Description

General Description

Inspired by the challenge of providing consistent and detailed feedback for educational programming projects, this platform aims to revolutionize the evaluation of “MIT Scratch projects” (https://scratch.mit.edu/). This project is specifically designed for the school system of the city of Nes Ziona, which has over 1000 students learning programming with the Scratch Platform. 
Leading the program is Mr. Rami Shaked, formerly commander of the School of Computer Science in the IDF. 

Currently, manual assessment of projects is the norm, but it can be subjective and time-consuming for educators. The required platform addresses several primary challenges:

Automated Project Analysis: Efficiently and consistently evaluating a high volume of Scratch projects submitted by students, providing objective feedback on computational thinking areas.

Personalized Evaluation: Moving beyond basic assessment to allow educators to create custom rubrics, offering more profound insights into programming practices. 

LLM support: Use of AI-powered models (LLMs) to assist teachers in designing comprehensive and effective assessments. And a bot to guide students in developing projects that benefit society.
The primary goals are to reduce the manual workload for educators dramatically, increase scoring consistency and accuracy, provide real-time, constructive feedback to students, and streamline the entire project evaluation process, making it an invaluable tool for computer science education.

Project Scope
The software will be a web-based application accessible to Students, Teachers, Students and Administrators. Build a real-time frontend dashboard using a well-known web framework, such as Angular, Vue, or React, for both users and administrators. Develop the backend server to handle APIs and implement the necessary logic. Store and manage all data using databases like MongoDB, PostgreSQL, and MySQL. Its scope covers three core modules, inspired by Dr. Scratch's (https://www.drscratch.org ) capabilities and extended with new AI functionalities:
1. Automated Project Analysis Module: For automatically evaluating Scratch projects submitted as a project URL. This module will analyze projects across various computational areas and provide detailed feedback.
2. Personalized Rubric Module: For enabling teachers to create their own custom evaluation rubrics with specific criteria. This module will also integrate an AI-powered model (LLM) to assist teachers in generating and refining assessment criteria and rubrics.
3. Social Impact Project Design Assistant Module: A new module specifically designed to assist students in brainstorming, planning, and designing Scratch projects that address real-world problems and contribute positively to society. This module will provide prompts, resources, and constructive feedback leveraging AI to guide students through the design process.
The system must be configurable to adapt to new evaluation criteria or changes in educational standards. It should allow for the storage and retrieval of past project analyses and personalized rubrics. In addition, it should be compatible with mobile devices, tablets, and computers.

Student Requirements
Familiarity with JavaScript.
Familiarity with React.js/Angular/Vue or the ability to master it by themselves.
Familiarity with SQL and MongoDB/PostgreSQL/MySQL, or the ability to master it by themselves.
Understanding of REST API design.
Familiarity with LLM API design or the ability to master it by themselves.
Strong teamwork skills.
Capacity for independent learning.
High motivation and interest in educational technology.
Suggested Development Tools
React.js, Node.js, MongoDB.

Deliverables
The “AI-Powered Scratch Project Analysis and Evaluation Platform”
Specification document
YouTube video demonstrating functionalities
Poster summarizing the project
Presentation slides
GitHub link to the code repository

Additional Notes
• Each project team may include up to 5 students.
    - Full name Dr. Gilad Shamir
    - Email address – giladsh@hit.ac.il
CodeImpact AI - Where Code Meets Social Impact

AI and Machine Learning

Description

Emphasis in project execution

The project is has cooperation with the industry and combines meeting deadlines while being creative and focused on the task

THE PROJECT IS AT FULL CAPACITY
