The project is an Artificially Intelligent e-learning web site using Fuzzy Logic to teach students C. The system will be a website that will be exclusive for each student according to his/her intellect. The site will provide reserves of theory and quizzing material (in a way not present on www yet) based on fuzzy logic and AI. Hence our system will change its preferences as the intellect of the student grows. The student is provided with Initial Mental ability Test to get the initial level of understanding of the student which is further improvised using Intuitionistic fuzzy algorithm and Mamdani algorithm. The hence defuzzified value will show the range in which the student lies.

1. Adaptive e-Learning Web Site
Created by:
Abhinav Singh 10103500
Faizan Akhtar 10103597
Priyam Awasthy 10103635
Submitted to:
Mr. Kishore Kumar
Ms. Arti Jain
Supervisor:
Ms. Mukta Goel

2. What is Artificial Intelligence??
It is the theory and
development of computer
systems able to perform tasks
normally requiring human
intelligence, such as visual
perception, speech
recognition, decision-
making, and translation
between languages.

3. Why Adaptive Learning ???
 What is it that you expect from a system which offers you the
opportunity to learn?
 Course Material
MAY BE…But is that all? What is it you are actually looking for?
 Something which can guide you along your whole path. Take
decisions for you. A system which interacts with you.
 BUT most importantly you are looking a system which can
understand you, and will change for you.
And that’s why we need an Adaptive System. A Perfect System.

4. What is Fuzzy logic??
 Fuzzy logic is an approach to
computing based on "degrees
of truth" rather than the usual
"true or false" (1 or
0) Boolean logic on which the
modern computer is based
Fuzzy logic includes 0 and 1 as extreme cases of truth (or "the
state of matters" or "fact") but also includes the various states of
truth in between so that, for example, the result of a
comparison between two things could be not “cold" or "hot"
but ".38 of hotness."

5.  Currently all available teaching systems work on precise evaluation.
 Computer can Evaluate and Manipulate Precise values while humans
evolution is affected by uncertainty, vagueness & judgments.
Adaptive Learning Systems

6. Human thinking process Perfect
+ = Online
Computer evaluation power Tutor
We propose web based tutoring model which is combination of
Intuitionistic fuzzy set theory + mamdani algorithm

7. Flow of Control
1. IQ TEST
2. CALCULATION SCORE FUNCTION
3. MAMDANI CALCULATIONS
4. CATEGORIZATION OF USER
5. COURSE DISPLAY
6. TOPIC TEST
7. CALCULATION OF SCORE FUNCTION
8. MAMDANI ALGORITHM FOR NEW FUZZY VALUE

8. ALGORITHMS

9. Intuitionistic Fuzzy
 X: set of questions.
 Ta: degree of true.
 Fa: degree of false.

10. Intuitionistic Fuzzy
 S(a) : Score function
 Ci: percentage of true.
 Wi: percentage of false.
 Ti: Ci/100
 Fi: Wi/100

11. Intuitionistic Fuzzy
 Intuitionistic Fuzzy Weighted Averaging (IFWA):
 Every question has specific initial fuzzy value QF, true weight
Tw, false weight & Fw.

12. Mamdani Model
 Fuzzification of Inputs.
 Rules Evaluation
 Defuzzification

13. Mamdani Model
 Fuzzification:
 Process of making Crisp value Fuzzy

14. Mamdani Model
 Rules Evaluation:

15. Mamdani Model
 Defuzzification:
 Weightage Average Model

16. MAMDANI STEPS
Step 1. Evaluate the antecedent for each rule
Calculate degree for each crisp input
Step 2. Obtain each rule's conclusion
OR = min(d1,d2)
AND = max(d1,d2)
Step 3. Aggregate conclusions
In this step we combine the outputs obtained for each rule in
step 2 (obtain conclusion) into a single fuzzy set, using a fuzzy
aggregation operator.
Step 4. Defuzzification
Caculating centroid

17. Time and Score Functions

18. The Good, The Average, The
Poor

21. Question
Data
Sample Questions and their
Fuzzy Values

22. Our Grouping
 0-.34 -> POOR
 .35-.75 -> AVERAGE
 .76-1 -> GOOD

23. Our Model
DATABASE
User

24. A look at The System

25. A look at The System

26. Test Report
A look at The System

27. A look at The System
Progress
Report

28. A look at The System
Progress
Report

29. FORUM
A look at The System

30. Practice
Compiler
A look at The System

31. THEORY
DATA
A look at The System

32. A look at The System
THEORY
DATA

33. A look at The System

34. THANK - YOU