Empirical Analysis and AI based Intelligent Evaluation of Korean Teachers' Guiding Ability in MOOC based on Data Clustering

Evaluation of Korean teachers' ability in MOOC environment based on the fingerprint data collection with the AI tools and the recognition is conducted in this paper. There are many data protocols in the wireless sensor networks, but cluster-based hierarchical routing protocols have received more attention due to improved scalability. Hence, this paper is based on the traditional model to construct the efficient data collection methods. The estimation model is validated through the test on the collected data. This research study has simulated the proposed algorithm and the evaluation accuracy is high. Furthermore, to estimate the performance of the model under different conditions, the AI model is designed to meet with the high frequency model scenario, and the traditional MOOC model is improved.