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dc.contributor.advisor Kannenberg, Elisabeth en_US
dc.contributor.author Spiva, Kate
dc.date.accessioned 2018-06-25T19:06:05Z
dc.date.available 2018-06-25T19:06:05Z
dc.date.issued 2018-06-25
dc.date.submitted 2018-06
dc.identifier.uri http://hdl.handle.net/10211.3/204037
dc.description.abstract This study explored the effects of data-driven professional learning communities on student achievement. The work of John Hattie served as the cornerstone with great influence from Robert Marzano and Richard DuFour. The study was conducted using a fifth grade experimental group and a sixth grade control group. The fifth grade teachers administered three math assessments based on Common Core State Standards (CCSS) after meeting in professional learning communities (PLCs), while the sixth grade team administered similar assessments also based on CCSS without meeting in PLCs. Quantitative data was collected in the form of assessment scores. Initial scores and final scores were compared and the Pearson Correlation Coefficient and T-Value were calculated. It was also collected through Likert style surveys given to the fifth grade teachers. Qualitative data was collected in the form of open ended questions for the fifth grade team. This study provided evidence to support that professional learning communities that use data to drive instruction positively impact student achievement. en_US
dc.description.sponsorship Education en_US
dc.language.iso en_US en_US
dc.subject Professional Learning Community en_US
dc.subject PLC en_US
dc.subject Data-Driven Instruction en_US
dc.title Red Ink on our Own Papers: Using Data-Driven Professional Learning Communities to Improve Student Achievement en_US
dc.genre Thesis en_US
dc.contributor.committeemember Monson, Robin en_US


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