SKILLIFY: Enhanced Learning Management System Using Generative AI

Abstract

Given Traditionally, students faced challenges in acquiring knowledge from textbooks due to difficulties in access and the high cost associated. Online Learning tries to overcome it. But accessibility of online learning is still a major challenge, especially for those who are visually impaired. Also, the number of courses offered on online platforms are enormous. It can be challenging to select the right course that can advance careers. Learners are therefore having trouble selecting the best course to improve their skills. To overcome accessibility of learning to visually impair our platform incorporates a text to speech feature using generative AI, where written text is converted into spoken words. To overcome the problem of choosing right course we are implementing course recommendation to enable learners to acquire new skills that are beneficial to their advancement. The project exemplifies the potential of artificial intelligence in revolutionizing education through visualized learning experiences. Our proposed model tries to improve efficiency of existing model by implementing text-to-speech and course recommendation.

Specification

Description:Field of the Invention

[01] This invention pertains to the field of adaptive learning systems that utilize artificial intelligence (AI) to enhance online educational accessibility and personalized course recommendations. Specifically, this invention addresses challenges faced by visually impaired learners and users in selecting relevant courses. The system integrates generative AI for text-to- speech (TTS) conversion and a recommendation engine to create an inclusive learning experience that is adaptive to individual needs.

Description of Related Art

[02] Existing e-learning systems often lack adequate accessibility features for visually impaired users and do not provide personalized course recommendations. While there are systems for online learning and basic accessibility, they do not sufficiently cater to the unique needs of visually impaired learners or provide personalized pathways in extensive course catalogs.


[03] Current learning platforms and accessibility tools have limited integration with generative AI technologies, which can enhance both the quality of text-to-speech (TTS) synthesis and the personalization of course recommendations. This lack of integration hampers their ability to meet diverse learning needs effectively.


[04] The need for inclusive, adaptable learning systems has increased, particularly for learners with disabilities. This invention addresses this demand by providing a unified platform that offers accessibility features tailored to visually impaired users and adaptive course recommendations.



SUMMARY

[05] The present invention introduces an AI-powered learning management system that incorporates generative AI for both accessibility and personalized learning. Key components include a TTS module for converting text into speech and a recommendation engine that customizes learning paths based on user preferences and behavior.

[06] The platform supports text-to-speech functionality, allowing visually impaired learners to access course materials, and leverages machine learning algorithms to recommend courses tailored to individual learning needs and career goals.

[07] The TTS Module for Accessibility converts text into audio, allowing visually impaired users to access educational materials through natural- sounding speech.

[08] The Personalized Recommendation Engine analyzes user behavior and preferences and uses machine learning algorithms to recommend courses, adjusting suggestions based on previous choices and study progress.

[09] This invention is therefore relatively flexible, accessible, through an inclusive platform that allows visually impaired users and general learners to benefit from a personalized, accessible online learning environment.

[0010] The invention is further characterized by an interactive, accessible user interface specifically designed for visually impaired users, with support for voice commands and screen readers, and includes Braille display compatibility.






BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:

[0012] FIG. 1 This architecture diagram shows the layered structure of the platform, detailing the frontend, backend, and AI-driven components. It illustrates how different modules communicate and ensures both accessibility and scalability.

[0013] The headings used in this document are provided solely for organizational purposes and are not intended to limit the scope of the description or claims in any way. Terms such as "may" are used in a permissive sense (i.e., meaning "having the potential to") rather than a mandatory sense (i.e., meaning "must"). Similarly, words like "include," "including," and "includes" are used to mean "including, but not limited to," allowing for the inclusion of additional features or variations beyond those explicitly described.














DETAILED DESCRIPTION

[0014] TTS Module The system converts course materials into speech using machine learning-based TTS technology. Users can adjust voice speed, tone, and accent for a customized listening experience. The TTS engine is capable of handling diverse text structures and adapting to different languages.

[0015] This document uses words similar as" including" that can be given more precise meaning as necessary for interpretation. The words" a"," an", and" the" shall be demonstrated as singular or plural and shall include the singular and plural forms appertained to thereby.

[0016] The engine analyzes user interactions, preferences, and goals to suggest personalized learning paths. It uses algorithms such as collaborative filtering and content-based filtering to recommend relevant courses based on the learner's previous activity and objectives.

[0017] The platform's interface is designed to support screen readers, voice navigation, and Braille displays, providing a fully accessible environment for visually impaired learners. The interface includes voice commands for easy navigation, and dynamic adjustments to learning paths based on user feedback.

[0018] The system utilizes Spring Boot and MySQL to handle large datasets and ensure secure, scalable management of user profiles and course content. Data is encrypted for privacy and processed in compliance with security standards.
, Claims:I/We Claim:

1. An AI-powered Learning Management System focused on enhancing educational accessibility and personalization. It includes a TTS module for converting text-based content into natural, clear audio for visually impaired users and a course recommendation engine that suggests relevant courses based on user goals, learning history, and behavior. The interface is accessible, supporting screen readers, voice commands, and Braille displays.
2. The system of claim 1, wherein the TTS Module allows customization of speech output, including options for language, accent, tone, and speed to enhance user experience.
3. The system of claim 1, wherein the Course Recommendation Engine uses machine learning techniques, such as collaborative filtering and content- based filtering, to optimize course suggestions based on user interaction and feedback.
4. The system of claim 1, wherein the Accessible User Interface supports voice command navigation and screen reader functionality, allowing visually impaired users to browse, select, and engage with course materials independently.


5. The system of claim 1, wherein the Backend Architecture is designed to be scalable and secure, utilizing frameworks such as Spring Boot and MySQL to manage high data volumes, user authentication, and data privacy.
6. The system of claim 1, further comprising an Interactive Progress Tracker that provides personalized feedback to users on their learning journey, allowing for adjustments in the recommended learning pathway based on real-time performance metrics.
7. The system of claim 1, wherein the Course Recommendation Engine refines course suggestions through a feedback loop, incorporating user ratings and behavior analysis to improve the relevance of recommendations over time.
8. The system of claim 1, wherein user data is anonymized and processed securely for improved recommendation accuracy, while ensuring privacy compliance.
9. The system of claim 1, wherein the TTS Module leverages generative AI to create high-quality, customizable audio output, which is automatically stored for replay at the user's convenience.

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