|
|||
|
This is version 29.
It is not the current version, and thus it cannot be edited. Faculty Institutes for Reforming Science Teaching (FIRST) has engaged faculty from over 50 institutions in professional development focused on active, inquiry-based teaching designed to improve student learning. We are building on the outcomes of FIRST to construct a database to support research on undergraduate STEM education. The database will support storing, searching and analyzing assessment data from undergraduate STEM courses and will facilitate both data-driven instructional decision making and research in science education. Our goals for this project include:
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 collected 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: Attachments:
|
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 |