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Computer Science Retention Study

Computer Science Retention Study. Data Collection Utility Eric L. Brown. Purpose. Develop a tool to get raw grade data from TTUMIS for local processing. Preprocess the raw text files into a SQL Server 2005 RDBMS.

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Computer Science Retention Study

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  1. Computer Science Retention Study • Data Collection Utility • Eric L. Brown

  2. Purpose • Develop a tool to get raw grade data from TTUMIS for local processing. • Preprocess the raw text files into a SQL Server 2005 RDBMS. • Develop a framework that can be easily extended to include other data sources as required by the study. • Use as many open source tools as possible.

  3. Parts of the Puzzle (Part 1 - The Process) • Raw Data Collection • Establishing Performance Metrics • Model Data via Established Metrics • Dissemination • Maintenance

  4. Parts of the Puzzle(Part 2 - the helpers) • pexpect-2.1beta (pexpect.sf.net) • freetds-0.63 (freetds.org) • pymssql-0.7.4 (pymssql.sf.net) • PyXML-0.8.4 (pyxml.sf.net) • Gnosis_Utils-1.2.1 (gnosis.cx) • FCKEditor-2.2 (fckeditor.net)

  5. Parts of the Puzzle(Part 3 - da systems)

  6. Parts of the Puzzle(Part 4 - the scripts) • createtables.py / parse.py / samplereport.py • index.py / form_action.py • mathdata.py / getdata.py • dataeditor.py / dataeditorpost.py

  7. Security • Security before all else... • Apache 1.3.33 / SSL • ssh / sftp • will have encrypted connection to MS-SQL • not on a public system

  8. Demo

  9. Conclusions • I love Python for a scripting language, but be aware of which version you are running. • There is more security work to be done. • Only small requests can be run through the browser window due to timeouts. • Web will be mostly for reporting in future releases.

  10. Thank You! • Questions • Questions • No Question

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