CN117198099A - Video teaching system - Google Patents
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Abstract
The application discloses a video teaching system, which comprises a teaching resource center and a teaching terminal, wherein the teaching terminal comprises a video communication module, an intelligent teaching auxiliary module, a learning resource sharing module, a real-time monitoring and evaluating module and a data analysis and prediction module; through the video communication module, teachers and students promote face-to-face communication and interaction experience, and real-time interaction and face-to-face communication are realized; through the intelligent teaching auxiliary module, students are helped to better understand and master knowledge, and intelligent teaching assistance and personalized learning are realized; the learning resource sharing module is used for realizing the convenience of learning resource sharing and access; the real-time monitoring and evaluation module is used for monitoring and evaluating the learning condition of the students in real time, so that the real-time monitoring and evaluation is realized; through the data analysis and prediction module, the learning trend and difficulty of students are predicted, and teachers and students are helped to formulate more effective learning strategies.
Description
Technical Field
The application relates to the technical field of remote interactive teaching, in particular to a video teaching system.
Background
Along with the rapid development of the internet, remote education gradually becomes an important trend in the education field, however, the remote education mode has the problems of unsatisfactory teaching effect, weak interactivity and the like, the remote education mainly depends on video recording and online courseware modes for teaching, so that real-time interaction between students and teachers is limited, face-to-face communication and interaction experience is lacked, learning effect is difficult to evaluate, the remote education often lacks a real-time monitoring and evaluating mechanism for the learning condition of students, and the learning effect and progress of the students are difficult to evaluate accurately.
Disclosure of Invention
The present application is directed to a video teaching system for solving the above-mentioned problems.
In order to achieve the above purpose, the present application provides the following technical solutions:
the video teaching system comprises a teaching resource center and a teaching terminal, wherein the teaching resource center is connected with the teaching terminal by adopting a distributed architecture, and the teaching terminal comprises a video communication module, an intelligent teaching auxiliary module, a learning resource sharing module, a real-time monitoring and evaluating module and a data analysis and prediction module;
the video communication module is used for carrying out real-time audio and video communication between teachers and students and promoting face-to-face communication and interaction experience;
the intelligent teaching auxiliary module is used for analyzing learning data of students and generating a personalized learning scheme by utilizing an artificial intelligence technology;
the learning resource sharing module is used for a teacher to upload teaching courseware and teaching video teaching materials to a platform through the learning resource sharing module,
the real-time monitoring and evaluating module is connected with the database in a two-way communication way through the intelligent teaching auxiliary module, the system monitors and evaluates the learning condition of the students in real time, and the system analyzes the learning progress and understanding degree index of the students by collecting the learning data and feedback of the students and provides corresponding personalized advice and coaching for the students according to the evaluation result;
the data analysis and prediction module predicts the learning trend and difficulty of students through analysis and pattern recognition of the learning data of the students, provides corresponding prediction results and suggestions, and helps teachers and students to formulate more effective learning strategies.
Preferably, the video communication module is divided into an audio/video transmission unit and an information interaction unit,
the audio and video transmission unit is used for being responsible for real-time audio and video communication between a teacher and students, transmitting the explanation video of the teacher and the answers and discussion sounds of the students, providing high-quality video streams, directly receiving the questions of the students by the teacher through the audio and video transmission unit, and giving feedback and guidance in time;
the information interaction unit is used for being responsible for the communication of text and image information between a teacher and students, providing a chat window interface, enabling the teacher and the students to send text messages, expression signs and picture information, and enabling the students to give questions, share ideas and communicate ideas through the information interaction unit, and enabling the teacher to respond and give explanations in time.
Preferably, the intelligent teaching assistance module is divided into a learning data analysis unit and a personalized learning recommendation unit,
the learning data analysis unit is used for collecting, processing and analyzing learning data of students, analyzing and modeling learning behaviors of the students by using artificial intelligence technology so as to know learning conditions, learning progress and learning difficulties of the students, and generating learning curves, knowledge mastery assessment and learning trend prediction information by analyzing the learning data of the students, thereby providing individualized learning suggestions and guidance for teachers and the students;
the personalized learning recommendation unit provides personalized learning resources, coaching materials and exercise questions for students by using machine learning and recommendation algorithms based on learning data analysis results, recommends the learning materials most suitable for the students according to the learning conditions and demands of the students, and provides a learning route planning and customized learning plan for individual students by analyzing the learning preference, interest and history learning record of the students so as to help the students to learn efficiently and pertinently.
Preferably, the learning resource sharing is divided into a resource collecting and sorting unit and a resource sharing and exchanging unit,
and the resource uploading and sharing unit is responsible for teachers to upload teaching courseware, teaching videos and teaching materials to the platform and share the teaching courseware, the teaching videos and the teaching materials with students, and provides a unified platform for teachers to conveniently sort, upload and manage the teaching resources.
And the resource sharing and exchanging unit is used for enabling students to access and download learning materials shared by teachers on line, providing a convenient platform for the students to access and download teaching resources shared by the teachers at any time, enabling the students to log in the system, finding out the learning materials required by the students in a searching, browsing and screening mode, and carrying out on-line learning or downloading to local use.
Preferably, the real-time monitoring and evaluating module is divided into a student learning monitoring unit and a learning evaluating and feedback unit,
the student study monitoring unit is used for collecting, processing and monitoring study data of students, collecting study data of the students in real time, including study activities, answering situations and access time, and through tracking and analysis of the study data of the students, the student study monitoring unit knows study states, study progress and study behaviors of the students, and after the change or dilemma of the study situations of the students are monitored, the student study monitoring unit can trigger corresponding warning or reminding, so that teachers and students can timely adjust study strategies to help the students to obtain better study effects.
The learning evaluation and feedback unit is used for evaluating and feeding back according to the learning data collected by the student learning monitoring unit, evaluating the learning condition of the student according to the analysis result of the learning data, providing personalized feedback and guidance for the student, evaluating the mastery degree of the student on different knowledge points by comparing the learning progress, the answering condition and the accuracy index of the student, and based on the evaluation result, the unit can provide personalized learning advice and coaching for the student, helping the student to strengthen weak knowledge points and improving the learning effect.
Preferably, the data analysis and prediction module comprises a data prediction unit,
the data prediction unit predicts the learning condition and the learning trend of the students by using machine learning and prediction algorithms based on the results of the data analysis unit, predicts the development direction of future learning and difficulties encountered by the students according to the training of the historical learning data and the model, generates curves and trend predictions of the students, helps teachers and students to know the challenges faced by the students, and correspondingly formulates corresponding learning plans and strategies.
Preferably, the teaching resource center further comprises a database, and the database establishes a unified student learning data storage database for recording learning conditions, progress and assessment result information of students.
Preferably, the teaching resource center further comprises a training module for storing training questions for teaching, classifying and organizing according to the difficulty level and the question type, and selecting the training questions with corresponding difficulty by students according to the learning progress and the ability of students for training.
Preferably, the teaching resource center further comprises a practice module for providing practice teaching resources and experimental equipment for teachers and students so as to help the teachers and students to perform field practice and experiment operation, resources and materials required by practice teaching are provided for the teachers, related teaching resources are obtained through the practice module, and are properly adjusted and applied according to the requirement of practice courses, the teachers and students provide support of the experimental equipment for the teachers and the students, the teachers and the students obtain the required experimental equipment through the practice module to perform experiment operation and data acquisition, and the purpose of the support of the experimental equipment is to provide good experimental environment for the teachers and the students so that the teachers and the students can perform practical experimental study and study.
Preferably, the learning resource sharing module comprises:
s1, designing and constructing a database, wherein the database is required to be designed and constructed and is used for storing related information of learning resources, such as resource names, descriptions, types, uploaders and scores;
s2, user authority management, namely designing different user authority management systems comprising user registration, login, identity verification and authority control functions, and ensuring the safety and legitimacy of resources;
s3, uploading and publishing resources, wherein a teacher uploads learning resources through an interface and fills in related information, and after uploading, the system stores and indexes the resources so as to facilitate searching and browsing of other users;
s4, searching and filtering resources, wherein a user searches required learning resources, designs searching and filtering functions, and searches according to conditions such as keywords, resource types, scores and the like, and the system returns a learning resource list meeting the conditions;
s5, resource evaluation and comment are realized, the resource evaluation and comment functions are realized, the improvement of the resource quality and the communication among users are promoted, and the users score and leave a message on the used resources;
s6, recommending resources, namely designing a resource recommendation algorithm according to the historical behaviors and interest preferences of the user, and recommending related learning resources to the user;
and S7, statistics and analysis, wherein the system collects and analyzes the user behavior and the resource use condition data, generates corresponding statistics report forms and charts, and provides references for decision making.
The beneficial effects are that:
through the video communication module, teachers and students can conduct real-time audio and video communication, face-to-face communication and interaction experience are promoted, interaction between the students and the teachers can be enhanced, teaching is enabled to be more vivid and effective, and real-time interaction and face-to-face communication are achieved;
through the intelligent teaching assistance module, the learning data of students are analyzed, a personalized learning scheme is generated, the students are helped to better understand and master knowledge, targeted learning suggestions and coaching are provided, and intelligent teaching assistance and personalized learning are realized;
through the learning resource sharing module, a teacher uploads teaching courseware, teaching video and teaching materials to the platform and shares the teaching courseware, the teaching video and the teaching materials with students, and the students access and download the teaching resources at any time through the platform, so that learning and review are facilitated, and learning resource sharing and convenient access are realized;
through the real-time monitoring and evaluating module, the learning condition of the student is monitored and evaluated in real time, and a teacher knows the learning progress and difficulty of the student in time and gives corresponding guidance and support to realize real-time monitoring and evaluation;
through the data analysis and prediction module, the learning data of students are analyzed, the learning trend and difficulty of the students are predicted, corresponding prediction results and suggestions are provided, and teachers and students are helped to formulate more effective learning strategies.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those skilled in the art from this disclosure that the drawings described below are merely exemplary and that other embodiments may be derived from the drawings provided without undue effort.
FIG. 1 is a block diagram of a video teaching system according to the present application.
Wherein,
the system comprises a 1-teaching terminal, a 2-teaching resource center, a 3-video communication module, a 31-audio and video transmission unit, a 32-information interaction unit, a 4-intelligent teaching auxiliary module, a 41-learning data analysis unit, a 42-personalized learning recommendation unit, a 5-learning resource sharing module, a 51-resource collecting and arranging unit, a 52-resource sharing and exchanging unit, a 6-real-time monitoring and evaluating module, a 61-student learning monitoring unit, a 62-learning evaluation and feedback unit, a 7-data analysis and prediction module, a 71-data prediction unit, an 8-database, a 9-training module and a 10-practice module.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus consistent with some aspects of the disclosure as detailed in the accompanying claims.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1
As shown in fig. 1, the embodiment realizes real-time audio and video communication between a teacher and students through the video communication module 3, promotes face-to-face communication and interaction, and enhances the liveliness and effectiveness of teaching. The intelligent teaching assistance module 4 analyzes the learning data of the students, generates personalized learning schemes, provides targeted learning suggestions and coaches, helps the students to better understand and master knowledge, the learning resource sharing module 5 enables the teachers to upload teaching courseware, videos and materials and share the teaching courseware, the students to conveniently access and review, the real-time monitoring and evaluating module 6 can timely monitor the learning condition of the students, the teachers can know the progress and difficulty of the students, provide guidance and support, the data analysis and prediction module 7 analyzes the learning data of the students, predicts learning trend and difficulty, provides suggestions for the teachers and the students to formulate more effective learning strategies, can improve teaching effects, personalized learning, facilitate resource sharing, monitor and evaluate the learning condition of the students in real time, and predict and optimize the learning strategies through data analysis.
The video teaching system comprises a teaching resource center 2 and a teaching terminal 1, wherein the teaching resource center 2 is connected with the teaching terminal 1 by adopting a distributed architecture, and the teaching terminal 1 comprises a video communication module 3, an intelligent teaching auxiliary module 4, a learning resource sharing module 5, a real-time monitoring and evaluating module 6 and a data analysis and prediction module 7;
the video communication module 3 is used for carrying out real-time audio and video communication between teachers and students and promoting face-to-face communication and interaction experience; the teacher can directly conduct interactive teaching with students, solve problems and give feedback and guidance in time.
The intelligent teaching auxiliary module 4 analyzes learning data of students and generates a personalized learning scheme by utilizing an artificial intelligent technology; the system can recommend proper learning resources, coaching materials and exercise questions according to the learning situation and the demands of students, and helps the students to master knowledge better.
The learning resource sharing module 5 is used for enabling teachers to upload teaching courseware and teaching video teaching materials to the platform through the learning resource sharing module 5 so as to enable students to review and learn online, enabling students to access and download learning materials shared by the teachers at any time, and promoting sharing and learning interaction of the learning resources.
The real-time monitoring and evaluating module 6 is in bidirectional communication connection with the database 8 through the intelligent teaching auxiliary module 4, the system monitors and evaluates the learning condition of the students in real time, and the system analyzes the learning progress and understanding degree index of the students by collecting the learning data and feedback of the students and provides corresponding personalized advice and coaching for the students according to the evaluation result; meanwhile, a teacher can know the learning condition of the student in time, and the teacher can conduct teaching adjustment and tutoring pertinently.
The data analysis and prediction module 7 can predict the learning trend and difficulty of the students through analysis and pattern recognition of the learning data of the students, and provide corresponding prediction results and suggestions to help teachers and students to formulate more effective learning strategies.
The video communication module 3 is divided into an audio-video transmission unit 31 and an information interaction unit 32,
the audio/video transmission unit 31 is used for real-time audio/video communication between a teacher and students, transmitting the explanation video of the teacher and the answers and discussion sounds of the students, providing high-quality video streams, and directly receiving the questions of the students by the teacher and giving feedback and guidance in time through the audio/video transmission unit 31; the real-time audio and video interaction can promote learning effect and efficiency, and enhance participation and understanding ability of students.
The information interaction unit 32 is used for being responsible for text and image information exchange between the teacher and the students, providing a chat window interface, enabling the teacher and the students to send text messages, expression signs and picture information, and the students give questions, share ideas and exchange ideas through the information interaction unit 32, and the teacher responds and gives explanation in time. The information interaction of the words and the images is helpful to supplement the deficiency of audio and video communication, for example, students can express own questions clearly through the words when noise interference exists or the conversation speed is high. At the same time, the teacher may also use the information interaction unit 32 to send supplementary materials, links, and other references to better understand and learn knowledge by the student.
The video communication module 3 is more comprehensive and flexible in the teaching process, the audio and video transmission unit 31 provides real-time experience of face-to-face communication, and interactivity and intuitiveness are enhanced; the information interaction unit 32 provides more communication modes, and meets the diversified communication demands between students and teachers. Integrating the two units can create a teaching environment with better effect and efficiency, and provide better teaching experience.
The intelligent teaching assistance module 4 is divided into a learning data analysis unit 41 and a personalized learning recommendation unit 42,
the learning data analysis unit 41 is configured to collect, process and analyze learning data of students, analyze and model learning behaviors of the students by using artificial intelligence technology, so as to learn learning conditions, learning progress and learning difficulties of the students, and by analyzing the learning data of the students, the system can generate learning curves, knowledge mastery assessment and learning trend prediction information, and provide individualized learning advice and guidance for teachers and students. For example, the learning data analysis unit 41 may determine the understanding degree of the student according to the answering situation and the response time of the student, and automatically generate corresponding exercise questions or recommend related learning resources to help the student strengthen knowledge points.
The personalized learning recommendation unit 42 provides personalized learning resources, tutoring materials and exercise questions for students based on learning data analysis results by using machine learning and recommendation algorithms, recommends learning materials most suitable for each student according to the learning condition and the requirement of the student, and provides learning route planning and customized learning plans for individual students by analyzing the learning preference, interest and history learning record of the students so as to help the students learn efficiently and pertinently.
The personalized learning recommendation unit 42 precisely picks the appropriate teaching materials, courses, and coaching resources for the student to help the student to better learn knowledge.
Wherein, the learning data analysis unit 41 learns the learning condition and the demand of the student by deeply mining the learning data of the student; the personalized learning recommendation unit 42 provides accurate learning resources and suggestions for students according to the analysis result of learning data, so that students can learn more efficiently in the field of personal interest, meanwhile, the students can supplement and promote the learning recommendation unit in a targeted manner aiming at own weak points, the functions of the two units are integrated, the learning requirements of the students can be met to the greatest extent, and the students are helped to obtain better learning results.
The learning resource sharing is divided into a resource collecting and sorting unit 51 and a resource sharing and exchanging unit 52,
the resource collecting and sorting unit 51 is responsible for a teacher to upload teaching courseware, teaching video and teaching materials to the platform and share the teaching courseware, the teaching video and the teaching materials with students, provides a unified platform for the teacher, and facilitates sorting, uploading and management of the teaching resources. And a teacher can upload courseware, teaching videos and other teaching materials manufactured by the teacher to the platform according to the course requirement. Once uploading is completed, the resources can be used for students to review, learn and download on line, so that sharing and interaction of learning resources are promoted, teachers and students can share teaching resources conveniently, and learning efficiency and learning results of the students are improved;
the resource sharing and exchanging unit 52 provides a convenient platform for students to access and download the learning materials shared by teachers on line, and the students log in the system to find the learning materials needed by the students through searching, browsing and screening modes and learn on line or download the learning materials to local use. The requirement of students on learning resources shared by teachers is met, so that the students can learn flexibly and independently, and the required learning materials can be acquired anytime and anywhere.
The learning resource collection and arrangement module provides rich learning resources for users to select and acquire, and the learning resource sharing and communication module promotes interaction and communication among users, so that learning becomes richer and more interesting. The user can find the required learning resources through the two units and share and communicate with other users, so that a more comprehensive and deep learning experience is obtained.
The real-time monitoring and assessment module 6 is divided into a student learning monitoring unit 61 and a learning assessment and feedback unit 62,
the student learning monitoring unit 61 is configured to collect, process and monitor learning data of a student, collect learning data of the student in real time, including learning activities, answering situations and access time, and through tracking and analysis of the learning data of the student, the student learning monitoring unit 61 learns about learning status, learning progress and learning behavior of the student, and after monitoring a change or dilemma of the learning situation of the student, the student learning monitoring unit 61 triggers a corresponding warning or reminding, so that a teacher and the student can timely adjust learning strategies to help the student obtain a better learning effect.
The learning evaluation and feedback unit 62 is configured to evaluate and feedback according to the learning data collected by the student learning monitoring unit 61, evaluate the learning situation of the student according to the analysis result of the learning data, provide personalized feedback and guidance for the student, evaluate the mastery degree of the student on different knowledge points by comparing the learning progress, the answering situation and the accuracy index of the student, and based on the evaluation result, the unit can provide personalized learning advice and coaching for the student, help the student to strengthen weak knowledge points and improve learning effect. Meanwhile, the teacher can also use the learning evaluation and feedback unit 62 to learn the learning condition of the student to conduct targeted teaching adjustment and tutoring.
The learning condition of the students is monitored and evaluated in real time, and personalized feedback and guidance are provided according to the evaluation result. The student learning monitoring unit 61 is responsible for collecting student learning data and monitoring learning conditions, while the learning evaluation and feedback unit 62 evaluates students and provides relevant feedback and guidance by analyzing the learning data, and through such real-time monitoring and evaluation, teachers and students can better understand the learning progress and demands of students, timely adjust teaching methods and learning strategies, and improve learning effects and achievements.
The data analysis and prediction module 7 comprises a data prediction unit 71,
the data prediction unit 71 predicts the learning situation and learning trend of the student by using machine learning and prediction algorithm based on the result of the data analysis unit, predicts the development direction of future learning and the possible difficulties encountered by the student according to the training of the historical learning data and model, generates the curve and trend prediction of the student learning, helps the teacher and the student to understand the possible challenges of the student, and makes corresponding learning plans and strategies accordingly.
Through the data prediction unit 71, the teacher predicts difficulties that the student may encounter in advance and gives targeted guidance and support to improve the learning effect of the student.
The teaching resource center 2 further comprises a database 8, wherein the database 8 is used for establishing a unified student learning data storage database 8 and recording learning conditions, progress and assessment result information of students. The teacher can acquire the learning record of the student through the database 8, know the learning state of the student, and provide reference for personalized coaching.
The teaching resource center 2 further comprises a training module 9 for storing training questions for teaching, classifying and organizing according to the difficulty level and the questions, and selecting the training questions with corresponding difficulty by students according to the learning progress and the ability of students to practice.
The teaching resource center 2 further includes a practice module 10 for providing practice teaching resources and experimental facilities for teachers and students to assist them in performing practice and experimental operations in the field, and providing the teacher with resources and materials required for practice teaching, which may include contents in terms of design of practice teaching courses, case analysis, practice guidance, etc. Related teaching resources are acquired through the practice module 10, and are appropriately adjusted and applied according to the needs of the practice courses, so that support of experimental equipment is provided for teachers and students, including support in purchasing, maintaining, managing and the like of the experimental equipment, and normal operation and reliability of the experimental equipment are ensured. The teacher and the students obtain the required experimental equipment through the practice module 10 to perform experimental operation and data acquisition, and the purpose of the experimental equipment support is to provide good experimental environment for the teacher and the students, so that the teacher and the students can perform actual experimental study and study.
The implementation steps of the learning resource sharing module 5 are as follows:
s1, designing and constructing a database 8, wherein the database 8 is required to be designed and constructed and is used for storing related information of learning resources, such as resource names, descriptions, types, uploaders and scores;
s2, user authority management, namely designing different user authority management systems comprising user registration, login, identity verification and authority control functions, and ensuring the safety and legitimacy of resources;
s3, uploading and publishing resources, wherein a teacher uploads learning resources through an interface and fills in related information, and after uploading, the system stores and indexes the resources so as to facilitate searching and browsing of other users;
s4, searching and filtering resources, wherein a user searches required learning resources, designs searching and filtering functions, and searches according to conditions such as keywords, resource types, scores and the like, and the system returns a learning resource list meeting the conditions;
s5, resource evaluation and comment are realized, the resource evaluation and comment functions are realized, the improvement of the resource quality and the communication among users are promoted, and the users score and leave a message on the used resources;
s6, recommending resources, namely designing a resource recommendation algorithm according to the historical behaviors and interest preferences of the user, and recommending related learning resources to the user;
and S7, statistics and analysis, wherein the system collects and analyzes the user behavior and the resource use condition data, generates corresponding statistics report forms and charts, and provides references for decision making.
Example 2
The embodiment can comprehensively understand the learning effect and progress of students, timely adjust teaching strategies and provide necessary support and guidance, thereby continuously optimizing the teaching effect of remote education.
Setting a learning target, namely before learning is started, defining a learning target and an expected result, and setting a specific target by a teacher according to course content and learning requirements of students;
the learning process evaluation, namely recording learning behaviors and interaction conditions of students, such as course access time, class participation, answering conditions and the like, through a remote education platform so as to evaluate the activity degree and participation degree of the students in the learning process;
learning outcome assessment, in which students are informed and the ability level assessed by means of online tests, homework, projects and the like, and teachers can assess the learning outcome of the students by correcting homework or assessing project outcomes;
feedback and guidance, teachers give students feedback and guidance in time, help them correct errors, improve learning effects, and enable the teachers to interact with students in an online discussion or individual communication mode to encourage them to ask questions and communicate;
the learning score tracking, the learning score and the learning progress of the students are tracked, and the learning score and the evaluation result of the students are recorded so as to adjust and improve the teaching method when needed;
and the student feedback collection periodically collects feedback comments and suggestions of the students on the remote education, and knows the learning experience and the requirements of the students so as to continuously improve the teaching mode and the teaching quality.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope of the disclosure being indicated by the following claims.
Claims (10)
1. The video teaching system is characterized by comprising a teaching resource center (2) and a teaching terminal (1), wherein the teaching resource center (2) is connected with the teaching terminal (1) by adopting a distributed architecture, and the teaching terminal (1) comprises a video communication module (3), an intelligent teaching auxiliary module (4), a learning resource sharing module (5), a real-time monitoring and evaluating module (6) and a data analysis and prediction module (7);
the video communication module (3) is used for carrying out real-time audio and video communication between teachers and students so as to promote face-to-face communication and interaction experience;
the intelligent teaching auxiliary module (4) is used for analyzing learning data of students and generating a personalized learning scheme by utilizing an artificial intelligent technology;
the learning resource sharing module (5) is used for a teacher to upload teaching courseware and teaching video teaching materials to a platform through the learning resource sharing module (5),
the real-time monitoring and evaluating module (6) is in bidirectional communication connection with the database (8) through the intelligent teaching auxiliary module (4), the system monitors and evaluates the learning condition of the students in real time, and analyzes the learning progress and understanding degree index of the students through collecting the learning data and feedback of the students, and provides corresponding personalized advice and coaching for the students according to the evaluation result;
the data analysis and prediction module (7) predicts the learning trend and difficulty of the students through analysis and pattern recognition of the learning data of the students, provides corresponding prediction results and suggestions, and helps teachers and students to formulate more effective learning strategies.
2. A video teaching system according to claim 1, characterized in that the video communication module (3) is divided into an audio-video transmission unit (31) and an information interaction unit (32),
the audio and video transmission unit (31) is used for being responsible for real-time audio and video communication between a teacher and students, transmitting the explanation video of the teacher and the answers and discussion sounds of the students, providing high-quality video streams, directly receiving the questions of the students by the teacher through the audio and video transmission unit (31), and giving feedback and guidance in time;
the information interaction unit (32) is used for being responsible for the communication of text and image information between a teacher and students, providing a chat window interface, enabling the teacher and the students to send text information, expression signs and picture information, and enabling the students to give questions, share ideas and communicate ideas through the information interaction unit (32), and enabling the teacher to respond and give explanations in time.
3. A video teaching system according to claim 1, characterized in that the intelligent teaching assistance module (4) is divided into a learning data analysis unit (41) and a personalized learning recommendation unit (42),
the learning data analysis unit (41) is used for collecting, processing and analyzing learning data of students, analyzing and modeling learning behaviors of the students by using artificial intelligence technology so as to know learning conditions, learning progress and learning difficulties of the students, and generating learning curves, knowledge mastery assessment and learning trend prediction information by analyzing the learning data of the students, thereby providing individualized learning suggestions and guidance for teachers and students;
the personalized learning recommendation unit (42) provides personalized learning resources, tutoring materials and exercise questions for students by utilizing machine learning and recommendation algorithms based on learning data analysis results, recommends the learning materials which are most suitable for the students according to the learning conditions and demands of the students, and provides learning route planning and customized learning plans for individual students by analyzing the learning preferences, interests and historic learning records of the students so as to help the students to learn efficiently and pertinently.
4. The video teaching system according to claim 1, wherein the learning resource sharing is divided into a resource collecting and organizing unit (51) and a resource sharing and exchanging unit (52),
and the resource collection and arrangement unit (51) is responsible for a teacher to upload teaching courseware, teaching video and teaching materials to the platform and share the teaching courseware, the teaching video and the teaching materials with students, provides a unified platform for the teacher, and facilitates arrangement, uploading and management of the teaching resources.
And the resource sharing and exchanging unit (52) is used for enabling students to access and download learning materials shared by teachers on line, providing a convenient platform for the students to access and download teaching resources shared by the teachers at any time, enabling the students to log in the system, finding out the learning materials required by the students in a searching, browsing and screening mode, and performing on-line learning or downloading to local use.
5. A video teaching system according to claim 1, characterized in that the real-time monitoring and assessment module (6) is divided into a student learning monitoring unit (61) and a learning assessment and feedback unit (62),
the student study monitoring unit (61) is used for collecting, processing and monitoring study data of students, collecting study data of the students in real time, including study activities, answering situations and access time, and the student study monitoring unit (61) is used for knowing the study state, study progress and study behaviors of the students through tracking and analyzing the study data of the students, and after the change or dilemma of the study situations of the students are monitored, the student study monitoring unit (61) can trigger corresponding warning or reminding, so that teachers and students can timely adjust study strategies to help the students to obtain better study effects;
the learning evaluation and feedback unit (62) is used for evaluating and feeding back according to the learning data collected by the student learning monitoring unit (61), evaluating the learning condition of the student according to the analysis result of the learning data, providing personalized feedback and guidance for the student, evaluating the grasping degree of the student on different knowledge points by comparing the learning progress, the answering condition and the accuracy index of the student, and based on the evaluation result, the unit can provide personalized learning advice and coaching for the student, helping the student to strengthen weak knowledge points and improving the learning effect.
6. A video teaching system according to claim 1, characterized in that the data analysis and prediction module (7) comprises a data prediction unit (71),
the data prediction unit (71) predicts the learning condition and the learning trend of the students by using machine learning and prediction algorithms based on the results of the data analysis unit, predicts the development direction of future learning and difficulties encountered by the students according to the training of the historical learning data and the model, generates curves and trend predictions of the students, helps teachers and students to learn the challenges faced by the students, and correspondingly formulates corresponding learning plans and strategies.
7. A video teaching system according to claim 1, characterized in that the teaching resource center (2) further comprises a database (8), the database (8) establishes a unified student learning data storage database (8) for recording student learning situation, progress and assessment result information.
8. A video teaching system according to claim 1, characterized in that the teaching resource center (2) further comprises a training module (9) for storing training questions for teaching, classifying and organizing according to difficulty level and questions, and selecting training questions with corresponding difficulty level for training by students according to their learning progress and ability.
9. A video teaching system according to claim 1, characterized in that the teaching resource center (2) further comprises a practice module (10) for providing practical teaching resources and experimental equipment for teachers and students to assist them in practice and experimental operations in the field, providing resources and materials required for practical teaching for teachers, obtaining relevant teaching resources by the practice module (10), and making appropriate adjustments and applications according to the needs of practical courses, providing experimental equipment support for teachers and students, obtaining required experimental equipment for teachers and students by the practice module (10), performing experimental operations and data collection, the purpose of experimental equipment support being to provide good experimental environments for teachers and students, enabling them to conduct practical experimental study and study.
10. A video teaching system according to claim 1, characterized in that the implementation of the learning resource sharing module (5) comprises the steps of:
s1, designing and constructing a database (8), wherein the database (8) is required to be designed and created and is used for storing related information of learning resources, such as resource names, descriptions, types, uploaders and scores;
s2, user authority management, namely designing different user authority management systems comprising user registration, login, identity verification and authority control functions, and ensuring the safety and legitimacy of resources;
s3, uploading and publishing resources, wherein a teacher uploads learning resources through an interface and fills in related information, and after uploading, the system stores and indexes the resources so as to facilitate searching and browsing of other users;
s4, searching and filtering resources, wherein a user searches required learning resources, designs searching and filtering functions, and searches according to conditions such as keywords, resource types, scores and the like, and the system returns a learning resource list meeting the conditions;
s5, resource evaluation and comment are realized, the resource evaluation and comment functions are realized, the improvement of the resource quality and the communication among users are promoted, and the users score and leave a message on the used resources;
s6, recommending resources, namely designing a resource recommendation algorithm according to the historical behaviors and interest preferences of the user, and recommending related learning resources to the user;
and S7, statistics and analysis, wherein the system collects and analyzes the user behavior and the resource use condition data, generates corresponding statistics report forms and charts, and provides references for decision making.
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| CN202311145149.4A CN117198099A (en) | 2023-09-06 | 2023-09-06 | Video teaching system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117406866A (en) * | 2023-12-14 | 2024-01-16 | 南昌大藏科技有限公司 | VR experience system and method |
| CN117492871A (en) * | 2023-12-29 | 2024-02-02 | 辽宁向日葵数字技术股份有限公司 | Teaching activity construction method based on low codes and related equipment |
| CN117540108A (en) * | 2024-01-10 | 2024-02-09 | 人民卫生电子音像出版社有限公司 | Intelligent recommendation answering system based on examination point data distributed summary |
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2023
- 2023-09-06 CN CN202311145149.4A patent/CN117198099A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117406866A (en) * | 2023-12-14 | 2024-01-16 | 南昌大藏科技有限公司 | VR experience system and method |
| CN117492871A (en) * | 2023-12-29 | 2024-02-02 | 辽宁向日葵数字技术股份有限公司 | Teaching activity construction method based on low codes and related equipment |
| CN117492871B (en) * | 2023-12-29 | 2024-04-23 | 辽宁向日葵数字技术股份有限公司 | Teaching activity construction method based on low codes and related equipment |
| CN117540108A (en) * | 2024-01-10 | 2024-02-09 | 人民卫生电子音像出版社有限公司 | Intelligent recommendation answering system based on examination point data distributed summary |
| CN117540108B (en) * | 2024-01-10 | 2024-04-02 | 人民卫生电子音像出版社有限公司 | Intelligent recommendation answering system based on examination point data distributed summary |
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