Intelligent teaching system for theory and practice integration and application method thereof

Abstract

According to the theory-practice-harmonizing intelligent teaching system and the application method thereof, through AI intelligent explanation, the workload of teachers is relieved, meanwhile, teaching interactivity is improved, students can better understand and master theoretical knowledge, practical teaching strategies are determined on the basis of student identity information, and the teaching efficiency is improved. The training process under the training teaching strategy is obtained and recorded, training teaching information is obtained, training operation of students is accurately recorded, the learning state is comprehensively tracked, data support is provided for education decision making, student personalization analysis is conducted on theoretical teaching information and training teaching information on the basis of the AI technology, student personalization data is obtained, and the teaching efficiency is improved. Theoretical teaching and practical training teaching are combined to form an all-around teaching system, double requirements of students on knowledge and practical skills are met, and based on personalized student portraits, a personalized learning scheme and a dynamic evaluation system are realized to help the students to define their own growth paths.

Description

Technical Field

[0001] The present invention relates to the field of intelligent teaching technology, and in particular to a theory-practice integrated intelligent teaching system and an application method thereof. Background Art

[0002] In the existing teaching system, such as the theoretical and practical teaching scenarios of vocational colleges and other educational institutions, theoretical teaching and practical training are often independent of each other and lack an effective integration mechanism. This makes it difficult for students to closely combine theoretical knowledge with practical operations during the learning process, affecting the teaching effect. At the same time, traditional teaching methods rely too much on teachers' personal experience and subjective judgment, lack accurate data collection and monitoring mechanisms, and cannot comprehensively and objectively evaluate students' learning status and learning outcomes. In addition, the existing teaching platforms also have many shortcomings in interactivity, personalized learning support, and distance learning, and it is difficult to meet the changes in educational needs in the new era.

[0003] The intelligent teaching system that integrates theory and practice deeply integrates artificial intelligence and educational concepts. Based on the large language model AI technology, it innovatively constructs a comprehensive teaching platform that integrates practical training teaching and theoretical teaching, and meets the above needs based on the intelligent teaching system that integrates theory and practice. Summary of the invention

[0004] The present invention provides a theory-practice integration intelligent teaching system and its application method, which is mainly applicable to the theory and practical training teaching scenarios of vocational colleges and other educational institutions, and aims to build a comprehensive teaching platform integrating theoretical teaching, practical training teaching, diversified evaluation and personalized learning through the deep integration of artificial intelligence and educational concepts. The system is not only suitable for traditional classroom teaching, but also supports remote interactive teaching, can break geographical restrictions, optimize the allocation of educational resources, and is widely used in vocational education, online education, skills training and other fields.

[0005] A theory-practice integrated intelligent teaching system, comprising: A1 intelligent teaching module is used to assist theoretical teaching based on AI digital tutors, and record teachers' teaching and theoretical teaching to obtain theoretical teaching information; A practical training teaching module is used to determine a practical training teaching strategy based on student identity information, and obtain the practical training process under the practical training teaching strategy for recording to obtain practical training teaching information; The information analysis module is used to conduct personalized analysis of theoretical teaching information and practical training teaching information based on AI technology to obtain personalized student data; The portrait generation module is used to generate personalized student portraits for students based on student personalized data and student management data.

[0006] Preferably, the AI ​​intelligent teaching module includes: The model learning unit is used to input theoretical teaching content into the large language model for learning, generate the digital tutor brain, and generate an intelligent question-answering system based on AI intelligent question-answering technology and the digital tutor brain; The tutor generation unit is used to generate a teaching demonstration strategy based on the teaching demonstration template and the digital tutor brain, and obtain an AI digital tutor based on the digital tutor brain, the intelligent question-and-answer system and the teaching demonstration strategy; Theoretical teaching unit, which is used to assist theoretical teaching based on AI digital tutor and combined with teacher operation; The recording and broadcasting unit is used to record the teacher's teaching and theoretical teaching based on the recording and broadcasting technology to obtain theoretical teaching information.

[0007] Preferably, the practical training module includes: A type determination unit, used to obtain practical training teaching content, divide the teaching content into multiple content groups based on the teaching type, and determine the practical training operation type of each content group; An operation determination unit, for generating a practical training teaching operation for each content group based on the practical training operation type of each content group; A strategy determination unit, used for generating a practical training teaching strategy based on the practical training teaching operation and the student identity information; The recording unit is used to record the practical training process under the practical training teaching strategy based on the non-perceptual data collection technology to obtain the practical training teaching information.

[0008] Preferably, the strategy determination unit includes: A correlation determination unit, used to determine the time correlation and operation continuity correlation between the practical training and teaching operations of adjacent content groups, and determine the comprehensive correlation between the content groups based on the time correlation and operation continuity correlation; A level determination unit, used to determine the historical practical training record of each student based on the student identity information, and to classify the practical training ability levels of all students based on the historical practical training records to determine the practical training ability levels of the students; A matching unit, for determining the practical training operation difficulty of each content group based on the operation difficulty of the practical training teaching operation, matching the practical training ability level with the practical training operation difficulty, and obtaining matching allocation information between the student and the content group; A strategy acquisition unit, configured to match the practical teaching operations of the content group to corresponding students according to the matching allocation information, to obtain an initial teaching strategy; A strategy analysis unit, used to obtain a set of practical training content groups for each student under the initial teaching strategy, obtain an average interval time between the practical training content groups, and determine the comprehensive correlation of the practical training content groups based on the comprehensive correlation between the content groups; an evaluation unit, configured to determine a first identification value based on the average interval time, determine a second identification value based on the comprehensive association degree, determine a matching degree between the first identification value and the second identification value based on a preset identification value matching table, determine a first strategy evaluation value based on the average interval time, and determine a second strategy evaluation value based on the comprehensive association degree; A strategy adjustment unit is used to perform weighted processing on the matching degree based on the first strategy evaluation value and the second strategy evaluation value to obtain a weighted matching degree. When the weighted matching degree is less than a preset matching degree, the content group set is adjusted to adjust the initial teaching strategy to obtain a final practical training teaching strategy.

[0009] Preferably, the recording unit comprises: A collection unit is used to collect students' facial expressions and behavioral actions based on non-perception data collection technology to obtain collected data; The recognition unit is used to recognize the collected data to obtain recognition data, and obtain practical training teaching information based on the recognition data.

[0010] Preferably, the information analysis module includes: An information matching unit, used for matching the theoretical teaching information and the practical teaching information based on the content relevance to obtain an information matching group; The information analysis unit is used to perform intelligent analysis on the information matching group based on AI technology to obtain personalized student data.

[0011] Preferably, the portrait generation module includes: A data analysis unit is used to obtain the learning process characteristics of students based on the personalized data of students, and establish a learning enthusiasm index and a learning ability index, and to establish a knowledge mastery index, a hands-on ability index and a knowledge-hands-on integration index based on the learning conditions of theoretical learning and practical training learning in the personalized data of students; The data analysis unit is further used to obtain the learning result characteristics of the students based on the student management data, and to establish learning performance indicators and learning attendance indicators; An indicator establishment unit, used to establish an acquisition link between each indicator and corresponding data, and to establish an indicator dynamic set based on the acquisition result of the acquisition link; An indicator analysis unit, used to determine the indicator weight based on the influence of the indicator attribute of each indicator in the indicator dynamic set on the healthy growth of students, and to determine the display distance between indicators based on the correlation between the indicator attributes; A portrait generating unit, configured to determine the indicator display size based on the indicator weight, determine the indicator display position based on the display distance between the indicators, and generate an initial student portrait according to the indicator display size and the indicator display position; The color assignment unit is used to determine the average value of each indicator based on all students, assign a first color to indicators greater than the average value, assign a second color to indicators equal to the average value, and assign a third color to indicators less than the average value. The initial student portrait is color processed according to the above color assignment strategy to obtain a personalized student portrait of the student.

[0012] Preferably, it also includes: a program recommendation module, which is used to recommend personalized teaching programs to students based on their personalized student portraits; The solution recommendation module includes: A curve determination unit, used for dynamically evaluating the personalized student portrait to obtain an evaluation curve for the student; The program determination unit is used to determine the student's learning attitude and learning ability based on the evaluation curve, determine the teaching method based on the student's attitude, determine the teaching time based on the student's ability, and establish a personalized learning program for the student based on the teaching method and teaching time.

[0013] Preferably, the curve determining unit comprises: An updating and obtaining unit, used for regularly updating the personalized student portrait, and determining a floating curve of each indicator according to each updating result; The evaluation unit is used to obtain the floating curve whose floating curve is greater than a preset amplitude as the main evaluation feature and other floating curves as secondary evaluation features to establish an evaluation curve for the student.

[0014] An application method of a theory-practice integrated intelligent teaching system, comprising: S1: AI digital tutor assists theoretical teaching and records teacher teaching and theoretical teaching to obtain theoretical teaching information; S2: Determine a practical training teaching strategy based on the student identity information, and obtain and record the practical training process under the practical training teaching strategy to obtain practical training teaching information; S3: Based on AI technology, conduct personalized analysis of theoretical teaching information and practical training teaching information to obtain personalized student data; S4: Generate personalized student portraits based on student personalized data and student management data.

[0015] Compared with the prior art, the present invention has achieved the following beneficial effects: Through the use of AI digital tutors to assist theoretical teaching, and record teachers' teaching and theoretical teaching to obtain theoretical teaching information, AI intelligent explanation can reduce teachers' workload and improve teaching interactivity, so that students can better understand and master theoretical knowledge. By determining the practical training teaching strategy based on students' identity information, and recording the practical training process under the practical training teaching strategy, practical training teaching information can be obtained, students' practical training operations can be accurately recorded, and learning status can be comprehensively tracked to provide data support for educational decision-making. Based on AI technology, students' personalized analysis of theoretical teaching information and practical training teaching information can be performed to obtain personalized student data. Theoretical teaching is combined with practical training to form a comprehensive teaching system to meet students' dual needs for knowledge and practical skills. Based on students' personalized data and student management data, personalized student portraits are generated to achieve personalized learning plans and dynamic evaluation systems to help students clarify their own growth paths.

[0016] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0017] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a structural diagram of a theory-practice integrated intelligent teaching system in an embodiment of the present invention; Figure 2 is a structural diagram of the information analysis module described in an embodiment of the present invention; Figure 3 The present invention is a flowchart of an application method of a theory-practice integrated intelligent teaching system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0020] Example 1 The embodiment of the present invention provides a theory-practice integrated intelligent teaching system, such as Figure 1 As shown, including: A1 intelligent teaching module is used to assist theoretical teaching based on AI digital tutors, and record teachers' teaching and theoretical teaching to obtain theoretical teaching information; A practical training teaching module is used to determine a practical training teaching strategy based on student identity information, and obtain the practical training process under the practical training teaching strategy for recording to obtain practical training teaching information; The information analysis module is used to conduct personalized analysis of theoretical teaching information and practical training teaching information based on AI technology to obtain personalized student data; The portrait generation module is used to generate personalized student portraits for students based on student personalized data and student management data.

[0021] In this embodiment, the AI ​​digital intelligence tutor is used to assist theoretical teaching, for example, by using the AI ​​digital intelligence tutor to perform animation display, task release, and voice broadcasting.

[0022] In this embodiment, the practical training teaching strategy includes, for example, the design of various aspects of teaching such as group teaching, identity determination, and issuing work orders.

[0023] In this embodiment, the personalized analysis of theoretical teaching information and practical teaching information can be specifically performed by determining the student's interest in and mastery of the teaching content through the student's facial expressions and student status under the corresponding teaching content.

[0024] In this embodiment, student management data includes grades, attendance, teacher evaluations, etc.

[0025] The beneficial effects of the above design scheme are: through the use of AI digital tutors to assist theoretical teaching, and record the teacher's teaching and theoretical teaching to obtain theoretical teaching information, through AI intelligent explanation, the teacher's workload is reduced, and at the same time, the teaching interactivity is improved, so that students can better understand and master theoretical knowledge, by determining the practical training teaching strategy based on the student's identity information, and obtaining the practical training process under the practical training teaching strategy for recording, to obtain practical training teaching information, accurately record the student's practical training operations, comprehensively track the learning status, and provide data support for educational decision-making, based on AI technology, conduct personalized analysis of theoretical teaching information and practical training teaching information, obtain personalized student data, combine theoretical teaching with practical training teaching, and form a comprehensive teaching system to meet students' dual needs in knowledge and practical skills, and generate personalized student portraits based on student personalized data and student management data, to achieve personalized learning plans and dynamic evaluation systems, and help students clarify their own growth paths.

[0026] Embodiment 2: Based on Example 1, the embodiment of the present invention provides a theory-practice integrated intelligent teaching system, wherein the AI ​​intelligent teaching module includes: The model learning unit is used to input theoretical teaching content into the large language model for learning, generate the digital tutor brain, and generate an intelligent question-answering system based on AI intelligent question-answering technology and the digital tutor brain; The tutor generation unit is used to generate a teaching demonstration strategy based on the teaching demonstration template and the digital tutor brain, and obtain an AI digital tutor based on the digital tutor brain, the intelligent question-and-answer system and the teaching demonstration strategy; Theoretical teaching unit, which is used to assist theoretical teaching based on AI digital tutor and combined with teacher operation; The recording and broadcasting unit is used to record the teacher's teaching and theoretical teaching based on the recording and broadcasting technology to obtain theoretical teaching information.

[0027] In this embodiment, the intelligent question-answering system is used to conduct question-answering training based on the content of the Digital Intelligence Tutor Brain to meet the needs of intelligently answering students' questions in class.

[0028] In this embodiment, the teaching presentation template is pre-designed according to teaching requirements, and a template that meets the requirements is selected when used.

[0029] The beneficial effects of the above design scheme are: by inputting theoretical teaching content into the large language model for learning, a digital intelligence tutor brain is generated; based on AI intelligent question and answer technology, combined with the digital intelligence tutor brain, an intelligent question and answer system is generated; based on the teaching display template combined with the digital intelligence tutor brain, a teaching display strategy is generated; based on the digital intelligence tutor brain, the intelligent question and answer system and the teaching display strategy, an AI digital intelligence tutor is obtained; based on the AI ​​digital intelligence tutor, auxiliary theoretical teaching is carried out in combination with teacher operations; based on the recording and broadcasting technology, the teacher's teaching and theoretical teaching are recorded to obtain theoretical teaching information; through AI intelligent explanation, the teacher's workload is reduced, and at the same time, the teaching interactivity is improved, so that students can better understand and master theoretical knowledge; through the large language model AI technology, the platform not only provides efficient theoretical teaching, but also provides real-time feedback and guidance for practical training operations, thereby improving the overall teaching quality.

[0030] Embodiment 3: Based on Example 1, the embodiment of the present invention provides a theory-practice integrated intelligent teaching system, wherein the practical training teaching module includes: A type determination unit, used to obtain practical training teaching content, divide the teaching content into multiple content groups based on the teaching type, and determine the practical training operation type of each content group; An operation determination unit, for generating a practical training teaching operation for each content group based on the practical training operation type of each content group; A strategy determination unit, used for generating a practical training teaching strategy based on the practical training teaching operation and the student identity information; The recording unit is used to record the practical training process under the practical training teaching strategy based on the non-perceptual data collection technology to obtain the practical training teaching information.

[0031] In this embodiment, the training operation type is determined according to the training content, such as the configuration of reagents and the identification of reagents when doing experiments.

[0032] The beneficial effects of the above design scheme are: by determining the practical training teaching strategy based on the student identity information, and obtaining the practical training process under the practical training teaching strategy for recording, the practical training teaching information is obtained, the student's practical training operations are accurately recorded, the learning status is comprehensively tracked, and data support is provided for educational decision-making.

[0033] Embodiment 4: Based on Example 3, the embodiment of the present invention provides a theory-practice integrated intelligent education system, wherein the strategy determination unit includes: A correlation determination unit, used to determine the time correlation and operation continuity correlation between the practical training and teaching operations of adjacent content groups, and determine the comprehensive correlation between the content groups based on the time correlation and operation continuity correlation; A level determination unit, used to determine the historical practical training record of each student based on the student identity information, and to classify the practical training ability levels of all students based on the historical practical training records to determine the practical training ability levels of the students; A matching unit, for determining the practical training operation difficulty of each content group based on the operation difficulty of the practical training teaching operation, matching the practical training ability level with the practical training operation difficulty, and obtaining matching allocation information between the student and the content group; A strategy acquisition unit, configured to match the practical teaching operations of the content group to corresponding students according to the matching allocation information, to obtain an initial teaching strategy; A strategy analysis unit, used to obtain a set of practical training content groups for each student under the initial teaching strategy, obtain an average interval time between the practical training content groups, and determine the comprehensive correlation of the practical training content groups based on the comprehensive correlation between the content groups; an evaluation unit, configured to determine a first identification value based on the average interval time, determine a second identification value based on the comprehensive association degree, determine a matching degree between the first identification value and the second identification value based on a preset identification value matching table, determine a first strategy evaluation value based on the average interval time, and determine a second strategy evaluation value based on the comprehensive association degree; A strategy adjustment unit is used to perform weighted processing on the matching degree based on the first strategy evaluation value and the second strategy evaluation value to obtain a weighted matching degree. When the weighted matching degree is less than a preset matching degree, the content group set is adjusted to adjust the initial teaching strategy to obtain a final practical training teaching strategy.

[0034] In this embodiment, the time association means, for example, that adjacent content groups must not affect each other in terms of the completion of the specified content or time.

[0035] In this embodiment, the operation continuity association is, for example, that adjacent content groups need to be completed continuously or do not need to be completed continuously. When adjacent content groups need to be completed continuously, the operations of the adjacent content groups can be assigned to the same student.

[0036] In this embodiment, the preset identification value matching table is reasonably set according to historical conditions.

[0037] In this embodiment, the matching degree is weighted based on the first strategy evaluation value and the second strategy evaluation value, such that the greater the strategy evaluation value, the greater the weight.

[0038] The beneficial effect of the above design scheme is: by dividing the practical training operations, relying on the temporal relationship and content relationship between the practical training operations after the division, to determine and adjust the practical training teaching strategy, to ensure the rationality of the obtained practical training teaching strategy, to stimulate the enthusiasm of each student, and to help students improve their practical training operation ability.

[0039] Embodiment 5: Based on Example 3, the embodiment of the present invention provides a theory-practice integrated intelligent teaching system, wherein the recording unit includes: A collection unit is used to collect students' facial expressions and behavioral actions based on non-perception data collection technology to obtain collected data; The recognition unit is used to recognize the collected data to obtain recognition data, and obtain practical training teaching information based on the recognition data.

[0040] In this embodiment, the identification data is the identification of important values ​​of the collected data.

[0041] The beneficial effects of the above design scheme are: by collecting students' facial expressions and behavioral actions based on non-perceptual data collection technology to obtain collected data, the collected data is identified to obtain recognition data, and practical training teaching information is obtained based on the recognition data, so as to accurately record students' practical training operations, comprehensively track learning status, and provide data support for educational decision-making.

[0042] Embodiment 6: Based on Example 1, the present invention provides a theory-practice integrated intelligent education system. Figure 2 As shown, the information analysis module includes: An information matching unit, used for matching the theoretical teaching information and the practical teaching information based on the content relevance to obtain an information matching group; The information analysis unit is used to perform intelligent analysis on the information matching group based on AI technology to obtain personalized student data.

[0043] The beneficial effects of the above design scheme are: by matching the theoretical teaching information and the practical teaching information based on content relevance to obtain an information matching group, based on AI technology, the information matching group is intelligently analyzed to obtain student personalized data, combining theoretical teaching with practical teaching to form a comprehensive teaching system to meet students' dual needs for knowledge and practical skills.

[0044] Embodiment 7: Based on Example 1, the embodiment of the present invention provides a theory-practice integrated intelligent education system, wherein the portrait generation module includes: A data analysis unit is used to obtain the learning process characteristics of students based on the personalized data of students, and establish a learning enthusiasm index and a learning ability index, and to establish a knowledge mastery index, a hands-on ability index and a knowledge-hands-on integration index based on the learning conditions of theoretical learning and practical training learning in the personalized data of students; The data analysis unit is further used to obtain the learning result characteristics of the students based on the student management data, and to establish learning performance indicators and learning attendance indicators; An indicator establishment unit, used to establish an acquisition link between each indicator and corresponding data, and to establish an indicator dynamic set based on the acquisition result of the acquisition link; An indicator analysis unit, used to determine the indicator weight based on the influence of the indicator attribute of each indicator in the indicator dynamic set on the healthy growth of students, and to determine the display distance between indicators based on the correlation between the indicator attributes; A portrait generating unit, configured to determine the indicator display size based on the indicator weight, determine the indicator display position based on the display distance between the indicators, and generate an initial student portrait according to the indicator display size and the indicator display position; The color assignment unit is used to determine the average value of each indicator based on all students, assign a first color to indicators greater than the average value, assign a second color to indicators equal to the average value, and assign a third color to indicators less than the average value. The initial student portrait is color processed according to the above color assignment strategy to obtain a personalized student portrait of the student.

[0045] In this embodiment, the acquisition link between each indicator and the corresponding data enables the indicator value to be automatically acquired from the data in real time.

[0046] In this embodiment, the dynamic set of indicators realizes real-time update of indicator values.

[0047] In this embodiment, the greater the correlation between indicator attributes, the smaller the display distance between indicators.

[0048] In this embodiment, the greater the indicator weight, the larger the indicator display size.

[0049] The beneficial effects of the above design scheme are: by obtaining the learning process characteristics of the students based on the personalized data of the students, and establishing the learning enthusiasm index and the learning ability index, based on the learning situation of theoretical learning and practical training learning in the personalized data of the students, establishing the knowledge mastery index, the hands-on ability index and the knowledge-hands-on integration index, realizing the corresponding relationship between data and indicators, realizing the construction of a dynamic set of indicators, providing a real-time indicator basis for the generation of student portraits, by determining the indicator display size based on the indicator weight, determining the indicator display position based on the display distance between the indicators, generating an initial student portrait according to the indicator display size and the indicator display position, determining the average value of each indicator based on all students, assigning a first color to the indicator greater than the average value, assigning a second color to the indicator equal to the average value, and assigning a third color to the indicator less than the average value, color processing the initial student portrait according to the above color assignment strategy, obtaining a personalized student portrait of the student, and making reasonable settings from the three aspects of display size, position and color in the portrait to ensure the intuitive display effect of the obtained personalized student portrait, facilitate quick acquisition of effective information from the personalized student portrait, and provide a basis for realizing personalized learning plans and dynamic evaluation systems to help students clarify their own growth paths.

[0050] Embodiment 8: Based on the first embodiment, the embodiment of the present invention provides a theory-practice integrated intelligent teaching system, further comprising: a program recommendation module for recommending personalized teaching programs to students based on their personalized student portraits; The solution recommendation module includes: A curve determination unit, used for dynamically evaluating the personalized student portrait to obtain an evaluation curve for the student; The program determination unit is used to determine the student's learning attitude and learning ability based on the evaluation curve, determine the teaching method based on the student's attitude, determine the teaching time based on the student's ability, and establish a personalized learning program for the student based on the teaching method and teaching time.

[0051] The beneficial effects of the above design scheme are: by dynamically evaluating the personalized student portrait, an evaluation curve for the student is obtained; based on the evaluation curve, the student's learning attitude and learning ability are determined; the teaching method is determined based on the student's attitude; the teaching time is determined based on the student's ability; a personalized learning plan for the student is established based on the teaching method and teaching time; a personal portrait is generated based on the student's learning data, a personalized learning plan and a dynamic evaluation system are implemented, and students are helped to clarify their own growth path.

[0052] Embodiment 9: Based on Example 8, the embodiment of the present invention provides a theory-practice integration intelligent education system, wherein the curve determination unit includes: An updating and obtaining unit, used for regularly updating the personalized student portrait, and determining a floating curve of each indicator according to each updating result; The evaluation unit is used to obtain the floating curve whose floating curve is greater than a preset amplitude as the main evaluation feature and other floating curves as secondary evaluation features to establish an evaluation curve for the student.

[0053] The beneficial effect of the above design scheme is: by regularly updating the personalized student portrait, determining the floating curve of each indicator according to the result of each update, obtaining the floating curve with a floating curve greater than a preset amplitude as the main evaluation feature, and other floating curves as secondary evaluation features, establishing an evaluation curve for students, achieving long-term and accurate evaluation of students, and providing a basis for program customization.

[0054] Embodiment 10: Based on Example 1, the present invention provides an application method of the theory-practice integration intelligent teaching system, such as Figure 3 As shown, including: S1: AI digital tutor assists theoretical teaching and records teacher teaching and theoretical teaching to obtain theoretical teaching information; S2: Determine a practical training teaching strategy based on the student identity information, and obtain and record the practical training process under the practical training teaching strategy to obtain practical training teaching information; S3: Based on AI technology, conduct personalized analysis of theoretical teaching information and practical training teaching information to obtain personalized student data; S4: Generate personalized student portraits based on student personalized data and student management data.

[0055] In this embodiment, the AI ​​digital intelligence tutor is used to assist theoretical teaching, for example, by using the AI ​​digital intelligence tutor to perform animation display, task release, and voice broadcasting.

[0056] In this embodiment, the practical training teaching strategy includes, for example, the design of various aspects of teaching such as group teaching, identity determination, and issuing work orders.

[0057] In this embodiment, the personalized analysis of theoretical teaching information and practical teaching information can be specifically performed by determining the student's interest in and mastery of the teaching content through the student's facial expressions and student status under the corresponding teaching content.

[0058] In this embodiment, student management data includes grades, attendance, teacher evaluations, etc.

[0059] The beneficial effects of the above design scheme are: through the use of AI digital tutors to assist theoretical teaching, and record the teacher's teaching and theoretical teaching to obtain theoretical teaching information, through AI intelligent explanation, the teacher's workload is reduced, and at the same time, the teaching interactivity is improved, so that students can better understand and master theoretical knowledge, by determining the practical training teaching strategy based on the student's identity information, and obtaining the practical training process under the practical training teaching strategy for recording, to obtain practical training teaching information, accurately record the student's practical training operations, comprehensively track the learning status, and provide data support for educational decision-making, based on AI technology, conduct personalized analysis of theoretical teaching information and practical training teaching information, obtain personalized student data, combine theoretical teaching with practical training teaching, and form a comprehensive teaching system to meet students' dual needs in knowledge and practical skills, and generate personalized student portraits based on student personalized data and student management data, to achieve personalized learning plans and dynamic evaluation systems, and help students clarify their own growth paths.

[0060] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention belong to the scope of this application document and its equivalent technology, the present invention is also intended to include these changes and variations.

Claims

1. A theory-practice integrated intelligent teaching system, characterized in that: include: A1 intelligent teaching module is used to assist theoretical teaching based on AI digital tutors, and record teachers' teaching and theoretical teaching to obtain theoretical teaching information; A practical training teaching module is used to determine a practical training teaching strategy based on the student identity information, and obtain the practical training process under the practical training teaching strategy for recording to obtain practical training teaching information; The information analysis module is used to conduct personalized analysis of theoretical teaching information and practical training teaching information based on AI technology to obtain personalized student data; The portrait generation module is used to generate personalized student portraits for students based on student personalized data and student management data.

2. The intelligent teaching system integrating theory and practice according to claim 1, characterized in that: The AI ​​intelligent teaching module includes: The model learning unit is used to input theoretical teaching content into the large language model for learning, generate the digital tutor brain, and generate an intelligent question-answering system based on AI intelligent question-answering technology and the digital tutor brain; The tutor generation unit is used to generate a teaching demonstration strategy based on the teaching demonstration template and the digital tutor brain, and obtain an AI digital tutor based on the digital tutor brain, the intelligent question-and-answer system and the teaching demonstration strategy; Theoretical teaching unit, which is used to assist theoretical teaching based on AI digital tutor and combined with teacher operation; The recording and broadcasting unit is used to record the teacher's teaching and theoretical teaching based on the recording and broadcasting technology to obtain theoretical teaching information.

3. The intelligent teaching system integrating theory and practice according to claim 1 is characterized in that: The practical training teaching module includes: A type determination unit, used to obtain practical training teaching content, divide the teaching content into multiple content groups based on the teaching type, and determine the practical training operation type of each content group; An operation determination unit, for generating a practical training teaching operation for each content group based on the practical training operation type of each content group; A strategy determination unit, used for generating a practical training teaching strategy based on the practical training teaching operation and the student identity information; The recording unit is used to record the practical training process under the practical training teaching strategy based on the non-perceptual data collection technology to obtain the practical training teaching information.

4. The intelligent teaching system integrating theory and practice according to claim 3 is characterized in that: The strategy determination unit includes: A correlation determination unit, used to determine the time correlation and operation continuity correlation between the practical training and teaching operations of adjacent content groups, and determine the comprehensive correlation between the content groups based on the time correlation and operation continuity correlation; A level determination unit, used to determine the historical practical training record of each student based on the student identity information, and to classify the practical training ability levels of all students based on the historical practical training records to determine the practical training ability levels of the students; A matching unit, for determining the practical training operation difficulty of each content group based on the operation difficulty of the practical training teaching operation, matching the practical training ability level with the practical training operation difficulty, and obtaining matching allocation information between the student and the content group; A strategy acquisition unit, configured to match the practical teaching operations of the content group to corresponding students according to the matching allocation information, to obtain an initial teaching strategy; A strategy analysis unit, used to obtain a set of practical training content groups for each student under the initial teaching strategy, obtain an average interval time between the practical training content groups, and determine the comprehensive correlation of the practical training content groups based on the comprehensive correlation between the content groups; an evaluation unit, configured to determine a first identification value based on the average interval time, determine a second identification value based on the comprehensive association degree, determine a matching degree between the first identification value and the second identification value based on a preset identification value matching table, determine a first strategy evaluation value based on the average interval time, and determine a second strategy evaluation value based on the comprehensive association degree; A strategy adjustment unit is used to perform weighted processing on the matching degree based on the first strategy evaluation value and the second strategy evaluation value to obtain a weighted matching degree. When the weighted matching degree is less than a preset matching degree, the content group set is adjusted to adjust the initial teaching strategy to obtain a final practical training teaching strategy.

5. The intelligent teaching system integrating theory and practice according to claim 3 is characterized in that: The recording unit comprises: A collection unit is used to collect students' facial expressions and behavioral actions based on non-perception data collection technology to obtain collected data; The recognition unit is used to recognize the collected data to obtain recognition data, and obtain practical training teaching information based on the recognition data.

6. The intelligent teaching system integrating theory and practice according to claim 1, characterized in that: The information analysis module comprises: An information matching unit, used for matching the theoretical teaching information and the practical teaching information based on the content relevance to obtain an information matching group; The information analysis unit is used to perform intelligent analysis on the information matching group based on AI technology to obtain personalized student data.

7. The intelligent teaching system integrating theory and practice according to claim 1, characterized in that: The portrait generation module includes: A data analysis unit is used to obtain the learning process characteristics of students based on the personalized data of students, and establish a learning enthusiasm index and a learning ability index, and to establish a knowledge mastery index, a hands-on ability index and a knowledge-hands-on integration index based on the learning conditions of theoretical learning and practical training learning in the personalized data of students; The data analysis unit is further used to obtain the learning result characteristics of the students based on the student management data, and to establish learning performance indicators and learning attendance indicators; An indicator establishment unit, used to establish an acquisition link between each indicator and corresponding data, and to establish an indicator dynamic set based on the acquisition result of the acquisition link; An indicator analysis unit, used to determine the indicator weight based on the influence of the indicator attribute of each indicator in the indicator dynamic set on the healthy growth of students, and to determine the display distance between indicators based on the correlation between the indicator attributes; A portrait generating unit, configured to determine the indicator display size based on the indicator weight, determine the indicator display position based on the display distance between the indicators, and generate an initial student portrait according to the indicator display size and the indicator display position; The color assignment unit is used to determine the average value of each indicator based on all students, assign a first color to indicators greater than the average value, assign a second color to indicators equal to the average value, and assign a third color to indicators less than the average value. The initial student portrait is color processed according to the above color assignment strategy to obtain a personalized student portrait of the student.

8. The intelligent teaching system integrating theory and practice according to claim 1, characterized in that: Also includes: The program recommendation module is used to recommend personalized teaching programs to students based on their personalized student portraits; The solution recommendation module includes: A curve determination unit, used for dynamically evaluating the personalized student portrait to obtain an evaluation curve for the student; The program determination unit is used to determine the student's learning attitude and learning ability based on the evaluation curve, determine the teaching method based on the student's attitude, determine the teaching time based on the student's ability, and establish a personalized learning program for the student based on the teaching method and teaching time.

9. The intelligent teaching system integrating theory and practice according to claim 8, characterized in that: The curve determination unit comprises: An updating and obtaining unit, used for regularly updating the personalized student portrait, and determining a floating curve of each indicator according to each updating result; The evaluation unit is used to obtain the floating curve whose floating curve is greater than a preset amplitude as the main evaluation feature and other floating curves as secondary evaluation features to establish an evaluation curve for the student.

10. The application method of the theory-practice integration intelligent teaching system according to claim 1 is characterized in that: include: S1: AI digital tutor assists theoretical teaching and records teacher teaching and theoretical teaching to obtain theoretical teaching information; S2: Determine a practical training teaching strategy based on the student identity information, and obtain and record the practical training process under the practical training teaching strategy to obtain practical training teaching information; S3: Based on AI technology, conduct personalized analysis of theoretical teaching information and practical training teaching information to obtain personalized student data; S4: Generate personalized student portraits based on student personalized data and student management data.

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