Computational Estimate Visualisation and Evaluation of Agent Classified Rules Learning System
This work addresses student modeling for educational assessment, but it appears incremental as it builds on prior research without reporting specific performance gains.
The paper tackles the development of an intelligent pre-assessment system using agent classified rules learning, presenting computational experiments and graph visualizations, with preliminary results showing the system performed as designed.
Student modelling and agent classified rules learning as applied in the development of the intelligent Preassessment System has been presented in [10],[11]. In this paper, we now demystify the theory behind the development of the pre-assessment system followed by some computational experimentation and graph visualisation of the agent classified rules learning algorithm in the estimation and prediction of classified rules. In addition, we present some preliminary results of the pre-assessment system evaluation. From the results, it is gathered that the system has performed according to its design specification.