Sakshm AI: Advancing AI-Assisted Coding Education for Engineering Students in India Through Socratic Tutoring and Comprehensive Feedback
Sakshm AI: Revolutionizing Coding Education in India
This study introduces Sakshm AI, an AI-powered intelligent tutoring system designed to enhance coding education for engineering students in India. It leverages Socratic tutoring, contextual hints, structured feedback, and adaptive guidance to foster critical thinking and problem-solving skills, addressing key limitations of existing AI tools like direct code generation and limited context retention.
A large-scale mixed-methods study involving 1170 registered participants (45 survey, 25 in-depth interviews) analyzed platform logs, engagement trends, and problem-solving behaviors. Findings reveal how AI-driven Socratic guidance influences learning, offering recommendations for optimizing AI-based coding platforms. Sakshm AI aligns with Sustainable Development Goal 4 (Quality Education) by providing accessible, structured learning, particularly for undergraduate students without expert guidance.
The platform integrates a comprehensive question bank of over 450 Data Structures and Algorithms (DSA) problems, categorized by difficulty and company relevance, making it suitable for both academic learning and interview preparation. Its performance feedback system evaluates correctness, efficiency, and code quality, ensuring thoughtful engagement and balancing AI assistance with pedagogical rigor.
Key Impact Metrics
Quantifiable results demonstrating Sakshm AI's effectiveness in coding education.
0
Active Learners
0
DSA Problems
0
Average Success Rate
0
AI Assistant Availability
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Socratic Tutoring
Enhances critical thinking and problem-solving without direct answers, fostering independent learning.
Sakshm AI Learning Workflow
User Submission
→
Initial Analysis
→
AI Evaluation
→
Hint & Feedback Generation
→
User Interaction
→
Final Assessment
→
Progress Tracking
| Feature | Sakshm AI | ChatGPT | LeetCode | CodeAid |
|---|---|---|---|---|
| AI Assistant | Integrated & Contextual | General | None | Limited |
| Socratic Guidance | ✓ Yes | X No | X No | Limited |
| Contextual Hints | ✓ Yes | X No | X No | Limited |
| Code Quality Feedback | ✓ Detailed | Limited | Limited | Limited |
| Company-Specific Questions | ✓ Yes | X No | X No | X No |
| Free Complexity Analysis | ✓ Yes | X No | Premium | X No |
User Engagement & Impact
One engineering student, P12, highlighted: 'Disha is helpful because it encourages problem-solving by providing hints rather than direct answers.' This reflects the core design principle of Sakshm AI in fostering independent thinking.
Another user, P8, praised the platform's usability: 'I got friendly with the platform in just a few minutes... navigation through multiple options was very intuitive.' This indicates the effectiveness of the user-friendly interface.
The quantitative analysis revealed that users engaged more with Disha on medium difficulty problems, suggesting its effectiveness in guided problem-solving, while for hard problems, users often switched to ChatGPT for direct solutions.
Adaptive Learning Models
Extend heuristic personalization to a fully adaptive engine for tailored recommendations and longitudinal support.
| Feature Area | Current | Future (Sakshm AI) |
|---|---|---|
| User Interface | Basic dark mode, limited customization | Autosave, full dark mode, chatbot persona customization |
| Feature Set | DSA problems only, Python/Java/C++/JS | Resume builder, mock interviews, broader language support (R, C#, SQL), collaborative coding spaces |
| Learning Enhancement | Heuristic hinting | Dynamic hinting, personalized learning paths, real-world scenarios |
Calculate Your AI-Driven Efficiency Gains
Estimate the potential time and cost savings by integrating AI-assisted coding education into your curriculum or personal learning.
Estimated Annual Savings
$0
Annual Hours Reclaimed
0
Sakshm AI Implementation Roadmap
A phased approach to integrating AI-assisted coding education for maximum impact and seamless adoption.
Phase 1: Initial Pilot & Integration
Deploy Sakshm AI with a select group of students to gather initial feedback and optimize integration with existing learning management systems. Focus on basic DSA problems and core Socratic tutoring features.
Phase 2: Feature Expansion & Scaling
Roll out to a larger student body, introduce advanced DSA problem sets, and activate features like company-specific questions and detailed performance reports. Begin incorporating initial adaptive learning heuristics.
Phase 3: Advanced AI & Personalized Learning
Implement fully adaptive learning models, expand language support, and introduce collaborative coding environments. Integrate career-oriented tools and real-world scenario challenges for comprehensive skill development.
Ready to Transform Your Coding Education?
Book a personalized session to see how Sakshm AI can elevate your institution's learning outcomes.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat