Exploration of the Alignment of State Data and Infrastructure to Mathematics and Science Success Indicators / Ellen B. Mandinach and Shandy Hauk.
A range of education initiatives in the U.S. are focusing on ways to improve curriculum, instruction, teacher development, and student assessment related to science, technology, engineering, and mathematics (STEM) education. Key indicators to monitor the quality of STEM education have been proposed...
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| Language: | English |
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Distributed by ERIC Clearinghouse,
2017.
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MARC
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| 100 | 1 | |a Mandinach, Ellen Beth. | |
| 245 | 1 | 0 | |a Exploration of the Alignment of State Data and Infrastructure to Mathematics and Science Success Indicators / |c Ellen B. Mandinach and Shandy Hauk. |
| 264 | 1 | |a [Place of publication not identified] : |b Distributed by ERIC Clearinghouse, |c 2017. | |
| 300 | |a 1 online resource (1 online resource (13 pages)) | ||
| 336 | |a text |b txt |2 rdacontent. | ||
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| 338 | |a online resource |b cr |2 rdacarrier. | ||
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| 500 | |a Contract Number: DGE1445522. |5 ericd. | ||
| 500 | |a Abstractor: As Provided. |5 ericd. | ||
| 500 | |a Educational level discussed: Elementary Education. | ||
| 516 | |a Text (Speeches/Meeting Papers) | ||
| 516 | |a Text (Reports, Research) | ||
| 520 | |a A range of education initiatives in the U.S. are focusing on ways to improve curriculum, instruction, teacher development, and student assessment related to science, technology, engineering, and mathematics (STEM) education. Key indicators to monitor the quality of STEM education have been proposed by the National Research Council. This paper is one in a series of reports on studies whose purpose was to investigate the nature, scope, and usefulness of measures for those indicators. For this report, through document and database analysis and interviews, the focus was an examination of the potential for measurement of progress through existing data sources from local, state, and national collections. Results from database analyses indicate that the availability of existing data sources to monitor a particular indicator varies from some (e.g., on the number of, and enrollment in different types of STEM schools and programs) to virtually none (e.g., on the time on and access to science learning for students in grades K-5). Meanwhile, conversations with state-level data system staff suggest a highly compliance-based and isolated approach that often did not include monitoring of data for teacher and leader level indicators--for example, data about the professional preparation and development of teachers and school leaders might exist at the state level in an office of teacher credentialing, but are not combined with or accessible through the statewide longitudinal data system (SLDS). While the national Common Educational Data System (CEDS) has developed and curates a highly detailed data dictionary whose data elements might be useful for monitoring the success of STEM education, that data dictionary is not in wide use at the state level by SLDS staff, in fact, many are not aware of its existence. Implications of the work include the future opportunities for communication among SLDS staff and state-level STEM experts about what might need to be measured in order for progress in an indicator to be monitored (e.g., an audit trail for teacher development as an online professional portfolio grows; whether or not an online professional course for leaders has Quality Matters certification; and other characteristics of professional learning processes, in addition to outcome measures like professional development units completed). The work of the SLDSs can function both as an essential tool for ensuring equity and excellence through compliance and as a means for supporting educational equity and excellence through the quality of the STEM indicator data they curate. | ||
| 524 | |a Grantee Submission, Paper presented at the Annual Meeting of the American Educational Research Association (San Antonio, TX, Apr 27-May 1, 2017). |2 ericd. | ||
| 650 | 0 | 7 | |a STEM Education. |2 ericd. |
| 650 | 0 | 7 | |a Educational Quality. |2 ericd. |
| 650 | 0 | 7 | |a Documentation. |2 ericd. |
| 650 | 0 | 7 | |a Content Analysis. |2 ericd. |
| 650 | 0 | 7 | |a Databases. |2 ericd. |
| 650 | 0 | 7 | |a Interviews. |2 ericd. |
| 650 | 0 | 7 | |a Measurement. |2 ericd. |
| 650 | 0 | 7 | |a Progress Monitoring. |2 ericd. |
| 650 | 0 | 7 | |a Educational Indicators. |2 ericd. |
| 650 | 0 | 7 | |a Qualitative Research. |2 ericd. |
| 650 | 0 | 7 | |a Statistical Analysis. |2 ericd. |
| 650 | 0 | 7 | |a Geographic Location. |2 ericd. |
| 650 | 0 | 7 | |a Enrollment Trends. |2 ericd. |
| 650 | 0 | 7 | |a Elementary Education. |2 ericd. |
| 650 | 0 | 7 | |a Access to Education. |2 ericd. |
| 650 | 0 | 7 | |a Pedagogical Content Knowledge. |2 ericd. |
| 650 | 0 | 7 | |a Faculty Development. |2 ericd. |
| 650 | 0 | 7 | |a Professional Development. |2 ericd. |
| 700 | 1 | |a Hauk, Shandy, |e author. | |
| 856 | 4 | 0 | |u http://files.eric.ed.gov/fulltext/ED577449.pdf |z Full Text (via ERIC) |
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