Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162706
Title: Next generation tutor-matching and education platform
Authors: Chang, Callista Rossary
Keywords: Engineering::Computer science and engineering::Computer applications
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Chang, C. R. (2022). Next generation tutor-matching and education platform. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/162706
Abstract: Within the rapidly growing supplementary education industry in Singapore lies significant inefficiencies and practices that do not meet the needs of the modern world. Learnable was proposed as a next generation tutor-matching and education platform with a large emphasis providing parents and tutors the necessary tools to improve learning outcomes for children in Singapore. At Learnable's core is a search engine and marketplace that allows tutors to advertise their services, and parents to choose the most suitable tutor for their children. Robust filters and performance-based search ranking algorithms were developed to incentivize tutors to perform their best, and for parents to find the closest fit for their children. Learnable provides a one-stop platform for tutors to manage their students, assignments, lessons and payments, relieving tutors of the hefty administration work that typically comes with tutoring. Similarly, Learnable provides a platform for parents to manage their children's supplementary education needs, and keep track of their children's learning progress via the qualitative and quantitative data gathered on the platform. Other modern features on Learnable include one-click cashless payments, automated invoices, data-driven dashboards, online assignment creation and grading, scheduling, and more. Artificial intelligence was used to aid the outcomes of the project, using sentiment analysis to detect toxicity and harassment in the platform and optical character recognition to extract text from uploaded proof documents.
URI: https://hdl.handle.net/10356/162706
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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