AI-based intelligent system for blended learning and education

Abstract

A system for implementing blended learning, including: • a central processing unit (CPU) configured to receive, process and store data from a range of user interfaces, learning management software modules, classroom interaction devices and cloud-based data storage; • an AI engine integrated into the CPU, configured to analyze students' interactions with educational content, classroom activities, and performance data in real time, with the AI ​​engine applying machine learning techniques to create personalized learning paths for each student based on their individual learning style, past performance, and engagement patterns; • A range of devices for classroom interaction, including at least one smartboard, tablet, or interactive projector, each configured to capture real-time data on classroom activities such as student participation, oral responses, and collaborative tasks. The captured data is then transferred to the CPU for analysis by the AI ​​engine to refine and dynamically adapt learning paths for each student; • a student user interface, wherein the student interface displays dynamically generated content tailored to the student's progress and performance, and wherein the content includes multimedia materials such as videos, tests and reading material adapted based on the student's interaction history and learning needs; • a CPU-connected teacher interface, wherein the teacher interface displays real-time analytics and insights from student data, including performance trends, engagement levels, and potential learning gaps, and wherein the AI ​​engine provides the teacher with actionable recommendations for adapting teaching strategies, resources, and interventions based on the individual needs of the students and their performance in class; • a cloud-based storage system, whereby the system securely stores student profiles, historical performance data and learning content, and whereby the CPU retrieves, updates and stores data from the cloud-based system in real time to ensure continuous adaptation of the learning experience.

Description

Field of invention:

[0001] The present invention relates to an intelligent system based on artificial intelligence for blended learning and education. Background of the invention:

[0002] Traditionally, the conventional education system has primarily revolved around classroom instruction, generally neglecting the individual learning needs of each student. However, with the advent of technology, particularly AI, and the increasing prevalence of digital tools in education, a more personalized approach to learning has emerged. Blended learning (the combination of online and in-person instruction), for example, has the potential to offer a more flexible and individualized learning experience. Successful implementation of such systems, however, requires a high degree of integration of technology, data analytics, and AI to ensure that learning is effective, engaging, and tailored to the needs of each individual student.

[0003] Today's blended learning systems still seem to lack a more intelligent, AI-driven framework that provides more dynamic, student-tailored materials, immediate, continuous feedback, and high-quality overall progress. This deficiency results in a substandard learning experience for both students and teachers. Therefore, there is a need for a system that can seamlessly combine the power of AI technologies with blended learning techniques to offer all stakeholders in the education system a tailored, real-time, and adaptive learning experience.

[0004] One of the most significant developments of the 21st century is the integration of technology into education, which has spawned a wide range of innovations that enhance both the teaching and learning experience. In recent years, blended learning, which combines traditional classroom work and classroom-style learning with online learning tools and even more resources, has emerged as one of the most exciting trends in modern education, offering a more flexible and personalized approach to learning. With blended learning, students get the best of both worlds—online access to content complemented by personalized support and collaboration with teachers. While it has been implemented in various forms and is in many cases considered an improvement over traditional learning, blended learning has yet to reach its full potential. Significant progress has already been made in its implementation.However, the lack of advanced, data-driven tools means that teachers cannot provide individualized learning approaches for every student. This is where artificial intelligence (AI) comes in, using machine learning methods to personalize and enhance educational experiences by adapting content, monitoring student progress, and providing real-time feedback. When it comes to AI and blended learning, existing solutions have shortcomings—serious shortcomings that fall far short of an ideal blend of AI and learning.

[0005] Currently, many blended learning platforms are based on learning management systems (LMS) that provide students with online content and facilitate interaction between students and instructors. While such systems offer a mix of self-paced learning modules, videos, and interactive assessments, they often lack the personalization that addresses the individual learning needs of each student. These systems are not dynamic, and the content is often generic, lacking the element of personalized adaptation based on the learner's performance or learning style (Moodle, Blackboard, Canvas). The content provided on these platforms is largely fixed, and although they offer adequate analytics for monitoring student performance, they lack adaptive learning paths that change instantly.This leads to a situation where those who don't understand part of the material fall behind, and those who do understand it aren't sufficiently challenged. Heard also agrees that due to the "poor data quality," educators have little insight that can be translated into action, and they find it difficult to get a sense of which students need more help or which teaching styles should be used.

[0006] Although some steps have been taken toward AI-based approaches to support blended learning environments, existing methods still cannot provide a complete, personalized, and holistic learning process for students and teachers. Current systems have their weaknesses, including limited personalization, a lack of online and offline learning integration, and data privacy concerns, which means they are still unable to fully address the challenges of modern education. What is needed at this point is a more sophisticated, AI-powered application that can deliver audible, fully personalized learning experiences in both traditional and virtual classrooms, while also addressing the increasingly diverse needs of students that extend beyond cognitive learning to include emotional and social development.Several questions arise when implementing such a system: It must also be structured in such a way that a strong emphasis is placed on security and transparency in order to build trust in the system among schools, students and parents alike. Summary of the invention:

[0007] According to the present invention, a system called "Smart School based on artificial intelligence and blended learning" is provided, comprising an educational ecosystem in which an artificial intelligence system is combined with a blended learning environment. Power House is an invention that combines AI technologies with online learners, classroom learners, and learning management systems to provide adaptive, real-time learning that meets the needs of individual learners. The system uses predictive analytics to create optimal learning paths, adapt content delivery, and provide actionable insights to both teachers and students.

[0008] The system features AI-powered tools for content personalization, data analysis, real-time feedback, and performance monitoring. It utilizes machine learning methods to assess each student's progress and instantly adjust the difficulty level, learning materials, and pace of instruction. Machine learning-based tools help teachers monitor the learning process, identify areas where students are struggling, and provide recommendations for teaching strategies and areas where interventions can be implemented to improve student outcomes.

[0009] The Smart School System is a systematic network device with hardware, software, and network technology components for realizing smart classrooms and smart campuses in physical and virtual learning environments. The device itself will likely include AI servers, a cloud-based data storage system, learning management software, interactive teaching tools, and interfaces for students and teachers. This could be easily integrated with existing classroom technology (smartboards, tablets, student laptops) to enable immediate interaction, feedback, and collaborative experiences. The primary goal of the invention is to provide a complete educational system that combines artificial intelligence (AI) and blended learning methods in a dynamic, personalized, and adaptive learning environment.The hybrid system aims to maximize both the teaching and learning process while maintaining the adaptability of online learning alongside the engaging, collaborative elements of the classroom environment. Utilizing AI technologies, this invention seeks to create an educational environment where study materials, assessments, and teaching methods are tailored in real time for each student based on their performance, learning styles, and progress.

[0010] Another important goal of the invention is to support educators in more effectively reaching at-risk students with relevant and actionable data. The invention aims to equip educators with AI-based tools that enable them to monitor student learning progress and provide actionable recommendations that can lead to improved learning outcomes. This robust data model allows educators to deliver more targeted, personalized instruction and make data-driven decisions in real time, both in online and face-to-face learning environments.

[0011] Another goal of the invention is to enable integrated online and face-to-face learning, allowing both to work together coherently and enabling the entire plan to function within existing educational infrastructures. It is scalable and adaptable for use from elementary school to higher education. The approach promotes the use of unified learning ecosystems of educational technologies in the classroom and offers a single platform that connects digital learning tools, classroom technologies, and AI analytics, helping to bridge virtual and physical learning spaces to support a continuous learning experience across different contexts.

[0012] By creating an adaptive learning platform, the invention aims to increase student engagement and retention rates through a unique, personalized learning experience that also considers non-cognitive attributes (e.g., motivation, emotional and mental state, collaborative skills). This means the AI ​​system must understand and respond to both of these factors to provide students with content and activities that are not only educational but also support learning and engagement, challenging for diverse students, and suitable for physical exertion, not just computer use. Learning should guarantee more than simply covering a standard set of topics; in this way, schools expect a more comprehensive educational experience that fosters intellectual, emotional, and social development and leads to better learning outcomes in the long run. BRIEF DESCRIPTION OF THE FIGURE Fig. Figure 1 shows a block diagram of a system for implementing a smart school based on artificial intelligence (AI) and blended learning. Detailed description of the invention:

[0013] In Fig.is a block diagram of a system for implementing a smart school based on artificial intelligence (AI) and blended learning, comprising: a central processing unit (CPU) 102 configured to receive, process, and store data from a range of user interfaces, learning management software modules, classroom interaction devices, and cloud-based data storage; an AI engine 104 integrated into the CPU, wherein the AI ​​engine is configured to analyze student interactions with educational content, classroom activities, and performance data in real time, applying machine learning techniques to create personalized learning paths for each student based on their individual learning style, past performance, and engagement patterns;a set of devices for classroom interaction 106, including at least one of the following: smartboard 106(a), tablet 106(b) or interactive projector 106(c), each device configured to capture real-time data of classroom activities such as student participation, verbal responses and collaborative tasks, the captured data being transferred to the CPU for analysis by the AI ​​engine to refine and dynamically adapt the learning paths for each student; a student user interface, the student interface 108 displaying dynamically generated content tailored to the student's progress and performance, and the content including multimedia materials such as videos, quizzes and reading material adapted based on the interaction history and the student's learning needs;a teacher interface 110 connected to the CPU, wherein the teacher interface displays real-time analytics and insights derived from student data, including performance trends, engagement levels, and potential learning gaps, and wherein the AI ​​engine provides the teacher with actionable recommendations for adapting teaching strategies, resources, and interventions based on individual student needs and classroom performance; a cloud-based storage system 112, wherein the system securely stores student profiles, historical performance data, and learning content, and wherein the CPU retrieves, updates, and stores data from the cloud-based system in real time to ensure continuous adaptation of the learning experience.

[0014] In one embodiment, the AI ​​engine uses 104 natural language processing (NLP) techniques to analyze student-generated content such as written answers and verbal input to assess the student's cognitive understanding, language proficiency, and reasoning skills, and the system adapts the provision of instructional materials based on these assessments.

[0015] In one embodiment, the student interface 108 also includes an interactive virtual assistant based on AI techniques, wherein the virtual assistant dynamically supports students by answering their questions, providing guidance on learning modules and making recommendations for supplementary learning materials based on the student's progress, learning objectives and identified knowledge gaps.

[0016] In one embodiment, the classroom interaction devices 106 also include sensor-based technologies, including speech recognition and motion detection, to capture and analyze students' participation in classroom activities, the system using this data to assess students' emotional and participation levels and to adjust the learning experience based on detected changes in students' behavior or mood.

[0017] In one embodiment, the AI ​​engine includes 104 predictive analyses to forecast student performance based on historical data, and the system proactively generates personalized tutoring assignments, supplementary content, or alternative learning strategies for students expected to struggle with certain learning objectives, thereby optimizing learning outcomes before problems arise.

[0018] In one embodiment, the AI ​​engine 104 is configured to analyze non-cognitive factors that influence student learning, including in particular motivation, engagement, and emotional well-being. The system then adapts learning content, pace, and delivery methods to optimize the overall learning experience and increase student engagement and success.

[0019] In one embodiment, the system includes a secure data management framework that uses end-to-end encryption to ensure the confidentiality and integrity of student data, including personal, academic, and interaction data, and where the framework complies with relevant data protection regulations such as FERPA and GDPR to protect student information while enabling data-driven decisions in real time.

[0020] In one embodiment, the system also includes a feedback mechanism 114 that allows students and teachers to provide input on AI-generated content and recommendations, with the feedback being analyzed by the AI ​​engine to refine personalization techniques and improve the quality of the learning experience over time.

[0021] In one embodiment, the system is configured to support the synchronization of multiple devices, allowing seamless access to student data, learning progress, and performance information across various devices, including smartphones, tablets, and PCs. This ensures that students can switch between learning environments without losing access to their personalized learning content.

[0022] This is an AI-based system that combines a wide range of technologies and methods to provide a well-structured, agile, and adaptive learning platform. Materials are delivered in a blended format, allowing students to access online content at their own pace and then participate in face-to-face sessions for interactive discussions, hands-on applications, and group work. The AI-powered element monitors student interaction with the materials and makes spontaneous adjustments to the teaching approach to ensure that no student falls behind, and that even high-achieving students are not left idly by.

[0023] Furthermore, the system's AI techniques can provide students with immediate feedback on their performance, including their strengths and weaknesses, as well as recommendations for additional resources or exercises to further improve their learning. The system also generates detailed analyses of student progress for teachers, identifying trends, problems, and concepts that may require further focus. By analyzing student data, teachers receive personalized suggestions for teaching methods, helping them to create more effective and targeted lessons.

[0024] The invention enables synchronous learning via digital platforms, allowing students to work at their own pace while still benefiting from the structure and interaction they receive in traditional classroom environments. This combination of self-directed and teacher-led instruction provides flexibility and ensures that students receive a comprehensive education.

[0025] This system, activated by the device, contains a number of different elements which, when combined, provide a complete smart school environment.

[0026] The present invention offers several significant advantages over conventional and current blended learning systems. Firstly, it provides a truly personalized learning experience, where AI is used to create content tailored to each student. This guarantees engagement and challenge from the outset at all performance levels.

[0027] The second aspect is that the invention improves teacher effectiveness by providing them with real-time analytics and AI-driven recommendations, enabling them to better serve their students and spontaneously adapt their teaching methods. The initial implementation of Test Blueprints allows teachers to use observational assessments to place each student into the appropriate target descriptor, thus freeing up more time for focused, high-quality instruction.

[0028] Thirdly, the system enables continuous, data-driven curriculum improvement by continuously assessing student progress and adapting the curriculum to new needs. This closes learning gaps and ensures students master the material.

[0029] Fourth, by implementing blended learning, students can benefit from the flexibility of online learning while also utilizing the face-to-face and experiential elements of the practical approach of traditional classrooms. This combination enables a holistic approach to creating a well-rounded education.

[0030] The model also offers potential for collaboration, as it allows for dissemination to different groups and can become a joint research development project in which different schools and organizations can test their own results based on the initial methodology.

[0031] Furthermore, a customizable interface allows the system to work with various devices and learning environments, from PCs and mobile phones to classroom terminals and interactive learning platforms. Update: We have a system that can synchronize learning progress and performance data across all devices, so students can move seamlessly between learning environments without ever losing their personalized learning content. This also gives students the freedom to access their work from any device, allowing them to continue their learning and studying wherever they are.

[0032] Furthermore, the AI-powered system can be deployed in diverse educational settings, from primary school classes with thirty or fewer students to universities with thousands of students on their campuses. This means the system is also highly scalable. It adapts to the specific needs of each educational environment—from small groups of students to advanced curricula. From small classes to large lectures, from primary school to the academic world, Romantic accommodates diverse subject areas and learning materials while remaining effective in every educational setting.

[0033] Another feature that would multiply the AI ​​engine's functionality is the integration of external learning tools and third-party platforms, from digital textbooks and online tutoring systems to student information systems (SIS). By linking external content, the system can provide a wider variety of learning materials that can be individually tailored to each learner. For example, if a particular student is struggling with a specific concept, the system could easily integrate a range of relevant external resources—additional digital textbooks or online exercises—into that student's personalized learning path. This adaptability allows the system to respond to the needs of both learners and instructors, creating a highly connected, AI-driven academic environment. REFERENCES 100 A block diagram of a system for implementing a smart school based on artificial intelligence (AI) and blended learning. 102 Central processing unit (CPU) 104 AI Engine 106 Set of Interaction Devices for the Classroom 106a S Martboard Article 106b Table 106c Interactive Projector 108 Student interface 110 Teacher interface 112 Cloud-based storage system 114 Feedback mechanism

Claims

[1] A system for implementing blended learning, comprising: • a central processing unit (CPU) configured to receive, process, and store data from a range of user interfaces, learning management software modules, classroom interaction devices, and cloud-based data storage; • an AI engine integrated into the CPU, configured to analyze student interactions with educational content, classroom activities, and performance data in real time, applying machine learning techniques to create personalized learning paths for each student based on their individual learning style, past performance, and engagement patterns; • A range of classroom interaction devices, including at least one smartboard, tablet, or interactive projector, with each device configured to collect real-time data from classroom activities, such as student engagement, oral responses, and collaborative tasks. The collected data is transferred to the CPU for analysis by the AI engine to refine and dynamically adapt learning paths for each student. • a student user interface, wherein the student interface displays dynamically generated content tailored to the student's progress and performance, and wherein the content includes multimedia materials such as videos, quizzes, and reading materials that are customized based on the student's interaction history and learning needs; • a teacher interface connected to the CPU, where the teacher interface displays real-time analytics and insights from student data, including performance trends, engagement levels, and potential learning gaps, and where the AI engine provides the teacher with actionable recommendations to adapt instructional strategies, resources, and interventions based on individual student needs and classroom performance; • a cloud-based storage system, whereby the system securely stores student profiles, historical performance data and learning content and whereby the CPU retrieves, updates and stores data in real time from the cloud-based system to ensure continuous adaptation of the learning experience. [2] The system of claim 1, wherein the AI engine uses natural language processing (NLP) techniques to analyze student-generated content, such as written responses and verbal inputs, to assess the student's cognitive understanding, language proficiency, and reasoning skills, and wherein the system adapts the delivery of instructional materials based on those assessments. [3] The system of claim 1, wherein the classroom interaction devices further comprise sensor-based technologies, including voice recognition and motion detection, to capture and analyze student engagement in classroom activities, the system using this data to assess student emotional levels and engagement and adapting the learning experience based on detected changes in student behavior or mood. [4] The system of claim 1, wherein the AI engine includes predictive analytics to forecast student performance based on historical data, and wherein the system proactively generates personalized remediation tasks, supplemental content, or alternative learning strategies for students predicted to have difficulty with specific learning objectives, thereby optimizing learning outcomes before problems arise. [5] The system of claim 1, wherein the AI engine is configured to analyze non-cognitive factors that influence student learning, including, but not limited to, motivation, engagement, and emotional well-being, and wherein the system adapts learning content, pace, and delivery methods to optimize the overall learning experience and promote better retention and greater student success.

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