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This is version 22.
It is not the current version, and thus it cannot be edited. The Faculty Institutes for Reforming Science Teaching (FIRST)  project builds upon the results and innovations from FIRST II as one of the components of the NSF Cyclic Model for knowledge production and improvement of practice in undergraduate biology education. To support data-driven instructional decision making, we are building a database for storing, searching and supporting a wide variety of analyses of assessment data from undergraduate science courses. The two major goals of the FIRST III project are 1) developing faculty expertise in assessing student learning and 2) evaluating innovations based on analyses of these data.
We have partnered with the National Center for Ecological Analysis and Synthesis (NCEAS) to build upon their database and metadata infrastructure for managing Ecological data. FIRST III is building upon existing metadata standards (e.g., Ecological Metadata Language, IMS, Dublin Core) to define an extensible Educational Metadata Language (EdML) for describing a wide variety of assessment data types and metadata about those assessments. This will allow assessments to be tagged based on taxonomies, standard psychometrics such as difficulty, discrimination, and other data to facilitate cross-study analyses.
We have begun the preliminary design work for the EdML and evaluation of EML, IMS and the NCEAS database tools to adapt them for our purposes. We continue to meet with the project metadata advisory committee to review draft documents and prepare the preliminary draft of the EdML standards.
We are using a large variety of assessment data we have been collecting at Michigan State University as part of the design specifications for developing both the Educational Metadata Language to describe the assessment data, and to test and evaluate the database backend and front-end tools we are building. We will incorporate the data from this proposed project, along with our other data sets, into this assessment database. For more information, please contact: Mark Urban-Lurain urban@msu.edu
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| This material is based upon work supported by the National Science Foundation under award 0618501. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF). Copyright 2008 |
