Final Project Report
<<AI Based Smart Teaching Assistant for Personalized Exam
Preparation>>
Project Supervisor
<<Waqas Ahmad>>
Submitted By
<<Bareerah Khalid>> <<BC200406966>>
Software Projects & Research Section,
Department of Computer Sciences,
Virtual University of Pakistan
CERTIFICATE
This is to certify that <<Bareerah Khalid>> (<<BC200406866>>),have worked on and
completed their Software Project at Software & Research Projects Section,
Department of Computer Sciences, Virtual University of Pakistan in partial fulfillment
of the requirement for the degree of BS in Computer Sciences under my guidance and
supervision.
In our opinion, it is satisfactory and up to the mark and therefore fulfills the
requirements of BS in Computer Sciences.
Supervisor / Internal Examiner
<<Waqas Ahmad>>
Supervisor,
Software Projects & Research Section,
Department of Computer Sciences
Virtual University of Pakistan
___________________
(Signature)
External Examiner/Subject Specialist
<<External Supervisor Name>>
___________________
(Signature)
Accepted By:
_____________
(For office use)
EXORDIUM
In the name of Allah, the Compassionate, the Merciful.
Praise be to Allah, Lord of Creation,
The Compassionate, the Merciful,
King of Judgment-day!
You alone we worship, and to You alone we pray for
help,
Guide us to the straight path
The path of those who You have favored,
Not of those who have incurred Your wrath,
Nor of those who have gone astray.
DEDICATION
I want to dedicate this Final Year Project to my wonderful parents. Their love, support, and
sacrifices have been the bedrock of my educational journey. I'm also very grateful to my
mentors and friends. Their guidance, encouragement,
and teamwork were essential throughout my project. Without their involvement and
support, I wouldn't have been able to accomplish this.
ACKNOWLEDGEMENT
Acknowledgments I want to express my heartfelt thanks to everyone
who helped me with my Final Year Project. First, I am truly grateful to my project
supervisor, Their valuable advice, helpful feedback, and
continuous support guided me every step of the way, from the beginning to the end.
I also want to thank the faculty and staff of the [Computer Science] at [Virtual
University]. They provided the necessary resources and
support, which were crucial for completing my project successfully.
A huge thank you goes to my teammates or colleagues (if any). Their cooperation
and teamwork made the whole experience both productive and enjoyable,
contributing greatly to this journey. Lastly, I owe a debt of gratitude to my family
and friends. Their unwavering support, patience, and motivation carried me
through this challenging yet rewarding period. I couldn't have done it without them.
PREFACE
This Final Year Project, called [AI Based Smart Teaching Assistant for Personalized Exam
Preparation ], is part of completing my degree in [Bachelor in Computer Science] at [Virtual
University]. The goal of this project is to use the knowledge from my classes to tackle a real-
world problem. By doing this, I gain practical experience and get a better grasp of the
subject. This report covers the steps taken for research, planning, building,
and implementing the project, and includes the challenges faced and solutions found along
the way. The experience of working on this project has been both educational and
personally fulfilling. It has boosted my ability to think critically, solve problems,
and use technical skills. I'm sure the knowledge and experience from this project
will be a strong base for my career. I sincerely hope this report will help future students and
researchers interested in this area.
TABLE OF CONTENTS
CHAPTER NO. 1
SRS DOCUMENTS
1.1 INTRODUCTION
1.2 PURPOSE
1.3 SCOPE
1.4 DEFINITIONS, ACRONYMS AND ABBREVIATIONS
1.5 PROJECT REQUIREMENTS
1.5.1 Functional Requirements
1.5.2 Non-Functional Requirements
1.6 USE CASES AND USAGE SCENARIOS
1.6.1 Use Case Diagrams
1.6.2 Usage Scenarios
1.7 DEVELOPMENT METHODOLOGY
1.7.1 Chosen Methodology
1.7.2 Reasons for Chosen Methodology
1.7.2 Work Plan (Gantt Chart)
1.7.2 Project Schedule (Submission Calendar)
CHAPTER NO. 2
DESIGNING THE PROJECT............................................................................................12
2.1 INTRODUCTION
2.2 PURPOSE
2.3 SCOPE
2.4 DEFINITIONS, ACRONYMS AND ABBREVIATIONS
2.5 ARCHITECTURAL REPRESENTATION (ARCHITECTURE DIAGRAM)
2.6 DYNAMIC MODEL: SEQUENCE DIAGRAMS
2.7 OBJECT MODEL/LOGICAL MODEL: CLASS DIAGRAM
2.8 DATABASE MODEL (DATABASE DIAGRAM)
2.9 GRAPHICAL USER INTERFACES
CHAPTER NO.3
PROTOTPYE PHASE
3.1 SCOPE OF THE PROTOTYPE
3.2 Tools and Technologies Used
3.3 Design Process
CHAPTER 1
SRS Documents
CHAPTER 2
Designing the Project
CHAPTER 3
Prototype Phase
REFERENCES
· Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
· Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.).
Pearson.
· Chen, X., Xie, H., Cheng, S., & Liu, K. (2020). "An AI-Based Personalized Learning
System for Exam Preparation." IEEE Access, 8, 94567–94577.
· Zhang, Y., & Lu, X. (2019). "Smart Educational Assistant Based on Natural Language
Processing and Machine Learning." International Journal of Emerging Technologies in
Learning, 14(12), 45–52.
· IBM Cloud Education. (2020). What is Natural Language Processing (NLP)?.
Retrieved from https://www.ibm.com/cloud/learn/natural-language-processing
· Khan, M. J., & Pathan, A. (2021). "Intelligent Tutoring Systems: Design and
Implementation Challenges." Journal of Educational Technology & Society, 24(3), 88–
98.
APPENDIX
Project Title: AI-Based Smart Teaching Assistant for Personalized Exam Preparation.
Appendix A: System Architecture
Diagram of the overall system architecture of the AI system.
Parts include:
User Interface (Web or App)
AI Recommendation Engine
Question Bank and Knowledge Graph
Performance Analytics Module
Feedback Loop System
Appendix B: Technology Stack
Frontend: React.js / Flutter
Backend: Node.js / Django
AI Models: NLP (e.g., BERT, GPT), Classification Algorithms
Database: PostgreSQL / MongoDB
Hosting: AWS / Azure
APIs: OpenAI API, Google Text-to-Speech
Appendix C: Features Overview
Personalized question suggestions based on performance
Real-time feedback and explanation
Adaptive difficulty level
Progress tracking dashboard
Voice-interactions
Appendix D: User Flow
User logs in or registers.
Takes a diagnostic test.
System assesses performance.
AI suggests personalized practice sets.
Feedback given after each question.
System adapts and updates recommendations for the future.
Appendix E: Sample Screenshots
Login screen
Quiz interface
Performance analytics dashboard
AI-generated feedback view
Appendix F: Test Results and Evaluation
Accuracy of AI suggestions
User satisfaction survey results
Learning improvement metrics pre and post usage
