Sakshm AI: Advancing AI-Assisted Coding Education for Engineering Students in India Through Socratic Tutoring and Comprehensive Feedback
Project Overview
The document examines the use of Sakshm AI, an innovative AI-assisted coding education platform designed for engineering students in India, emphasizing the transformative potential of Large Language Models (LLMs) in educational settings, particularly in programming. By leveraging a Socratic tutoring approach, Sakshm AI facilitates personalized feedback and adaptive learning, enhancing critical thinking and independent problem-solving skills among learners. Key features of the platform include the Disha chatbot, which supports students in navigating coding challenges. Research findings reveal that while Sakshm AI significantly improves engagement and learning outcomes, it also faces challenges related to user engagement and technical performance. Overall, the document underscores the promising role of generative AI in revolutionizing education by fostering a more interactive and personalized learning experience, despite some existing hurdles.
Key Applications
Sakshm AI - Intelligent Tutoring System
Context: Coding education for engineering students in India, particularly for undergraduate learners.
Implementation: Implemented as a web-based platform that integrates AI-driven components, including a chatbot for Socratic tutoring and feedback.
Outcomes: Improved problem-solving skills, enhanced engagement, personalized learning experiences, and support for diverse learners.
Challenges: Technical issues, limited question variety, and the potential for decreased independent thinking due to reliance on AI assistance.
Implementation Barriers
Technical Barrier
Users reported technical issues such as slow performance and bugs that disrupt the learning experience.
Proposed Solutions: Implementing an autosave feature, enhancing system stability, and ensuring fast response times.
Content Barrier
Limited variety in coding problems and lack of real-world application scenarios were noted by users.
Proposed Solutions: Expanding the question bank to include more diverse and complex problems, and incorporating real-world scenarios.
Project Team
Raj Gupta
Researcher
Harshita Goyal
Researcher
Dhruv Kumar
Researcher
Apurv Mehra
Researcher
Sanchit Sharma
Researcher
Kashish Mittal
Researcher
Jagat Sesh Challa
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Raj Gupta, Harshita Goyal, Dhruv Kumar, Apurv Mehra, Sanchit Sharma, Kashish Mittal, Jagat Sesh Challa
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai