Java Implementation of Teacher Information Ability Measurement and Analysis Intelligent System (AMAIS) Based on ICT-TPACK and Recurrent Neural Network
Kuiliang Fu · 2022 International Conference on Inventive Computation Technologies (ICICT) · 2022
This study discusses about the implementation of Java in the process of teacher information ability measurement and analysis based on ICT-TPACK and recurrent neural network. From the research study it is evident that when using the lock cache mechanism in the Java virtual machine to improve its runtime cache performance, the dynamic lock cache method can achieve an optimization effect that is not weaker than the static lock cache method. At this point, if other memory accesses in the system conflict with the compiled method, the compiled method may be replaced by the cache. The proposed architecture assist in finding the best solution for the teacher information ability measurement and intelligent system analysis. To apply the system into various model, the ICT-TPACK and recurrent neural network are combined. The performance of the proposed model is then validated by performing an experimental testing.