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INTELLICODE

Introduction to

APPLICATION

FINAL YEAR PROJECT

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INTELLICODE

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AMIR IRFAN BIN MOHD AMRAN

19DDT23F1058

MUHAMMAD ANNAZ HAIEQAL BIN AZMAN

19DDT23F1010

MUHAMMAD AIDIEL BIN MOHAMAD FAIZAL

19DDT23F1064

SITI NORHIDAYAH BINTI SAAD

SUPERVISOR

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PROBLEM

STATEMENT

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Many TVET students face difficulties in learning programming effectively. Some cannot afford to buy a personal laptop, making it hard for them to practice coding outside the classroom.

At the same time, some lecturers still ask students to write code on paper to help them memorize syntax. However, this method often leads to mistakes such as missing semicolons or brackets that are hard to detect without a computer.

IntelliCode was created to solve these problems. It allows students to scan handwritten or printed code using their smartphone, run it instantly, and get AI-powered explanations or corrections.

Objectives:

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PROJECT OBJECTIVES

    • Scanning handwritten or printed code using OCR technology.

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    • Running the code instantly with real-time debugging,

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    • Using AI assistance to explain errors and suggest improvements.

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The goal is to enhance learning efficiency, reduce mistakes, and motivate students through an intelligent and modern coding experience.

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MAIN FUNCTIONS

IntelliCode consists of three main functions:

• Code Scanning (OCR): Uses the phone camera to detect handwritten or printed code.

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• Real-Time Code Execution: Allows users to test their code immediately without retyping.

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• AI Assistant: Provides explanations and suggestions to help fix coding errors and improve understanding.

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AI Chat Box — lets users chat with an AI assistant to ask coding questions, get explanations, and receive improvement suggestions instantly.

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TECHNICAL FEATURES

The application is developed for Android using modern technologies such as:

🔹 OCR API – for text recognition.

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🔹 Real-Time Code Execution API – to run and test code instantly.

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🔹 AI Integration – to analyze code and suggest corrections.

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Some challenges included unclear handwriting recognition and system optimization, which were solved through OCR model training and multiple testing phases.

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CONCLUSION

IntelliCode has strong potential to be used as a modern digital learning tool in TVET education.

In the future, we plan to add more programming language support and introduce interactive learning features.

This project shows how AI and OCR technology can transform programming education into a smarter and more engaging experience for students.

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THANK YOU

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