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Agley, Jon; Tidd, David; Jun, Mikyoung; Eldridge, Lori; Xiao, Yunyu; Sussman, Steve; Jayawardene, Wasantha; Agley, Daniel; Gassman, Ruth; Dickinson, Stephanie L. – Educational and Psychological Measurement, 2021
Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…
Descriptors: Data Analysis, Longitudinal Studies, Data Collection, Intervention
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Oranje, Andreas; Freund, David; Lin, Mei-jang; Tang, Yuxin – ETS Research Report Series, 2007
In this paper, a data perturbation method for minimizing the possibility of disclosure of participants' identities on a survey is described in the context of the National Assessment of Educational Progress (NAEP). The method distinguishes itself from most approaches because of the presence of cognitive tasks. Hence, a data edit should have minimal…
Descriptors: Student Surveys, Risk, National Competency Tests, Data Analysis
Data Quality Campaign, 2010
Now that all 50 states and the District of Columbia are building statewide longitudinal data systems, the next step is to ensure that the information in these systems is used to improve student learning. The Data Quality Campaign (DQC) has identified 10 actions that states can take to ensure that the right data are available and accessible and…
Descriptors: Academic Achievement, Feedback (Response), High School Graduates, Graduation Rate