Immersive video situation-based English accidental learning system and method
By introducing immersive video and virtual reality technology into English learning, we dynamically generate and recommend personalized learning content, and solve the problem of lack of interactivity and contextualization of traditional English learning methods, and achieve an efficient and interesting English learning experience.
Patent Information
- Application Number
- CN202411454633.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-17
- Publication Date
- 2025-05-02
AI Technical Summary
The lack of interactivity and contextualization of traditional English learning methods leads to insufficient motivation and interest among learners, making it difficult to flexibly apply the learned knowledge in actual communication.
By combining immersive video technology and contextual learning theory, an English occasional learning system based on virtual reality is developed. The system uses a large language model to generate learning content dynamically, personalizes recommendations based on user interests and emotions, and displays learning materials in video contexts through augmented reality technology.
It has achieved a high degree of interaction and contextualization of English learning, stimulated learners' interest and motivation, improved learning efficiency and practical application ability, and effectively made up for the shortcomings of traditional learning models.
Smart Images
Figure FT_1
Abstract
Description
Technical Field
[0002] The present invention relates to the field of English teaching technology, and in particular to an English occasional learning system and method based on immersive video and context. The system integrates immersive video technology and contextual learning theory to provide users with an efficient and interesting way to learn English, and improves users' learning efficiency and interest by naturally integrating English learning content into daily life. Background Art
[0003] In the traditional English learning environment, learners often face two major challenges. First, traditional learning methods focus more on mechanical memorization and repeated practice. Although this method has a certain effect on strengthening memory, it ignores the interactivity and contextualization of learning, and it is difficult to effectively stimulate learners' intrinsic motivation and interest. The lack of simulation of real context limits learners' ability to flexibly apply what they have learned to actual communication, which in turn affects the depth and breadth of learning results. Secondly, English learning is essentially a process of gradual accumulation and continuous practice. However, repetitive learning activities under the traditional education model often appear monotonous and boring, which easily makes students feel bored, thereby weakening their willingness and motivation to continue learning. This lack of learning motivation is undoubtedly a major obstacle for English learning, which requires long-term investment and persistence.
[0004] In recent years, with the increasing maturity and popularity of virtual reality (VR) technology, immersive video technology has brought new possibilities for English learning. This technology creates a highly interactive and immersive learning scene for learners by simulating a realistic audio-visual environment. This immersive experience can not only attract students' attention, improve the fun and participation of learning, but also promote the absorption and application of English knowledge in simulated real situations, effectively making up for the shortcomings of traditional learning models. The English occasional learning system and method based on immersive video situations conforms to this technological trend. It aims to make full use of students' fragmented time, interests and current specific situations through intelligent and personalized learning content generation, so as to carry out flexible and efficient English learning. This learning method encourages learners to discover and explore English knowledge in a natural situation, so as to accumulate language skills unconsciously and achieve seamless integration and long-term accumulation of English learning. Summary of the invention
[0005] The purpose of the present invention is to provide an English sporadic learning system and method based on immersive video and context. Combining the emerging immersive video technology, sporadic learning mechanism and the inference ability of large language models, the system can dynamically generate and push suitable English learning content based on the video elements in the immersive video, the current context and the user's emotions using the large model, thereby realizing English sporadic learning based on immersive context.
[0006] Technical Solution
[0007] This invention proposes an "English sporadic learning system and method based on immersive video context", which aims to provide English learners with a highly interactive and contextualized learning environment through virtual reality (VR) technology, so as to achieve sporadic and efficient English learning. The specific technical solution is as follows:
[0008] 1. System architecture
[0009] This system mainly includes virtual reality equipment, video playback module, user interaction module, image recognition and analysis module, large model retrieval and learning material generation module and augmented reality display module.
[0010] 2. Workflow
[0011] 2.1 Virtual Reality Video Watching
[0012] Step 1: The user wears the virtual reality device, starts the system and enters the immersive video viewing mode. The system plays the immersive video content prepared in advance or acquired in real time.
[0013] 2.2 User Interest Identification
[0014] Step 2: During video viewing, the system monitors the user's gaze through the eye tracking function of the VR device and identifies the user's interest in specific elements in the video (such as objects, places, environments, etc.).
[0015] 2.3 Gaze target location and analysis
[0016] Step 3: When the user's gaze stays on an element of interest for a long time, the system obtains the screen coordinates of the element and its corresponding video area.
[0017] Step 4: Use the image recognition and analysis module to perform image processing and feature extraction on the acquired video area, identify the category, attributes and other information of the video element target, and generate corresponding keywords.
[0018] 2.4 Learning material generation
[0019] Step 5: Based on the generated keywords, the system uses a large model retrieval mechanism (such as a model based on natural language processing or knowledge graph) to retrieve and generate English learning materials related to the target of the video element, including but not limited to English words, English descriptions of background knowledge, relevant English examples, etc.
[0020] 2.5 Material screening based on user emotions
[0021] Step 6: For users wearing devices such as smart watches, predict user emotions and adaptively select English learning materials that are suitable for user emotions to enhance user learning interest and learning efficiency.
[0022] 2.5 Augmented Reality Display
[0023] Step 7: Users can choose to display the above learning materials in an immersive environment at any time according to their needs. The system uses augmented reality technology to display the learning materials in an overlay around or at related locations of the video element target, ensuring that the learning materials are closely integrated with the video context and enhancing the learning experience.
[0024] 3. Technical features
[0025] Highly interactive: Through eye tracking and augmented reality technology, users can interact with video content in real time, improving learning participation.
[0026] Contextualized learning: Integrating English learning into real video contexts makes the learning process more vivid and interesting, and helps with the memory and application of knowledge.
[0027] Personalized learning: Generate learning materials based on the user's interests and current situation to customize personalized learning paths.
[0028] Efficiency: Use large models to quickly generate learning materials, reduce the time users spend searching for information manually, and improve learning efficiency.
[0029] 4. Implementation Effect
[0030] The implementation of this invention will effectively improve the monotony and inefficiency of traditional English learning methods, stimulate learners' learning interest and motivation, and promote the long-term accumulation of English knowledge and the improvement of practical application ability. At the same time, it also provides new ideas and practical cases for the application of virtual reality technology in the field of education. Instruction Manual Figure 1 It is a flow chart of the English incidental learning system and method based on immersive video context.
Claims
1. An English sporadic learning system based on immersive video context, characterized by include: 1.1 Virtual reality devices, used to provide users with immersive video viewing experience; 1.2 Video playback module, used to play immersive video content; 1.3 User interaction module, including eye tracking function, which is used to monitor the user's gaze and identify the user's interest in elements in the video; 1.4 Image recognition and analysis module, used to process images and extract features of the video area that the user is looking at, and generate keywords for the corresponding elements; 1.5 Large model retrieval and learning material generation module, which retrieves and generates English learning materials related to the element based on the generated keywords, including English words, English descriptions of background knowledge and related English sentences; 1.6 Augmented reality display module, used to overlay learning materials around video elements of interest to the user in an immersive environment in an augmented reality manner.
2. The system according to claim 1, characterized in that The user interaction module further includes a gaze detection algorithm for determining whether the user's gaze stays on a certain video element for a long time to determine the user's interest point.
3. The system according to claim 1, characterized in that The image recognition and analysis module uses machine learning or deep learning technology to automatically identify and classify video areas to accurately generate element keywords.
4. The system according to claim 1, characterized in that The large model retrieval and learning material generation module is connected to an external database or knowledge graph to retrieve and generate rich English learning materials.
5. The system according to claim 1, characterized in that It also includes a user selection module, which allows the user to choose whether to display the learning materials and the display method of the learning materials according to their own needs.
6. An English sporadic learning method based on immersive video context, characterized by comprising the following steps: 6.1 Users wear virtual reality devices and watch immersive videos; 6.2 Monitor the user's gaze through eye tracking and identify the user's interest in elements in the video; 6.3 Perform image recognition and analysis on the video area that the user is looking at, and generate keywords for the corresponding elements; 6.4 Search the large model based on keywords and generate English learning materials related to the element; 6.5 For users wearing smart watches and other devices, predict the user's emotions and adaptively select English learning materials that are suitable for the user's emotions; 6.6 Upon user request or system preset conditions, learning materials will be displayed in an augmented reality manner around video elements for users to learn from.
7. The method according to claim 6, characterized in that The step of allowing the user to adjust the display position and form of the learning materials according to their own needs is also included.
8. The method according to claim 6 or 7, characterized in that: The method also includes the steps of collecting learning feedback from users to optimize the generation and display strategies of learning materials.
9. A computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method according to any one of claims 6 to 8.
10. An English sporadic learning device based on immersive video context, comprising a processor and a memory, wherein a computer program is stored in the memory, and when the processor executes the computer program, the method according to any one of claims 6 to 8 is implemented.