  Teaching and Learning process of an educational institution needs to be
monitored and effectively analysed for enhancement. Teaching and Learning is a
vital element for an educational institution. It is also one of the criteria
set by majority of the Accreditation Agencies around the world. Learning
analytics and Educational Data Mining are relatively new. Learning analytics
refers to the collection of large volume of data about students in an
educational setting and to analyse the data to predict the students' future
performance and identify risk. Educational Data Mining (EDM) is develops
methods to analyse the data produced by the students in educational settings
and these methods helps to understand the students and the setting where they
learn. Aim of this research is to collect large collection of data on students'
performance in their assessment to discover the students at risk of failing the
final exam. This analysis will help to understand how the students are
progressing. The proposed research aimed to utilize the result of the analysis
to identify the students at risk and provide recommendations for improvement.
The proposed research aimed to collect and analyse the result of the assessment
at the course level to enhance the teaching and learning process. The research
aimed to discuss two feature selection techniques namely information gain and
gain ratio and adopted to use gain ratio as the feature selection technique.
