Systems and methods to generate personalized lesson content based on user content preferences are described herein.
Systems and methods to generate personalized lesson content based on user content preferences are described herein. Exemplary implementations: stores user preference information for individual users; stores vectorized content belonging to one or more bodies of content; provide an assessment to a first user; receive a response to the assessment from the first user; identify one or more skills that require improvement based on the response; provide at least the one or more skills and the first preference information as input to a machine-learning model; provide one or more prompts to the machine-learning model that configure the machine-learning model to obtain vectorized content and generate first lesson content based on the obtained vectorized content, the first lesson content being generated to facilitate improvements to the one or more skills; obtain the first lesson content from the machine-learning model; and provide the first lesson content to the first user.
FIELD OF THE DISCLOSURE
The field of this disclosure includes generative artificial intelligence for dynamically generating educational content. BACKGROUND
Programs and application for language learning and development are known. Many of these are designed for children and may offer standardized lessons based on the child's age. The lessons often focus on improving reading, reading comprehension, writing, speaking, and math skills. While these lessons may be effective for many learners, the lack of personalization and customization limits the effectiveness for a wider range of users. SUMMARY OF THE INVENTION
System(s) and method(s) to generate personalized lesson content based on user content preferences are described herein. User content preferences may identify types and kinds of content typically enjoyed by users. The content preferences may be determined based on user activity and interaction across a plurality of applications and/or platforms. The system(s) and method(s) may utilize the content preferences of users to generate customized lesson content that includes the content typically enjoyed by the users and/or similar content. Additionally, the lesson content may be customized to target specific skills of which the particular users require improvement. The result is lesson content that enhances learning by identifying and targeting specific skills, while incorporating content users enjoy to promote engagement.
The system may include one o
1. A system configured to generate personalized lesson content based on user content preferences, the system comprising: electronic storage that stores user preference information for individual users, wherein the user preference information specifies one or more bodies of content preferred by the individual users, and wherein the user preference information includes first preference information for a first user specifying a first body of content; a vectorized content repository that stores vectorized content belonging to the one or more bodies of content, wherein individual bodies of content include vectorized content sharing one or more characteristics, and wherein the vectorized content includes vectorized representations of text content, image content, video content, audio content, or a combination thereof; one or more physical processors configured by machine-readable instructions to: provide an assessment to the first user; receive a response to the assessment from the first user; identify one or more skills that require improvement based on the response; provide at least one of the one or more skills and the first preference information as input to a machine-learning model; provide one or more prompts to the machine-learning model that configure the machine-learning model to: obtain vectorized content from the vectorized content repository in accordance with the first preference information such that the obtained vectorized content belongs to the first body of content; generate first lesson content based on the obtained vectorized content belonging to the first body of content and the at least one of the one or more skills, wherein the first lesson content is generated to facilitate an improvement to the at least one of the one or more skills by the first user, responsive to the first user engaging with the first lesson content; obtain output from the machine-learning model, wherein the output includes the first lesson content; and provide the first lesson content to the first user. ||
14. A method configured for generating personalized lesson content based on user content preferences, the method comprising: storing user preference information for individual users, wherein the user preference information specifies one or more bodies of content preferred by the individual users, including storing first preference information for a first user specifying a first body of content; storing, via a vectorized content repository, vectorized content belonging to the one or more bodies of content, wherein individual bodies of content include vectorized content sharing one or more characteristics, and wherein the vectorized content includes vectorized representations of text content, image content, video content, audio content, or a combination thereof; providing an assessment to the first user; receiving a response to the assessment from the first user; identifying one or more skills that require improvement based on the response; providing at least one of the one or more skills and the first preference information as input to a machine-learning model; providing one or more prompts to the machine-learning model that configure the machine-learning model to: obtain vectorized content from the vectorized content repository in accordance with the first preference information such that the obtained vectorized content belongs to the first body of content; generate first lesson content based on the obtained vectorized content belonging to the first body of content and the at least one of the one or more skills, wherein the first lesson content is generated to facilitate an improvement to the at least one of the one or more skills by the first user, responsive to the first user engaging with the first lesson content; obtaining output from the machine-learning model, wherein the output includes the first lesson content; and providing the first lesson content to the first user.