Teaching interaction device based on artificial intelligence

Abstract

The invention provides a teaching interaction device based on artificial intelligence, and relates to the field of teaching interaction methods. The teaching interaction device based on artificial intelligence comprises a teaching total system, the teaching interaction device based on artificial intelligence is controlled by the teaching total system, and the teaching total system comprises three functional modules including a management module, a teacher teaching end module and a student learning end module. The management module comprises a hardware management function module and a system management module, the teacher teaching end module and the student learning end module share one teaching public module, and the teacher teaching end module comprises an independent special teacher function module. According to the teaching interaction device disclosed by the invention, a teacher can comprehensively know each student in a more detailed manner through the visual data report, so that teaching according to materials is really achieved, the excellent effect of personalized autonomous learning of each student is met, and the differentiated learning requirements of different students are practically met.

Description

Technical Field

[0001] The present invention relates to the field of teaching interaction methods, and in particular to a teaching interaction device based on artificial intelligence. Background Art

[0002] In the digital age, artificial intelligence technology is booming at an unprecedented rate, profoundly changing the face of various industries. The traditional education model focuses on one-way knowledge transfer, students passively accept, and it is difficult to meet individual differences. In addition, due to the imbalance of regional development, the educational gap between regions has become more and more obvious. Therefore, in remote areas or places where educational resources are relatively scarce, problems such as scarcity of excellent teachers and outdated teaching facilities have long restricted the development of local education. With the help of artificial intelligence teaching interactive equipment, students in these areas can transcend geographical restrictions and obtain massive high-quality educational resources. Therefore, the present invention proposes an artificial intelligence-based teaching interactive device, so as to effectively meet the above needs, improve teachers' teaching quality and students' learning efficiency, and at the same time greatly narrow the educational gap caused by geographical, economic and other factors, providing strong support for achieving educational equity. Summary of the invention

[0003] 1. Technical issues to be resolved

[0004] In view of the shortcomings of the prior art, the present invention provides an interactive teaching device based on artificial intelligence, which can process and generate voice recognition and image recognition. The voice recognition technology aims to accurately convert human voice into text form, bringing a new and convenient experience to teaching interaction. When students encounter learning difficulties, they can directly ask questions to the smart device. The device uses voice recognition technology to accurately understand the problem and quickly give an answer. The image recognition technology can use a learning device equipped with image recognition function to scan mathematical geometry figures, physical experiment device diagrams, and chemical molecular structure diagrams in textbooks. The device can instantly recognize the graphics and link to relevant knowledge point explanations, demonstration videos, and supporting exercises, providing students with a complete set of learning experience. It provides all-round and multi-level learning resources, and teachers can, with the assistance of the big data management system, quickly customize and compile courses based on the actual situation of each student. The big data management system can collect detailed information such as students' daily learning time, answer accuracy, time spent on knowledge points, course browsing records, etc. according to each student's learning situation. It also obtains in-depth data such as students' interests, learning motivation, and anxiety level through questionnaires, psychological assessments, etc. Teachers can understand each student in more detail and comprehensively through visual data reports, so as to truly teach students in accordance with their aptitude, thereby meeting the excellent results of each student's personalized and independent learning, and effectively meeting the differentiated learning needs of different students.

[0005] (II) Technical solution

[0006] To achieve the above purpose, the present invention is implemented through the following technical solutions: an artificial intelligence-based teaching interactive device, including a teaching system, the artificial intelligence-based teaching interactive device is controlled by a teaching system, the teaching system includes three functional modules: a management module, a teacher teaching end module and a student learning end module, the management module includes a hardware management function module and a system management module, the teacher teaching end module and the student learning end module share a teaching common module, the teacher teaching end module includes a separate teacher-specific function module, the equipment managed by the hardware management function module includes input equipment, output equipment and hardware equipment, the functions managed by the system management module include intelligent auxiliary modules, data management modules and information announcement modules, the artificial intelligence-based teaching interactive device realizes speech recognition technology, image recognition technology, natural speech processing technology and machine learning technology through hardware equipment;

[0007] Through the above technical solutions, the teaching interactive device achieves the function of intelligent teaching interaction through the cooperation of various functional hardware and system software, uses artificial intelligence technology, and deeply integrates various cutting-edge technologies such as computer vision, speech recognition, natural language processing, and machine learning. While improving students' learning efficiency and teachers' teaching quality, it can also effectively reduce the burden of teaching and learning.

[0008] Preferably, the hardware controlled by the teaching system is divided into three types: input devices, output devices and hardware devices. The input devices include touch screens, electronic writing boards, keyboards and mice, image input devices and audio input devices. The output devices include projection devices, display screens and audio output devices. The hardware devices include core processors, servers, network communication devices and data storage devices.

[0009] Through the above technical solutions, input devices and output devices assist teachers and students to realize a series of teaching functions such as remote teaching, voice interaction, online testing, etc. Data storage devices, core processors and other equipment are used to realize intelligent teaching interaction through distributed storage, optimize data processing algorithms, improve computing power, and realize efficient processing of massive student data, providing strong guarantees for precise teaching.

[0010] Preferably, the intelligent assistance system function of the management module includes a speech recognition processing function, a speech generation function, an image recognition processing function and an image generation function; the data management system function of the management module includes a data statistics and summarization function, a data analysis function, a data report visualization function and a data storage function; the information announcement module includes an announcement information release function and a teaching achievement display function;

[0011] Through the above technical solutions, the voice recognition and generation functions of voice recognition technology help to achieve barrier-free learning and communication. When students encounter learning difficulties, they can directly ask questions to the smart device. The device uses voice recognition technology to accurately understand the problem and quickly give answers. The answer can be generated through voice. Through intelligent training, the voice generation is consistent with the teacher's voice, making the student learning process more realistic. The image recognition and generation function can be used when students use learning devices equipped with image recognition functions to scan mathematical geometry figures, physical experiment equipment diagrams, and chemical molecular structure diagrams in textbooks. The device can instantly recognize the graphics and link to relevant knowledge point explanations, demonstration videos, and supporting exercises, providing students with all-round and multi-level learning resources.

[0012] Preferably, the teacher teaching end module and the student learning end module realize login distinction through a login identification system, the login identification system includes an identity recognition system module, the teacher end module and the student end module are both logged in and identified through the identity recognition system module in the login system module, and the identity recognition system module verifies the identity of the teacher and the student through account password, fingerprint recognition technology and face recognition technology;

[0013] Through the above technical solution, students and teachers are identified through the login identification system, so that the system can distinguish the use of functions, making the use of the entire device more targeted, safe and efficient.

[0014] Preferably, the common teaching module in the overall teaching system includes homework answering function, forum communication function, teaching resource sharing function, online testing function and remote teaching function. The common teaching module realizes barrier-free learning communication through an intelligent auxiliary system. The homework answering function and the online testing function are both quickly identified through image recognition technology, and the correct answers and test reports are given through machine learning technology and big data search technology.

[0015] Preferably, the teacher-specific module in the overall teaching system includes a course writing function, an online teaching function, a data sorting function, a personalized customization function, and a discussion and answering function. The personalized customization is based on the big data summary statistics and data analysis functions to conduct a comprehensive and in-depth analysis of students' learning behaviors and knowledge mastery. The system records in detail the multi-dimensional data such as students' learning time, answer accuracy, wrong question types, and knowledge point dwell time, and builds a personalized learning model for students through intelligent algorithms. The course writing function is based on the data analysis function and the data report visualization generation function, and can conduct targeted course teaching based on a large amount of students' learning records, classroom performance, homework completion status and other data, quickly and accurately analyze these complex and diverse data, extract valuable information from them, and provide support for teaching decisions;

[0016] Through the above technical solutions, students' personalized needs can be understood by collecting their learning data, such as learning progress, learning style, knowledge mastery, etc. Data mining and machine learning algorithms in artificial intelligence technology can be used to analyze students' learning behaviors, thereby providing a basis for personalized customization, and building personalized teaching content based on the results of student demand analysis. Machine learning-based teaching content customization methods can be used, such as building an inverse optimization model, minimizing the adjustment of configuration parameters and customizing resource constraints, generating more reasonable and effective teaching content configuration plans, and considering content diversity, student needs and resource constraints to ensure that the teaching content not only meets students' personalized needs, but also achieves efficient teaching under limited resources.

[0017] (III) Beneficial effects

[0018] The present invention provides a teaching interactive device based on artificial intelligence. It has the following beneficial effects:

[0019] 1. The present invention provides an interactive teaching device based on artificial intelligence. An intelligent auxiliary system is installed in the teaching device. Through voice recognition processing and generation functions and image recognition processing and generation functions, the voice recognition technology aims to accurately convert human voice into text form, bringing a new and convenient experience to teaching interaction. When students encounter learning difficulties, they can directly ask questions to the intelligent device. The device uses voice recognition technology to accurately understand the problem and quickly give answers. The image recognition technology can use a learning device equipped with image recognition function to scan mathematical geometry figures, physical experiment device diagrams, and chemical molecular structure diagrams in the textbook. The device can instantly recognize the graphics and link to relevant knowledge point explanations, demonstration videos, and supporting exercises, providing students with all-round and multi-level learning resources.

[0020] 2. The present invention provides an interactive teaching device based on artificial intelligence. With the assistance of a big data management system, teachers can quickly customize and compile courses according to the actual personal situation of each student. The big data management system can collect detailed information such as the student's daily learning time, answer accuracy, knowledge point dwell time, course browsing history, etc. according to each student's learning situation. It can also obtain in-depth data such as students' interests, learning motivation, anxiety level, etc. through questionnaires, psychological assessments, etc. Teachers can understand each student in more detail and comprehensively through visual data reports, thereby truly achieving teaching students in accordance with their aptitude, thereby meeting the excellent results of each student's personalized and independent learning, and effectively meeting the differentiated learning needs of different students. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The figure is a whole system diagram of the teaching interactive device based on artificial intelligence of the present invention;

[0022] Figure 2 A system management diagram of a management module of the teaching interactive device based on artificial intelligence of the present invention;

[0023] Figure 3 A hardware management diagram of a management module of the teaching interactive device based on artificial intelligence of the present invention;

[0024] Figure 4 It is a system diagram of the teaching module of the teaching interaction device based on artificial intelligence of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In the description of this application, it should be noted that the terms used here are only for describing specific implementations, and are not intended to limit the exemplary implementations according to the present application. For ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The techniques, methods and devices known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the techniques, methods and devices should be regarded as part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary, not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0026] Embodiment 1:

[0027] like Figure 1-4As shown, an embodiment of the present invention provides an artificial intelligence-based teaching interaction device, including a teaching system. The artificial intelligence-based teaching interaction device is controlled by a teaching system. The teaching system includes three functional modules: a management module, a teacher teaching end module, and a student learning end module. The management module includes a hardware management function module and a system management module. The teacher teaching end module and the student learning end module share a common teaching module. The teacher teaching end module includes a separate teacher-specific function module. The devices managed by the hardware management function module include input devices, output devices, and hardware devices. The functions managed by the system management module include an intelligent auxiliary module, a data management module, and an information announcement module. The artificial intelligence-based teaching interaction device realizes speech recognition technology, image recognition technology, natural speech processing technology, and machine learning technology through hardware devices. The teaching interaction device achieves the function of intelligent teaching interaction through the cooperation of multiple functional hardware and system software. It uses artificial intelligence technology and deeply integrates multiple cutting-edge technologies such as computer vision, speech recognition, natural language processing, and machine learning. While improving students' learning efficiency and teachers' teaching quality, it can also effectively reduce the burden of teaching and learning. The entire system uses machine learning algorithms to deeply analyze students' learning data and accurately understand students' knowledge mastery, learning styles, and interest preferences. On this basis, the system can intelligently push learning content that meets students' needs and realize personalized customization of learning paths. For example, when students are learning mathematical knowledge, if they frequently make mistakes in geometric figure-related knowledge points, the system will automatically push more targeted geometry exercises, detailed explanation videos, and extended reading materials to help students strengthen their weak links.

[0028] Embodiment 2:

[0029] like Figure 1-4 As shown in the figure, the hardware controlled by the teaching system is divided into three types: input devices, output devices and hardware devices. Input devices include touch screens, electronic writing boards, keyboards and mice, image input devices and audio input devices. Output devices include projection devices, display screens and audio output devices. Hardware devices include core processors, servers, network communication devices and data storage devices. Input devices and output devices assist teachers and students in realizing a series of teaching functions such as remote teaching, voice interaction, and online testing. Data storage devices, core processors and other equipment realize intelligent teaching interaction through distributed storage, optimize data processing algorithms, improve computing power, and realize efficient processing of massive student data, providing strong guarantees for precise teaching.

[0030] The intelligent assistance system functions of the management module include speech recognition processing function, speech generation function, image recognition processing function and image generation function. The data management system functions of the management module include data statistical induction function, data analysis function, data report visualization function and data storage function. The information announcement module includes announcement information release function and teaching achievement display function. The speech recognition and generation function speech recognition technology helps it achieve barrier-free learning and communication. When students encounter learning difficulties, they can directly ask questions to the smart device. The device uses speech recognition technology to accurately understand the problem and quickly give answers. It can also generate answers through speech. Through intelligent training, the speech generation is consistent with the teacher's voice, making the student learning process more real. The image recognition and generation function can be used when students use learning devices equipped with image recognition functions to scan mathematical geometry figures, physical experiment device diagrams, and chemical molecular structure diagrams in the textbooks. The device can instantly recognize the graphics and link to relevant knowledge point explanations, demonstration videos, and supporting exercises to provide students with all-round and multi-level learning resources.

[0031] The teacher teaching end module and the student learning end module realize login distinction through a login identification system. The login identification system includes an identity identification system module. Both the teacher end module and the student end module perform login identification through the identity identification system module in the login system module. The identity identification system module verifies the identity of teachers and students through account passwords, fingerprint recognition technology, and face recognition technology. Students and teachers are identified through the login identification system, so that the system can distinguish between functional usage, making the entire device more targeted, safe and efficient to use.

[0032] The common teaching module in the teaching system includes homework answering function, forum communication function, teaching resource sharing function, online testing function and remote teaching function. The common teaching module realizes barrier-free learning communication through the intelligent auxiliary system. The homework answering function and online testing function are quickly identified through image recognition technology, and the correct answers and test reports are given through machine learning technology and big data search technology. The teacher-specific module in the teaching system includes course writing function, online teaching function, data sorting function, personalized customization function and discussion and answering function. Personalized customization is based on big data inductive statistics and data analysis functions to analyze students' learning behavior and knowledge. The system can conduct a comprehensive and in-depth analysis of the mastery of the situation, and the system can record in detail the multi-dimensional data such as the student's learning time, answer accuracy, wrong question type, knowledge point dwell time, etc., and build a personalized learning model for students through intelligent algorithms. The course writing function is based on the data analysis function and the data report visualization generation function, which can conduct targeted course teaching based on the learning records, classroom performance, homework completion status and other data of massive students, quickly and accurately analyze these complex and diverse data, extract valuable information from them, and provide support for teaching decisions. By collecting students' learning data, such as learning progress, learning style, knowledge mastery, etc., students' personalized needs can be understood. Data mining and machine learning algorithms in artificial intelligence technology can be used to analyze students' learning behaviors, thereby providing a basis for personalized customization, and personalized teaching content can be constructed according to the results of student demand analysis. A teaching content customization method based on machine learning can be adopted, such as constructing an inverse optimization model, minimizing the adjustment of configuration parameters and customizing resource constraints, generating a more reasonable and effective teaching content configuration plan, considering content diversity, student needs and resource constraints, and ensuring that the teaching content not only meets the personalized needs of students, but also can achieve efficient teaching under limited resources.

[0033] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An interactive teaching device based on artificial intelligence, comprising a teaching system, characterized in that: The teaching interactive device based on artificial intelligence is controlled by a general teaching system, which includes three functional modules: a management module, a teacher teaching end module and a student learning end module. The management module includes a hardware management function module and a system management module. The teacher teaching end module and the student learning end module share a common teaching module. The teacher teaching end module includes a separate teacher-specific function module. The devices managed by the hardware management function module include input devices, output devices and hardware devices. The functions managed by the system management module include an intelligent auxiliary module, a data management module and an information announcement module. The teaching interactive device based on artificial intelligence realizes voice recognition technology, image recognition technology, natural speech processing technology and machine learning technology through hardware devices.

2. The teaching interactive device based on artificial intelligence according to claim 1, characterized in that: The hardware controlled by the teaching system is divided into three types: input devices, output devices and hardware devices. The input devices include touch screens, electronic writing boards, keyboards and mice, image input devices and audio input devices. The output devices include projection devices, display screens and audio output devices. The hardware devices include core processors, servers, network communication devices and data storage devices.

3. The teaching interactive device based on artificial intelligence according to claim 1, characterized in that: The intelligent assistance system functions of the management module include speech recognition processing function, speech generation function, image recognition processing function and image generation function; the data management system functions of the management module include data statistics and summarization function, data analysis function, data report visualization function and data storage function; the information announcement module includes announcement information release function and teaching achievement display function.

4. The teaching interactive device based on artificial intelligence according to claim 1, characterized in that: The teacher teaching end module and the student learning end module realize login distinction through a login identification system. The login identification system includes an identity recognition system module. The teacher end module and the student end module both perform login identification through the identity recognition system module in the login system module. The identity recognition system module verifies the identity of the teacher and the student through account password, fingerprint recognition technology and face recognition technology.

5. The teaching interactive device based on artificial intelligence according to claim 1, characterized in that: The common teaching module in the overall teaching system includes homework answering function, forum communication function, teaching resource sharing function, online testing function and remote teaching function. The common teaching module realizes barrier-free learning and communication through an intelligent auxiliary system. The homework answering function and the online testing function are both quickly identified through image recognition technology, and the correct answers and test reports are given through machine learning technology and big data search technology.

6. The teaching interactive device based on artificial intelligence according to claim 1, characterized in that: The teacher-specific module in the overall teaching system includes course writing function, online teaching function, data sorting function, personalized customization function and discussion and answering function. The personalized customization is based on big data summary statistics and data analysis functions to conduct a comprehensive and in-depth analysis of students' learning behavior and knowledge mastery status. The system records in detail multi-dimensional data such as students' learning time, answer accuracy, wrong question types, and knowledge point dwell time, and builds students' personalized learning models through intelligent algorithms. The course writing function is based on data analysis function and data report visualization generation function, which can conduct targeted course teaching based on massive students' learning records, classroom performance, homework completion status and other data, quickly and accurately analyze these complex and diverse data, extract valuable information from them, and provide support for teaching decisions.

Images