Award Abstract #9907447
Statistical Models for Monitoring Educational Progress

NSF Org:	SES Division of Social and Economic Sciences
Initial Amendment Date:	September 7, 1999
Latest Amendment Date:	September 7, 1999
Award Number:	9907447
Award Instrument:	Fellowship
Program Manager:	Cheryl L. Eavey SES Division of Social and Economic Sciences SBE Directorate for Social, Behavioral & Economic Sciences
Start Date:	September 1, 1999
Expires:	August 31, 2000 (Estimated)
Awarded Amount to Date:	$64870
Investigator(s):	Brian Junker brian@stat.cmu.edu (Principal Investigator)
Sponsor:	Carnegie-Mellon University 5000 Forbes Avenue PITTSBURGH, PA 15213 412/268-8746
NSF Program(s):	METHOD, MEASURE & STATS, STATISTICS
Field Application(s):
Program Reference Code(s):	OTHR, 0000
Program Element Code(s):	1333, 1269

ABSTRACT

This award supports the investigator's work at the University of Pittsburgh's Learning Research and Development Center (LRDC). Projects to be initiated include: (1) Analyzing school district data archives with an eye toward evaluating educational progress and monitoring the outcomes of educational innovations; (2) Exploring social judgement in education, in particular in the development of an institutional portfolio rating system for classrooms and schools, based on the "Principles for Learning" of LRDC's Institute for Learning; and (3) Laying technical groundwork for a bank of linked topical tests instantiating a purely standards-referenced testing program. All three are connected to ongoing research programs at LRDC. These projects are designed to contribute to the development of data collection systems for adequate school accountability systems and for educational policy evaluation. Research conducted through the Institute for Learning and elsewhere suggests that sustained improvement in student achievement is most reliably attained through institutional change. Yet most currently implemented accountability systems focus instead on individual student outcomes, and often are confounded with high-stakes decisions for individual students. The first project will explore whether existing school district data archives can be exploited to limit additional individual student testing when student achievement data is called for. The second project will apply methodology developed over the past ten years for student portfolio assessment to the development and rating of institutional portfolios intended to show that local institutions (e.g., classrooms, schools and districts) are engaged in a process of professional development that ensures long term gains for students. The banked tests in the third project would each cover fairly narrow topics, such as integer arithmetic, fractions, etc., and could be used for example to assess the distribution of student achievement within a district, school, or classroom relative to specific learning standards. This research is supported by the Methodology, Measurement, and Statistics Program and the Statistics and Probability Program under the Mid-Career Methodological Opportunities Fellowship Announcement.

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