Applying Business Analytic Methods To Improve Organizational Performance In The Public School System
Description
This work applies business analytics techniques to the setting of the public school system to improve educational attainment in both junior high and high school in the United States. In particular, this paper reviews common factors identified in the literature as influencing a student’s success in secondary school, discusses how those factors could be digitized and collected through information systems and theorizes how big data and analytics could be further applied to these organization to manage their performance. We then look at the uses of analytics in schools to see how well they match and identify areas for improvement. This work hopes to show that there has been a large effort to digitize some of the prediction factors; however, a large number of the more readily influenced factors have yet to be digitized and used to make evidence based decisions to improve student outcomes in the public school system.
Recommended Citation
Cazier, Joseph; Cech, Thomas; and Spaulding, Trent, "Applying Business Analytic Methods To Improve Organizational Performance In The Public School System" (2015). AMCIS 2015 Proceedings. 36.
https://aisel.aisnet.org/amcis2015/BizAnalytics/GeneralPresentations/36
Applying Business Analytic Methods To Improve Organizational Performance In The Public School System
This work applies business analytics techniques to the setting of the public school system to improve educational attainment in both junior high and high school in the United States. In particular, this paper reviews common factors identified in the literature as influencing a student’s success in secondary school, discusses how those factors could be digitized and collected through information systems and theorizes how big data and analytics could be further applied to these organization to manage their performance. We then look at the uses of analytics in schools to see how well they match and identify areas for improvement. This work hopes to show that there has been a large effort to digitize some of the prediction factors; however, a large number of the more readily influenced factors have yet to be digitized and used to make evidence based decisions to improve student outcomes in the public school system.