# US 2023/0056570 A1 · Device and method for assessing learning ability of user

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- Number: US 2023/0056570 A1
- Document ID: US20230056570A1
- Status: Published application
- Kind: A1
- Application number: 17/890,612
- Filed: 2022-08-18
- Published: 2023-02-23
- Earliest claimed: 2021-08-20
- Assignees: Riiid Inc.
- Applicants: Riiid Inc.
- Inventors: Hyun Bin LOH
- Web page: https://patentgrep.com/patent/US20230056570A1

## CPC

- G06N 3/096: Transfer learning
- G09B 7/00: Electrically-operated teaching apparatus or devices working with questions and answers (mechanically operated G09B3/00; computing arrangements G06F)
- G06N 3/0499: Feedforward networks
- G06N 3/063: using electronic means
- G06N 3/09: Supervised learning
- G09B 7/02: of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
- G06N 5/041: {Abduction}
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G09B: EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS (devices for psychotechnics or for testing reaction times A61B5/16; games, sports, amusements A63; projectors, projector screens G03B)

## Abstract

Provided are a device and method for assessing a user's learning ability. The method includes acquiring target assessment data of a target user and a reference user related to a target domain, wherein the target assessment data includes question data related to the target domain and answer data of each of the target user and the reference user for the question data, acquiring a target neural network model of which training has been completed, acquiring comparison information representing the target user's ability in relation to the reference user's ability in the target domain through the target neural network model, and calculating the target user's virtual score in the target domain on the basis of the comparison information.

## Claims

### Claim 1

A method of assessing a learning ability of a user by a learning ability assessment device for assessing a learning ability of a user according to an answer of the user to a question, the method comprising:
acquiring target assessment data of a target user and a reference user related to a target domain, wherein the target assessment data includes question data related to the target domain and answer data of the target user and the reference user for the question data;
acquiring a target neural network model of which training has been completed;
acquiring comparison information representing an ability of the target user in relation to an ability of the reference user in the target domain through the target neural network model; and
calculating a virtual score of the target user in the target domain on the basis of the comparison information.

### Claim 2 (depends on 1)

The method of claim 1, wherein the target neural network model comprises:
an input layer configured to receive the target assessment data;
an output layer configured to output the comparison information representing the ability of the target user in relation to the ability of the reference user in the target domain; and
a hidden layer having a plurality of nodes connecting the input layer and the output layer.

### Claim 3 (depends on 2)

The method of claim 2, wherein the target neural network model is acquired by transferring a reference neural network model which has been trained to output label information representing an ability ratio of users on the basis of a reference assessment database related to a reference domain different from the target domain, and
the reference neural network model has been trained by adjusting weights of the plurality of nodes so that the label information is output on the basis of the reference assessment database.

### Claim 4 (depends on 1)

The method of claim 1, wherein the acquiring of the target neural network model comprises:
acquiring a reference assessment database related to a reference domain different from the target domain, wherein the reference assessment database includes reference question data related to the reference domain, answer data of each of two or more users for the reference question data, and score data of each of the two or more users in the reference domain;
extracting a feature, which is a base for calculating relative abilities of the two or more users, from the reference assessment database;
training a reference neural network model on the basis of the extracted feature; and
transferring the reference neural network model of which training has been completed to the target domain.

### Claim 5 (depends on 4)

The method of claim 4, wherein the training of the reference neural network model comprises:
acquiring a training set including label information related to a relative ability ratio of the two or more users from the reference assessment database; and
inputting the feature to an input layer of the reference neural network model and adjusting weights of nodes of the reference neural network model on the basis of a difference between an output value output through an output layer of the reference neural network model and the label information to train the reference neural network model.

### Claim 6

A non-transitory computer-readable recording medium in which a computer program executed by a computer is recorded, the computer program comprising:
acquiring target assessment data of a target user and a reference user related to a target domain, wherein the target assessment data includes question data related to the target domain and answer data of the target user and the reference user for the question data;
acquiring a target neural network model of which training has been completed;
acquiring comparison information representing an ability of the target user in relation to an ability of the reference user in the target domain through the target neural network model; and
calculating a virtual score of the target user in the target domain on the basis of the comparison information.

### Claim 7

A device for assessing a learning ability of a user by receiving an answer of the user to a question, the device comprising:
a transceiver configured to communicate with a user terminal; and
a controller configured to acquire assessment data of a user through the transceiver and assess a learning ability on the basis of the assessment data,
wherein the controller acquires target assessment data of a target user and a reference user related to a target domain, wherein the target assessment data includes question data related to the target domain and answer data of each of the target user and the reference user for the question data, acquires a target neural network model of which training has been completed, acquires comparison information representing an ability of the target user in relation to an ability of the reference user in the target domain through the target neural network model, and calculates a virtual score of the target user in the target domain on the basis of the comparison information.