IES Blog

Institute of Education Sciences

A Slightly More Diverse Public School Teaching Workforce

There is research evidence that having a teacher of the same race/ethnicity can have positive impacts on a student’s attitudes, motivation, and achievement[1] and that minority teachers may have more positive expectations for minority students’ achievement than nonminority teachers.[2] New data from the National Center for Education Statistics show that the public school teaching workforce is becoming more diverse, but is still predominantly White.

The majority of public elementary and secondary school teachers were White in both 2003–04 and 2015–16. However, the percentage of teachers who were White was lower in 2015–16 than in 2003–04 (80 vs. 83 percent). While the percentage of teachers who were Black also fell slightly in that time, the percentages of teachers who were Hispanic, Asian, and of Two or more races were higher in 2015–16 than in 2003–04.

 


Figure 1. Percentage distribution of teachers in public elementary and secondary schools, by race/ethnicity: School years 2003–04 and 2015–16



# Rounds to zero.
NOTE: Data are based on a head count of full-time and part-time teachers. Race categories exclude persons of Hispanic ethnicity. Detail may not sum to totals because of rounding. Although rounded numbers are shown, figures are based on unrounded estimates.
SOURCE: U.S. Department of Education, National Center for Education Statistics, Schools and Staffing Survey (SASS), “Public School Teacher Data File,” 2003–04; and National Teacher and Principal Survey (NTPS), “Public School Teacher Data File,” 2015–16. See Digest of Education Statistics 2017, table 209.10.


 

The racial/ethnic diversity of teachers differed somewhat by school characteristics. For example, schools with more racial/ethnic diversity in their student populations also tended to have more racial/ethnic diversity among teachers. In 2015–16, the percentage of minority[3] teachers was highest at schools that had 90 percent or more minority students (55 percent) and was lowest at schools with less than 10 percent minority students (2 percent). The opposite pattern was observed for White teachers, who accounted for 98 percent of teachers at schools with less than 10 percent minority students but made up only 45 percent of staff at schools with 90 percent or more minority students.

 


Figure 2. Percentage distribution of teachers in public elementary and secondary schools, by percentage of minority students in school and teacher minority status: School year 2015–16



NOTE: Excludes the 7 percent of teachers for whom the percentage of minority enrollment in the school was not available. Minority teachers include all racial/ethnic groups except for White. Race categories exclude persons of Hispanic ethnicity. Detail may not sum to totals because of rounding.
SOURCE: U.S. Department of Education, National Center for Education Statistics, National Teacher and Principal Survey (NTPS), “Public School Teacher Data File,” 2015–16. See Digest of Education Statistics 2017, table 209.23.


 

Are you interested in other differences in teacher characteristics by race/ethnicity? Then check out the spotlight feature in the Status and Trends in the Education of Racial and Ethnic Groups 2018 report.

 

By Lauren Musu

 

[1] Egalite, A.J., and Kisida, B. (2018). The Effects of Teacher Match on Students’ Academic Perceptions and Attitudes. Educational Evaluation and Policy Analysis, 40(1): 59–81; Egalite, A.J., Kisida, B., and Winters, M.A. (2015). Representation in the Classroom: The Effect of Own-Race Teachers on Student Achievement. Economics of Education Review, 45, 44–52.

[2] Gershenson, S., Holt, S.B., and Papageorge, N.W. (2016). Who Believes in Me? The Effect of Student-Teacher Demographic Match on Teacher Expectations. Economics of Education Review, 52, 209–224.

[3] Minority teachers include all racial/ethnic groups except for White.

IES Announces Forthcoming Funding Opportunity For the R&D of an “ROI Tool” to Inform Students’ Postsecondary Education and Career Decision Making

Students with electronic devices sitting against a wall.

Overview

On or about February 15, 2019, the Small Business Innovation Research Program at the US Department of Education’s Institute of Education Sciences (ED/IES SBIR) anticipates releasing a Special Topic Solicitation #91990019R0016 in Postsecondary Education. The solicitation will be announced through an IES Newsflash and will be posted here. It will request Phase I proposals for awards of up to $200,000 for 8 months to develop a prototype of a "ROI tool.” The tool will be designed to measure the costs versus benefits (the return on investment) of different postsecondary education and training programs to help students make well-informed choices about options to pursue after they complete high school.

Applicants must be a for-profit business 500 employees or less, and U.S. owned and operated. Applicants may partner with entities or organizations working on related initiatives in the field of postsecondary education, or may subcontract to non-profit researchers or individuals with specialized expertise as needed. The due date for submission for proposals will likely be on or about April 15, 2019, with awards in mid-June, and projects beginning shortly thereafter. All Phase I awardees will be eligible to apply for a Phase II award in 2020, for $900,000 for full scale development and research to test and validate the ROI tool.

Background

While many websites provide ways for students to explore colleges or careers and occupations of interest (e.g., such as College Scorecard and CareerOneStop), there is currently no tool that helps students understand the costs and benefits of individual postsecondary programs in an integrated, customizable, and user-friendly manner.  An ROI tool would likely combine information on individual program’s tuition and fees, time needed to complete, and expected earnings. Because these characteristics can vary significantly across programs and institutions, creating a single estimated measure of ROI would allow students to more easily compare postsecondary program options. If it helps students make better choices, it could lead to improved program completion rates, higher levels of employment and earnings, less education-related debt, and more satisfaction with their selected education and career paths. 

The ED/IES SBIR Special Topic intends to fund up to five (5) Phase I projects to (a) develop and research a prototype of an ROI tool, and (b) conduct planning and concept testing for a fully developed ROI tool that provides a user-friendly experience for students. The prototype of the ROI tool developed in Phase I shall integrate with one or more existing technology systems, data sets, data standards, or resources (such as CareerOneStop or College Scorecard), and add new data elements provided by an end-user.  After a successful Phase I project, it is anticipated that small businesses that win Phase II awards will complete the full-scale development of the ROI tool that was started in Phase I, including developing an interface to improve the experience of students using the ROI tool.

Because data for ROI at the program level may only be available from some states, regions, or sets of institutions at this time, it is expected that the scope of the ROI tool developed in Phase I & II would be limited and would not be an attempt to calculate ROI for every program and institution in the country. Applicants must propose a project scope that appropriately reflects the datasets that are to be integrated within the new ROI tool, and the amount of funding and time allotted for development and research of the SBIR awards in Phase I and II.  Small businesses that are interested in this solicitation must have expertise with related efforts in the field to enhance student choices by linking education and workforce information.

Potential applicants may submit questions to ED’s Contracting Specialist Kevin.Wade@ed.gov. All questions and responses will be posted publically on the same website where the solicitation is posted as Amendments to the Solicitation.

 

Explore Transfer Student Data from the Integrated Postsecondary Education Data System (IPEDS)

Transfer students who attend full time complete a degree at higher rates than those attending part time. There were 2.1 million students who transferred into a 4-year institution during the 2009-10 academic year. At public institutions, which had the majority of transfer students (1.3 million) in 2009-10, 61 percent of full-time transfers completed their degree after 8 years of entering the institution, compared to 32 percent of part-time transfers (figure 1).

 



 

While NCES data users may be more familiar with the postsecondary transfer student data in the Beginning Postsecondary Study, NCES also collects data on this topic through the Integrated Postsecondary Education Data System (IPEDS) collection. IPEDS annually requires over 4,000 colleges and universities to report their transfer data starting from enrollment to completion. As defined by IPEDS, students who transfer into an institution with prior postsecondary experience–whether credit was earned or not–are considered transfer-in students. Students who leave an institution without completing their program of study and subsequently enrolled in another institution are defined as transfer-out students.

Below are some of the key data collected on student transfers through the different IPEDS survey components:

  • Fall Enrollment (EF): Transfer-in data

Collected since 2006-07, institutions report the fall census count and specific characteristics—i.e., gender, race/ethnicity, and attendance status (full and part time)—of transfer-in students.

  • Graduation Rates (GR): Transfer-out data

Collected since 1997-98, GR collects counts of students who are part of a specific first-time, full-time student cohort. Data users can calculate the transfer-out rates of first-time, full-time students by race/ethnicity and gender for each institution that reports transfer-out data. NCES requires the reporting of transfer-out data if the mission of the institution includes providing substantial preparation for students to enroll in another eligible institution without having completed a program. If it is not part of the institution’s mission, an institution has the option to report transfer-out data.

  • Outcome Measures (OM): Transfer-in and transfer-out data

Collected since 2015-16, OM collects information on entering students who are first-time students as well as non-first-time students (i.e., transfer-in students). Institutions report on the completions of transfer-in students at three points in time: at 4, 6, and 8 years. Also, any entering student who does not earn an award (i.e., certificate, associate’s degree, or bachelor’s degree), leaves the institution, and subsequently enrolls in another institution is reported as a transfer-out student. Click to learn more about OM. All institutions reporting to OM must report their transfer-out students regardless of mission.

 

NCES has been collecting IPEDS for several decades, which allows for trend analysis. Check out the IPEDS Trend Generator’s quick analysis of transfer-in students' fall enrollment. Also, the National Postsecondary Education Cooperative commissioned a 2018 paper that provides a high-level examination of the most common issues regarding U.S. postsecondary transfer students and presents suggestions on how NCES could enhance its student transfer data collection. For example, one caveat to using IPEDS transfer data is that information on where students transfer from or to is not collected. This means IPEDS data cannot be used to describe the various pathways of transfer students, such as reverse, swirling, and lateral transferring.[1]. While these nuances are important in today’s transfer research, they are out of the scope of the IPEDS collection. However, IPEDS data do provide a valuable national look at transfers and at the institutions that serve them. 

 

[1] A reverse transfer is defined as a student who transfers from a high-level institution to a low-level institution (e.g., transferring from a 4-year institution to a 2-year institution). Students who take a swirling pathway move back and forth between multiple institutions. A lateral transfer student is a student who transfers to another institution at a similar level (e.g., 4-year to 4-year or 2-year to 2-year). 

 

 

By Gigi Jones

 

 

 

IES is Expanding the Evidence Base for Career and Technical Education (CTE)

Since February is Career and Technical Education (CTE) Month—let’s look at what is going on in CTE training and research. Formerly known as “vocational education,” CTE generally comprises instruction in the academic, technical, and employability skills and knowledge required to enter into and succeed in specific occupations. CTE can introduce high school students to different career paths and help them build marketable skills or even credentials. For college students, CTE offers an entry point for new and returning students as they gain knowledge and skills in certain occupational fields.

Many policymakers consider CTE to be a key aspect of “college and career readiness.” In 2017, 49 states enacted 241 CTE policies, and 42 states enacted an additional 146 CTE policies in 2018. However, CTE practice and policy are way ahead of research—particularly in terms of research that can more definitively link CTE to specific outcomes and impacts. Over the past few years, IES has made some important strides in this area.

Following a Technical Working Group meeting on the future of CTE research, IES partnered with the Office of Career Technical and Adult Education to launch a new research network called “Expanding the Evidence Base for Career and Technical Education (CTE).” 

 

 

The CTE research network is a five-year grant, to be led by the American Institutes for Research (AIR), with partners at Vanderbilt University, Jobs for the Future, and the Association for Career and Technical Education (ACTE). Currently, three IES research projects have joined the new network, and we hope to eventually include up to six. All of these projects will look at the causal impact of CTE on student outcomes.

Throughout the five-year grant period, the Network Lead will bring together project teams and help to provide vision and support to the research projects as a whole. The Network Lead will also conduct research, provide CTE research training activities, and work to disseminate the Network’s research products so that they can reach the widest possible stakeholder audience. 

The first meeting of the Network members occurred on January 8, 2019 in Washington, DC, where members began to set the priorities for collaborative work across projects. Network members agreed that it is critical for all research projects to provide detailed data broken out by CTE field and by student subgroups, including students with disabilities.

One key priority of the Network is to develop a working definition of CTE for research purposes (i.e., how to define a CTE student and how to measure CTE participation). A related priority is to identify or develop appropriate measures of CTE participation and outcomes that network members, as well as other CTE researchers, can use. Over the course of the grant, network members will have the opportunity to collaborate on a variety of activities.

We will be reporting on the Network’s progress periodically on this blog, but readers are also encouraged to visit the CTE Research Network website, housed by AIR.

 

Blog post by Corinne Alfeld, program officer in the IES National Center for Education Research (NCER)

For more information about the CTE research network, contact corinne.alfeld@ed.gov. Corinne is also the program officer for NCER’s CTE research topic, which will be accepting grant applications for all types of CTE research later in 2019! (Note that funded studies designed to measure the causal impact of CTE programs or policies may be eligible to join the CTE research network in future years). Sign up for the IES Newsflash to be notified when the NCER Requests for Applications are released.

Classification of Instructional Programs and the 2020 Update

How many bachelor’s degrees in computer science were awarded to women last year? What is Megatronics? What colleges and universities in Rhode Island offer degree programs in Animal Science?1

These are examples of the many questions NCES receives related to fields of postsecondary study. The ability of NCES to provide information on these topics and many related questions rests on the standardized use of the Classification of Instructional Programs (CIP).                         

The CIP, a taxonomy of instructional programs, provides a classification system for the thousands of different programs offered by postsecondary institutions. Its purpose is to facilitate the organization, collection, and reporting of fields of study and program completions.

NCES uses CIP Codes in the Integrated Postsecondary Education Data System (IPEDS) Completion Survey to report how many degrees and certificates were awarded for each field of study. Each field is represented by a 6-digit CIP code, and classified according to 2- and 4-digit prefixes of the code. Each 6-digit CIP Code includes the following elements:  Numeric Code, Title, Description, Illustrative Example and Cross Reference. For example:

 

11.1003 Computer and Information Systems Security/Information Assurance.
A program that prepares individuals to assess the security needs of computer and network systems, recommend safeguard solutions, and manage the implementation and maintenance of security devices, systems, and procedures. Includes instruction in computer architecture, programming, and systems analysis; networking; telecommunications; cryptography; security system design; applicable law and regulations; risk assessment and policy analysis; contingency planning; user access issues; investigation techniques; and troubleshooting.

Examples: [Information Assurance], [IT Security], [Internet Security], [Network Security], [Information Systems Security]
See also: 43.0116 – Cyber/Computer Forensics and Counterterrorism

 

CIP Codes and IPEDS Completions Survey data are used by many different groups of people for many different reasons. For instance, economists use the data to study the emerging labor pools to identify people with specific training and skills. The business community uses IPEDS Completions Survey data to help recruit minority and female candidates in specialized fields, by identifying the numbers of these students who are graduating from specific institutions.  Prospective college students can use the data to look for institutions offering specific programs of postsecondary study at all levels, from certificates to doctoral degrees.

 

 

2020 CIP Update:  Call for Comments

The CIP was initiated in 1980 and has been revised four times since—in 1985, 1990, 2000, and 2010. The 2020 CIP will focus on identifying new and emerging programs of study and presenting an updated taxonomy of instructional program classifications and descriptions. A CIP code will be deleted only when there is strong evidence that it is no longer offered at any IPEDS postsecondary institutions. NCES tentatively plans to implement the CIP 2020 during the 2020–21 IPEDS collection year.

The 2020 CIP revision will be the first time that NCES has solicited comments from the general public about a planned revision. To view the 2020 CIP Federal Register Notice (FRN), please visit: https://www.regulations.gov/document?D=ED-2018-IES-0126-0002.  Comments regarding the 2020 CIP were submitted on the regulations.gov website through March 27, 2019.

UPDATE: Following the public comment and revision period, the final version of CIP:2020 was posted on July 1, 2019: https://nces.ed.gov/ipeds/cipcode/Default.aspx?y=56

 

By Michelle Coon

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1How many bachelor’s degrees in computer science were awarded to women last year? A total of 4,134 women received a bachelor’s degree in computer science for the 2016–17 academic year.

What is Megatronics? A program that prepares individuals to apply mathematical and scientific principles to the design, development and operational evaluation of computer controlled electro-mechanical systems and products with embedded electronics, sensors, and actuators; and which includes, but is not limited to, automata, robots and automation systems. Includes instruction in mechanical engineering, electronic and electrical engineering, computer and software engineering, and control engineering.

What colleges and universities in Rhode Island offer degree programs in Animal Science? Only The University of Rhode Island offers degrees in Animal Science.