System

A system comprising:

• circuitry configured to:
• acquire, via a communication interface coupled to a packet-switched network, interaction record data associated with a user from a storage device, perform preprocessing on the interaction record data including normalization of correctness data, time data, and difficulty data to generate feature data, and input the feature data to a machine learning model comprising a supervised classification algorithm to compute a proficiency score;
• perform clustering processing on proficiency scores of a plurality of users to classify the plurality of users into a plurality of groups, and generate, for each group, a group-specific prompt sentence including condition information comprising a target field, a difficulty level, and an output format;
• input each group-specific prompt sentence to a generative neural network model comprising a transformer-based architecture to generate group-specific structured output data items, transmit the group-specific structured output data items to a terminal device associated with each user, and receive response data from the terminal device;
• generate determination data by comparing the response data with reference data, generate evaluation data comprising the determination data and the proficiency score, input a second prompt sentence based on the evaluation data to the generative neural network model to generate evaluation response data, and transmit the evaluation response data as a notification data packet to the terminal device;
• and
• estimate an emotional state of the user based on at least one of facial image data or voice waveform data received from the terminal device, and adjust the condition information in subsequent prompt sentences based on the estimated emotional state and the updated proficiency score.

A method comprising:

• acquiring, via a communication interface coupled to a packet-switched network, interaction record data associated with a user from a storage device, and applying a machine learning algorithm to feature data derived from the interaction record data to compute a proficiency score indicating a comprehension level of the user;
• generating a first prompt sentence based on the proficiency score and condition information comprising at least a target field, a difficulty level, and an output format, and inputting the first prompt sentence to a generative neural network model to cause the generative neural network model to generate structured output data items in accordance with the proficiency score;
• transmitting, via the communication interface, the structured output data items as a notification data packet to a terminal device, receiving response data from the terminal device, and generating determination data by comparing the response data with reference data associated with the structured output data items;
• generating evaluation data comprising the structured output data items, the reference data, the response data, the determination data, and the proficiency score, generating a second prompt sentence based on the evaluation data, and inputting the second prompt sentence to the generative neural network model to cause the generative neural network model to generate evaluation response data indicating an error tendency and supplemental content;
• and
• storing the determination data and the evaluation response data in the storage device as updated interaction record data, and updating the proficiency score based on the updated interaction record data.