Students Communicative Competence Prediction and Performance Analysis of Probabilistic Neural Network Model

The purpose of the research paper is to classify and assess the communicative competence of a class of thirty students of higher secondary school in India, before and after a well formulated training with the specially designed syllabus for the reinforcement of communicative competence. Regression statistics is applied to analyse the impact of different predictor variables for the total performance. The affecting variables or predictors are modelled applying Probabilistic Neural Network (PNN) techniques to classify the category of communicative competence performance of the learners. Learners are trained and tested in each component of communicative competence, based on the guidelines of Common European Framework of Reference for Language, Teaching and Assessment (CEFR).