IES Blog

Institute of Education Sciences

Revenues and Expenditures for Public Schools Rebound for Third Consecutive Year in School Year 2015–16

Revenues and expenditures per pupil on elementary and secondary education increased in school year 2015–16 (fiscal year [FY] 2016), continuing a recent upward trend in the amount of money spent on public preK–12 education. This is the third consecutive year that per pupil revenues and expenditures have increased, reversing three consecutive years of declines in spending between FY 10 and FY 13 after adjusting for inflation. The findings come from the recently released Revenues and Expenditures for Public Elementary and Secondary School Districts: School Year 2015–16 (Fiscal Year 2016).

 

 

The national median of total revenues across all school districts was $12,953 per pupil in FY 16, reflecting an increase of 3.2 percent from FY 15, after adjusting for inflation.[1] This increase in revenues per pupil follows an increase of 2.0 percent for FY 15 and 1.6 percent for FY 14. These increases in revenues per pupil between FY 14 and FY 16 contrast with the decreases from FY 10 to FY 13. The national median of current expenditures per pupil was $10,881 in FY 16, reflecting an increase of 2.4 percent from FY 15. Current expenditures per pupil also increased in FY 15 (1.7 percent) and FY 14 (1.0 percent). These increases in median revenues and current expenditures per pupil between FY 14 and FY 16 represent a full recovery in education spending following the decreases from FY 10 to FY 13.

The school district finance data can help us understand differences in funding levels for various types of districts. For example, median current expenditures per pupil in independent charter school districts were lower than in noncharter and mixed charter/noncharter school districts in 21 out of the 25 states that were able to report finance data for independent charter school districts. Three of the 4 states where median current expenditures were higher for independent charter school districts had policies that affected charter school spending. The new School District Finance Survey (F-33) data offer researchers extensive opportunities to investigate local patterns of revenues and expenditures and how they relate to conditions for other districts across the country.

 

 

By Stephen Q. Cornman, NCES; Malia Howell, Stephen Wheeler, and Osei Ampadu, U.S. Census Bureau; and Lei Zhou, Activate Research


[1] In order to compare from one year to the next, revenues are converted to constant dollars, which adjusts figures for inflation. Inflation adjustments use the Consumer Price Index (CPI) published by the U.S. Department of Labor, Bureau of Labor Statistics. For comparability to fiscal education data, NCES adjusts the CPI from a calendar year basis to a school fiscal year basis (July through June). See Digest of Education Statistics 2016, table 106.70, https://nces.ed.gov/programs/digest/d16/tables/dt16_106.70.asp.

Seeking your feedback on the Regional Educational Laboratory program

IES is seeking feedback about what is working well in the current Regional Educational Laboratories (REL) program, what can be improved, and the kinds of resources and services related to evidence-based practice and data use that are most needed by educators and policymakers to improve student outcomes. We are seeking comments that are practical, specific, and actionable, and that demonstrate a familiarity with the mission and work of the RELs.

We are particularly interested in responses to these questions:

  • What types of materials or tools would be helpful to educators implementing What Works Clearinghouse Practice Guide Recommendations or other evidence-based practices? Are there other ways the RELs could make research evidence more accessible for educators and administrators?
     
  • What types of data and research support are most needed by educators and policymakers to improve student outcomes?
     
  • IES believes that robust partnerships, comprised of a diverse set of stakeholders, are critical to the translation and mobilization of evidence-based practices. Currently, research partnerships are a centerpiece of the REL program. What working models have you observed to be particularly effective in improving student outcomes?  
     
  • In what ways can RELs best serve the country as well as their designated regions?

Please send feedback to NCEE.Feedback@ed.gov by September 6, 2019. 

 

Leading experts provide evidence-based recommendations on using technology to support postsecondary student learning

By Michael Frye and Sarah Costelloe. Both are part of Abt Associates team working on the What Works Clearinghouse.

Technology is part of almost every aspect of college life. Colleges use technology to improve student retention, offer active and engaging learning, and help students become more successful learners. The What Works Clearinghouse’s latest practice guide, Using Technology to Support Postsecondary Student Learning, offers several evidence-based recommendations to help higher education instructors, instructional designers, and administrators use technology to improve student learning outcomes.

IES practice guides incorporate research, practitioner experience, and expert opinions from a panel of nationally recognized experts. The panel that developed Using Technology to Support Postsecondary Student Learning included five experts with many years of experience leading the adoption, use, and research of technology in postsecondary classrooms.  Together, guided by Abt Associates’ review of the rigorous research on the topic, the Using Technology to Support Postsecondary Student Learning offers five evidence-based recommendations:

Practice Recommendations: Use communication and collaboration tools to increase interaction among students and between students and instructors, Minimal evidence. 2. Use varied, personalized, and readily available digital resources to design and deliver instructional content, moderate evidence. 3. Incorporate technology that models and fosters self-regulated learning strategies. Moderate evidence. 4. Use technology to provide timely and targeted feedback on student performance, moderate evidence. 5. Use simulation technologies that help students engage in complex problem-solving, minimal evidence.

 

Each recommendation is assigned an evidence level of minimal, moderate, or strong. The level of evidence reflects how well the research demonstrates the effectiveness of the recommended practices. For an explanation of how levels of evidence are determined, see the Practice Guide Level of Evidence Video.   The evidence-based recommendations also include research-based strategies and examples for implementation in postsecondary settings. Together, the recommendations highlight five interconnected themes that the practice guide’s authors suggest readers consider:

  • Focus on how technology is used, not on the technology itself.

“The basic act of teaching has actually changed very little by the introduction of technology into the classroom,” said panelist MJ Bishop, “and that’s because simply introducing a new technology changes nothing unless we first understand the need it is intended to fill and how to capitalize on its unique capabilities to address that need.” Because technology evolves rapidly, understanding specific technologies is less important than understanding how technology can be used effectively in college settings. “By understanding how a learning outcome can be enhanced and supported by technologies,” said panelist Jennifer Sparrow, “the focus stays on the learner and their learning.”

  • Technology should be aligned to specific learning goals.

Every recommendation in this guide is based on one idea: finding ways to use technology to engage students and enhance their learning experiences. Technology can engage students more deeply in learning content, activate their learning processes, and provide the social connections that are key to succeeding in college and beyond. To do this effectively, any use of technology suggested in this guide must be aligned with learning goals or objectives. “Technology is not just a tool,” said Panel Chair Nada Dabbagh. “Rather, technology has specific affordances that must be recognized to use it effectively for designing learning interactions. Aligning technology affordances with learning outcomes and instructional goals is paramount to successful learning designs.”

  • Pay attention to potential issues of accessibility.

The Internet is ubiquitous, but many households—particularly low-income households and those of recent immigrants and in rural communities—may not be able to afford or otherwise access digital communications. Course materials that rely heavily on Internet access may put these students at a disadvantage. “Colleges and universities making greater use of online education need to know who their students are and what access they have to technology,” said panelist Anthony Picciano. “This practice guide makes abundantly clear that colleges and universities should be careful not to be creating digital divides.”

Instructional designers must also ensure that learning materials on course websites and course/learning management systems can accommodate students who are visually and/or hearing impaired. “Technology can greatly enhance access to education both in terms of reaching a wide student population and overcoming location barriers and in terms of accommodating students with special needs,” said Dabbagh. “Any learning design should take into consideration the capabilities and limitations of technology in supporting a diverse and inclusive audience.”

  • Technology deployments may require significant investment and coordination.

Implementing any new intervention takes training and support from administrators and teaching and learning centers. That is especially true in an environment where resources are scarce. “In reviewing the studies for this practice guide,” said Picciano, “it became abundantly clear that the deployment of technology in our colleges and universities has evolved into a major administrative undertaking. Careful planning that is comprehensive, collaborative, and continuous is needed.”

“Hardware and software infrastructure, professional development, academic and student support services, and ongoing financial investment are testing the wherewithal of even the most seasoned administrators,” said Picciano. “Yet the dynamic and changing nature of technology demands that new strategies be constantly evaluated and modifications made as needed.”

These decisions are never easy. “Decisions need to be made,” said Sparrow, “about investment cost versus opportunity cost. Additionally, when a large investment in a technology has been made, it should not be without investment in faculty development, training, and support resources to ensure that faculty, staff, and students can take full advantage of it.”

  • Rigorous research is limited and more is needed.

Despite technology’s ubiquity in college settings, rigorous research on the effects of technological interventions on student outcomes is rather limited. “It’s problematic,” said Bishop, “that research in the instructional design/educational technology field has been so focused on things, such as technologies, theories, and processes, rather than on the problems we’re trying to solve with those things, such as developing critical thinking, enhancing knowledge transfer, and addressing individual differences. It turns out to be very difficult to cross-reference the instructional design/educational technology literature with the questions the broader field of educational research is trying to answer.”

More rigorous research is needed on new technologies and how best to support instructors and administrators in using them. “For experienced researchers as well as newcomers,” said Picciano, “technology in postsecondary teaching and learning is a fertile ground for further inquiry and investigation.”

Readers of this practice guide are encouraged to adapt the advice provided to the varied contexts in which they work. The five themes discussed above serve as a lens to help readers approach the guide and decide whether and how to implement some or all of the recommendations.

Download Using Technology to Support Postsecondary Student Learning from the What Works Clearinghouse website at https://ies.ed.gov/ncee/wwc/PracticeGuide/25.

 

Announcing the Condition of Education 2019 Release

We are pleased to present The Condition of Education 2019, a congressionally mandated annual report summarizing the latest data on education in the United States. This report is designed to help policymakers and the public monitor educational progress. This year’s report includes 48 indicators on topics ranging from prekindergarten through postsecondary education, as well as labor force outcomes and international comparisons.

In addition to the regularly updated annual indicators, this year’s spotlight indicators show how recent NCES surveys have expanded our understanding of outcomes in postsecondary education.

The first spotlight examines the variation in postsecondary enrollment patterns between young adults who were raised in high- and low-socioeconomic status (SES) families. The study draws on data from the NCES High School Longitudinal Study of 2009, which collected data on a nationally representative cohort of ninth-grade students in 2009 and has continued to survey these students as they progress through postsecondary education. The indicator finds that the percentage of 2009 ninth-graders who were enrolled in postsecondary education in 2016 was 50 percentage points larger for the highest SES students (78 percent) than for the lowest SES students (28 percent). Among the highest SES 2009 ninth-graders who had enrolled in a postsecondary institution by 2016, more than three-quarters (78 percent) first pursued a bachelor’s degree and 13 percent first pursued an associate’s degree. In contrast, the percentage of students in the lowest SES category who first pursued a bachelor’s degree (32 percent) was smaller than the percentage who first pursued an associate’s degree (42 percent). In addition, the percentage who first enrolled in a highly selective 4-year institution was larger for the highest SES students (37 percent) than for the lowest SES students (7 percent).

The complete indicator, Young Adult Educational and Employment Outcomes by Family Socioeconomic Status, contains more information about how enrollment, persistence, choice of institution (public, private nonprofit, or private for-profit and 2-year or 4-year), and employment varied by the SES of the family in which young adults were raised.

 


Among 2009 ninth-graders who had enrolled in postsecondary education by 2016, percentage distribution of students' first credential pursued at first postsecondary institution, by socioeconomic status: 2016

1 Socioeconomic status was measured by a composite score of parental education and occupations and family income in 2009.
NOTE: Postsecondary outcomes are as of February 2016, approximately 3 years after most respondents had completed high school. Although rounded numbers are displayed, the figures are based on unrounded data. Detail may not sum to totals because of rounding.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), Base Year and Second Follow-up. See Digest of Education Statistics 2018, table 302.44.


 

The second spotlight explores new data on postsecondary outcomes, including completion and transfer rates, for nontraditional undergraduate students. While the Integrated Postsecondary Education Data System formerly collected outcomes data only for first-time, full-time students, a new component of the survey includes information on students who enroll part time, transfer among institutions, or leave postsecondary education temporarily but later enroll again. These expanded data are particularly important for 2-year institutions, where higher percentages of students are nontraditional. For example, the indicator finds that, among students who started at public 2-year institutions in 2009, completion rates 8 years after entry were higher among full-time students (30 percent for first-time students and 38 percent for non-first-time students) than among part-time students (16 percent for first-time students and 21 percent for non-first-time students). Also at public 2-year institutions, transfer rates 8 years after entry were higher among non-first-time students (37 percent for part-time students and 30 percent for full-time students) than among first-time students (24 percent for both full-time and part-time students).

For more findings, including information on outcomes for nontraditional students at 4-year institutions, read the complete indicator, Postsecondary Outcomes for Nontraditional Undergraduate Students.

 


Percentage distribution of students' postsecondary outcomes 8 years after beginning at 2-year institutions in 2009, by initial attendance level and status: 2017

# Rounds to zero.
1 Attendance level (first-time or non-first-time student) and attendance status (full-time or part-time student) are based on the first full term (i.e., semester or quarter) after the student entered the institution. First-time students are those who had never attended a postsecondary institution prior to their 2009–10 entry into the reporting institution.
2 Includes certificates, associate’s degrees, and bachelor’s degrees. Includes only those awards that were conferred by the reporting institution (i.e., the institution the student entered in 2009–10); excludes awards conferred by institutions to which the student later transferred.
3 Refers to the percentage of students who were known transfers (i.e., those who notified their initial postsecondary institution of their transfer). The actual transfer rate (including students who transferred, but did not notify their initial institution) may be higher.
4 Includes students who dropped out of the reporting institution and students who transferred to another institution without notifying the reporting institution.
NOTE: The 2009 entry cohort includes all degree/certificate-seeking undergraduate students who entered a degree-granting institution between July 1, 2009, and June 30, 2010. Student enrollment status and completion status are determined as of August 31 of the year indicated; for example, within 8 years after the student’s 2009–10 entry into the reporting institution means by August 31, 2018. Detail may not sum to totals because of rounding. Although rounded numbers are displayed, the figures are based on unrounded data.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Winter 2017–18, Outcome Measures component; and IPEDS Fall 2009, Institutional Characteristics component. See Digest of Education Statistics 2018, table 326.27.


 

The Condition of Education includes an At a Glance section, which allows readers to quickly make comparisons within and across indicators, and a Highlights section, which captures key findings from each indicator. The report also contains a Reader’s Guide, a Glossary, and a Guide to Sources that provide additional background information. Each indicator provides links to the source data tables used to produce the analyses.

As new data are released throughout the year, indicators will be updated and made available on The Condition of Education website. In addition, NCES produces a wide range of reports and datasets designed to help inform policymakers and the public. For more information on our latest activities and releases, please visit our website or follow us on TwitterFacebook, and LinkedIn.

 

By James L. Woodworth, NCES Commissioner

Equity Through Innovation: New Models, Methods, and Instruments to Measure What Matters for Diverse Learners

In today’s diverse classrooms, it is both challenging and critical to gather accurate and meaningful information about student knowledge and skills. Certain populations present unique challenges in this regard – for example, English learners (ELs) often struggle on assessments delivered in English. On “typical” classroom and state assessments, it can be difficult to parse how much of an EL student’s performance stems from content knowledge, and how much from language learner status. This lack of clarity makes it harder to make informed decisions about what students need instructionally, and often results in ELs being excluded from challenging (or even typical) coursework.

Over the past several years, NCER has invested in several grants to design innovative assessments that will collect and deliver better information about what ELs know and can do across the PK-12 spectrum. This work is producing some exciting results and products.

  • Jason Anthony and his colleagues at the University of South Florida have developed the School Readiness Curriculum Based Measurement System (SR-CBMS), a collection of measures for English- and Spanish-speaking 3- to 5-year-old children. Over the course of two back-to-back Measurement projects, Dr. Anthony’s team co-developed and co-normed item banks in English and Spanish in 13 different domains covering language, math, and science. The assessments are intended for a variety of uses, including screening, benchmarking, progress monitoring, and evaluation. The team used item development and evaluation procedures designed to assure that both the English and Spanish tests are sociolinguistically appropriate for both monolingual and bilingual speakers.

 

  • Daryl Greenfield and his team at the University of Miami created Enfoque en Ciencia, a computerized-adaptive test (CAT) designed to assess Latino preschoolers’ science knowledge and skills. Enfoque en Ciencia is built on 400 Spanish-language items that cover three science content domains and eight science practices. The items were independently translated into four major Spanish dialects and reviewed by a team of bilingual experts and early childhood researchers to create a consensus translation that would be appropriate for 3 to 5 year olds. The assessment is delivered via touch screen and is equated with an English-language version of the same test, Lens on Science.

  • A University of Houston team led by David Francis is engaged in a project to study the factors that affect assessment of vocabulary knowledge among ELs in unintended ways. Using a variety of psychometric methods, this team explores data from the Word Generation Academic Vocabulary Test to identify features that affect item difficulty and explore whether these features operate similarly for current, former, as well as students who have never been classified as ELs. The team will also preview a set of test recommendations for improving the accuracy and reliability of extant vocabulary assessments.

 

  • Researchers led by Rebecca Kopriva at the University of Wisconsin recently completed work on a set of technology-based, classroom-embedded formative assessments intended to support and encourage teachers to teach more complex math and science to ELs. The assessments use multiple methods to reduce the overall language load typically associated with challenging content in middle school math and science. The tools use auto-scoring techniques and are capable of providing immediate feedback to students and teachers in the form of specific, individualized, data-driven guidance to improve instruction for ELs.

 

By leveraging technology, developing new item formats and scoring models, and expanding the linguistic repertoire students may access, these teams have found ways to allow ELs – and all students – to show what really matters: their academic content knowledge and skills.

 

Written by Molly Faulkner-Bond (former NCER program officer).