Teacher recruitment data analytics using association rule mining in Indian context
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.
2016 International Conference on Data Science and Engineering (ICDSE)