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Teacher recruitment data analytics using association rule mining in Indian context

机译:在印度背景下使用关联规则挖掘进行教师招聘数据分析

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The recruitment of good teachers is crucial for educational institutions to provide quality education, thereby moulding the students to face challenges of tomorrow. Traditional approaches may fail to choose the right teachers for the right job. In this paper, we apply association rule mining on engineering college teachers data to elicit hidden relationships among the characteristics of the teachers. We use 1992 teachers data collected from AICTE mandatory disclosure documents for our investigation. The study helps the college administration to develop recruitment and HR policies to enhance quality of research, teaching and learning. The study brings out various recommendations for improved research output, patents, awards, R & D grants and book publications.
机译:招聘优秀教师对于教育机构提供优质教育至关重要,从而使学生适应未来的挑战。传统方法可能无法为合适的工作选择合适的老师。在本文中,我们将关联规则挖掘应用于工科院校教师数据中,以找出教师特征之间的隐藏关系。我们使用从AICTE强制性公开文件中收集的1992年教师数据进行调查。该研究有助于大学行政管理部门制定招聘和人事政策,以提高研究,教学和学习的质量。该研究提出了各种建议,以改善研究成果,专利,奖励,研发资助和书籍出版。

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