"Priority 2030": Moscow Polytech Researcher Receives University Grant for Digitalizing Project-Based Learning
Moscow Polytechnic University postgraduate student Vladislav Filipovich has been awarded the Vladimir Fortov Grant for digitalizing student project activities. Over the next year, the researcher will work on the project "Information Technology for Data Extraction and Generation in Intelligent Project-Based Learning Support Systems."
The grant implementation is expected to result in a software package designed for integration into digital tools supporting project-based learning, such as Folipro. The methodology will enhance collaboration efficiency among students, faculty, and industry partners, reduce time expenditures, and improve documentation quality and completeness. The system can also be implemented at other universities as a standalone technology for supporting student project activities.
Project Passport as a Guiding Tool
Student project activities represent one of the key directions in modern education. Universities are actively developing this format, enabling students to work on their startups and real-world tasks alongside industry partners. According to the Russian Ministry of Science and Higher Education, the number of such projects is expected to exceed 28,000 by 2025.
Each project is based on a project passport - a document outlining goals, objectives, expected outcomes, team composition, and technologies. This passport serves as a navigator, helping students, faculty, and partners understand ongoing work, while also providing an information resource for prospective students, project supervisors, and university administration.
Digital Support Platforms
Digital platforms are being actively implemented to support student project activities, helping automate project creation and management. However, analysis shows that completion rates for key passport sections rarely exceed 20-30%. The main reasons include students' insufficient competencies in precisely formulating goals and objectives, structuring texts, and mastering modern project management methods and artificial intelligence technologies.
Multi-Stage Processing Pipeline
Vladislav Filipovich will develop a methodology for automatically generating student project passports fr om unstructured textual and graphic data.
The implementation will feature a multi-stage pipeline: data extraction from various document formats; lexical normalization; semantic analysis; entity recognition; passport structure formation; and visual materials generation.
The new service will analyze any materials - from Word drafts to presentations and images - and independently create structured documents.
"The system will process information step by step, like an assembly line: extracting data, analyzing content, identifying key points, and forming a complete project passport," explains the researcher. "The AI won't simply copy information but will provide recommendations for improving formulations and project passport details."
For developing the complex, the young researcher plans to use traditional natural language processing approaches (NER, topic modeling, frequency analysis), OCR tools (EasyOCR, Tesseract) for text recognition from scanned documents, and advanced artificial intelligence technologies including large language models (ChatGPT, DeepSeek, Claude) and image generation models (Kandinsky, YandexART, Sora).
Background: The Vladimir Fortov Grant competition is conducted within the federal program "Priority 2030," wh ere Moscow Polytech participates with the strategic project "Accessible Electric Vehicle."
