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The Promise and Limitations of Synthetic Data as a Strategy to Expand Access to State-Level Multi-Agency Longitudinal Data

Title: The Promise and Limitations of Synthetic Data as a Strategy to Expand Access to State-Level Multi-Agency Longitudinal Data
Language: English
Authors: Bonnéry, Daniel; Feng, Yi (ORCID 0000-0002-3487-908X); Henneberger, Angela K. (ORCID 0000-0002-0068-9691); Johnson, Tessa L.; Lachowicz, Mark (ORCID 0000-0002-3575-2160); Rose, Bess A. (ORCID 0000-0002-1212-0363); Shaw, Terry (ORCID 0000-0002-6692-384X); Stapleton, Laura M. (ORCID 0000-0003-2383-772X); Woolley, Michael E. (ORCID 0000-0003-0965-7175); Zheng, Yating (ORCID 0000-0003-0565-9683)
Source: Journal of Research on Educational Effectiveness. 2019 12(4):616-647.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 32
Publication Date: 2019
Document Type: Journal Articles; Reports - Descriptive
Education Level: High Schools; Secondary Education; Higher Education; Postsecondary Education
Descriptors: Data Collection; Access to Information; Privacy; Information Dissemination; Information Security; Databases; High Schools; Colleges; Labor Force; Records (Forms); State Departments of Education; Information Management; Disclosure; Governing Boards; Role; Cost Effectiveness; Program Evaluation
DOI: 10.1080/19345747.2019.1631421
ISSN: 1934-5747
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. We present a case study in the 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 our federally-funded project, proposing the steps required to synthesize a statewide longitudinal data system covering high school, postsecondary, and workforce data. Last, for use as a template for other agencies considering synthetic data, we review the challenges we have confronted in the development of our synthetic data system for research and policy evaluation purposes.
Abstractor: As Provided
Entry Date: 2019
Accession Number: EJ1236531
Database: ERIC