IES Blog

Institute of Education Sciences

How Often Do High School Students Meet With Counselors About College? Differences by Parental Education and Counselor Caseload

There are many factors that can affect students’ decisions to apply to college, such as income, school engagement, and coursework.1 Similarly, previous research has reported that students whose parents did not hold a college degree (i.e., first-generation college students) enrolled in college at a lower rate than did peers whose parents held a college degree.2 However, high school counselors may help students choose colleges and apply to them, meaning that students who meet with a counselor about college could be more likely to attend college.3 Counselors may help potential first-generation college students plan for college by providing information that continuing-generation students already have access to via their parents who had attained college degrees themselves. Despite the potential benefits of meeting with a counselor, a school's counselor caseloads may affect its students' counseling opportunities.4

What percentage of high school students met with a counselor about college? How did this percentage vary by parental education and counselor caseload?

Around 47 percent of 2009 ninth-graders were potential first-generation college students whose parents did not hold a college degree (table U1). These students met with a counselor at a lower rate than did students whose parents held a college degree. Figure 1 shows that 72 percent of students whose parents did not hold a college degree met with a counselor, compared with 76 and 82 percent of students whose parents held an associate’s degree and a bachelor’s degree or higher, respectively.


Figure 1. Percentage of students who met with a counselor about college in 2012–13, by average counselor caseload level at the school and parents' highest education level

NOTE: Caseload is a continuous variable based on counselor reports of the average number of students per counselor at the school. Each caseload category accounts for roughly one-third of the sample in the unweighted data. Low caseload refers to counselors responsible for 40 to 299 students, medium caseload refers to counselors responsible for 300 to 399 students, and high caseload refers to counselors responsible for 400 or more students. The category high school degree or less incudes high school diploma or GED and those who started college but did not complete a degree. Respondents who did not know whether they met with a counselor are excluded from the analyses. These represent approximately 8 percent of weighted cases. 
SOURCE: U.S. Department of Education, National Center for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09) Base year, First Follow-up, and 2013 update.


During the senior year of most of the cohort of 2009 ninth-graders, the average counselor caseload at schools attended by these students5 was 375 students per counselor. The average caseload at public schools was 388, and the average caseload at private schools was 202.

Students attending schools with low counselor caseloads met with a counselor about college at a higher rate than did students at schools with high counselor caseloads, when comparing students whose parents had similar attainment levels. For example, at schools with low caseloads, 79 percent of students whose parents held a high school degree or less met with a counselor about college, compared with 70 percent of these students at schools with high caseloads. This pattern is also true for students at schools with low caseloads compared with medium caseloads (i.e., 86 vs. 76 percent of students whose parents held an associate’s degree and 89 vs. 81 percent of students whose parents held a bachelor’s degree), except among students whose parents held a high school degree or less (79 percent was not statistically different from 74 percent). Finally, students whose parents held a high school degree or less met with a counselor at a lower rate than did students whose parents held a bachelor’s degree or higher in each caseload category (i.e., 79 vs. 89 percent for low caseload schools, 74 vs. 81 percent for medium caseload schools, and 70 vs. 77 percent for high caseload schools).

For more information about counselor meetings and college enrollment, check out this Data Point: High School Counselor Meetings About College, College Attendance, and Parental Education.

This blog post uses data from the High School Longitudinal Study of 2009 (HSLS:09), a national study of more than 23,000 ninth-graders and their school counselors in fall 2009. Student sample members answered surveys between 2009 and 2016. Sample members or their parents reported on whether the student met with a counselor about college during the 2012–13 school year (most students’ 12th-grade year).

While data presented here are the most recent data available on the topic, NCES will have new data on high schoolers’ experiences in the 2020s coming soon. In particular, data from the High School and Beyond Longitudinal Study of 2022 (HS&B:22), which also includes information about students’ visits to school counselors, is forthcoming.

Until those data are released, we recommend you access HSLS:09 student and counselor data to conduct your own analyses via NCES’s DataLab.

 

By Catharine Warner-Griffin, AnLar, and Elise Christopher, NCES


[1] See, for example, Fraysier, K., Reschly, A., and Appleton, J. (2020). Predicting Postsecondary Enrollment With Secondary Student Engagement Data. Journal of Psychoeducational Assessment, 38(7), 882–899.

[2] Cataldi, E. F., Bennett, C. T., and Chen, X. (2018). First-Generation Students: College Access, Persistence, and Postbachelor’s Outcomes (2018-421). U.S. Department of Education. Washington, DC: National Center for Education Statistics.

[3] Tang, A. K., and Ng, K. M. (2019). High School Counselor Contacts as Predictors of College Enrollment. Professional Counselor, 9(4), 347–357.

[4] Woods, C. S., and Domina, T. (2014). The School Counselor Caseload and the High School-to-College Pipeline. Teachers College Record, 116(10), 1–30.

[5] These schools are only those sampled in the base year (i.e., students’ 2009 schools).

The Impact of Parent-Mediated Early Intervention on Social Communication for Children with Autism

A key challenge for children with autism is the need to strengthen social communication, something that can be supported early in a child’s development. Dr. Hannah Schertz, professor at Indiana University Bloomington’s School of Education, has conducted a series of IES-funded projects to develop and evaluate the impact of early intervention, mediated through parents, for improving social communication in toddlers with or at risk for autism. We recently interviewed Dr. Schertz to learn more about the importance of guiding parents in the use of mediated learning practices to promote social communication, how her current research connects with her prior research, and what she hopes to accomplish.

Why is parental mediation in early intervention important for very young children with autism? How does it work and why do you focus this approach on improving children’s social communication development?

Headshot of Hannah Schertz

The intervention targets social communication because it is the core autism challenge and it’s important to address concerns early, as signs of autism emerge. Research has found that preverbal social communication is related to later language competency. Our premise is that this foundation will give toddlers a reason to communicate and set the stage for verbal communication. More specifically, joint attention—one preverbal form of social communication—is the key intervention target in our research. It is distinct from requesting/directing or following requests, which are instrumental communications used to accomplish one’s own ends. Joint attention, which takes the partner’s interests and perspectives into account, is an autism-specific challenge whereas more instrumental communication skills are not.

Our research team incorporates a mediated learning approach at two levels—early intervention providers supporting parents and then parents supporting their toddlers. The approach is designed to promote active engagement in the learning process and leverage the parent’s privileged relationship with the child as the venue for social learning. Early intervention providers help parents understand both the targeted social communication outcomes for their children (intervention content) and the mediated learning practices (intervention process) used to promote these child outcomes. As parents master these concepts, they can translate them flexibly into a variety of daily parent-child interactions. This understanding allows parents to naturally integrate learning opportunities with child interests and family cultural/language priorities and preferences. Over time, their accrued knowledge, experience, and increased self-efficacy should prepare them to continually support the child’s social learning even after their participation in the project ends.

How does your more recent work, developing and testing Building Interactive Social Communication (BISC), extend your prior research examining Joint Attention Mediated Learning (JAML)?

Both JAML and BISC address the same goal—supporting social communication as early signs of autism emerge. In JAML, researchers guided parent learning directly while parents incorporated social communication into interaction with their toddlers. BISC extends the intervention by supporting community-based practitioners in facilitating parent learning rather than parents learning directly from the research team. BISC also added a component to address cases in which parents identify child behaviors that substantially interfere with the child’s social engagement.

You recently completed a pilot study to test a new professional development framework for supporting early intervention providers in implementing BISC. Please tell us about the findings of this study. What were the impacts on the early intervention providers, parents, and toddlers?

We tested an early version of BISC to study its preliminary effects on early intervention provider, parent, and child outcomes for 12 provider/parent/child triads. In effect size estimates derived from single-case design data, we found large effects for early intervention provider fidelity (for example, mediating parent learning, guiding parents’ reflection on video-recorded interaction with their toddlers, and supporting active parent engagement) and parent application of mediated learning practices to promote toddler social communication. We also found large effects on child outcomes (social reciprocity, child behavior, and social play) and a small effect on joint attention.

As you begin your larger-scale trial to examine the efficacy of BISC on provider, parent, and child outcomes, what impact do you hope your work will have on the field of early intervention generally and the development of social communication in children with autism more specifically? 

Approximately 165 community-based early intervention practitioners will have learned to support parent learning through direct participation or as control group participants who receive self-study materials. These providers will be equipped to bring this knowledge to their future work. We anticipate that practitioners will experience their implementation role as feasible and effective. Ultimately, toddlers with early signs of autism will have greater access to early, developmentally appropriate, and family-empowering early intervention that directly addresses the core social difficulty of autism. Forthcoming published materials will extend access to other providers, offering an intervention that is more specifically tailored to the needs of very young children with social communication challenges than other approaches.

Is there anything else you would like to share/add regarding your projects? 

I would like to thank my colleagues and project co-principal investigators (Co-PIs) for their expertise and contributions to this work. For our current BISC efficacy project, Co-PI Dr. Patricia Muller (Director of the Center for Evaluation, Policy, and Research) is leading the randomized controlled trial and cost-effectiveness study, and Co-PI Dr. Jessica Lester (professor of Counseling and Educational Psychology) is overseeing the qualitative investigation of parent-child interactions using conversation analysis to explore potential influences on child outcomes. Kathryn Horn coordinates intervention activities, Lucia Zook oversees operational and assessment activities, and Addison McGeary supports recruitment and logistical activities.

This blog was authored by Skyler Fesagaiga, a Virtual Student Federal Service intern for NCSER and graduate student at the University of California, San Diego. The grants in this connected line of research have been managed by Amy Sussman (PO for NCSER’s early intervention portfolio) and Emily Weaver (PO for NCSER’s autism research portfolio).

ED/IES SBIR Special Education Technology is Showcased at the White House Demo Day

On Tuesday, November 7, 2023, the White House’s Office of Science and Technology Policy hosted a Demo Day of American Possibilities at the Showroom in Washington, DC.  The event featured 45 emerging technologies created by innovators through federal research and development programs across areas such as health, national security, AI, robotics, climate, microelectronics, and education. President Biden attended the event and met with several developers to learn about and see demonstrations of the innovations.

An IES-supported project by a Michigan-based Alchemie, the KASI Learning System (KASI), was invited to represent the U.S. Department of Education and its Small Business Innovation Research program, which IES administers.

KASI is an inclusive assistive technology that employs computer vision and multi-sensory augmented reality to support blind and low vision learners in using hand-held physical manipulatives to practice chemistry. A machine learning engine in KASI generates audio feedback and prompts to personalize the experience as learners progress. At the event, the project’s principal investigator and former high school chemistry educator, Julia Winter, demonstrated KASI to leaders in government and to attendees from the assistive technology field.

ED/IES SBIR supported the initial development for KASI through three awards. Based on these awards, Alchemie received funding from angel investors in Michigan, won a commercialization grant from the Michigan Emerging Technology Fund, and is establishing partnerships with publishers in K-12 and higher education. To extend KASI to more topics, Alchemie has won additional SBIR awards from the National Science Foundation, the National Institutes of Health, and the National Institute of Disability, Independent Living, and Rehabilitation Research, and is currently a finalist in the 2024 Vital Prize Challenge competition. KASI has also recently been highlighted in Forbes and Crain’s Detroit Business.

 

 

Stay tuned for updates on KASI and other education technology projects through the ED/IES SBIR program on Twitter, Facebook, and LinkedIn.


About ED/IES SBIR: The Department of Education’s (ED) Small Business Innovation Research (SBIR) program, administered by the Institute of Education Sciences (IES), funds entrepreneurial developers to create the next generation of technology products for learners, educators, and administrators. The program, known as ED/IES SBIR, emphasizes an iterative design and development process and pilot research to test the feasibility, usability, and promise of new products to improve outcomes. The program also focuses on planning for commercialization so that the products can reach schools and end-users and be sustained over time. Millions of students in thousands of schools around the country use technologies developed through ED/IES SBIR.

Edward Metz (Edward.Metz@ed.gov) is the Program Manager of the ED/IES SBIR program.

Laurie Hobbs (Laurie.Hobbs@ed.gov) is the Program Analyst of the ED/IES SBIR program.

NCES Provides New Data Table on School District Structures

The National Center for Education Statistics (NCES) has released a new data table (Excel) on local education agencies (LEAs)1 that serve multiple counties. This new data table can help researchers understand how many LEAs exist and break down enrollment by LEA and county.

Variation in School District Structures

The organizing structures for LEAs vary across the United States. In many areas of the country, LEAs share boundaries with counties or cities. In other areas, there are multiple LEAs within a single county. LEAs also can span multiple counties.

The organizing structures for LEAs or school districts reflect the policies and practices of local and state governments and historical trends across many states. For example, there was a large consolidation in LEAs in the last century as the number of regular school districts decreased from 117,100 in 1939–40 to fewer than 14,900 in 2000–01. In contrast to these declines, the numbers of charter schools and charter school agencies operating outside of regular school district and county frameworks have increased over the past 2 decades.2

Impact of Structural Differences in School Districts

These structural differences can make it challenging for researchers to estimate student enrollment by county and drill down into other data. This is important because the structure of LEAs and their relationships to county boundaries can impact the capability of researchers and policy analysts to align existing county and district data in ways that could better inform education policies.3 In addition, these structures can affect the designs of new surveys and research activities. For example, research or data collections on career and technical education (CTE) activities at the district level would need to accommodate structural differences in where CTE activities are typically provided—that is, in general education districts (as is the case in most states) or through separate CTE-focused LEAs.

New Data Table on LEAs Serving Multiple Counties

NCES has taken valuable steps to increase the amount of information available to the research community about funding crossing district lines. In fiscal year 2018, a data item was added to the School District Finance Survey (F-33) that includes current expenditures made by regional education service agencies (RESAs) and other specialized service agencies (e.g., supervisory unions) that benefit the reporting LEA.4

Our recently released data table (Excel)—which shows the prevalence and enrollment size of LEAs that serve multiple counties—will facilitate a better understanding of how RESA expenditures are included in the district-level total current expenditures and current expenditure per pupil amounts displayed in the annual Revenues and Expenditures for Public Elementary and Secondary School Districts finance tables.

Understanding the New Data Table

The data table uses data from the Common Core of Data (CCD) and Demographic and Geographic Estimates (EDGE) to provide county and student enrollment information on each LEA in the United States (i.e., in the 50 states and the District of Columbia) with a separate row for each county in which the agency has a school presence. The table includes all LEA types, such as regular school districts, independent charter school districts, supervisory union administrative centers, service agencies, state agencies, federal agencies, specialized public school districts, and other types of agencies.

LEA presence within a county is determined by whether it had at least one operating school in the county. School presence within a county is determined by whether there is at least one operating school in the county identified in the CCD school-level membership file. For example, an LEA that is coterminous with a county has one record (row) in the listing. A charter school LEA that serves a region of a state and has a presence in five counties has five records. LEA administrative units, which do not operate schools, are listed in the county in which the agency is located.

In the 2021–22_LEA_List tab, column D shows the “multicnty” (i.e., multicounty) variable. LEAs are assigned one of the following codes:

1 = School district (LEA) is in single county and has reported enrollment.

2 = School district (LEA) is in more than one county and has reported enrollment.

8 = School district (LEA) reports no schools and no enrollment, and the county reflects county location of the administrative unit. 

9 = School district (LEA) reports schools but no enrollment, and the county reflects county location of the schools.

In the Values tab, the “Distribution of local education agencies, by enrollment and school status: 2021–22” table shows the frequency of each of the codes (1, 2, 8, and 9) (i.e., the number of records that are marked with each of the codes in the 2021–22_LEA_List tab):

  • 17,073 LEAs had schools in only one county.
  • 1,962 LEAs had schools located in more than one county and reported enrollment for these schools.
  • 1,110 LEAs had no schools of their own and were assigned to a single county based on the location of the LEA address. (Typically, supervisory union administrative centers are examples of these LEAs.)
  • 416 LEAs had schools located in one county but did not report enrollment for these schools.

 

By Tom Snyder, AIR


[1] Find the official definition of an LEA.

[4] The annual School District Finance Survey (F-33) is collected by NCES from state education agencies and the District of Columbia. See Documentation for the NCES Common Core of Data School District Finance Survey (F-33) for more information.

Designing Culturally Responsive and Accessible Assessments for All Adult Learners

Dr. Meredith Larson, program officer for adult education at NCER, interviewed Dr. Javier Suárez-Álvarez, associate professor and associate director at the Center for Educational Assessment, University of Massachusetts Amherst. Dr. Suárez-Álvarez has served as the project director for the Adult Skills Assessment Project: Actionable Assessments for Adult Learners (ASAP) grant and was previously an education policy analyst in France for the Organisation for Economic Co-operation and Development (OECD), where he was the lead author of the PISA report 21st-Century Readers: Developing Literacy Skills in a Digital World. He and the ASAP team are working on an assessment system to meet the needs of adult education learners, educators, and employers that leverages online validated and culturally responsive banks of literacy and numeracy tasks. In this interview, Dr. Suárez-Álvarez discusses the importance of attending to learners’ goals and cultural diversity in assessment.

How would you describe the current context of assessment for adult education, and how does ASAP fit in it?

In general, the adult education field lacks assessments that meet the—sometimes competing—needs and goals of educators and employers and that attend to and embrace learner characteristics, goals, and cultural diversity. There is often a disconnect where different stakeholders want different things from the same assessments. Educators ask for curriculum-aligned assessments, learners want assessments to help them determine whether they have job-related skills for employment or promotion, and employers want to determine whether job candidates are trained in high-demand skills within their industries.

Despite these differing needs and interests, everyone involved needs assessment resources for lower skilled and culturally diverse learners that are easy to use, affordable or free, and provide actionable information for progress toward personal or occupational goals. ASAP is one of the first attempts to respond to these needs by developing an assessment system that delivers real-time customizable assessments to measure and improve literacy and numeracy skills. ASAP incorporates socioculturally responsive assessment principles to serve the needs of all learners by embracing the uniqueness of their characteristics. These principles involve ensuring that stakeholders from diverse socioeconomic, cultural, linguistic, racial, and ethnic groups are represented in our test design and development activities.

Why is attending to cultural diversity important to ASAP and assessment, and how are you incorporating this into your work?

U.S. Census projections for 2045 predict a shift in the demographic composition of the population from a White majority to a racially mixed majority. This suggests that we should prepare for cultural shifts and ensure our assessments fully embrace socioculturally responsive assessment practices. Without these practices, assessments limit the ability of adults from varied demographic backgrounds to demonstrate their capabilities adequately. Socioculturally responsive assessments are pivotal for representing the growing diversity in the learner population and for uncovering undetected workforce potential.

In ASAP, we are conducting focus groups, interviews, and listening sessions with learners, educators, and employers to understand their needs. We are also co-designing items in collaboration with key stakeholders and building consensus across adult education, workforce, and policy experts. We are developing use cases to understand hypothetical product users and conducting case studies to establish linkages between instruction and assessment as well as across classroom and workplace settings.

How has your background informed your interest in and contributions to ASAP?

As a teenager growing up in Spain, I saw first-hand the possible negative impact assessments could have when they don’t attend to learner goals and circumstances. When I was 15, my English teacher, based on narrow assessments, told my parents I was incapable of learning English, doubted my academic potential, and suggested I forego higher education for immediate employment. Defying this with the support of other teachers and my family, I pursued my passion. I became proficient in English at the age of 25 when I needed it to be a researcher, and I completed my PhD in psychology (psychometrics) at the age of 28.

Many adult students may have heard similar messages from prior teachers based on assessment results. And even now, many of the assessments the adult education field currently uses for these learners are designed by and for a population that no longer represents most learners. These adult learners may be getting advice or feedback that does not actually reflect their abilities or doesn’t provide useful guidance. Unfortunately, not all students are as lucky as I was. They may not have the support of others to counterbalance narrow assessments, and that shouldn’t be the expectation.

What are your hopes for the future of assessments for this adult population and the programs and employers that support them?

I hope we switch from measuring what we know generally how to measure (such as math and reading knowledge on a multiple-choice test) to measuring what matters to test takers and those using assessment results so that they can all accomplish goals in ways that honor individuals’ circumstances. Knowledge and skills—like the real world—are much more than right and wrong responses on a multiple-choice item. I also hope that as we embrace the latest developments in technology, such as AI, we can use them to deliver more flexible and personalized assessments.

In addition, I hope we stop assuming every learner has the same opportunities to learn or the same goals for their learning and that we start using assessments to empower learners rather than just as a measure of learning. In ASAP, for example, the adult learner will decide the type of test they want to take when to take it, the context within which the assessment will be framed, and when, where, and to whom the assessment result will be delivered.


This blog was produced by Meredith Larson (Meredith.Larson@ed.gov), program officer for adult education at NCER.