  The performance in higher secondary school education in India is a turning
point in the academic lives of all students. As this academic performance is
influenced by many factors, it is essential to develop predictive data mining
model for students' performance so as to identify the slow learners and study
the influence of the dominant factors on their academic performance. In the
present investigation, a survey cum experimental methodology was adopted to
generate a database and it was constructed from a primary and a secondary
source. While the primary data was collected from the regular students, the
secondary data was gathered from the school and office of the Chief Educational
Officer (CEO). A total of 1000 datasets of the year 2006 from five different
schools in three different districts of Tamilnadu were collected. The raw data
was preprocessed in terms of filling up missing values, transforming values in
one form into another and relevant attribute/ variable selection. As a result,
we had 772 student records, which were used for CHAID prediction model
construction. A set of prediction rules were extracted from CHIAD prediction
model and the efficiency of the generated CHIAD prediction model was found. The
accuracy of the present model was compared with other model and it has been
found to be satisfactory.
