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PERSONALIZED LEARNING PATHWAYS FOR STUDENTS USING REINFORCEMENT LEARNING

ORDINARY APPLICATION

Published

date

Filed on 20 November 2024

Abstract

PERSONALIZED LEARNING PATHWAYS FOR STUDENTS USING REINFORCEMENT LEARNING ABSTRACT In the rapidly evolving landscape of education, personalized learning has emerged as a crucial approach to address the diverse needs of students. This paper introduces an innovative system that leverages reinforcement learning algorithms to create personalized learning pathways for students. The primary objective is to optimize the learning experience by adapting content, pace, and teaching methods to individual student needs and preferences. Reinforcement learning is chosen for its ability to make sequential decisions and improve over time based on feedback, making it well-suited for the dynamic nature of learning processes. The system processes student data, including performance metrics, learning styles, and engagement levels, to continuously refine and adapt the learning path. It is designed to operate across various subjects and grade levels, accommodating different learning environments from traditional classrooms to online platforms. A comprehensive dataset was collected, encompassing student interactions, assessment results, and learning outcomes across diverse educational contexts. The trained reinforcement learning model is deployed to process real-time student data and make decisions about the next best learning activities or content to present. The system's performance is evaluated using metrics such as learning outcome improvements, student engagement levels, and the rate of knowledge retention. Results demonstrate significant improvements in learning efficiency and student satisfaction, indicating the system's potential effectiveness in real-world educational settings. This automated personalized learning system represents a significant advancement in educational technology. It offers a scalable solution to provide individualized instruction at a level previously unattainable in traditional educational models. Future work could focus on integrating more sophisticated cognitive models, expanding to a wider range of subjects, and incorporating collaborative learning aspects. The implementation of this system can significantly enhance the capabilities of educational institutions, contributing to more effective and engaging learning experiences for students of all backgrounds and abilities.

Patent Information

Application ID202441089938
Invention FieldCOMPUTER SCIENCE
Date of Application20/11/2024
Publication Number48/2024

Inventors

NameAddressCountryNationality
Nagaram Kiran KumarSAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia
Mr P S RohitSAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia
Dr. A. SeethalakshmySAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia
Dr G SelviSAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia
Dr D IranianSAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia
Dr R RevathiSAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia
Dr S PoomavelSAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia
Dr M Eswara RaoSAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia
Dr Ramya MohanSAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia

Applicants

NameAddressCountryNationality
SAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCESSAVEETHA INSTITUTE OF MEDICAL AND TECHNICAL SCIENCES, SAVEETHA NAGAR, THANDALAM, CHENNAI, TAMIL NADU, INDIA, PIN CODE - 602105. MOB: 9884293869, patents.sdc@saveetha.comIndiaIndia

Specification

FORM - 2
THE PATENTS ACT, 1970
(39 OF 1970)
&
THE PATENTS RULES, 2003
COMPLETE SPECIFICATION
(see Section 10 & rule 13)

1. TITLE OF THE INVENTION : PERSONALIZED LEARNING PATHWAYS FOR
STUDENTS USING REINFORCEMENT LEARNING
2. APPLICANT:
S.No NAME NATIONALITY ADDRESS
1 Saveetha Institute of Medical and
Technical Sciences
INDIAN Saveetha Nagar, Thandalam,
Chennai - 602 105,Tamil Nadu,
India
20-Nov-2024/138526/202441089938/Form 2(Title Page)
.3..BREAMBLE-l^O-TIIE-DESCRI PTION:-
The following specification describes the invention and how it is to be performed.
4. COMPLETE SPECIFICATION
The following specification particularly describes the invention and the manner in which it is tobe
performed. ....................... Separate sheet is attached......................................
5. DESCRIPTION .
Separate sheet is attached______
6. CLAIMS
Separate sheet is attached______
DATE:
SIGNATURE:
NAME
1. ABSTRACT OF THE INVENTION
Separate sheet is attached--
Dr. B.RAMESH
principal
SIM ATS SCHOO!. OF ENGINEERING
SAVEETHA INSTITUTE OF MEDICAL AND
TECHNIAL SCIENCES


Note:-
*Repeat boxes inn case of more than one entry.
*To be signed by the applicant(s) or by authorized registered patent agentotherwise where mentioned.
*Tic (V)/cross(x) whichever is applicable/not applicable in declaration inpara-9.
*Name of the Inventor and applicant should be given in full, family name in the beginning.
*Complete address of the inventor and applicant should be given stating the postal Indexno./code. state and country,
*Strike out the column which is/are not applicable

Bank : INDUSIND BANK
Branch : NUNGAMBAKKAM
( SAVEETHA UNIVERSITY )
DD No : 402546
DD Date: 14/11/2024
DD Amount: 8,900/-

PERSONALIZED LEARNING PATHWAYS FOR STUDENTS USING
REINFORCEMENT LEARNING
PREAMBLE TO THE DESORPTION
THE FIELD OF INVENTION (TRANSPORTATION SYSTEM)
The present invention relates to the field of educational' technology and personalized learning systems. Specifically, it involves the development and application of advanced machine learning techniques, particularly reinforcement learning, for creating adaptive and personalized learning pathways for students. This invention addresses the need for efficient and effective methods to tailor educational experiences to individual student needs, improve learning outcomes, and increase student engagement. The technology integrates real-time data processing and reinforcement learning algorithms to dynamically adjust learning content, pace, and methods based on each student's progress and preferences.

BACKGROUND OF THE INVENTION
With the increasing recognition of diverse learning needs and styles among students, traditional one-size-fits- all approaches to education have shown limitations in effectively engaging all learners. Personalized learning has emerged as a promising solution, but its implementation at scale has been challenging due to the complexity of individual learning processes
and the resource and the resources required for individualized instruction.

Recent advancements in artificial intelligence, particularly in the field of reinforcement learning, offer new possibilities for creating adaptive learning systems. Reinforcement learning, with its ability to make sequential decisions and improve based on feedback, is well-suited to model the learning process and make real-time adjustments to educational content and strategies.

This invention aims to leverage the capabilities of reinforcement learning algorithms to develop an automated system for creating and managing personalized learning pathways. By integrating advanced machine learning techniques with educational data analytics, the system addresses the limitations of static curriculum designs and provides a scalable, efficient solution for enhancing learning outcomes and student engagement.

The system is designed to operate across various subjects and educational levels, ensuring adaptability to diverse learning environments and curricula. Through this innovative approach, the invention seeks to contribute to the development of more effective and equitable educational systems, ultimately improving learning experiences and outcomes for students of all backgrounds and abilities.

SUMMARY OF INVENTION
This invention introduces a system leveraging reinforcement learning algorithms for creating personalized learning pathways, enhancing educational effectiveness and student engagement. Utilizing reinforcement learning's sequential decision-making capabilities, the system processes student data to continuously adapt and optimize learning experiences. A comprehensive dataset and sophisticated modeling techniques are employed to train the system, ensuring robustness across various educational contexts.

Real-time student interaction data is processed to dynamically adjust learning content, pace, and methods. High adaptability is achieved, accommodating diverse learning styles and preferences. Scalable and enterable into existing educational platforms, this system streamlines personalized instruction and reduces reliance on one-size-fits-all approaches. Future improvements may include integration of more advanced cognitive models and expansion to a wider range of subjects and collaborative learning scenarios.

PERSONALIZED LEARNING PATHWAYS FOR STUDENTS USING
REINFORCEMENT LEARNING

COMPLETE SPECIFICATION

Specifications
The system described herein utilizes reinforcement learning algorithms to automate the creation and
management of personalized learning pathways, addressing critical needs in educational effectiveness and student engagement. Leveraging reinforcement learning's ability to make sequential decisions and improve over time, the system efficiently processes student data, enabling dynamic adaptation of learning experiences.

To ensure effective training, a comprehensive dataset is meticulously curated, encompassing diverse student interactions, assessment results, and learning outcomes across various educational contexts. This dataset, coupled with sophisticated modeling techniques, enhances the system's resilience and adaptability to different
learning styles and environments.

In practice, the system demonstrates real-time processing capabilities, swiftly analyzing student interactions and performance data for immediate adjustments to learning pathways. Through a combination of predictive analytics, it accurately assesses student needs, recommends appropriate learning activities, and adjusts the difficulty and pace of instruction.

With scalability in mind, the system is designed to seamlessly integrate into existing educational platforms, thereby augmenting the capabilities of educational institutions to provide personalized instruction at scale. Future enhancements may include the integration of more advanced cognitive models, expansion to a wider range of subjects, and incorporation of collaborative learning aspects, aimed at further improving-educalional
outcomes and engagement.

PERSONALIZED LEARNING PATHWAYS FOR STUDENTS USING
REINFORCEMENT LEARNING
DESCRIPTION
The system is a cutting-edge solution engineered to automate the creation and management of personalized learning pathways, leveraging reinforcement learning algorithms. With its advanced capabilities, reinforcement learning enables rapid and accurate processing of student data, facilitating dynamic adaptation of learning experiences. For effective operation, the system relies on a meticulously curated dataset containing diverse student interactions, assessment results, and learning outcomes across various educational contexts. This dataset, coupled with sophisticated modeling techniques, enhances the system's adaptability to different
learning styles and environments, ensuring robust performance in real-world educational scenarios.

In practical application, the system showcases its real-time processing prowess by swiftly analyzing student interaction and performance data. Through a seamless integration of predictive analytics and adaptive algorithms, it accurately assesses student needs, recommends appropriate learning activities, and adjusts the difficulty and pace of instruction in real-time. Furthermore, the system is designed with scalability in mind, allowing for effortless integration into existing educational platforms. This integration enhances the operational capabilities of educational institutions, enabling them to provide personalized instruction at a scale previously unattainable.

As the system evolves, future enhancements may include the integration of more advanced cognitive models, expansion to a wider range of subjects, and incorporation of collaborative learning aspects. Through continued innovation and refinement, the system remains at the forefront of personalized learning technologies, contributing significantly to improved educational outcomes and student engagement.

PERSONALIZED LEARNING PATHWAYS FOR STUDENTS USING
REINFORCEMENT LEARNING

CLAIM
We Claim

1. Innovative System: Our system represents an innovative approach to automate the creation
and management of personalized learning pathways for students.

2. Reinforcement Learning Integration: We leverage powerful reinforcement learning algorithms, renowned for their ability to make sequential decisions and improve over time based on feedback.

3. Comprehensive Dataset: The system is backed by a comprehensive dataset comprising diverse student interactions, assessment results, and learning outcomes across various educational.contexts.

4. Advanced Modeling Techniques: Through the utilization of sophisticated modeling techniques, our system enhances adaptability to different learning styles and environments.

5. Seamless Integration: Our system seamlessly integrates into existing educational platforms,
ensuring efficient collaboration with educational institutions and learning management systems.

6. Educational Effectiveness Enhancement: By automating the personalization of learning
pathways, our system significantly contributes to improved educational outcomes and enhanced student engagement.

Documents

NameDate
202441089938-Form 1-201124.pdf22/11/2024
202441089938-Form 18-201124.pdf22/11/2024
202441089938-Form 2(Title Page)-201124.pdf22/11/2024
202441089938-Form 3-201124.pdf22/11/2024
202441089938-Form 5-201124.pdf22/11/2024
202441089938-Form 9-201124.pdf22/11/2024

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