Data Analysis and Research Intern
e-Yantra, IIT Bombay
Focused on automating data collection and analysis for log generation using AI and visualization tools.
Data Analysis and Research Intern - e-Yantra, IIT Bombay
Internship Overview
Served as a Data Analysis and Research Intern at e-Yantra, IIT Bombay, focusing on automating data collection and analysis for log generation using AI and advanced visualization tools. This role combined cutting-edge research with practical applications in educational technology.
About e-Yantra
e-Yantra is a prestigious robotics and embedded systems initiative by IIT Bombay, aimed at promoting excellence in robotics education across India. The research conducted here directly impacts educational methodologies and student learning experiences.
Research Focus
Primary Research Area
Automating Log Generation for Collaborative Problem-Solving Activities
The research focused on developing automated systems to analyze student interactions in digital collaborative environments, extracting meaningful insights about learning patterns and collaborative behaviors.
Key Responsibilities and Achievements
Research Publication
- Conference Presentation: Presented research findings at COMPUTE 2024 conference organized by ACM India
- Academic Recognition: Research was accepted and published by Springer in the Communications in Computer and Information Science (CCIS) series
- Peer Review: Successfully defended research methodology and findings in front of academic peers
Technical Development
Video-to-Logs Data Pipeline
- Computer Vision: Utilized OpenCV for video processing and frame analysis
- OCR Integration: Implemented Optical Character Recognition to extract text from screen recordings
- Data Processing: Built comprehensive data pipelines using Pandas for log generation and analysis
- Performance: Achieved over 200% improvement in data usability through automated processing
Data Visualization and Analysis
- Process Modeling: Used Celonis and other advanced tools for process visualization
- Log Analysis: Developed sophisticated methods for analyzing user interaction logs
- Pattern Recognition: Identified key patterns in collaborative problem-solving behaviors
- Insights Generation: Created actionable insights for improving educational platforms
Technical Implementation
Computer Vision Pipeline
- Video Processing: Automated analysis of screen recordings using OpenCV
- Frame Extraction: Intelligent frame sampling for optimal data extraction
- Object Detection: Identification of UI elements and user interactions
- Quality Control: Robust error handling and validation systems
OCR and Text Processing
- Text Extraction: High-accuracy OCR implementation for digital content
- Natural Language Processing: Text analysis and categorization
- Data Validation: Automated verification of extracted information
- Multi-format Support: Handling various document and interface formats
Data Analysis Framework
- Pandas Integration: Comprehensive data manipulation and analysis
- Statistical Analysis: Advanced statistical methods for pattern identification
- Visualization: Creating meaningful visualizations using Matplotlib and other tools
- Reporting: Automated report generation for research findings
Research Methodology
Data Collection
- Screen Recording Analysis: Systematic analysis of user interaction recordings
- Log Aggregation: Comprehensive collection of system interaction logs
- Multi-source Integration: Combining data from various sources for complete analysis
Analysis Techniques
- Behavioral Analysis: Understanding user interaction patterns
- Collaborative Patterns: Identifying effective collaboration strategies
- Learning Outcomes: Correlating interaction patterns with learning success
- Process Optimization: Recommendations for platform improvements
Impact and Contributions
Academic Impact
- Research Publication: Contributing to academic knowledge in educational technology
- Methodology Development: Creating reusable frameworks for similar research
- Tool Development: Building tools that can be used by other researchers
- Conference Presentation: Sharing findings with the broader academic community
Practical Applications
- Educational Platform Improvement: Direct insights for enhancing collaborative learning platforms
- Data Pipeline Automation: Reducing manual effort in educational data analysis
- Quality Assurance: Improving the reliability of educational technology research
- Scalable Solutions: Creating systems that can be applied to other educational contexts
Learning Outcomes
This internship provided comprehensive experience in:
Research Skills
- Academic Writing: Developing skills in research paper composition and publication
- Data Analysis: Advanced techniques in educational data mining
- Presentation Skills: Effectively communicating research findings to academic audiences
- Peer Review: Understanding the academic review and publication process
Technical Skills
- Computer Vision: Practical application of OpenCV and image processing
- Data Science: Advanced data manipulation and analysis using Python
- Process Mining: Using tools like Celonis for business process analysis
- Research Methodology: Systematic approaches to data collection and analysis
Professional Development
- Research Collaboration: Working with academic researchers and faculty
- Project Management: Managing complex research projects with multiple deliverables
- Quality Standards: Meeting academic and publication standards
- Innovation: Contributing novel approaches to educational technology research
This internship served as a foundation for my continued research work at e-Yantra and contributed significantly to my understanding of educational technology and research methodology.