Real-Time Tutor Matching via AI Question Synthesis
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Solution Overview
Problem
Existing education platforms struggle to effectively connect students with suitable tutors in real-time, as they lack accurate methods for synthesizing student questions into relevant parameters and dynamically assigning tutors based on relevancy scores, leading to inefficient learning experiences.
Innovation Solution
A system and method that utilize machine learning models for Natural Language Processing and Artificial Intelligence Techniques to synthesize student questions into parameters like subject, topic, category, and difficulty level, and calculate relevancy scores between student and tutor profiles to dynamically assign tutors, ensuring real-time connections based on relevancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional education platforms use static course ratings and tutor ratings for matching, then the system is simple to operate, but the matching accuracy and learning effectiveness deteriorate
Solution Approach 1:
The system transforms static ratings into dynamic parameters by synthesizing student questions into multiple parameters (subject, topic, concept, difficulty level) and calculating dynamic relevancy scores between student and tutor profiles, enabling accurate real-time matching without excessive complexity
Solution Approach 2:
The patent replaces manual rating-based matching with automated AI-based question synthesis and relevancy score calculation systems, using machine learning models to automatically determine tutor-student compatibility based on question parameters and profile characteristics
2Reliability
If the system dynamically assigns tutors based on relevancy scores computed using AI techniques, then the learning effectiveness is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system segments the tutor assignment process into distinct stages: question synthesis into parameters, cohort determination, relevancy score calculation, and tutor notification. This segmentation allows complex AI processing to be broken down into manageable steps, improving reliability while controlling computational complexity
Solution Approach 2:
The system performs preliminary actions by pre-processing student questions into standardized parameters and pre-calculating relevancy scores before actual tutor assignment. This preliminary processing ensures accurate matching while optimizing computational efficiency during real-time operations
3Adaptability or versatility
If the system processes student questions in multiple forms (image, text, voice) through machine learning models, then the adaptability to student needs is improved, but the processing time and system complexity increase
Solution Approach 1:
The system introduces an intermediary processing layer that converts diverse question formats (image, text, voice) into standardized parameters through machine learning models. This intermediary synthesis process enables versatile format handling while managing processing time by transforming multiple input types into a unified parameter structure for efficient tutor matching
Data Source
AI summary
A system and a method for connecting a tutor with a student in real time. Initially, the system receives a student profile. Further, the system receives a question from the student. Furthermore, the system synthesizes the question based on a set of predefined machine learning model. Subsequently, the system determines a cohort of the students from the set of the cohort of the students. The cohort of the students is determined based on the one or more parameters related to the question. Further, the system identifies a tutor assigned to the cohort of the students. Subsequently, the system notifies the tutor in real time. Further, the system receives an acknowledgement from the tutor within a predefined time. Finally, the system connects the tutor with the student in real time when the acknowledgement is the positive acknowledgement.