Mining Educational Data

8/10/2019 Mining Educational Data

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MINING EDUCATIONAL DATA

TOANALYZE STUDENTS PERFORMANCE

BATCH NO: 04

J.V.MOUNICA 311129210019

N.LAVANYA 311129210036

V.RAMAKRISHNA 311129210054

Y.MOUNICA YADAV - 311129210056

GUIDED BY,

Ms. D.PADMAJA

ASSISTANT PROFESSOR

DEPARTMENT OF CSE


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1.INTRODUCTION

1.1) PURPOSE OF THE SYSTEM:

The main aim of this system is to analyze the students data and

predict the performance at the end of the semester.

1.2) SCOPE OF THE SYSTEM:

To provide quality education to the students in higher

educational institutes.

1.3) OBJECTIVES:

To collect the data from students management

system.

To analyze the data using classification like ID3

algorithm.

To predict the performance of the students

based on the data.

To provide quality education to the institutions.


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1.4) DEFINITIONS AND ABBREVATIONS :

Data mining: It is defined as extracting theinformation/ knowledge from the huge set of data

Educational data mining: It is defined as a

process of discovering knowledge from data

origination from educational environment.

Classification: is the task of generalizing knownstructure to apply to new data.

ID3 Algorithm: ID3 (Iterative Dichotomiser 3) is

an algorithm used to generate a decision tree from a

dataset.

Entropy: Entropy H(S) is a measure of the

amount of uncertainty in the (data) set S (i.e. entropy

characterizes the (data) set S).

Information gain: Information gain IG(A) is the

measure of the difference in entropy from before to

after the set S is split on an attribute A. n other

words, how much uncertainty in S was reduced after

splitting set S on attribute A.


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1.5) REFERENCES:

i)http://en.wikipedia.org/wiki/Decision_tree_learning

ii) Mining Educational Data to Analyze Students

Performance (IJACSA) International Journal of

Advanced Computer Science and Applications, Vol. 2,

No. 6, 2011.

2) CURRENT SYSTEM:

In the existing system the student performance is

assessed upon various parameters like CGPA,

attendance, mid marks individually. All these

parameters are being assessed manually. There is no

common single application which is analyzing theabove parameters thereby leading to increase in the

work of the user.


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3. PROPOSED SYSTEM

3.1) OVERVIEW:

In the proposed system, various parameters like mid

marks, previous semester marks, attendance ,

seminar performance are taken into consideration

and would be developed into a single application to

analyze the performance.

The classification task is used on student database to

predict the students division on the basis of previous

database. There are many approaches that are used

for data classification; the decision tree method is

used here.

This study will help the students and the teachers toimprove the division of the student. This study will

also work to identify those students who need special

attention to reduce fail ratio and taking appropriate

actionfor the next semester examination


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3.2) FUNCTIONAL REQUIREMENTS:

The functional requirements describe the core

functionality of the application. This section includes

the data and functional process requirements.

The main function of this system is to collect data like

attendance, mid marks, previous year marks, seminar

performance etc. from student management system.

It analyzes the data and predicts the performance of

the student at the end semester.


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3.3) NON-FUNCTIONAL REQUIREMENTS:

Interface:

The System has a very user-friendly interface. Thusthe users will feel very easy to work on it. The

software provides accuracy along with a pleasant

interface. Make the present manual system more

interactive, speedy and user friendly.

Efficiency:

This involves accuracy, timeliness and

comprehensiveness to the system output

Flexibility:

The system should be modifiable depending on the

changing needs of the user. Such modifications

should not entail extensive reconstructing or

recreation of software. It should also be portable to

different computer systems.

Reliability:

Reliability of this system can be able to process work

correctly and completely without being aborted.


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4) CONCLUSION:

This system will help the students and teachers toprove the division of the student and it also used to

identify those students who need special attention to

reduce fail ration and taking appropriate action for

the next semester examination.

Documents

Mining Educational Data