Educational data mining is an emerging technology concerned with developing methods for exploring the various unique data that exists in the educational settings and uses them to understand the students as well as the domain in which they learn. Educational domain consists of a lot of data related to students, teachers and other learning strategies. Classification algorithms can be used on various educational data to mine the academic records. It can be used to predict student‘s outcome based on their previous academic performance. The various predictive algorithms like, C4.5, Random tree are applied on student‘s previous academic results to predict the outcome of the students in the university examination. The prediction would help the tutor in understanding the progress and attitude of the student towards the studies. It would also help them to identify the students who are constantly improving in their studies and help them to achieve a higher percentage. It also helps them to identify the underperformers so that extra effort can be taken to achieve a better result. The algorithms are analyzed based on their accuracy of predicting the result, the recall and the precision values. The accuracy of the algorithm is predicted by comparing the output generated by the algorithm with the original result obtained by the students in the university examination.
Comments: 7 Pages.
[v1] 2016-01-09 22:17:06
Unique-IP document downloads: 27 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.