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NAEP Doctoral Internship Alumni at NCME and AERA 2023 Annual Meetings

Published On Friday, March 17, 2023

The National Council on Measurement in Education (NCME) and American Educational Research Association (AERA) Annual Meetings are taking place in Chicago on April 12–15 and 13–16, respectively. In this post, we put the spotlight on the NAEP Doctoral Internship alumni who will have a presence either virtually or in person as presenters or participants at the NCME and AERA Annual Meetings this year.  We are proud of their contributions to education research and involvement as members of the NAEP R&D program community.

NAEP Process Data Researcher Goes International to Explore Academic Resilience

Published On Friday, September 2, 2022

NAEP Researcher Dr. Juanita Hicks was recently invited to Norway to present NAEP process data at a workshop on Academic Resilience (AR) along with others from the international research community. The workshop, which is the first in a series, is part of a grant awarded to Dr. Nani Teig, associate professor at the University of Oslo, Norway through the Centre for Advanced Studies Fellowship Program.

Process Squared: Mining Processes in NAEP Process Data

Published On Friday, January 14, 2022

The National Assessment of Educational Progress (NAEP) began to transition to digitally based assessments (DBAs) in 2017. DBAs enable the collection of data on students’ interactions with the assessment. However, these data are not trivial to analyze, given their time-dependent nature, abundance, structural complexity, and inevitable errors in collection. For the full potential of process data to be realized, researchers must possess analytical skills that go beyond traditional statistical analysis. In the upcoming 2022 NCME conference, researchers from American Institutes for Research (AIR) , under the guidance of the National Center for Education Statistics (NCES), will conduct a training session using methods taken from business process mining and graph theory to advance the use of NAEP process data.

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