Artificial Intelligence and Communication Technologies
Effective Performance Evaluation of Faculty
Authors: Preeti Jain, Gyanesh Shrivasta and Umesh Kumar Pandey
Publishing Date: 29-03-2023
ISBN: 978-81-955020-5-9
Abstract
The purpose of educational data mining is to uncover hidden knowledge in academic domain data. Learning analytics, artificial intelligence, database administration, psychometrics, and data science are all used in educational data mining to give it more dimensions. Every company recognizes the importance of an evaluation process, but putting one in place is challenging due to a variety of factors. Governments and societies around the world want higher education teaching staff to engage in real-world problem-solving instruction. Any university faces difficulties in measuring faculty performance. The mathematical modeling of evaluation parameters only provides a sliver of teacher effectiveness. Various teaching evaluation methodologies, such as student feedback, peer review, and reference to assessment parameters, will be included in the teaching group. According to the debate offered in the literature review, the following parameters must be studied while evaluating the performance of a faculty. Silhouette index is a set of internal measures used to evaluate the clustering algorithm’s performance.
Keywords
Educational Data Mining, Performance Analysis, Silhouette index.
Cite as
Preeti Jain, Gyanesh Shrivasta and Umesh Kumar Pandey, "Effective Performance Evaluation of Faculty", In: Saroj Hiranwal and Garima Mathur (eds), Artificial Intelligence and Communication Technologies, SCRS, India, 2023, pp. 873-877. https://doi.org/10.52458/978-81-955020-5-9-82