MACHINE LEARNING BASED SYSTEM WITH DIGITAL MEDIA TECHNOLOGIES FOR RESOLVING OBSTRUCTIONS IN ONLINE TEACHING

Abstract

The present invention relates to a machine learning-based system integrated with digital media technologies to enhance the efficiency and effectiveness of online teaching. The system comprises wearable haptic feedback devices, VR/AR headsets, AI-powered digital pens, and eye tracking sensors to address common obstructions in virtual classrooms, such as student disengagement, limited interaction, ineffective content delivery, and lack of immersive experiences. Machine learning models are used to continuously monitor student engagement, facilitate adaptive learning, and provide personalized educational pathways. The system aims to improve student engagement, enhance learning outcomes, and provide a more inclusive and adaptive learning environment by utilizing real-time data analysis, immersive tools, and personalized feedback mechanisms, ultimately promoting effective and interactive online education.

Specification

Description:[013] The following sections of this article will provide various embodiments of the current invention with references to the accompanying drawings, whereby the reference numbers utilised in the picture correspond to like elements throughout the description. However, this invention is not limited to the embodiment described here and may be embodied in several other ways. Instead, the embodiment is included to ensure that this disclosure is extensive and complete and that individuals of ordinary skill in the art are properly informed of the extent of the invention. Numerical values and ranges are given for many parts of the implementations discussed in the following thorough discussion. These numbers and ranges are merely to be used as examples and are not meant to restrict the claims' applicability. A variety of materials are also recognised as fitting for certain aspects of the implementations. These materials should only be used as examples and are not meant to restrict the application of the innovation.
[014] Referring now to the drawings, these are illustrated in FIG. 1, the present invention is a machine learning-based system integrated with digital media technologies designed to address and resolve various obstructions commonly faced in online teaching environments. The system utilizes a combination of advanced hardware components and machine learning algorithms to create an adaptive and engaging virtual classroom.
[015] In accordance with another embodiment of the present invention, wearable haptic feedback device is a key component designed to enhance engagement in online teaching. It consists of a wearable band equipped with a vibration motor and haptic feedback sensors. The wearable band is provided to both students and instructors, with the primary objective of discreetly alerting students when their attention drops. By monitoring physiological indicators such as hand movements and skin conductivity, which correlate with attention levels, the wearable band can activate a vibration motor to provide immediate, discrete feedback. This nudging mechanism helps remind students to refocus during lessons. Moreover, the band also serves instructors by notifying them when a student's engagement has dropped, allowing for timely intervention to maintain an effective and interactive learning environment.
[016] In accordance with another embodiment of the present invention, the VR/AR headset plays a critical role in providing an immersive learning environment that bridges the gap between theoretical and hands-on learning experiences. Using devices such as Oculus Quest 2 or Microsoft HoloLens, the system delivers virtual experiments, 3D visualizations, and interactive group activities that simulate real-world scenarios. The VR/AR technology allows students to visualize complex subjects through immersive interactions, significantly improving comprehension and retention. The headset's detailed operation includes configuring simulations, virtual tours, and collaborative environments that can cater to both individual and group-based learning needs. By engaging in virtual, hands-on experiences, students can better grasp complex topics, which are often challenging in traditional online learning environments.
[017] In accordance with another embodiment of the present invention, AI-powered digital pen, such as the Livescribe Echo, enhances the note-taking experience by enabling students to take handwritten notes that are simultaneously converted into digital text. The pen is integrated with motion tracking sensors and Bluetooth connectivity, allowing for real-time transcription and seamless digital storage. This system bridges the physical and digital aspects of learning, providing feedback on written content to ensure students fully understand the material. In addition, notes are automatically digitized and organized, making them easily accessible for future reference and enhancing the learning continuity as illustrated in figure 2.
[018] In accordance with another embodiment of the present invention, the eye tracking sensor, such as the Tobii Eye Tracker, is utilized to continuously monitor student engagement during lessons by tracking their eye movements. It captures critical data on gaze direction, blinks, and duration of focus, feeding this information into machine learning models that analyze patterns of attention or distraction. When a drop in focus is detected, the system generates alerts for both students and instructors, prompting corrective actions to maintain student engagement. This technology enables a deeper understanding of how students interact with online content, allowing instructors to adjust teaching strategies to optimize learning effectiveness.
[019] The system monitors student focus levels in real-time using the eye tracking sensor, and valuable data is analyzed through machine learning algorithms. If a drop in engagement is detected, the system sends haptic feedback through the wearable band, gently nudging the student to refocus on the lesson. Instructors are also provided with visual indicators regarding overall class engagement, allowing them to adapt their teaching style or introduce interactive activities as needed.
By utilizing the VR/AR headset, the system creates an immersive classroom experience that simulates real-world experiments, 3D models, and virtual field trips. This environment caters to visual and experiential learners, overcoming the limitations of traditional online education that lack physical interaction. The use of immersive tools enhances understanding and allows students to engage more deeply with the subject matter, thereby improving learning outcomes.
[020] The AI-powered digital pen provides a natural note-taking experience while converting notes into a digital format for easy access and review. The system allows for keyword searches and provides real-time feedback on the quality of notes, ensuring that students comprehend the material effectively. The seamless transition from physical to digital note-taking enhances the overall learning process by integrating traditional study methods with modern technologies.
[021] The wearable haptic feedback device serves as a key mechanism for maintaining student and instructor engagement throughout each session. Subtle vibrations are sent to students when attention levels drop, while instructors are reminded to re-engage students or modify their teaching approach as necessary. This feature is crucial for preventing distractions and ensuring that all participants remain actively involved in the learning process.
[022] The machine learning models utilized in this system analyze data gathered from the eye tracking sensor, VR/AR interactions, haptic feedback devices, and digital pen usage. These models generate insights that enable the system to recommend personalized content, adjust the difficulty of lessons, and modify pacing based on individual needs. The adaptive teaching mechanism ensures that students receive the support they need, regardless of their learning style or proficiency level, ultimately providing a tailored educational experience. By integrating machine learning, wearable technology, VR/AR, and other digital media technologies, the proposed system creates an engaging and effective online teaching environment that addresses common challenges faced in traditional online education. The system ultimately promotes higher engagement, improved learning outcomes, and a more personalized approach to education.
[023] The benefits and advantages that the present invention may offer have been discussed above with reference to particular embodiments. These benefits and advantages are not to be interpreted as critical, necessary, or essential features of any or all of the embodiments, nor are they to be read as any elements or constraints that might contribute to their occurring or becoming more evident.
[024] Although specific embodiments have been used to describe the current invention, it should be recognized that these embodiments are merely illustrative and that the invention is not limited to them. The aforementioned embodiments are open to numerous alterations, additions, and improvements. These adaptations, changes, additions, and enhancements are considered to be within the purview of the invention. , Claims:1. A machine learning-based system for enhancing online teaching, comprising:
a wearable haptic feedback device configured to provide discrete feedback to students and instructors, enhancing engagement and enabling timely intervention;
a VR/AR headset configured to create an immersive virtual classroom environment for facilitating hands-on learning experiences;
an AI-powered digital pen configured to convert handwritten notes into digital formats, providing real-time transcription and feedback;
an eye tracking sensor configured to monitor student focus levels during online sessions and provide data for analysis by machine learning models;
a computing system configured to analyze data from the wearable haptic feedback device, VR/AR headset, AI-powered digital pen, and eye tracking sensor to provide adaptive and personalized learning experiences.
2. The system as claimed in claim 1, wherein the wearable haptic feedback device alerts students to refocus when engagement drops, and notifies instructors of disengagement for timely intervention.
3. The system as claimed in claim 1, wherein the VR/AR headset is further configured to provide simulations of real-world experiments, 3D visualizations, and virtual field trips to enhance comprehension and retention.
4. The system as claimed in claim 1, wherein the AI-powered digital pen digitizes handwritten notes, supports keyword search, and offers feedback to students during note-taking.
5. The system as claimed in claim 1, wherein the eye tracking sensor provides real-time engagement data, enabling instructors to adapt their teaching style or introduce interactive activities based on student focus levels.
6. The system as claimed in claim 1, wherein the computing system utilizes machine learning models to analyze engagement data and recommend personalized content, adjust lesson difficulty, and modify lesson pacing for individual students.
7. The system as claimed in claim 1, wherein the wearable haptic feedback device is configured to provide different levels of vibration intensity based on the level of student disengagement.
8. The system as claimed in claim 1, wherein the VR/AR headset is configured to allow students to interact with virtual objects and collaborate with peers in a shared virtual environment.
9. The system as claimed in claim 1, wherein the computing system includes a feedback loop for instructors, providing insights on the effectiveness of teaching strategies and recommending adjustments.
10. A method for enhancing online teaching using machine learning and digital media technologies, comprising the steps of:
a) Monitoring student engagement levels using an eye tracking sensor to capture data on gaze direction, blinks, and duration of focus;
b) Analyzing the engagement data in real-time using machine learning models to detect drops in student attention;
c) Sending discrete feedback through a wearable haptic feedback device to alert students when engagement drops;
d) Providing immersive learning experiences using a VR/AR headset, including virtual experiments, 3D visualizations, and collaborative group activities;
e) Facilitating personalized note-taking using an AI-powered digital pen that converts handwritten notes into digital formats with real-time transcription and feedback;
f) Generating adaptive learning recommendations based on data from the eye tracking sensor, wearable haptic feedback device, VR/AR interactions, and digital pen usage to tailor the content, pacing, and difficulty level of lessons to individual student needs.

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