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| ERIC #: | EJ762433 |
| Title: | "Scrubbing" Data for D3M |
| Authors: | Mercurius, Neil |
| Descriptors: | Educational Technology; Academic Achievement; Educational Improvement; Data Collection; Error Correction; Quality Control; Data Analysis; Influences; Decision Making |
| Source: | T.H.E. Journal, v33 n3 p15-18 Oct 2005 |
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| Publisher: | 1105 Media, Inc. Available from: T.H.E. Journal Magazine. P.O. Box 2170, Skokie, IL 60076. Tel: 866-293-3194; Tel: 866-886-3036; Fax: 847-763-9564; e-mail: THEJournal@1105service.com; Web site: http://www.thejournal.com/ |
| Publication Date: | 2005-10-00 |
| Pages: | 4 |
| Pub Types: | Journal Articles; Reports - Descriptive |
| Abstract: | Data-driven decision-making (D3M) appears to be the new buzz phrase for this century, the information age. On the education front, teachers and administrators are engaging in data-centered dialog in grade-level meetings, lounges, hallways, and classrooms as they brainstorm toward closing the gap in student achievement. Clearly, such discussion among professional educators has dramatically increased since the enactment of the No Child Left Behind Act of 2001. As a result of NCLB, the teaching community is establishing data repositories to analyze information to improve teaching and learning within the school environment. In addition, business organizations specializing in data collection, analysis, and technology reporting are rapidly emerging in large numbers to assist schools as they struggle to meet state, federal, and local requirements. Many software vendors, in fact, now serve the education market through their development of disaggregation products--those specifically designed to help schools meet their goals and close the gap in student achievement via D3M. In this process, data scrubbing or cleansing is crucial; the process results in high-quality data that are appropriate for effective data analysis. It removes fallacious marks or debris either manually or through a series of scripts. Ultimately, data scrubbing or cleansing is the most critical step in the data-collection process toward effective analysis that results in top-flight data-driven decision-making. This article discusses procedures for ensuring quality data through data scrubbing for an effective and consistent D3M. |
| Abstractor: | ERIC |
| Reference Count: | 0 |
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| Note: | N/A |
| Identifiers: | No Child Left Behind Act 2001 |
| Record Type: | Journal |
| Level: | N/A |
| Institutions: | N/A |
| Sponsors: | N/A |
| ISBN: | N/A |
| ISSN: | ISSN-0192-592X |
| Audiences: | N/A |
| Languages: | English |
| Education Level: | Elementary Secondary Education |
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