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Weakest integrity traits identification of teachers using association rule mining

机译:基于关联规则挖掘的教师最弱完整性特征识别

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The government has arranged many programs for teacher development however the training is organized to fit yearly calendar without considering the right teacher for the right training. The selection of teacher to attend training is done randomly, by rotation and not based on their work performance. This paper investigate the weakest integrity trait of teacher using association rule technique with the aim can assists the school management to organize training related to teachers integrity performance and avoid sending a wrong teacher for a training. A dataset of Trainees Integrity Dataset (TID) representing 1500 secondary school teachers in Langkawi Island, Malaysia in the year 2009 were pre-processed and mined using apriori. The knowledge from the mining was analyzed based on demographic and integrity trait of teacher. The finding indicates that adaptability and stability are the weakest integrity trait among teachers. Besides that, the analysis also unable to prove that demographic factor such as the age and gender of teachers reflect their low integrity performance. The finding can be a guideline for school management to propose a suitable training program for teacher to improve integrity mainly at the adaptability and stability trait.
机译:政府为教师发展安排了许多计划,但是培训安排得适合每年的日历,而没有考虑合适的教师进行适当的培训。参加培训的老师的选择是通过轮换方式随机进行的,而不是根据他们的工作表现来选择的。本文运用关联规则技术研究了教师最弱的人格特质,旨在帮助学校管理人员组织与教师的人格绩效相关的培训,避免派遣错误的教师进行培训。使用apriori对2009年在马来西亚兰卡威岛(Langkawi Island)的1500名中学教师的培训者完整性数据集(TID)进行了预处理和挖掘。根据教师的人口统计和完整性特征,分析了从采矿中获得的知识。研究结果表明,适应性和稳定性是教师中最弱的诚信特质。除此之外,分析还无法证明人口统计学因素(例如教师的年龄和性别)反映了他们的廉正表现。这一发现可以作为学校管理者为教师提出合适的培训计划的指南,以提高教师的适应性和稳定性。

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