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ResearchSeries titleMLDSC Research Series
The MLDS Center research series is a forum to bring together researchers, policy makers, and practitioners to discuss MLDS Center research works in progress. Additionally, we invite experts from across the State to present research studies that may inform MLDS Center research projects.

Note: The MLDS Center research series will return in the Fall of 2020.

    • Date: Thursday, June 4, 2020 12:30-1:30 PM

      Presenter: Dr. Rachel Durham

      Topic: Student and School Predictors of Career and College Persistence among Baltimore City Schools Graduates: Research in Progress to Identify Differences between Career and College Readiness

      Presentation Abstract: Recently, policies supporting college readiness have shifted to Career and College Readiness. However, whether readiness for ‘career’ and ‘college’ is a singular construct is a hypothesis requiring empirical research. In-progress research will be presented that attempts to address this gap, investigating whether the same high school factors (e.g., grades, assessments, CTE) predict college persistence and workforce persistence over the first four years after graduation. Data for three consecutive cohorts of graduates from Baltimore City Public Schools progressing to both college and the workforce are examined, as well as students' academic profiles from high school and their high schools’ characteristics. Several differences between factors that predict college persistence relative to workforce persistence are found. The relative importance of different factors for each pathway and their implications for policy will be discussed.

      Presenter Bio:

      Rachel E. Durham, Ph.D., is an Associate Research Scientist at the Baltimore Education Research Consortium (BERC) within the School of Education at Johns Hopkins University. She currently serves as BERC’s Research Co-Director, teaches methods and statistics, and has research interests in college access, adult readiness, and the transition to adulthood. She is also interested in community schools, school climate, program evaluation, as well as research-practice partnerships' impact on practitioners’ capacity for research and data use.

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    • Date: Thursday, May 7, 2020 12:30-1:30 PM

      Presenters: Dr. Mark Lachowicz and Dr. Terry Shaw

      Topic: The MLDS Synthetic Data Project: Evaluation of Research Utility and Disclosure Risk

      Presentation Abstract: The Maryland Longitudinal Data System (MLDS) Center is a central repository of highly confidential student and workforce data. The Institute of Educational Sciences funded a project to create, evaluate, and potentially release Synthetic versions of the MLDS data. We will start this presentation with a brief overview of synthetic data, and we will present an evaluation of the research validity and disclosure risk associated with the synthetic datasets created. The evaluation of research validity of the synthetic data will include efforts to assess the general utility (e.g., comparisons of variable distributions between the real and synthetic data) and specific utility (e.g., comparisons of parameter estimates from statistical analyses between the real and synthetic data). We will also present another vital step in our synthetic data project: the assessment of disclosure risk, which is required to ensure compliance with laws governing the confidentiality of state held data. Finally, we will discuss the benefits of the synthetic data for researchers who do not have access to the real data.

      Presenter Bio:

      Dr. Mark Lachowicz is a postdoctoral research associate with the University of Maryland, College Park. He joined the Synthetic Data Project in the fall of 2018 after completing his doctorate in Quantitative Methods from Vanderbilt University. His expertise is in methodology for the design and analysis of research studies with clustered and longitudinal data.

      Dr. Terry Shaw is an Associate Professor at the University of Maryland, School of Social Work and Research Director for The Institute for Innovation and Implementation. Dr. Shaw’s background and interests focus on leveraging existing administrative data systems to improve state policy and practice related to child and family health. Dr. Shaw uses administrative data to examine the pathways into and through child serving systems, focusing on opportunities for state systems to collaborate, understand service overlaps, improve overall service delivery and address the multiple needs of the children and families involved with these systems.

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    • Date: Thursday, March 5, 2020 12:30-1:30 PM

      Presenters: Drs. Jill Farrell and Terry Shaw, University of Maryland School of Social Work

      Topic: The Power of University/Agency Partnerships – Examples in Juvenile Services and Child Welfare

      Presentation Abstract: Research partnerships between universities and human service agencies offer mutually beneficial opportunities to leverage the research infrastructure and resources of universities to generate information agencies can use to improve overall policy and practice. The University of Maryland, School of Social Work has a long history of collaborating with state and local agencies in Maryland and nationally. Presenters will discuss the formation and structure of their respective long-time research partnerships with the Maryland Department of Juvenile Services (DJS) and Department of Human Services (DHS) including a brief overview of each system, the types of projects undertaken, and their current work with agencies. Dr. Farrell will discuss research with DJS that focuses on enhancing case management practices to reduce recidivism and increase successful outcomes. Dr. Shaw will discuss research with DHS that focuses on understanding foster care reentry and opportunities to reduce recidivism. A discussion will focus on future research possibilities with MLDS data.

      Presenter Bio:

      Jill Farrell is a Research Assistant Professor at the University of Maryland, School of Social Work and Deputy Director of Research and Evaluation for The Institute for Innovation and Implementation. Dr. Farrell’s background and interests concentrate on improving experiences and outcomes for youth involved with child- and family-serving systems, particularly the juvenile justice system. She has served as a primary research partner to the Maryland Department of Juvenile Services for over 15 years, collaborating on the development, implementation, and evaluation of evidence-based case management practices, assessment tools, and programs for youth. Prior to joining the School of Social Work, Dr. Farrell conducted applied policy research at the University of Maryland’s Innovations Institute, the Institute for Governmental Service and Research, the Urban Institute, and the Maryland State Commission on Criminal Sentencing Policy. She holds both a Ph.D. and M.A. in Criminology and Criminal Justice from University of Maryland, and a B.A. with distinction in Psychology from Boston College.

      Terry Shaw is an Associate Professor at the University of Maryland, School of Social Work and Research Director for The Institute for Innovation and Implementation. Dr. Shaw’s background and interests focus on leveraging existing administrative data systems to improve state policy and practice related to child and family health. Dr. Shaw uses administrative data to examine the pathways into and through child serving systems, focusing on opportunities for state systems to collaborate, understand service overlaps, improve overall service delivery and address the multiple needs of the children and families involved with these systems. Dr. Shaw has over two decades of experience and expertise in developing the infrastructure, relationships and programming structure to implement multi-agency data linking systems and has extensive experience utilizing longitudinal data systems to answer questions related to service outcomes in order to inform policy and practice.

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    • Date: Thursday, February 6, 2020 12:30-1:30 PM

      Presenters: Dr. Megean Garvin, Director of Research and Assessment at the Maryland Center for Computing Education, University System of Maryland

      Topic: Maryland Center for Computing Education: State Case Study of Computing Education Governance

      Presentation Abstract: Maryland Center for Computing Education (MCCE) was established by legislation in 2018 to expand access to high-quality computing education by strengthening educator skills and increasing the number of computing teachers in Maryland’s public schools. Teacher capacity is required to provide all students with access and increase student participation in meaningful computing education experiences. This case study examines how the State began broadening participation in computing for public school students from 2010 through 2016. Using data from the MLDS, the research examines the different policy initiatives at various governance levels and reveals the successes achieved and the persistent barriers to democratizing computing education.

      Presenter Bio: Megean Garvin, Ph.D., is the Director of Research and Assessment at the Maryland Center for Computing Education, University System of Maryland. Megean's research focuses on broadening participation in computing through policy and organizational change from the classroom to the state levels of education. She obtained her Ph.D. from the University of Maryland.

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    • Date: Thursday, December 5, 2019 12:30-1:30 PM

      Presenters: Dr. Bess A. Rose, Statistician, MLDS Center and University of Maryland, School of Social Work

      Topic: Long-term Educational and Workforce Outcomes of Adolescent Poverty and Homelessness

      Presentation Abstract: The MLDS Center focuses on the relationships of K12 experiences with postsecondary and workforce outcomes. The Center has been conducting ongoing research related to the roles of household poverty and school concentrated poverty in these relationships. Some of this research informed the recommendations of Maryland’s Commission on Innovation and Excellence in Education (“Kirwan Commission”) to improve the state’s public education system. At their request, the Center has continued to examine the variation among levels and types of poverty. This presentation will use data from the MLDS to examine homelessness as an extreme form of poverty and its role in long-term college and workforce outcomes. Results from multilevel models will be presented as predicted outcomes (high school dropout, college enrollment, and wages) for 3 groups: homeless adolescents, adolescents who experienced poverty but not homelessness, and adolescents who never experienced homelessness or poverty. All model results will control for race/ethnicity, baseline academic performance, and school composition. The research will inform practitioners and policymakers about the impact of homelessness during adolescence on college and workforce outcomes.

      Presenter Bio: Bess A. Rose, Ed.D., is a statistician with the University of Maryland School of Social Work and the MLDS Center research team. She has extensive experience with quantitative and mixed methods evaluations and research studies. Previously, she was a Senior Study Director at Westat and Research and Evaluation Coordinator at the Maryland State Department of Education. She completed her doctorate at the Johns Hopkins School of Education with support from an IES Pre-Doctoral Research Trainee fellowship. She has also advised master’s students in technical writing at Goucher College’s Graduate Programs in Education and taught undergraduate courses in English and Comparative Literature at the University at Buffalo.

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    • Date: Thursday, November 7, 2019 12:30 PM - 1:30 PM

      Presenters: Dr. Wade Jacobsen, Assistant Professor, University of Maryland

      Topic: Juvenile Arrest and Peer Relationships: Findings from Rural Schools in Pennsylvania and Iowa*

      *Note: Each semester we select one external research project to be the focus of the Research Series. We are interested in this topic because it will help inform our work as we begin to gather student discipline and juvenile justice data.

      Presentation Abstract: Friends are a key source of social capital during adolescence. They provide emotional support and transmit attitudes and skills that are important for academic success and wellbeing. Prior research has hypothesized that juvenile justice system involvement may constrain adolescent peer relationships, resulting in fewer friendships with normative peers, what we refer to as interpersonal exclusion. Our study examines the association between arrest and friendship ties among school peers. We extend prior work by focusing on three mechanisms of friendship selection implied in stigma theories: rejection, withdrawal, and homophily. Analyses of 48 rural peer networks over six time points are consistent with hypotheses about rejection and withdrawal. Arrested youth are less likely to receive friendship ties from school peers, and also less likely to extend them. Furthermore, these negative associations are attenuated by higher levels of antisocial or deviant behavior among peers, suggesting results are more heavily driven by exclusion from normative peers. We do not find evidence that arrested youth are more likely to prefer other arrested youth as friends. Overall, our findings speak to how juvenile arrest may contribute to social inequality among rural youth by excluding already disadvantaged youth from normative peer networks.

      Presenter Bio: Dr. Wade Jacobsen is an Assistant Professor in the Department of Criminology and Criminal Justice at the University of Maryland and a Faculty Associate at the Maryland Population Research Center. His research investigates the roles of schools and the criminal justice system in shaping child wellbeing and inequality. His current work examines social and behavioral outcomes of school punishment and juvenile arrest. He is particularly interested in (1) how these formal sanctions affect a child or adolescent's social networks, including family and friendship networks, and (2) understanding the extent to which these network changes can explain associations of punishment with subsequent behavior and educational outcomes. Dr. Jacobsen earned a PhD from the Department of Sociology and Criminology at Penn State University and MS degree from the Department of Sociology at Brigham Young University. He also spent two years as a Research Specialist in the Center for Research on Child Wellbeing at the Office of Population Research at Princeton University.


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    • Date: 10/03/2019

      Presenters: Dr. Angela K. Henneberger & Dr. Bess Rose, MLDS Center and University of Maryland School of Social Work

      Topic: Multiple Membership Modeling Versus Traditional Multilevel Modeling for Handling Student Mobility in Maryland

      Presentation Abstract: Researchers using data from the Maryland Longitudinal Data System (MLDS) are often interested in the effects of both student-level variables and school-level variables on long-term educational and workforce outcomes. Thus the longitudinal nature of the data in the MLDS requires a statistical approach that can disentangle effects at multiple levels of the educational hierarchy. However, following students over time means that they are likely to attend more than one school. The traditional statistical approach, hierarchical linear modeling or multilevel modeling, assume that each student is nested within only one school, an assumption that is violated when students are mobile. Multiple membership modeling (Beretvas, 2010) presents a viable solution for correctly modeling the effects of student-level and school-level variables on outcomes in data with mobile students. The purpose of this presentation is to: (1) investigate the prevalence of multiple memberships across cohorts and grade levels for students in Maryland public schools; (2) investigate the prevalence of multiple membership for specific subgroups of students and schools in Maryland public schools; and (3) apply multiple membership modeling and compare the results to those obtained from traditional multilevel modeling approaches.

      Presenter Bio: Angela K. Henneberger is Principal Investigator and Director of Research of the MLDSC. She is a Research Assistant Professor at the University of Maryland School of Social Work. Dr. Henneberger’s research applies advanced quantitative methods to examine the academic, social, emotional, and behavioral development of children and adolescents, with a specific focus on at-risk students. Dr. Henneberger received her Ph.D. from the University of Virginia, where she was awarded an Institute of Education Sciences (IES) predoctoral fellowship. She completed a postdoctoral fellowship at the Pennsylvania State University in the Prevention and Methodology Training (PAMT) program.

      Bess A. Rose is a statistician with the University of Maryland School of Social Work and the MLDS Center research team. She has extensive experience with quantitative and mixed methods evaluations and research studies. Previously, she was a Senior Study Director at Westat and Research and Evaluation Coordinator at the Maryland State Department of Education. She completed her doctorate at the Johns Hopkins School of Education with support from an IES Pre-Doctoral Research Trainee fellowship. She has also advised master’s students in technical writing at Goucher College’s Graduate Programs in Education and taught undergraduate courses in English and Comparative Literature at the University at Buffalo.


      Presentation Link

    • Date: 05/02/2019

      Presenters: Laura Stapleton, PhD, Professor and Associate Dean,Research, Innovation and Partnerships

      Topic: An Update on the MLDS Synthetic Data Project

      Presentation Abstract: There is demand among policy-makers for the use of state education longitudinal data systems, yet laws and policies regulating data disclosure limit access to such data, and security concerns and risks remain high. Well-developed synthetic datasets that statistically mimic the relations among the variables in the data from which they were derived, but which contain no records that represent actual persons, present a viable solution to these laws, policies, concerns, and risks. In this presentation, we present our in-progress development of a synthetic data system and highlight potential applications of synthetic data. We begin with an overview of synthetic data, what it is, how it has been utilized thus far, and the potential benefits and concerns in its application to education data systems. We then describe the project, funded by a grant from the State Longitudinal Data Systems Program at the U.S. Department of Education to the Maryland State Department of Education. In this project, we have proposed the steps required to synthesize the data from the Maryland Longitudinal Data System. We review the challenges that we have confronted, and the successes experienced, in the development of our synthetic data system and explain the process going forward for validity testing and data disclosure risk evaluation.

      Presenter Bio: Laura M. Stapleton is Associate Dean for Research, Innovation, and Partnerships. She is also a Professor in Measurement, Statistics and Evaluation (EDMS) in the Department of Human Development and Quantitative Methodology at the University of Maryland and served as the Associate Director of the Research Branch of the Maryland State Longitudinal Data System Center from 2013-2018. She joined the faculty of the college in Fall 2011 after being on the faculty in Psychology at the University of Maryland, Baltimore County and in Educational Psychology at the University of Texas, Austin. She currently serves as Associate Editor of AERA Open and each year teaches as part of the faculty of the National Center for Education Research funded Summer Research Training Institute on Cluster Randomized Trials at Northwestern University. Prior to earning her Ph.D. in Measurement, Statistics and Evaluation, she was an economist at the Bureau of Labor Statistics and, subsequently, conducted educational research at the American Association of State Colleges and Universities and as Associate Director of institutional research at the University of Maryland.


      Presentation Link

    • Date: 04/04/2019

      Presenters: Dr. Bess A. Rose, Statistician, MLDS Center and University of Maryland, School of Social Work


      Topic: Applying Longitudinal Data Analysis Methods to Examine Poverty as a Predictor of Wage Trajectories


      Presentation Abstract: “In life, everything that is truly important is longitudinal.” – John Willett

      Most studies conducted using MLDS data have examined wages as an outcome variable, and estimated the relationship of schooling experiences with total wages. However, we have not yet examined the full picture of how individuals’ wages change over time, and the effect of K12 and postsecondary education experiences on their wage trajectories. This presentation will examine one method researchers could use to examine wage patterns over time in more detail by using repeated measure or growth curve modeling. This method would enable researchers to estimate individuals’ initial outcomes at a set point in time (e.g., in the first quarter after high school graduation), their estimated subsequent growth for each increment of time (e.g., quarter), and the impact of individual events (e.g., enrolling in college, obtaining a college degree) or policy changes (e.g., making two-year college tuition free to all income-eligible individuals) on the shape of these trajectories. This presentation will provide an overview of growth modeling techniques and an applied example using MLDS data from a study of the impact of student and school poverty and race/ethnicity on long-term outcomes. These analyses will further clarify the roles of poverty and race/ethnicity on individuals’ wages over time.


      Presentation Link

    • Date: 03/07/2019

      Presenters: F. Chris Curran, PhD, is an Assistant Professor of Public Policy at the UMBC School of Public Policy where he teaches and advises in the education policy track and the evaluation and analytic methods track. His research focuses on early elementary education, with a specific focus on early science achievement, as well as on issues of school discipline and safety. His research has been published in journals such as Educational Researcher and Educational Evaluation and Policy Analysis and has been featured in outlets such as Education Week and Politico. Previously, Dr. Curran was a middle school science teacher and department chair. More on his work can be found here


      Topic: Early Elementary Science Test Score Gaps: Differences by Race/Ethnicity, Gender, and Language Backgrounds


      Presentation Abstract: Student achievement in science is a pressing goal of educators and policymakers. However, until recently, there has been limited research on the performance of students in science in the earliest grades of elementary school. Recent evidence suggests that the earliest years of elementary school may be critical for setting trajectories of science learning as well as disparities in such achievement between subgroups. This talk draws on several recent studies that examine science achievement in the earliest grades of school (kindergarten to second grade). In particular, it explores how science achievement varies by race/ethnicity and gender and how these disparities compare to early test score gaps in other subject areas. Findings suggest that early elementary test score gaps are often larger in science than in mathematics or reading. For example, while Asian students perform as well or better than their white peers in mathematics and reading, they lag significantly behind in early science test score performance. This work explores some of the predictors of these differences, finding an important role for language and immigration status as well as variability explained by both in and out of school factors. Implications for policy and practice in early STEM are discussed.

      Each semester the MLDS Center invites one external scholar who is engaged in research that can inform current MLDS research initiatives. Dr. Curran will help to inform the MLDS Center’s research efforts on STEM achievement.


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    • Date: 02/07/2019

      Presenters: Dr. Tracy M. Sweet & Tessa L. Johnson


      Topic: Using Social Network Methods to Inform MLDS Center Research: An Example with Student Mobility


      Presentation Abstract: A social network consists of a group of individuals (or entities) and the relationships (or connections) among them. Examples of social networks outside of Facebook and Twitter include friendship ties among a group of students in a classroom, co-authorship, or other types of collaborative networks, and childcare sharing networks. Due to the structure of these data, social networks have unique methods for analysis. We will present an introduction to social network analysis, a brief introduction to social network models, and discuss how quantitative methods used for network analysis can be used in MLDS research. As an example, we use network methods to explore student mobility across schools within several counties in the state of Maryland.


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    • Date: 12/06/2018

      Presenters: Dr. Dawnsha R. Mushonga, Investigator, MLDS Center and Postdoctoral Fellow, University of Maryland, School of Social Work


      Topic: Using Longitudinal Data to Assess Long-Term Outcomes Associated with Poverty in Maryland Students


      Presentation Abstract: Poverty affects more than 15 million children who are disproportionately racial/ethnic minorities and has been linked to negative outcomes such as poor academic achievement and decreased lifelong earnings. Extant literature has highlighted the profound effects of poverty for students exposed for longer periods of time; however, few studies have focused on disentangling the roles of poverty and race on students’ long-term outcomes. To better understand the multifaceted role of poverty, this study used data from the Maryland Longitudinal Data System (MLDS) to examine the relation between student-level poverty and race and school-level poverty and racial composition to predict students’ long-term educational and career outcomes. This presentation provides an update on findings presented in July to the Commission on Innovation and Excellence in Education. Our findings aid policy makers and practitioners in identifying at-risk students and targeting interventions at the individual and school levels to combat the negative effects of poverty and promote students’ academic and career success.


      Presentation Link

    • Date: 11/01/2018

      Presenters: Dr. Mathew C. Uretsky, Investigator, MLDS Center & Dr. Angela K. Henneberger, Research Director, MLDS Center


      Topic: Remedial Coursework in Maryland Community Colleges: Disentangling Student and High School Level Predictors


      Presentation Abstract: Remedial courses at community colleges are designed to develop the skills of students who are underprepared for the academic rigor of college courses. A significant portion of students in Maryland and nationwide are assessed to need remedial coursework each year. This study used data from the Maryland Longitudinal Data System (MLDS) to examine the individual- and high school-level characteristics that predict the need for remediation in Maryland community colleges. The results can help policy makers and practitioners identify at-risk students before they arrive at college in order to help better prepare them for college-level coursework and reduce the need for remediation among recent high school graduates.


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    • Date: 10/04/2018

      Presenters: Romona C. Carrico, Christopher Wohn, and Amir François


      Topic: Problem, Research, Action: Poverty Measurement Transition in Baltimore City Public Schools


      Presentation Abstract: This presentation will cover the methodology of the longitudinal and historical poverty analysis and subsequent school-level and student subgroup analyses using data from Baltimore City Public Schools. The second part of the presentation will discuss how the Office of Achievement and Accountability (OAA) in Baltimore City Public Schools assessed the impact of the change in the poverty measurement process on school-level poverty rates using a multivariate prediction model.


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    • Date: 05/03/2018

      Presenters: Bess A. Rose, Dawnsha R. Mushonga, and Angela K. Henneberger


      Topic: The Relationship Between Poverty and Long-Term Student Outcomes: Disentangling the Effects of Individual and School Poverty


      Presentation Abstract: The MLDS Center is examining the effects of school-level concentrated poverty and individual student poverty on outcomes such as high school graduation, entry and persistence in post-secondary education, entry into the workforce, and wages earned. From previous research, we know that both individual poverty and school-level poverty are significant barriers to educational success, but the relative impact of these factors and how they interact is unclear. We used statewide longitudinal data to examine the relative impact and interaction of student- and school-level poverty on long-term outcomes. Preliminary findings suggest that defining poverty based on students’ status at a single point in time, rather than considering their history of poverty, may lead to underestimating poverty’s effects. Findings also suggest that while both student poverty and school-level concentrations of poverty have a significant and negative effect on students’ outcomes, the effect of school-level poverty is considerably larger than that of individual poverty alone.


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    • Date: 04/19/2018

      Presenters: Dr. Nolan G. Pope


      Topic: The Multidimensional Impact of Teachers on Students


      Presentation Abstract: For decades, policymakers and researchers have used value-added models that rely solely on student test scores to measure teacher quality. However, since teaching ability is multidimensional, test-score value-added measures of teacher quality may not fully capture the impact of teachers on students. In this talk, Dr. Pope will present research using test-score and non-test-score measures of student achievement and behavior from over a million students in the Los Angeles Unified School District to estimate multiple dimensions of teacher quality. Results indicate that test-score and non- test-score measures of teacher quality are only weakly correlated, and that both measures of teacher quality affect students’ performance in high school. Results from a simulation study removing teachers based on both dimensions of teacher quality show improvement in most long-term student outcomes by over 50 percent compared to removal of teachers using test scores alone. The long-term effects of teachers in later grades are larger than in earlier grades and that performance in core elementary school subjects matters more for long-term outcomes than other subjects.


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    • Date: 02/01/2018

      Presenters: Heath Witzen, Research Fellow, Maryland Longitudinal Data System Center


      Topic: The Effect of High School Career and Technical Education on Postsecondary Enrollment and Early Career Wages


      Presentation Abstract: Career and Technical Education (CTE) has become a topic of considerable policy-making interest as a way of providing specialized education and expanding the number of career pathways available to high schools students. This research examines the effect of CTE program completion during high school on postsecondary outcomes, including college enrollment and workforce wages. Using propensity score matching, this research uses MLDS data to estimate a causal effect of CTE on postsecondary enrollment and wages up to six years after high school graduation.


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