Educonnect: Ai-enabled peer-to-peer learning framework for university students
| dc.contributor.author | Ronald Tusiime | |
| dc.contributor.author | Hellen Noeline Nambooze | |
| dc.contributor.author | Lynn Amoit | |
| dc.date.accessioned | 2026-07-15T08:50:28Z | |
| dc.date.available | 2026-07-15T08:50:28Z | |
| dc.date.issued | 2026-06-01 | |
| dc.description | Undergraduate | |
| dc.description.abstract | EduConnect is a web-based, AI-enabled peer learning platform designed to revolutionize how university students discover study partners, access high quality academic resources, and sustain progress. The project addresses three critical local challenges: fragmented peer-learning coordination, limited personalisation in study support and weak integration between collaboration tools and progress tracking. The implemented client-server architecture utilises a React frontend, Node.js/Express API and SQLite database persistence (sql.js) with optional Python services for advanced NLP intent classification and sequence-to-sequence quiz generation. EduConnect integrates intelligent peer recommendations, multi-discipline resource browsing, adaptive quiz workflows, study groups with direct and group messaging and a chatbot (EduBot) for intent based assistance. A key technical contribution is a trained multinomial logistic regression model for predicting next study topics based on user engagement statistics, trained in Python and exported to a JSON weight matrix for native JavaScript inference. Pilot survey evidence from 50 students indicates strong adoption potential and problem relevance. The average student difficulty in finding study partners was rated at 3.80/5, and overall interest in the platform was 4.36/5, with 78% of respondents willing to join beta testing. Combined with a fully functional, deployed MVP, these findings support the technical viability and educational significance of the EduConnect framework. Keywords: Peer learning, educational technology, recommendation systems, logistic regression, NLP intent classification, student collaboration. | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12311/3468 | |
| dc.language.iso | en | |
| dc.publisher | Uganda Christian University | |
| dc.title | Educonnect: Ai-enabled peer-to-peer learning framework for university students | |
| dc.type | Project Report |