Teacher absenteeism is a problem that needs a solution. It is imperative that teachers come to work each day to prepare their students for academic achievement. If teachers are chronically absent from work, the students’ academic achievement suffers. There needs to be a way to minimize teacher absences. School districts must track data that shows teacher absences in order to get a clear picture of when and where the absences are the greatest problem.
A review of the literature identified several studies conducted over the years that document the effects of teacher absenteeism. With this in mind, it is recommended that incentives be put in place to reduce the absences of the teachers. I furthered the research to include data from a school district by researching teacher perceptions of the use of teacher attendance incentives in the school district.
The purpose of this study was to determine which schools within the school district have Incentive programs in place to motivate teachers to come to work. Existing attendance data was obtained to analyze the attendance of the teachers at each building. The teachers were then surveyed to identify the incentives that are in place at each building and the teachers’ perceptions of those incentives. The surveys conducted also assisted in determining if the attendance incentives that are used as motivation are effective to motivate teachers to attend work. The results of the teachers’ perceptions of the incentive program at each school will be compared with the teacher attendance data to determine which teacher attendance incentives are effective in motivating teachers to attend work as scheduled. The incentives that are the most effective will be shared with each principal in the district to utilize in maintaining better teacher attendance throughout the school district.
Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-6918 |
Date | 08 August 2023 |
Creators | Cockrell, Ginger Hearon |
Publisher | Scholars Junction |
Source Sets | Mississippi State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses and Dissertations |
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