pay policies, salary, working conditions, professional recognition, etc. What teachers did before they began teaching at this school. Data can be analyzed by teaching field.
The SASS design used schools as the primary sampling unit. Once a school was selected for the sample, the School Administrator Questionnaire was sent to the principal of the school, the Teachers Questionnaire was sent to a sample of four to eight teachers from that school, and in the public sector the Teacher Demand and Shortage Questionnaire was sent to the district in which the school was located. This design permits linking data from one questionnaire to another.
The 1987–88 SASS, as well as the 1990–91 SASS, includes approximately 12,800 schools (9,300 public and 3,500 private), 65,000 teachers (52,000 public and 13,500 private) and 5,600 public school districts. SASS was administered in the form of mail questionnaires, with extensive telephone follow-up. Consequently, questionnaire response rates were high—on the order of 90 percent in the public sector and 80 percent in the private sector.
Teacher Follow-up Survey
SASS also has a small but important longitudinal component termed the Teacher Follow-up Survey. During spring 1989, one year after the base survey, the Questionnaire for Former Teachers was sent to the approximately 2,500 teachers who left the teaching profession at the end of the 1987–88 school year. In addition the Questionnaire for Current Teachers was sent to a probability sample of approximately 5,000 teachers who remained active in the profession. This latter sample was divided equally into (a) teachers who remained in the same school and (b) teachers who transferred to a different school. The response rate for this survey was 93 percent for teachers who left and 97 percent for teachers who remained in the profession. Following the 1990–91 SASS, a second Teacher Follow-up Survey, similar to the first, was conducted in spring 1992. The content of the two follow-up questionnaires is summarized below:
TFS 2—Teacher Follow-up Survey (Questionnaire for former teachers sampled in SASS). Teacher attrition, salary, other factors or reasons for leaving teaching. What former teachers did after leaving. Comparison of teaching with current occupation with regard to salary, working conditions, and job satisfaction. Data can be analyzed by subject.
TFS 3—Teacher Follow-up Survey (Questionnaire for sampled teachers who remained in teaching). Factors in retention; reasons for possible change in school assignment. Salary, other income. Data can be analyzed by subject.
The Teacher Follow-up Survey provides the first data at the national level that permit the study of attrition from the profession and comparisons of "leavers," "stayers," and ''movers" (i.e., those teachers who remain in the profession but move to a different school). Sampled teachers can be linked to SASS data to determine relationships among district and school policies/practices, teacher characteristics, and teacher attrition and retention. Furthermore, additional follow-up surveys of the teachers from the 1990–91 SASS are planned subsequent to the 1992 follow-up survey. Consequently, it will also be possible to study, from a national perspective, reentry to the profession of experienced teachers from the reserve pool.
Contact: |
Mary Rollefson National Center for Education Statistics 555 New Jersey Avenue, N.W. Washington, D.C. 20208 202/219-1336 |
STATUS OF THE AMERICAN PUBLIC SCHOOL TEACHER
In 1956 the National Education Association (NEA) developed the first of a series of surveys covering numerous aspects of U.S. public school teachers' professional, family, and civic lives. This survey project, titled The Status of the American Public School Teacher, has been conducted every five years since 1956. Although the questionnaire has been revised to update items of concern, the wording still provides comparable data on most items from survey to survey (except for 1961, which contained some differences in the wording of questions). The most recent survey was conducted in 1990–91 and will be published by the NEA in spring 1992.
The sample of respondents for 1990–91 contained 1,351 usable responses (73.5 percent of the questionnaires originally mailed). Participants were selected through a two-stage sample design: first, a stratified sample of public school districts was drawn with the districts classified by pupil enrollment into nine strata. All school districts in the sample were asked to submit a list of all their teachers. Using that list, systematic sampling with a random start was used. A 58-item questionnaire was then mailed, in spring 1991, to all teachers in the sample. Questionnaire items span teaching experience, educational background, subject(s) taught, income, workload, school environment, demographic and family information, and civic interests. Subject area taught is self-reported, with the teacher filling in a blank with the main subject taught (i.e., "science"). The sample size is large enough to provide regional data and data by school district size as well as national data.
Items related to supply include demographic data, number of breaks in service and (one) primary reason, salaries from teaching and from additional employment, what the person did the previous year, what he or she plans to do next year, and how long the person plans to remain in teaching.
Items related to quality include highest college degree and recentness of that degree; teaching and nonteaching loads; type of teaching certificate held, including emergency and provisional certificates; college credits earned in the past three years and how much of the teacher's own money was spent for credits and other school expenses; detailed information about professional growth activities (workshops, university extension, college courses in education/other than education, etc.); whether the person would become a teacher if he or she started over again; reasons for teaching; what helps/
hinders the teacher most in his or her position; and presence of teaching assistants.
Only the published statistics are available from these surveys.
Contact: |
Valencia Campbell Research Division National Education Association 1201 Sixteenth St., N.W. Washington, D.C. 20036 202/822-7400 |
SURVEYS OF RECENT COLLEGE GRADUATES
The National Center for Education Statistics has conducted periodic surveys (1976, 1978, 1981, 1985, 1987, and 1991) on outcomes of college graduation. These surveys have primarily addressed the issues of employment related to individuals' field of study and their access to graduate or professional programs. The Recent College Graduates (RCG) surveys have concentrated especially on those graduates qualified to teach at the elementary and secondary levels, estimating the potential supply of newly qualified teachers and the number who were employed as teachers in the year following graduation. Education majors are thus oversampled for the RCG. The RCG surveys were not longitudinal, but in 1993 NCES will replace the RCG with the Baccalaureate and Beyond Longitudinal Study, a longitudinal survey of graduating college seniors. Recent studies were also designed to examine the relationship between courses taken, student achievement, and occupational outcomes.
The survey involves a two-stage sampling procedure, representative at the national level. First, a sample of institutions awarding bachelor's or master's degrees is selected and stratified by percent of education graduates, control, and type. Special emphasis is placed on institutions granting degrees in education and on traditionally black institutions. For each of the selected schools, a sample of degree recipients is chosen. Included are both B.A. and M.A. degree recipients.
The survey of 1974–75 college graduates was the first and smallest of the series. The sample consisted of 200 responding schools. Of the 5,506 graduates in that sample, 4,350 responded (79 percent). The 1981 survey was somewhat larger, covering 301 institutions and 15,852 students. The student response rate was 62 percent. The 1985 survey (which collected race/ethnicity data for the first time) requested data from 18,738 students from 404 colleges. The student response rate was an effective 70 percent,. with just under 11,000 participating. Response rates in these cycles (except for the 1976 survey) tend not to be higher because of invalid mailing ad-
dresses, reflecting the difficulty in tracing students after graduation. The 1987 study (which included transcripts for the first time) was more effective in locating graduates as the file contains 16,878 respondents from 400 higher education institutions, representing an 80 percent response rate. The 1991 survey involved 400 institutions and 18,000 graduates. The RCG may thus be biased against more mobile graduates. Students are surveyed once, without additional follow-ups.
Questionnaire items request data including degrees and teaching certificates; continuing education; additional formal training; what job was held as of April 27, 1987, and its relation to educational training; subjects eligible/certified to teach, whether/when entered teaching; subjects taught; marital status and number of children; and further degree plans. The questionnaire asks whether the person taught in grades K–12 before completing the degree requirement. Subjects taught are phrased generally: mathematics, computer science, biological science, and physical sciences. Information on the graduates' incentives for choosing particular careers or jobs is limited.
Thus, the RCG offers a general, nonlongitudinal picture of the new graduates component of the supply pool. Its inclusion of items that may suggest incentives and disincentives to enter teaching make it a possible source of reserve pool information. In addition to supply related to potential teachers and potential minority teachers, a few aspects of the qualification component of quality may be touched on rather indirectly, such as grades (self-reported).
Contact: |
Peter Stowe Postsecondary Education Statistics Division National Center for Education Statistics 555 New Jersey Avenue, N.W. Washington, D.C. 20208-5652 202/219-1363 |
C
Teacher Supply, Demand, and Quality Variables: National Data Base Sources
Erling E. Boe and Dorothy M. Gilford
Sources of TSDQ variables within national data bases are identified and organized in the tables of this appendix. Tables 1 and 2 contain dependent variables and independent variables respectively, related to teacher supply and quality. Tables 3 and 4 contain teacher demand variables, and Table 5 contains variables relevant to the student interest in and preparation for teaching careers. The definitions and procedures used in the construction of these tables, and certain qualifications of importance to potential users, are described in the following paragraphs.
National data bases are defined here as organized collections of data drawn from the nation as a whole. A total of 15 such data bases were identified and selected for inclusion because they contain national data on variables relevant to analyses of TSDQ issues and because they are generally accessible for data analysts. Representative examples of data bases included are the Schools and Staffing Survey (SASS) and the Common Core of Data (CCD) of the National Center for Education Statistics (NCES) and the Graduate Record Examination (GRE) data base. The 15 data bases were developed by various means, the principal methods being questionnaire surveys of national probability samples of teachers and schools (e.g., SASS), reports submitted by the population of public school districts in the nation (e.g., CCD), and self-selected samples of individuals (e.g., GRE).
A data base, as defined here, is composed of information drawn from a number of particular sources, some of which are very similar in content while others are very different. The SASS data base, for example, contains information from questionnaires completed by teachers about themselves, from questionnaires completed by school administrative personnel about
school attributes, and from questionnaires completed by school district personnel about district variables. These different sources provide quite different sets of data. The SASS data base also contains information from questionnaires completed by one sample of teachers in 1988 and another sample in 1991. The contents of these two particular questionnaire sources are quite similar. Likewise, the National Assessment of Education Progress (NAEP) includes information from somewhat different versions of questionnaires for science and for mathematics teachers at the eighth grade level in 1990, each of which can be considered a particular source. Other data bases, such as CCD, amass similar data annually, each installment of which constitutes a particular source.
The five tables of this appendix were developed to provide helpful guidance for researchers, modelers, data base managers, and others interested in identifying sources of national data about variables relevant to analyses of teacher supply and demand issues. However, data bases are too complex internally to serve as the optimal unit of analysis for the purpose of providing helpful guidance. On the other hand, particular sources within data bases are too numerous to serve as a manageable unit of analysis, and, in any event, many particular sources contain a great deal of overlapping content.
In view of these considerations, an intermediate unit of analysis was devised—a unit more particular than a data base but broader than a particular source. This intermediate unit of analysis is a cluster of particular sources within a data base. To define such clusters, particular sources of data within data bases were analyzed to identify those sources that contained substantially overlapping information. For example, the teacher questionnaires of SASS for 1988 and 1991 were clustered together because there was a high degree of overlap of information collected. Similarly, the school questionnaires of SASS for 1988 and 1991 formed another cluster because of overlapping content. However, the differences between the teacher and school questionnaires were sufficiently great that they were treated as different clusters of particular sources. As a result of this type of analysis, the 15 national data bases were broken down into a total of 29 clusters of particular data sources. The particular sources contained within these 29 clusters are listed in the section preceding Table 1.
Though useful, the strategy of consolidating particular data sources into 29 clusters was adopted at the cost of obscuring certain differences among sources included in a cluster. These differences are not revealed in the five tables of this appendix. For example, variations in similar questionnaires collected on two different occasions are not reported here, such as the differences between the teacher questionnaires of SASS for 1988 and 1991. Likewise, variations between similar questionnaires collected from different groups of teachers at a particular time (such as from eighth grade mathematics teachers and science teachers in 1990 for the NAEP) are not re-
ported here. Interested users must review questionnaire forms to determine the specific information contained in each data base.
Although the rows of Tables 1 through 5 are termed variables and are intentionally very specific, different definitions of each variable may be used in different data bases, and sometimes for particular data sources within a data base. For example, the numbers of employed teachers are based on different operational definitions of a teacher and may be reported as either the number of full-time equivalent teachers, the number of full-time teachers only, or the number of full-time plus part-time teachers. Therefore, users of TSDQ data must review the original questionnaires and related documentation to determine specific definitions of TSDQ variables used.
In addition, some variables included in the tables are not recorded as such in their designated data base sources. These are derived variables. For example, combinations of questionnaire items included in the teacher questionnaires of SASS provide a basis for computing the percentage of teachers who transfer from primary teaching assignments in special education to general education from one year to the next even though there is no particular questionnaire item about such cross-field transfer. Of course, data users can generate many other useful derived variables.
Finally, some national data bases (such as SASS) have been structured to provide national estimates of TSDQ variables, while other data bases do not because they are not derived from national probability samples. For example, some teacher samples (e.g., from NELS:88, NAEP, and LSAY) have been formed by selecting teachers linked to national probability samples of students. Therefore, these teacher samples are not representative of the national teaching force. In another example, data on entering teachers from the Surveys of College Graduates are limited to graduates at the baccalaureate level. Since new teachers graduating at the masters level are not included, these surveys are not representative of all recently graduated new teachers. Therefore, users of data bases must determine the population represented in the TSDQ data.
For the several reasons described above, entries in Tables 1 through 5 should be viewed only as promising leads to data base sources of TSDQ variables. Users of this information should review the specific contents of data elements in each relevant data base before concluding whether needed information about particular variables is either available or is not available.
Data Sources Reported in Tables 1 through 5
-
Schools and Staffing Survey: Public School Teacher Questionnaire (1988 and 1991) (Sponsor: National Center for Education Statistics)
-
Schools and Staffing Survey: Public School Questionnaire (1988 and 1991) (Sponsor: National Center for Education Statistics)
-
Schools and Staffing Survey: Teacher Demand and Shortage Questionnaire for Public School Districts (1988 and 1991) (Sponsor: National Center for Education Statistics)
-
Schools and Staffing Survey: Public School Administrator Questionnaire (1988 and 1991) (Sponsor: National Center for Education Statistics)
-
Teacher Followup Survey: Questionnaire for Current Teachers (1989) (Sponsor: National Center for Education Statistics)
-
Teacher Followup Survey: Questionnaire for Former Teachers (1989) (Sponsor: National Center for Education Statistics)
-
Common Core of Data (1989–90) (Sponsor: National Center for Education Statistics)
-
National Education Longitudinal Study of 1988: Teacher Questionnaire (Base Questionnaire of 1988 and Following), Questionnaire for History, English, Mathematics, and Science Versions of 1990) (Sponsor: National Center for Education Statistics)
-
National Education Longitudinal Study of 1988: School Questionnaire (Base 1988 and 1990 Followup) (Sponsor: National Center for Education Statistics)
-
National Assessment of Educational Progress: Teacher Questionnaire for Grade 3, Grade 7, and Grade 11 (1986) (Sponsor: National Center for Education Statistics)
-
National Assessment of Educational Progress: Teacher Questionnaire for Grade 4 and Grade 8 (1988) (Sponsor: National Center for Education Statistics)
-
National Assessment of Educational Progress: Teacher Questionnaires for Math Teachers and For Science Teachers, both for Grade 8 (1990) (Sponsor: National Center for Education Statistics)
-
National Assessment of Educational Progress: Teacher Questionnaires for Grade 4, Mathematics Teachers and Writing Teachers, both for Grade 8 (1991–92) (Sponsor: National Center for Education Statistics)
-
National Longitudinal Study (NLS-72) (1972, 1973–74, 1974–75, 1976–77, 1978–80, and 1986) (Sponsor: National Center for Education Statistics)
-
High School and Beyond: Administrator and Teacher Surveys (1984) (Sponsor: National Center for Education Statistics)
-
Current Population Survey (March, May, and October 1991 and January 1992) (Sponsor: Bureau of the Census)
-
National Survey of Science and Mathematics Education: Teacher Questionnaire in (a) Elementary, (b) Elementary Mathematics, (c) Secondary, and (d) Secondary Mathematics (1985) (Sponsor: National Science Foundation)
-
National Surveys of Science and Mathematics Education: Principal Questionnaire (1985) (Sponsor: National Science Foundation)
-
Status of the American Public School Teacher (1991) (Sponsor: National Education Association)
-
American Freshman Survey (1990) (Sponsor: Cooperative Institutional Research Program. University of California, Los Angeles)
-
American Freshman Followup Survey (1991) (Sponsor: Cooperative Institutional Research Program, University of California, Los Angeles)
-
Association of American Colleges: Curriculum Data Base (1991) (Sponsor: Association of American Colleges)
-
Integrated Postsecondary Education Data Base (1991) (Sponsor: National Center for Education Statistics)
-
Survey of 1989–90 College Graduates (1991) (Sponsor: National Center for Education Statistics)
-
Survey of 1985–86 College Graduates (1987) (Sponsor: National Center for Education Statistics)
-
Graduate Record Examination (1991) (Sponsor: Educational Testing Service)
-
Longitudinal Survey of American Youth: Teacher Questionnaires (1987, 89, and 90) (Sponsor: National Science Foundation)
-
Longitudinal Survey of American Youth: Student Questionnaire (1987, 88, 89, and 90) (Sponsor: National Science Foundation)
-
Longitudinal Survey of American Youth: Principal Questionnaire (1988–89) (Sponsor: National Science Foundation)
TABLE 1 Supply of Teachers for Public Education: Dependent Variables and Data Sources
Teacher Flow Variables |
Key to Data Sourcesa |
||||||||||||
1. Entering leachers hired into positions (inflow): Numbers of entering teachers disaggregated by |
|
||||||||||||
A. Recent college graduates hired, disaggregated by |
|
||||||||||||
1. Grade level |
1 |
24 |
25 |
|
|||||||||
2. Major teaching field |
1 |
24 |
25 |
|
|||||||||
3. Subject matter specialty |
1 |
24 |
25 |
|
|||||||||
4. Total recent college graduates hired |
1 |
24 |
25 |
|
|||||||||
B. Entering teachers hired from the reserve pool, disaggregated by |
|
||||||||||||
1. Grade level |
1 |
|
|||||||||||
2. Major teaching field |
1 |
|
|||||||||||
3. Subject matter specialty |
1 |
|
|||||||||||
4. Total leachers hired from the reserve pool |
1 |
|
|||||||||||
C. Total entering teachers hired into positions disaggregated by |
|
||||||||||||
1. Grade level |
1 |
10 |
11 |
|
|||||||||
2. Major teaching field |
1 |
|
|||||||||||
3. Subject matter specialty |
1 |
10 |
11 |
|
|||||||||
4. Total entering teachers hired |
1 |
2 |
8 |
10 |
11 |
12 |
17 |
||||||
II. Retained teachers in public education classified by type of position shift from one year to the next (withinflow): Numbers of retained teachers disaggretated by |
|
||||||||||||
A. Stable retention/no transfer (same school and teaching assignment): Numbers of teachers disaggregated by |
|
||||||||||||
1. Grade level |
1 |
5 |
8 |
10 |
11 |
|
|||||||
2. Major teaching field |
1 |
5 |
|
||||||||||
3. Subject matter specialty |
1 |
5 |
10 |
|
|||||||||
4. Total teachers retained in same school and teaching assignment |
1 |
5 |
8 |
10 |
11 |
|
|||||||
B. Transfer retention within public education, disaggregated by type of transfer supply to different positions in public education: Numbers of teachers transferring to different positions disaggregated by |
|
||||||||||||
1. Different school (school migration), same primary assignment dissaggregated by |
|
||||||||||||
a. Grade level |
1 |
5 |
|
||||||||||
b. Major teaching field |
1 |
5 |
|
||||||||||
c. Subject matter specialty |
1 |
5 |
|
||||||||||
d. Total migrating teachers |
1 |
5 |
|
||||||||||
2. Same school, different primary assignment (reassignment) disaggretated by |
|
||||||||||||
a. Grade level |
1 |
5 |
|
||||||||||
b. Major teaching field |
1 |
5 |
|
||||||||||
c. Subject matter specially |
1 |
5 |
|
||||||||||
d. Total teachers reassigned |
1 |
5 |
|
|
|
|
|
Teacher Flow Variables |
Key to Data Sourcesa |
||||||||
3. Different school, different primary assignment disaggregated by |
|
||||||||
a. Grade level |
1 |
5 |
|
||||||
b. Major teaching field |
1 |
5 |
|
||||||
c. Subject matter specialty |
1 |
5 |
|
||||||
d. Total teachers migrating and reassigned |
1 |
5 |
|
||||||
C. School transfer supply within public education: Numbers of teachers transferring to a different school (school migration) whether or not changing primary teaching assignment (sum of categories II.B.1. and 3. above), disaggregated by |
|
||||||||
1. Grade level |
1 |
5 |
8 |
10 |
11 |
|
|||
2. Major teaching field |
1 |
5 |
|
||||||
3. Subject matter specialty |
1 |
5 |
10 |
|
|||||
4. Total migrating teachers |
1 |
2 |
5 |
8 |
10 |
11 |
|
||
D. Total teachers retained in public education from one year to the next: Numbers of teachers retained disaggregated by |
|
||||||||
1. Grade level |
1 |
5 |
8 |
10 |
11 |
|
|||
2. Major teaching field |
1 |
5 |
|
||||||
3. Subject matter specialty |
1 |
5 |
10 |
12 |
13 |
|
|||
4. Total teachers retained in public education |
1 |
5 |
8 |
10 |
11 |
12 |
13 |
17 |
|
III. Total teachers employed in public education in any one year (sum of I.C. and II.D.): Numbers of teachers employed disaggregated by |
|
||||||||
A. Grade level |
1 |
3 |
|
||||||
B. Major teaching field |
1 |
|
|||||||
C. Total teachers employed in public education |
1 |
9 |
13 |
|
|||||
D. Total teachers employed in public education |
1 |
2 |
3 |
8 |
9 |
13 |
17 |
27 |
29 |
IV. Attrition of teachers from public education from one year to the next (i.e., outflow): Numbers of exiting teachers disaggregated by |
|
||||||||
A. Grade level |
6 |
|
|||||||
B. Major teaching field |
6 |
|
|||||||
C. Subject matter specialty |
6 |
|
|||||||
D. Total exiting teachers |
6 |
|
|||||||
V. Reserve pool component: Former teachers unemployed since leaving teaching |
|
||||||||
A. Number of years out of work |
16 |
|
|||||||
B. Intention to look for work in next 12 months |
16 |
|
|||||||
aNumbers refer to preceding list of data source clusters. |
TABLE 2 Supply of Teachers for Public Education: Independent Variables and Data Sources
Predictor Variables |
Key to Data Sourcesa |
|||||||||||
I. Year of |
|
|||||||||||
|
A. Most recent entry into teaching |
|
|
1 |
14 |
|
||||||
|
B. Exit attrition (last year in teaching) |
|
|
6 |
14 |
|
||||||
II. Employment Status |
|
|||||||||||
|
A. Type of position |
|
||||||||||
|
|
1. Regular: Full time |
|
1 |
8 |
10 |
11 |
15 |
|
|||
|
|
2. Regular: Part time |
|
1 |
8 |
|
||||||
|
|
3. Substitute |
|
1 |
8 |
10 |
11 |
25 |
|
|||
|
|
4. Itinerant |
|
1 |
|
|||||||
|
B. Percent of full time |
|
|
1 |
2 |
5 |
14 |
24 |
25 |
|
||
III. Teacher characteristics: Demographic |
|
|||||||||||
|
A. Age |
|
|
1 |
8 |
10 |
11 |
14 |
15 |
16 |
||
|
|
|
|
17 |
19 |
24 |
25 |
|
||||
|
B. Gender |
|
|
1 |
8 |
9 |
10 |
11 |
12 |
13 |
||
|
|
|
|
14 |
15 |
16 |
17 |
19 |
24 |
25 |
||
|
C. Race/ethnicity |
|
|
1 |
2 |
8 |
10 |
11 |
12 |
13 |
||
|
|
|
|
14 |
15 |
16 |
17 |
19 |
24 |
25 |
||
|
D. Marital/family status |
|
|
1 |
5 |
6 |
14 |
15 |
16 |
19 |
||
|
|
|
|
24 |
25 |
|
||||||
|
E. Number of dependent children |
|
|
1 |
5 |
6 |
24 |
25 |
|
|
||
VI. Teacher characteristics: Qualifications |
|
|||||||||||
|
A. Degree(s) earned by |
|
||||||||||
|
|
1. Subject matter |
|
|||||||||
|
|
|
(1) Major |
1 |
5 |
6 |
8 |
10 |
11 |
12 |
||
|
|
|
|
13 |
14 |
15 |
17 |
24 |
25 |
27 |
||
|
|
|
(2) Minor |
1 |
5 |
6 |
8 |
11 |
12 |
14 |
||
|
|
|
|
15 |
25 |
27 |
|
|||||
|
|
2. Level |
|
1 |
2 |
5 |
6 |
8 |
9 |
10 |
||
|
|
|
|
11 |
12 |
13 |
16 |
17 |
19 |
27 |
||
|
|
3. Year |
|
1 |
5 |
6 |
14 |
15 |
19 |
24 |
||
|
|
|
|
25 |
27 |
|
||||||
|
B. Type of teaching certification held |
|
|
1 |
3 |
5 |
6 |
8 |
10 |
11 |
||
|
|
|
|
12 |
13 |
15 |
17 |
19 |
24 |
25 |
||
|
C. Nonteaching experience |
|
|
1 |
6 |
14 |
|
|||||
|
D. Prior teaching experience |
|
||||||||||
|
|
1. Any prior teaching experience |
|
1 |
24 |
25 |
|
|||||
|
|
2. Number of years taught |
|
|||||||||
|
|
|
a. In public sector |
1 |
15 |
|
||||||
|
|
|
b. In private sector |
1 |
15 |
|
||||||
|
|
|
c. Both sectors combined |
1 |
10 |
11 |
12 |
13 |
14 |
15 |
||
|
|
|
|
17 |
19 |
27 |
|
|||||
|
|
3. Last year taught |
|
14 |
15 |
|
||||||
|
|
4. Grade level(s) taught |
|
1 |
10 |
15 |
|
|||||
|
|
5. Major teaching field(s) |
|
1 |
15 |
|
||||||
|
|
6. Subject matter specialty(s) |
|
1 |
|
|||||||
|
E. Teacher competence ratings |
|
|
18 |
|
|||||||
|
F. Inservice training |
|
|
1 |
8 |
12 |
13 |
17 |
19 |
27 |
||
|
G. College GPA |
|
|
24 |
25 |
|
||||||
|
H. Tested ability score(s) |
|
|
— |
|
|||||||
V. Teaching practice variables |
|
|
|
1 |
8 |
10 |
11 |
12 |
13 |
17 |
||
|
|
|
|
27 |
|
Predictor Variables |
Key to Data Sourcesa |
||||||||||||
VI. Financial Variables |
|
||||||||||||
|
A. Teacher compensation (current year) |
|
|||||||||||
|
|
1. Annual base teaching salary |
|
1 |
3 |
5 |
19 |
24 |
25 |
29 |
|||
|
|
2. Benefits provided |
|
3 |
17 |
|
|||||||
|
|
3. Salary/bonus inducements |
|
1 |
5 |
9 |
19 |
|
|||||
|
|
4. Supplemental earnings opportunities |
|
1 |
5 |
19 |
|
||||||
|
|
5. Extended contract |
|
18 |
|
||||||||
|
|
6. Subsidized retraining |
|
17 |
18 |
|
|||||||
|
B. Total family income |
|
|
1 |
5 |
6 |
|
||||||
|
C. Relative wages by occupation |
|
|||||||||||
|
|
1. Local |
|
— |
|
||||||||
|
|
2. State |
|
— |
|
||||||||
|
|
3. National |
|
16 |
|
||||||||
|
D. Former earned income |
|
|
6 |
14 |
15 |
|
||||||
|
E. Income earned in year after leaving teaching |
|
|
6 |
|
||||||||
|
F. Local employment rates |
|
|
— |
|
||||||||
|
G. District (LEA) financial variables |
|
|
— |
|
||||||||
|
H. Retirement financial incentives |
|
|
— |
|
||||||||
VII. School Variables |
|
||||||||||||
|
A. Urbanicity |
|
|
2 |
5 |
9 |
18 |
19 |
24 |
|
|||
|
B. Total enrollment |
|
|
2 |
9 |
18 |
|
||||||
|
C. Enrollment trends |
|
|
2 |
|
||||||||
|
D. Distance from high school home to school of employment |
|
|
25 |
|
||||||||
VIII. School transfer variable (from prior year) |
|
||||||||||||
|
A. Different school, same district |
|
|
1 |
5 |
|
|||||||
|
B. Different school, different district within same state |
|
|
1 |
5 |
|
|||||||
|
C. Different school in contiguous slate |
|
|
1 |
5 |
|
|||||||
|
D. Different school in noncontiguous state |
|
|
1 |
5 |
|
|||||||
XI. Distance from residence to school of employment |
19 |
|
|||||||||||
X. Working conditions |
|
||||||||||||
|
A. Teaching load |
|
|||||||||||
|
|
1. Number of teaching contact hours per week |
|
1 |
10 |
13 |
19 |
27 |
|
||||
|
|
2. Average number of students per contact hour |
|
1 |
10 |
13 |
19 |
27 |
|
||||
|
B. Availability of teaching assistant(s) |
|
|
2 |
13 |
19 |
|
||||||
|
C. Adequacy of |
|
|||||||||||
|
|
1. Instructional materials |
|
1 |
11 |
12 |
13 |
27 |
|
||||
|
|
2. Instructional equipment |
|
1 |
5 |
12 |
19 |
27 |
|
|
|||
|
|
3. Administrative support |
|
1 |
5 |
8 |
27 |
|
|||||
|
|
4. Teacher authority over |
|
||||||||||
|
|
|
a. Instruction and marking |
1 |
5 |
8 |
10 |
11 |
12 |
13 |
|||
|
|
|
|
27 |
|
||||||||
|
|
|
b. Student conduct |
1 |
5 |
8 |
10 |
11 |
13 |
27 |
|||
|
D. School safety |
|
|
1 |
5 |
8 |
9 |
|
|||||
|
E. Student variables |
|
|||||||||||
|
|
1. Academic performance |
|
1 |
11 |
12 |
13 |
17 |
27 |
|
|||
|
|
2. SES |
|
2 |
9 |
18 |
29 |
|
|||||
|
|
3. Race/ethnicity |
|
2 |
9 |
17 |
18 |
29 |
|
|
|||
aNumbers refer to preceding list of data source clusters. |
TABLE 3 Demand for Teachers in Public Education: Dependent Variables and Data Sources
Teacher Demand Variables |
Key to Data Sourcesa |
|||||
1. Funded positions for teachers disaggregated by status from prior year: Numbers of funded full-time (FTE) positions by |
|
|||||
|
A. Continued funded FTE positions from prior year: Numbers of continued FTE positions |
|
|
— |
|
|
|
B. Newly created and funded FTE positions for current year (i.e., new positions): Numbers of new FTE positions |
|
|
— |
|
|
|
C. Total funded FTE positions for current year: Numbers of total FTE positions disaggregated by |
|
|
|
|
|
|
|
1. Grade level |
|
— |
|
|
|
|
2. Subject matter specialty |
|
— |
|
|
|
|
3. Total funded FTE positions |
|
3 |
|
|
II. Funded positions for teachers disaggregated by filled vs shortage positions: Numbers of funded full-time equivalent (FTE) positions by |
|
|||||
|
A. Positions filled by employed FTE teachers in current year, disaggregated by |
|
|
|
|
|
|
|
1. Grade level |
|
— |
|
|
|
|
2. Subject matter specialty |
|
— |
|
|
|
|
3. Total employed FTE teachers |
|
3 |
7 |
|
|
B. Teacher shortage for current year as measured by |
|
||||
|
|
1. Retained, but open, FTE positions for current year, disaggregated by |
|
|||
|
|
|
a. Grade level |
— |
|
|
|
|
|
b. Subject matter specialty |
— |
|
|
|
|
|
c. Total open FTE positions |
3 |
|
|
|
|
2. Unfunded (i.e., discontinued) FTE positions for current year due to inadequate supply of applicants, disaggregated by |
|
|
||
|
|
|
a. Grade level |
— |
|
|
|
|
|
b. Subject matter specialty |
— |
|
|
|
|
|
c. Total discontinued FTE positions |
3 |
|
|
|
|
3. Total teacher shortage for current year, as measured by initially funded, but unfilled, FTE positions, disaggregated by |
|
|
||
|
|
|
a. Grade level |
— |
|
|
|
|
|
b. Subject matter specialty |
— |
|
|
|
|
|
c. Total unfilled FTE positions |
3 |
|
|
III. Unfunded (i.e., discontinued) positions for teachers from prior year: Numbers of discontinued FTE positions |
— |
|
||||
IV. Teacher shortage for current year as measured by: Degree of difficulty in filling funded, but open, positions. disaggregated by |
|
|||||
|
|
A. Grade level |
|
— |
|
|
|
|
B. Subject matter specialty |
|
18 |
|
|
|
|
C. Overall difficulty in filling positions |
|
4 |
18 |
|
aNumbers refer to preceding list of data source clusters. |
TABLE 4 Demand for Teachers in Public Education: Independent Variables and Data Sources
Predictor Variables |
Key to Data Sourcesa |
||||||
I. Teachers required (i.e., needed) variables |
|
||||||
A. Student enrollment variables |
|
||||||
|
1. Student/population ratio |
|
|
|
— |
|
|
|
2. Student K-12 school enrollment |
|
|
|
2 |
3 |
|
|
3. Public/private split of student enrollment |
|
|
|
1 |
7 |
|
|
4. Public school student enrollment: Numbers of students disaggregated by |
|
|
|
|
|
|
|
|
a. Instructional variables |
|
|
|
|
|
|
|
|
(1) Level |
|
2 |
3 |
7 |
|
|
|
(2) Subject matter |
|
— |
|
|
|
|
|
(3) Course |
|
— |
|
|
|
|
b. Student variables |
|
|
|
|
|
|
|
|
(1) Age |
|
3 |
|
|
|
|
|
(2) Race/ethnicity |
|
2 |
7 |
|
|
|
|
(3) Special needs |
|
|
|
|
|
|
|
|
(a) Handicap |
2 |
7 |
|
|
|
|
|
(b) Limited English proficiency |
2 |
|
|
|
|
|
(4) Free lunch eligible |
|
2 |
3 |
7 |
B. Curriculum requirements |
|
|
|
||||
|
1. Elementary school |
|
|
|
— |
|
|
|
2. High school graduation |
|
|
|
3 |
|
|
C. Work load variables |
|
|
|
||||
|
1. Planned teacher-pupil ratio |
|
|
|
— |
|
|
|
2. Teaching load: Number of teaching contact hours per week |
|
|
|
— |
|
|
D. Total teachers required (i.e. needed) |
|
|
|
|
— |
|
|
II. Financial variables |
|
||||||
A. Exogenous financial variables |
|
|
|
|
— |
|
|
B. District (LEA) endogenous financial variable |
|
|
|
|
— |
|
|
III. Employment obligations to teachers retained from prior year |
— |
|
|
||||
IV. School variables |
|
||||||
A. Urbanicity |
|
|
|
|
2 |
7 |
|
B. Student enrollment |
|
|
|
|
2 |
7 |
|
C. Number of teachers |
|
|
|
|
2 |
7 |
|
V. LEA Variables |
|
||||||
A. Urbanicity |
|
|
|
|
7 |
|
|
B. Student enrollment |
|
|
|
|
3 |
7 |
|
C. Number of teachers |
|
|
|
|
3 |
7 |
|
D. Number of schools |
|
|
|
|
7 |
|
|
aNumbers refer to preceding list of data source clusters. |
TABLE 5 Student Interest In and Preparation for Teaching Careers
Student Variables |
Key to Data Sourcesa |
|||||
I. Student interest in teaching careers |
|
|
|
|
|
|
A. Educational level of interested persons |
|
|
|
|
|
|
|
1. Students in seventh grade |
28 |
|
|
|
|
|
2. High school seniors |
28 |
|
|
|
|
|
3. College freshmen |
20 |
|
|
|
|
|
4. College upperclassmen |
21 |
|
|
|
|
|
5. College graduates |
26 |
|
|
|
|
B. Demographic characteristics of interested persons |
|
|
|
|
|
|
|
1. Age |
20 |
21 |
22 |
26 |
28 |
|
2. Gender |
20 |
21 |
22 |
26 |
28 |
|
3. Race/ethnicity |
21 |
22 |
26 |
|
|
C. Tested ability scores of students interested in enrolling in teacher preparation programs |
|
21 |
22 |
26 |
|
|
D. Grade point averages |
|
|
|
|
|
|
|
1. High school |
28 |
|
|
|
|
|
2. College |
26 |
|
|
|
|
II. Teacher education enrollments disaggregated by |
|
|
|
|
|
|
A. Subject matter specialty |
|
22 |
|
|
|
|
B. Degree level |
|
— |
|
|
|
|
C. Total teacher education enrollments |
|
22 |
|
|
|
|
III. Teacher education enrollments as a proportion of total higher education enrollments at the baccalaureate level |
22 |
|
|
|
|
|
IV. Number of teacher education graduates disaggregated by |
|
|
|
|
|
|
A. Grade level |
|
23 |
|
|
|
|
B. Major teaching field |
|
23 |
|
|
|
|
C. Subject matter specialty |
|
23 |
|
|
|
|
D. Degree level |
|
23 |
|
|
|
|
E. Total teacher education graduates |
|
23 |
24 |
25 |
|
|
V. Year of graduation from teacher education program |
8 |
14 |
15 |
24 |
25 |
|
VI. Sources of college funding |
24 |
25 |
|
|
|
|
aNumbers refer to preceding list of data source clusters. |