CN113409635A - Interactive teaching method and system based on virtual reality scene - Google Patents

Interactive teaching method and system based on virtual reality scene Download PDF

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CN113409635A
CN113409635A CN202110675557.5A CN202110675557A CN113409635A CN 113409635 A CN113409635 A CN 113409635A CN 202110675557 A CN202110675557 A CN 202110675557A CN 113409635 A CN113409635 A CN 113409635A
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王鑫
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Shanghai Squirrel Classroom Artificial Intelligence Technology Co Ltd
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Shanghai Squirrel Classroom Artificial Intelligence Technology Co Ltd
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    • G09B7/04—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
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Abstract

The invention provides an interactive teaching method and system based on virtual reality scene, which can identify course knowledge related to corresponding course knowledge teaching links as difficult knowledge and non-difficult knowledge by collecting body action states of students in different course knowledge teaching links in the virtual reality teaching scene, thus being capable of determining learning reaction of students to different knowledge contents in the teaching process in real time, so as to select the operation subjects with different difficulty degrees in a subsequent targeted manner to form the operation examination and evaluation paper, and determining weak links of knowledge learning of students according to answer results of the students who finish homework examination and test paper, thereby when the teaching course of the corresponding course knowledge teaching link is adjusted in the subsequent virtual reality scene teaching, therefore, intelligent and targeted teaching content adjustment can be performed according to the learning abilities of different students, and the learning efficiency and the learning quality of the students in the virtual reality scene are greatly improved.

Description

Interactive teaching method and system based on virtual reality scene
Technical Field
The invention relates to the technical field of intelligent teaching, in particular to an interactive teaching method and system based on a virtual reality scene.
Background
At present, virtual reality technique wide application is in intelligent teaching, and the student can obtain immersive experience of going to class through wearing wear-type virtual reality display device. Teaching in class in virtual reality scene usually shows three-dimensional teaching course image to the student directly, and it does not carry out the interaction with the student in the virtual reality scene to in time gather student's action in the teaching process, this leads to can't respond the content of adjusting course teaching in real time and in time remind the student according to the student in the teaching process. Therefore, the existing virtual reality teaching mode cannot realize interactive teaching with students, and cannot carry out intelligent and targeted teaching content adjustment according to the learning abilities of different students, so that the learning efficiency and the learning quality of the students in a virtual reality scene are greatly reduced.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an interactive teaching method and system based on a virtual reality scene, which collects student whole body images corresponding to different course knowledge teaching links of students in the virtual reality scene; analyzing the whole body image of the student so as to determine the corresponding body action state of the student in each course knowledge teaching link; according to the body action state, identifying the course knowledge related to the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge; selecting a plurality of first type operation questions and a plurality of second type operation questions corresponding to difficult knowledge and non-difficult knowledge respectively from a preset operation question database so as to form corresponding operation test and evaluation papers; finally, judging the homework test paper finished by the students so as to determine the answering results of all the homework questions in the homework test paper; according to the answering result, adjusting the teaching time of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching; therefore, the interactive teaching method and the system based on the virtual reality scene can identify the course knowledge related to the corresponding course knowledge teaching link as the difficult knowledge and the non-difficult knowledge by collecting the body action states of the students in different course knowledge teaching links in the virtual reality teaching scene, thereby determining the learning reaction of the students to different knowledge contents in the teaching process in real time, so as to select the operation subjects with different difficulty degrees in a subsequent targeted manner to form the operation examination and evaluation paper, and determining weak links of knowledge learning of students according to answer results of the students who finish homework examination and test paper, thereby when the teaching course of the corresponding course knowledge teaching link is adjusted in the subsequent virtual reality scene teaching, therefore, intelligent and targeted teaching content adjustment can be performed according to the learning abilities of different students, and the learning efficiency and the learning quality of the students in the virtual reality scene are greatly improved.
The invention provides an interactive teaching method based on a virtual reality scene, which is characterized by comprising the following steps:
step S1, collecting student whole body images corresponding to different course knowledge teaching links of students in a virtual reality scene; analyzing the whole body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link;
step S2, according to the body action state, identifying the course knowledge related to the corresponding course knowledge teaching link as problematic knowledge and non-problematic knowledge; selecting a plurality of first type operation questions and a plurality of second type operation questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset operation question database so as to form corresponding operation test paper;
step S3, judging the homework test paper finished by the student, and determining the answer results of all homework questions in the homework test paper; according to the answer result, adjusting the teaching time of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching;
further, in step S1, collecting student whole body images corresponding to different courses of knowledge teaching links of students in a virtual reality scene; analyzing the whole-body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link specifically comprises:
step S101, in each course knowledge teaching link carried out in a virtual reality scene, respectively carrying out binocular shooting on students so as to acquire corresponding binocular student whole body images; carrying out background noise filtering processing on the binocular student images;
step S102, generating a student whole-body image in a three-dimensional form according to the image parallax of the binocular student whole-body image; recognizing the head postures of the students in the three-dimensional student whole-body images;
step S103, determining the corresponding head swing direction and head swing amplitude of the student in each course knowledge teaching link according to the head posture, and taking the corresponding head swing direction and head swing amplitude as the body action state;
further, in the step S2, according to the body motion state, the course knowledge related to the corresponding course knowledge teaching link is identified as problematic knowledge and non-problematic knowledge; selecting a plurality of first type operation questions and a plurality of second type operation questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset operation question database, so that the forming of the corresponding operation evaluation paper specifically comprises the following steps:
step S201, judging whether the corresponding head swing direction of the student in each course knowledge teaching link is a left-right swing direction and the corresponding actual swing amplitude when the head swings left and right;
step S202, when the swing direction of the head of the student swings leftwards and the actual swing amplitude of the leftward swing is larger than a preset swing amplitude threshold value, identifying course knowledge related to a corresponding course knowledge teaching link as difficult knowledge; when the swing direction of the head of the student swings rightwards and the actual swing amplitude of the head swings rightwards is larger than a preset swing amplitude threshold value, identifying the course knowledge related to the corresponding course knowledge teaching link as non-problematic knowledge;
step S203, selecting a plurality of first type operation questions and a plurality of second type operation questions which respectively have the same knowledge point key words with the difficult knowledge and the non-difficult knowledge from a preset operation question database; selecting a specific number of first type of operation questions and second type of operation questions according to a preset operation question configuration proportion to jointly form a corresponding operation test paper;
further, in step S203, according to the preset job topic configuration proportion, selecting a specific number of first type job topics and second type job topics, and jointly forming a corresponding job test paper, specifically, selecting a specific number of first type job topics and second type job topics, and determining the topic setting sequence positions of the first type job topics and the second type job topics in the job test paper specifically includes:
step S2031, determining first task difficulty characteristic values S1 of all the selected first type of task tasks and second task difficulty characteristic values S2 of all the second type of tasks by using the following formulas (1) - (2),
Figure BDA0003120498330000041
Figure BDA0003120498330000042
in the above formulas (1) to (2), αi1The title word space representing the i1 th first-type task accounts for the total title word space of all the first-type tasks, and the value range is (0, 1), alphai2The title word space representing the i2 th second-type task accounts is the ratio of the total title word space of all the second-type tasks, and the value range is (0, 1), beta0nRepresents the average task difficulty value, beta, corresponding to all the first type of task0mRepresenting the average task difficulty values corresponding to all the second type of task, wherein n represents the total number of the first type of task, and m represents the total number of the second type of task;
step S2032, determining a first layout position weight value of each first type of the homework and a second layout position weight value of each second type of the homework by using the following formulas (3) to (4); when the weight value of the first layout position of a certain first type of job topic is larger, the setting position of the certain first type of job topic in the whole layout area of all the first type of job topics is more backward; when the weighted value of the second layout position of a certain second type of operation task is larger, the setting position of the second type of operation task in the overall layout area is more back,
Figure BDA0003120498330000043
Figure BDA0003120498330000044
in the above formulas (3) to (4), Pi1The first layout weight, χ, representing the i1 th first type of job titlei1Topic scores representing the i1 th first-class job topic across all first-class jobsThe total topic score of the topic, and
Figure BDA0003120498330000045
ri1the ratio of the topic score of the i1 th first-class task to the total score of the operation evaluation paper is shown, and the value range is (0, 1), ri1maxRepresenting the ratio of the topic score of the first-class job topic with the highest topic score among all the first-class job topics to the total score of the job evaluation paper, Pi2Second layout position weight, χ, representing i2 th second type of job titlei2Indicates the ratio of the topic score of the i2 th second-type task to the total topic score of all second-type tasks
Figure BDA0003120498330000051
ri2The ratio of the topic score of the i2 th second-class task to the total score of the operation test paper is shown, and the value range is (0, 1), ri2maxShowing the proportion of the topic score of the second type of operation topic with the highest topic score in the total score of the operation evaluation volume in all the second type of operation topics;
when the weight value of the first layout position of a certain first type of job topic is larger, the setting position of the certain first type of job topic in the whole layout area of all the first type of job topics is more backward; when the weight value of a second layout position of a certain second type of operation topic is larger, the setting position of the second layout position of the certain second type of operation topic in the whole layout area is more back;
step S2033, using the following formula (5) to determine the verification values Y corresponding to the layout of all the task positions in the task test and review paper,
Figure BDA0003120498330000052
in the above-mentioned formula (5),
Figure BDA0003120498330000053
an average value of the weight values of the first layout positions representing all the jobs of the first kind,
Figure BDA0003120498330000054
the average value of the weight values of the second layout positions of all the second type of operation tasks is represented, a1 represents the floating change ratio value of the quantity of all difficult knowledge points contained in all the first type of operation tasks, the value range of the floating change ratio value is 0.01-0.05, a2 represents the floating change ratio value of the quantity of all the non-difficult knowledge points contained in all the second type of operation tasks, and the value range of the floating change ratio value is 0.02-0.04;
comparing the verification value Y with a preset verification threshold Y1, and if the verification value is greater than or equal to a preset verification threshold Y1, reserving the obtained operation test and evaluation paper; otherwise, deleting the obtained operation test and evaluation paper;
further, in the step S3, the homework test paper finished by the student is judged, so as to determine the answer results of all the homework questions in the homework test paper; according to the answer result, when the teaching of the corresponding course knowledge teaching link is adjusted in the subsequent virtual reality scene teaching, the method specifically comprises the following steps:
step S301, evaluating the homework test paper finished by the students so as to determine the correct/wrong condition of the answer result of each homework subject in the homework test paper finished by the students;
step S302, if the answer result of a certain task is correct, the teaching time of the corresponding course knowledge teaching link is reduced in the virtual reality scene teaching; if the answer result of a certain task is wrong, increasing the teaching time of a corresponding course knowledge teaching link in the subsequent virtual reality scene teaching;
step S303, regularly sending a reminding message to students in a course knowledge teaching link of subsequent virtual reality scene teaching when teaching is increased; the reminding message comprises voice content for reminding the current teaching progress of the student.
The invention also provides an interactive teaching system based on the virtual reality scene, which is characterized by comprising a student image shooting and analyzing module, a course knowledge identification module, an operation test and review paper generating module and a course teaching adjustment module; wherein,
the student image shooting and analyzing module is used for collecting student whole-body images corresponding to different course knowledge teaching links of students in a virtual reality scene; analyzing the whole body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link;
the course knowledge identification module is used for identifying the course knowledge related to the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body action state;
the operation examination and evaluation generating module is used for selecting a plurality of first type operation questions and a plurality of second type operation questions which respectively correspond to the difficult knowledge and the non-difficult knowledge from a preset operation question database so as to form corresponding operation examination and evaluation;
the course professor adjusting module is used for judging the homework test and evaluation paper finished by the students so as to determine answer results of all homework questions in the homework test and evaluation paper; according to the answer result, adjusting the teaching time of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching;
furthermore, the student image shooting and analyzing module is used for collecting student whole-body images corresponding to different course knowledge teaching links of students in a virtual reality scene; analyzing the whole-body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link specifically comprises:
in each course knowledge teaching link carried out in a virtual reality scene, carrying out binocular shooting on students respectively so as to acquire corresponding binocular student whole body images; carrying out background noise filtering processing on the binocular student images;
generating a three-dimensional student whole-body image according to the image parallax of the binocular student whole-body image; recognizing the head postures of the students in the three-dimensional student whole-body images;
according to the head posture, determining the corresponding head swing direction and head swing amplitude of the student in each course knowledge teaching link as the body action state;
further, the course knowledge identification module is configured to identify, according to the body motion state, course knowledge related to a corresponding course knowledge teaching link as problematic knowledge and non-problematic knowledge, and specifically includes:
judging whether the corresponding head swing direction of the student in each course knowledge teaching link is the left-right swing direction or not and the corresponding actual swing amplitude when the head swings left and right;
when the swing direction of the head of the student swings leftwards and the actual swing amplitude of the leftward swing is larger than a preset swing amplitude threshold value, identifying course knowledge related to a corresponding course knowledge teaching link as difficult knowledge; when the swing direction of the head of the student swings rightwards and the actual swing amplitude of the head swings rightwards is larger than a preset swing amplitude threshold value, identifying the course knowledge related to the corresponding course knowledge teaching link as non-problematic knowledge;
and the number of the first and second groups,
the operation examination and evaluation paper generation module is used for picking a plurality of first type operation questions and a plurality of second type operation questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset operation question database, so that the corresponding operation examination and evaluation paper is formed by the following steps:
selecting a plurality of first type operation questions and a plurality of second type operation questions which respectively have the same knowledge point key words with the difficult knowledge and the non-difficult knowledge from a preset operation question database; selecting a specific number of first type of operation questions and second type of operation questions according to a preset operation question configuration proportion to jointly form a corresponding operation test paper;
further, the course professor adjusting module is used for judging the homework test paper finished by the students so as to determine the answer results of all the homework questions in the homework test paper; according to the answer result, when the teaching of the corresponding course knowledge teaching link is adjusted in the subsequent virtual reality scene teaching, the method specifically comprises the following steps:
judging the homework test paper finished by the student so as to determine the correct/wrong condition of the response result of each homework subject in the homework test paper finished by the student;
if the answer result of a certain task is correct, the teaching time of the corresponding course knowledge teaching link is reduced in the virtual reality scene teaching; if the answer result of a certain task is wrong, increasing the teaching time of a corresponding course knowledge teaching link in the subsequent virtual reality scene teaching;
in a course knowledge teaching link of subsequent virtual reality scene teaching, which is increased in teaching course, a reminding message is sent to students at regular time; the reminding message comprises voice content for reminding the current teaching progress of the student.
Compared with the prior art, the interactive teaching method and system based on the virtual reality scene provided by the invention collect student whole body images corresponding to different course knowledge teaching links of students in the virtual reality scene; analyzing the whole body image of the student so as to determine the corresponding body action state of the student in each course knowledge teaching link; according to the body action state, identifying the course knowledge related to the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge; selecting a plurality of first type operation questions and a plurality of second type operation questions corresponding to difficult knowledge and non-difficult knowledge respectively from a preset operation question database so as to form corresponding operation test and evaluation papers; finally, judging the homework test paper finished by the students so as to determine the answering results of all the homework questions in the homework test paper; according to the answering result, adjusting the teaching time of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching; therefore, the interactive teaching method and the system based on the virtual reality scene can identify the course knowledge related to the corresponding course knowledge teaching link as the difficult knowledge and the non-difficult knowledge by collecting the body action states of the students in different course knowledge teaching links in the virtual reality teaching scene, thereby determining the learning reaction of the students to different knowledge contents in the teaching process in real time, so as to select the operation subjects with different difficulty degrees in a subsequent targeted manner to form the operation examination and evaluation paper, and determining weak links of knowledge learning of students according to answer results of the students who finish homework examination and test paper, thereby when the teaching course of the corresponding course knowledge teaching link is adjusted in the subsequent virtual reality scene teaching, therefore, intelligent and targeted teaching content adjustment can be performed according to the learning abilities of different students, and the learning efficiency and the learning quality of the students in the virtual reality scene are greatly improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
In order to more clearly illustrate the embodiments of the present invention 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 is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of an interactive teaching method based on a virtual reality scene provided by the invention.
Fig. 2 is a schematic structural diagram of the interactive teaching system based on the virtual reality scene provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of an interactive teaching method based on a virtual reality scene according to an embodiment of the present invention. The interactive teaching method based on the virtual reality scene comprises the following steps:
step S1, collecting student whole body images corresponding to different course knowledge teaching links of students in a virtual reality scene; analyzing the whole body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link;
step S2, according to the body action state, identifying the course knowledge related to the corresponding course knowledge teaching link as the difficult knowledge and the non-difficult knowledge; selecting a plurality of first type operation questions and a plurality of second type operation questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset operation question database so as to form corresponding operation test paper;
step S3, judging the homework test paper finished by the student, and determining the answer results of all homework questions in the homework test paper; and adjusting the teaching time of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching according to the answering result.
The beneficial effects of the above technical scheme are: the interactive teaching method based on the virtual reality scene collects the body action states of students in different course knowledge teaching links in the virtual reality teaching scene, identifies the course knowledge related to the corresponding course knowledge teaching links as difficult knowledge and non-difficult knowledge, thus being capable of determining the learning reaction of the students to different knowledge contents in the teaching process in real time, so as to select the operation subjects with different difficulty degrees in a subsequent targeted manner to form the operation examination and evaluation paper, and determining weak links of knowledge learning of students according to answer results of the students who finish homework examination and test paper, thereby when the teaching course of the corresponding course knowledge teaching link is adjusted in the subsequent virtual reality scene teaching, therefore, intelligent and targeted teaching content adjustment can be performed according to the learning abilities of different students, and the learning efficiency and the learning quality of the students in the virtual reality scene are greatly improved.
Preferably, in step S1, acquiring student whole-body images corresponding to different courses of knowledge teaching links of students in the virtual reality scene; analyzing the whole-body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link specifically comprises:
step S101, in each course knowledge teaching link carried out in a virtual reality scene, respectively carrying out binocular shooting on students so as to acquire corresponding binocular student whole body images; carrying out background noise filtering processing on the binocular student images;
step S102, generating a student whole-body image in a three-dimensional form according to the image parallax of the binocular student whole-body image; recognizing the head postures of the students in the three-dimensional student whole-body images;
step S103, according to the head posture, determining the corresponding head swing direction and head swing amplitude of the student in each course knowledge teaching link as the body action state.
The beneficial effects of the above technical scheme are: students learn knowledge in different courses in a virtual reality scene, and generally, the students have questions about the learning knowledge contents or have places where the learning knowledge contents are not understood in the learning process, and at the moment, the students need to perform corresponding feedback to determine which knowledge contents belong to difficult knowledge for the students. In order to facilitate clear and rapid real-time analysis of the student's reaction in the teaching process, the student's head posture can be determined by shooting the student's whole body image and analyzing the whole body image. In actual operation, it can be determined in advance for a student that, in a teaching process, when the student considers that the current knowledge content is difficult knowledge, the head of the student needs to perform a first type of action (for example, the head swings to the left by a preset amplitude), and in a teaching process, when the student considers that the current knowledge content is not difficult knowledge, the head of the student needs to perform a second type of action (for example, the head swings to the right by a preset amplitude), so that the knowledge involved in the teaching process can be distinguished quickly and accurately according to the head action of the student.
Preferably, in the step S2, according to the body motion state, the course knowledge related to the corresponding course knowledge teaching link is identified as problematic knowledge and non-problematic knowledge; selecting a plurality of first type operation questions and a plurality of second type operation questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset operation question database, so that the forming of the corresponding operation evaluation paper specifically comprises the following steps:
step S201, judging whether the corresponding head swing direction of the student in each course knowledge teaching link is a left-right swing direction and the corresponding actual swing amplitude when the head swings left and right;
step S202, when the swing direction of the head of the student swings leftwards and the actual swing amplitude of the leftward swing is larger than a preset swing amplitude threshold value, identifying course knowledge related to a corresponding course knowledge teaching link as difficult knowledge; when the swing direction of the head of the student swings rightwards and the actual swing amplitude of the head swings rightwards is larger than a preset swing amplitude threshold value, identifying the course knowledge related to the corresponding course knowledge teaching link as non-problematic knowledge;
step S203, selecting a plurality of first type operation questions and a plurality of second type operation questions which respectively have the same knowledge point key words with the difficult knowledge and the non-difficult knowledge from a preset operation question database; and selecting a specific number of first type of operation questions and second type of operation questions according to a preset operation question configuration proportion to jointly form a corresponding operation test and evaluation paper.
The beneficial effects of the above technical scheme are: the method comprises the steps of calibrating different difficult and easy knowledge contents related to a teaching process by identifying the head action type of a student in the teaching process, for example, in the course learning about calculus, in the course knowledge teaching link of one-dimensional integral, the head of the student swings rightwards, the actual swing amplitude of the head of the student swings rightwards is larger than a preset swing amplitude threshold value, at the moment, the knowledge corresponding to the one-dimensional integral is marked with non-difficult knowledge, in the course knowledge teaching link of two-dimensional integral, the head of the student swings leftwards, the actual swing amplitude of the head of the student swings leftwards is larger than the preset swing amplitude threshold value, and at the moment, the knowledge corresponding to the two-dimensional integral is marked with difficult knowledge. Through the mode, the difficulty identification of different types of course knowledge can be quickly and accurately carried out without influencing the normal course listening condition of students.
In addition, after the difficult knowledge and the non-difficult knowledge are identified for all the course knowledge, the corresponding work topics can be picked from the preset work topic database in a keyword matching mode. For example, for the one-dimensional integral knowledge content identified as non-problematic knowledge, a job topic associated with the one-dimensional integral can be searched in a preset job topic database through a keyword 'one-dimensional integral', and the searched job topic is used as a second type of job topic; for the two-dimensional integral knowledge content identified as difficult knowledge, a job topic associated with the two-dimensional integral can be searched in a preset job topic database through a keyword 'two-dimensional integral', and the two-dimensional integral is used as a first type of job topic. And then selecting a corresponding number of first-class operation questions and second-class operation questions to jointly form the operation test paper according to the proportion requirement of the number of the questions between the subjective questions such as the selection questions and the objective questions such as the calculation questions in the operation test paper as a preset operation question configuration proportion, so that the coverage comprehensiveness of the operation test paper on different knowledge contents can be improved.
Preferably, in step S203, according to a preset job topic configuration ratio, selecting a specific number of first type job topics and a specific number of second type job topics, and jointly forming a corresponding job test review, specifically, selecting a specific number of first type job topics and a specific number of second type job topics, and determining topic setting sequence positions of the first type job topics and the second type job topics in the job test review specifically includes:
step S2031, determining first task difficulty characteristic values S1 of all the selected first type of task tasks and second task difficulty characteristic values S2 of all the second type of tasks by using the following formulas (1) - (2),
Figure BDA0003120498330000121
Figure BDA0003120498330000122
in the above formulas (1) to (2), αi1Denotes the i1 th first classThe title word space of the job title is in the ratio of the total title word space of all the first type of job titles, and the value range is (0, 1), alphai2The title word space representing the i2 th second-type task accounts is the ratio of the total title word space of all the second-type tasks, and the value range is (0, 1), beta0nRepresents the average task difficulty value, beta, corresponding to all the first type of task0mRepresenting the average task difficulty values corresponding to all the second type of task, wherein n represents the total number of the first type of task, and m represents the total number of the second type of task;
step S2032, determining a first layout position weight value of each first type of the homework and a second layout position weight value of each second type of the homework by using the following formulas (3) to (4); when the weight value of the first layout position of a certain first type of job topic is larger, the setting position of the certain first type of job topic in the whole layout area of all the first type of job topics is more backward; when the weighted value of the second layout position of a certain second type of operation task is larger, the setting position of the second type of operation task in the overall layout area is more back,
Figure BDA0003120498330000131
Figure BDA0003120498330000132
in the above formulas (3) to (4), Pi1The first layout weight, χ, representing the i1 th first type of job titlei1Indicates the ratio of the topic score of the i1 th first-type task to the total topic score of all the first-type tasks, and
Figure BDA0003120498330000133
ri1the ratio of the topic score of the i1 th first-class task to the total score of the operation evaluation paper is shown, and the value range is (0, 1), ri1maxIndicating the highest topic score among all topics of the first type of jobThe ratio of the topic score of the first class of task to the total score of the task evaluation volume, Pi2Second layout position weight, χ, representing i2 th second type of job titlei2Indicates the ratio of the topic score of the i2 th second-type task to the total topic score of all second-type tasks
Figure BDA0003120498330000134
ri2The ratio of the topic score of the i2 th second-class task to the total score of the operation test paper is shown, and the value range is (0, 1), ri2maxShowing the proportion of the topic score of the second type of operation topic with the highest topic score in the total score of the operation evaluation volume in all the second type of operation topics;
in the operation test paper evaluation, a first type of operation questions and a second type of operation questions are respectively arranged in two mutually independent areas in the operation test paper evaluation, the first type of operation questions and the second type of operation questions are not mutually crossed in the operation test paper, and when the weight value of a first layout position of a certain first type of operation questions is larger, the setting positions of the first type of operation questions in the whole layout area of all the first type of operation questions are more back; when the weight value of a second layout position of a certain second type of operation topic is larger, the setting position of the second layout position of the certain second type of operation topic in the whole layout area is more back;
step S2033, using the following formula (5) to determine the verification values Y corresponding to the layout of all the task positions in the task test and review paper,
Figure BDA0003120498330000141
in the above-mentioned formula (5),
Figure BDA0003120498330000142
an average value of the weight values of the first layout positions representing all the jobs of the first kind,
Figure BDA0003120498330000143
show all the second type of questionsThe average value of the weighted values of the second layout positions of the objects, a1 represents the floating change ratio value of the quantity of all difficult knowledge points contained in all the first type of task, the value range is 0.01-0.05, the quantity of the difficult knowledge points contained in all the first type of task can be changed along with the content of the specifically selected first type of task, the quantity of the difficult knowledge points contained in all the first type of task can be correspondingly set to be higher than the preset reference value of the quantity of the difficult knowledge points while the first type of task is selected, a1 represents the upward floating ratio of the quantity of all the difficult knowledge points contained in all the first type of task compared with the preset reference value of the quantity of the difficult knowledge points, a2 represents the floating change ratio value of the quantity of all the non-difficult knowledge points contained in all the second type of task, the value range is 0.02-0.04, and the quantity of the non-difficult knowledge points contained in all the second type of task can be changed along with the specifically selected second difficult knowledge points The contents of the class operation topics are changed, the number of the non-problematic knowledge points contained in all the second class operation topics is correspondingly set to be higher than a preset reference value of the number of the non-problematic knowledge points while the second class operation topics are selected, and a2 represents the proportion that the number of the non-problematic knowledge points contained in all the second class operation topics floats upwards compared with the preset reference value of the number of the non-problematic knowledge points;
comparing the verification value Y with a preset verification threshold Y1, and if the verification value is greater than or equal to a preset verification threshold Y1, reserving the obtained operation test and evaluation paper; otherwise, deleting the obtained job test and evaluation paper, reselecting a corresponding number of first type job titles and second type job titles after deleting the obtained job test paper, and traversing the steps S2031 to S2033 again in sequence until the verification value is greater than or equal to the preset verification threshold Y1.
The beneficial effects of the above technical scheme are: because the first type of operation subject contains problematic knowledge points and the second type of operation subject contains non-problematic knowledge points, the first type of operation subject and the second type of operation subject are independently arranged in the operation test paper. The formulas (1) to (2) can be used for respectively carrying out quantitative evaluation on the overall difficulty level of the first type of operation subject and the second type of operation subject so as to obtain corresponding difficulty characteristic values; and then, respectively determining the respective layout position weighted values of the first type of task and the second type of task by using the formulas (3) to (4), so that the corresponding layout setting position sequence of the first type of task and the second type of task in the operation test paper can be quickly determined according to the ascending arrangement condition of the layout position weighted values, and a corresponding operation test paper is preliminarily formed. And finally, verifying the homework test paper by using the formula (5) so as to determine whether the preliminarily formed homework test paper meets the requirement of difficult and easy layout of corresponding homework subjects, so that the finally determined homework test paper can be matched with the requirement of students on homework to the maximum extent.
Preferably, in the step S3, the homework test paper finished by the student is evaluated, so as to determine the answer results of all the homework questions in the homework test paper; according to the answer result, the teaching and teaching process of adjusting the teaching and teaching link of the corresponding course knowledge in the subsequent virtual reality scene teaching specifically comprises the following steps:
step S301, evaluating the homework test paper finished by the students so as to determine the correct/wrong condition of the answer result of each homework subject in the homework test paper finished by the students;
step S302, if the answer result of a certain task is correct, the teaching time of the corresponding course knowledge teaching link is reduced in the virtual reality scene teaching; if the answer result of a certain task is wrong, increasing the teaching time of a corresponding course knowledge teaching link in the subsequent virtual reality scene teaching;
step S303, regularly sending a reminding message to students in a course knowledge teaching link of subsequent virtual reality scene teaching when teaching is increased; wherein, the reminding message comprises voice content for prompting the current teaching progress of the student.
The beneficial effects of the above technical scheme are: by judging the correctness/wrong condition of the respective response result of each homework subject obtained by homework examination and evaluation completed by the student, the mastering firmness of the student aiming at different knowledge contents in the teaching process can be accurately determined. For example, if the answer result accuracy of the student on the homework questions related to the one-dimensional integral is higher, it indicates that the student has higher mastery firmness degree on the knowledge content of the one-dimensional integral, and if the answer result error rate of the student on the homework questions related to the two-dimensional integral is higher, it indicates that the student has lower mastery firmness degree on the knowledge content of the two-dimensional integral; at the moment, the teaching course of the two-dimensional integral knowledge content can be increased and the teaching course of the one-dimensional integral knowledge content can be reduced in the follow-up virtual reality scene teaching; meanwhile, a voice message of the current teaching progress of the two-dimensional integral knowledge content can be sent to the students in the process of teaching the two-dimensional integral knowledge content, wherein the teaching progress of the two-dimensional integral knowledge content can be but is not limited to the number of teaching sections which have been taught by the two-dimensional integral knowledge content and the number of teaching sections which are not taught by the two-dimensional integral knowledge content.
Fig. 2 is a schematic structural diagram of an interactive teaching system based on a virtual reality scene according to an embodiment of the present invention. The interactive teaching system based on the virtual reality scene comprises a student image shooting and analyzing module, a course knowledge identification module, an operation test and review paper generating module and a course teaching adjustment module; wherein,
the student image shooting and analyzing module is used for collecting student whole-body images corresponding to different course knowledge teaching links of students in a virtual reality scene; analyzing the whole body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link;
the course knowledge identification module is used for identifying the course knowledge related to the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body action state;
the operation examination and evaluation generation module is used for selecting a plurality of first type operation questions and a plurality of second type operation questions which respectively correspond to the difficult knowledge and the non-difficult knowledge from a preset operation question database so as to form corresponding operation examination and evaluation;
the course teaching adjustment module is used for judging the homework test and evaluation paper finished by the students so as to determine the answering results of all homework questions in the homework test and evaluation paper; and adjusting the teaching time of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching according to the answering result.
The beneficial effects of the above technical scheme are: the interactive teaching system based on the virtual reality scene collects the body action states of students in different course knowledge teaching links in the virtual reality teaching scene, identifies the course knowledge related to the corresponding course knowledge teaching links as difficult knowledge and non-difficult knowledge, thus being capable of determining the learning reaction of the students to different knowledge contents in the teaching process in real time, so as to select the operation subjects with different difficulty degrees in a subsequent targeted manner to form the operation examination and evaluation paper, and determining weak links of knowledge learning of students according to answer results of the students who finish homework examination and test paper, thereby when the teaching course of the corresponding course knowledge teaching link is adjusted in the subsequent virtual reality scene teaching, therefore, intelligent and targeted teaching content adjustment can be performed according to the learning abilities of different students, and the learning efficiency and the learning quality of the students in the virtual reality scene are greatly improved.
Preferably, the student image shooting and analyzing module is used for collecting student whole-body images corresponding to different course knowledge teaching links of students in a virtual reality scene; analyzing the whole-body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link specifically comprises:
in each course knowledge teaching link carried out in a virtual reality scene, carrying out binocular shooting on students respectively so as to acquire corresponding binocular student whole body images; carrying out background noise filtering processing on the binocular student images;
generating a three-dimensional student whole-body image according to the image parallax of the binocular student whole-body image; recognizing the head postures of the students in the three-dimensional student whole-body images;
and determining the corresponding head swing direction and head swing amplitude of the student in each course knowledge teaching link according to the head posture, and taking the corresponding head swing direction and head swing amplitude as the body action state.
The beneficial effects of the above technical scheme are: students learn knowledge in different courses in a virtual reality scene, and generally, the students have questions about the learning knowledge contents or have places where the learning knowledge contents are not understood in the learning process, and at the moment, the students need to perform corresponding feedback to determine which knowledge contents belong to difficult knowledge for the students. In order to facilitate clear and rapid real-time analysis of the student's reaction in the teaching process, the student's head posture can be determined by shooting the student's whole body image and analyzing the whole body image. In actual operation, it can be determined in advance for a student that, in a teaching process, when the student considers that the current knowledge content is difficult knowledge, the head of the student needs to perform a first type of action (for example, the head swings to the left by a preset amplitude), and in a teaching process, when the student considers that the current knowledge content is not difficult knowledge, the head of the student needs to perform a second type of action (for example, the head swings to the right by a preset amplitude), so that the knowledge involved in the teaching process can be distinguished quickly and accurately according to the head action of the student.
Preferably, the course knowledge identification module is configured to identify, according to the body motion state, course knowledge related to a corresponding course knowledge teaching link as problematic knowledge and non-problematic knowledge, and specifically includes:
judging whether the corresponding head swing direction of the student in each course knowledge teaching link is the left-right swing direction or not and the corresponding actual swing amplitude when the head swings left and right;
when the swing direction of the head of the student swings leftwards and the actual swing amplitude of the leftward swing is larger than a preset swing amplitude threshold value, identifying course knowledge related to a corresponding course knowledge teaching link as difficult knowledge; when the swing direction of the head of the student swings rightwards and the actual swing amplitude of the head swings rightwards is larger than a preset swing amplitude threshold value, identifying the course knowledge related to the corresponding course knowledge teaching link as non-problematic knowledge;
and the number of the first and second groups,
the operation examination and evaluation paper generation module is used for selecting a plurality of first type operation questions and a plurality of second type operation questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset operation question database, so that the corresponding operation examination and evaluation paper is formed and specifically comprises the following steps:
selecting a plurality of first type operation questions and a plurality of second type operation questions which respectively have the same knowledge point key words with the difficult knowledge and the non-difficult knowledge from a preset operation question database; and selecting a specific number of first type of operation questions and second type of operation questions according to a preset operation question configuration proportion to jointly form a corresponding operation test and evaluation paper.
In addition, after the difficult knowledge and the non-difficult knowledge are identified for all the course knowledge, the corresponding work topics can be picked from the preset work topic database in a keyword matching mode. For example, for the one-dimensional integral knowledge content identified as non-problematic knowledge, a job topic associated with the one-dimensional integral can be searched in a preset job topic database through a keyword 'one-dimensional integral', and the searched job topic is used as a second type of job topic; for the two-dimensional integral knowledge content identified as difficult knowledge, a job topic associated with the two-dimensional integral can be searched in a preset job topic database through a keyword 'two-dimensional integral', and the two-dimensional integral is used as a first type of job topic. And then selecting a corresponding number of first-class operation questions and second-class operation questions to jointly form the operation test paper according to the proportion requirement of the number of the questions between the subjective questions such as the selection questions and the objective questions such as the calculation questions in the operation test paper as a preset operation question configuration proportion, so that the coverage comprehensiveness of the operation test paper on different knowledge contents can be improved.
Preferably, the course professor adjusting module is used for judging the homework test paper finished by the students so as to determine the answering results of all the homework questions in the homework test paper; according to the answer result, the teaching and teaching process of adjusting the teaching and teaching link of the corresponding course knowledge in the subsequent virtual reality scene teaching specifically comprises the following steps:
judging the homework test paper finished by the student so as to determine the correct/wrong condition of the response result of each homework subject in the homework test paper finished by the student;
if the answer result of a certain task is correct, the teaching time of the corresponding course knowledge teaching link is reduced in the virtual reality scene teaching; if the answer result of a certain task is wrong, increasing the teaching time of a corresponding course knowledge teaching link in the subsequent virtual reality scene teaching;
in a course knowledge teaching link of subsequent virtual reality scene teaching, which is increased in teaching course, a reminding message is sent to students at regular time; wherein, the reminding message comprises voice content for prompting the current teaching progress of the student.
The beneficial effects of the above technical scheme are: by judging the correctness/wrong condition of the respective response result of each homework subject obtained by homework examination and evaluation completed by the student, the mastering firmness of the student aiming at different knowledge contents in the teaching process can be accurately determined. For example, if the answer result accuracy of the student on the homework questions related to the one-dimensional integral is higher, it indicates that the student has higher mastery firmness degree on the knowledge content of the one-dimensional integral, and if the answer result error rate of the student on the homework questions related to the two-dimensional integral is higher, it indicates that the student has lower mastery firmness degree on the knowledge content of the two-dimensional integral; at the moment, the teaching course of the two-dimensional integral knowledge content can be increased and the teaching course of the one-dimensional integral knowledge content can be reduced in the follow-up virtual reality scene teaching; meanwhile, a voice message of the current teaching progress of the two-dimensional integral knowledge content can be sent to the students in the process of teaching the two-dimensional integral knowledge content, wherein the teaching progress of the two-dimensional integral knowledge content can be but is not limited to the number of teaching sections which have been taught by the two-dimensional integral knowledge content and the number of teaching sections which are not taught by the two-dimensional integral knowledge content.
From the content of the above embodiment, the interactive teaching method and system based on the virtual reality scene can identify the course knowledge related to the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge by collecting the body action states of the students in different course knowledge teaching links in the virtual reality teaching scene, so as to determine the learning reaction of the students to different knowledge contents in the teaching process in real time, so as to conveniently and specifically select the homework subjects with different difficulty degrees to form the homework examination and review paper in the follow-up process, and determine the weak link of the student knowledge learning according to the answer result of the student completing the homework examination and review paper, thereby not only performing intelligent and targeted teaching content adjustment according to the learning abilities of different students in the follow-up virtual reality scene teaching, and the learning efficiency and the learning quality of students in the virtual reality scene are also greatly improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (9)

1. The interactive teaching method based on the virtual reality scene is characterized by comprising the following steps:
step S1, collecting student whole body images corresponding to different course knowledge teaching links of students in a virtual reality scene; analyzing the whole body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link;
step S2, according to the body action state, identifying the course knowledge related to the corresponding course knowledge teaching link as problematic knowledge and non-problematic knowledge; selecting a plurality of first type operation questions and a plurality of second type operation questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset operation question database so as to form corresponding operation test paper;
step S3, judging the homework test paper finished by the student, and determining the answer results of all homework questions in the homework test paper; and adjusting the teaching time of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching according to the answering result.
2. The interactive teaching method based on virtual reality scene as claimed in claim 1, characterized in that: in step S1, collecting student whole body images corresponding to different courses of knowledge teaching links of a student in a virtual reality scene; analyzing the whole-body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link specifically comprises:
step S101, in each course knowledge teaching link carried out in a virtual reality scene, respectively carrying out binocular shooting on students so as to acquire corresponding binocular student whole body images; carrying out background noise filtering processing on the binocular student images;
step S102, generating a student whole-body image in a three-dimensional form according to the image parallax of the binocular student whole-body image; recognizing the head postures of the students in the three-dimensional student whole-body images;
and step S103, determining the corresponding head swing direction and head swing amplitude of the student in each course knowledge teaching link according to the head posture, and taking the corresponding head swing direction and head swing amplitude as the body action state.
3. The interactive teaching method based on virtual reality scene as claimed in claim 2, characterized in that: in step S2, according to the body motion state, identifying the course knowledge related to the corresponding course knowledge teaching link as problematic knowledge and non-problematic knowledge; selecting a plurality of first type operation questions and a plurality of second type operation questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset operation question database, so that the forming of the corresponding operation evaluation paper specifically comprises the following steps:
step S201, judging whether the corresponding head swing direction of the student in each course knowledge teaching link is a left-right swing direction and the corresponding actual swing amplitude when the head swings left and right;
step S202, when the swing direction of the head of the student swings leftwards and the actual swing amplitude of the leftward swing is larger than a preset swing amplitude threshold value, identifying course knowledge related to a corresponding course knowledge teaching link as difficult knowledge; when the swing direction of the head of the student swings rightwards and the actual swing amplitude of the head swings rightwards is larger than a preset swing amplitude threshold value, identifying the course knowledge related to the corresponding course knowledge teaching link as non-problematic knowledge;
step S203, selecting a plurality of first type operation questions and a plurality of second type operation questions which respectively have the same knowledge point key words with the difficult knowledge and the non-difficult knowledge from a preset operation question database; and selecting a specific number of first type of operation questions and second type of operation questions according to a preset operation question configuration proportion to jointly form a corresponding operation test and evaluation paper.
4. The interactive teaching method based on virtual reality scene as claimed in claim 3, characterized in that: in step S203, selecting a specific number of first type of job questions and a specific number of second type of job questions according to a preset job question configuration ratio, and combining them together to form a corresponding job test paper, specifically, selecting a specific number of first type of job questions and a specific number of second type of job questions, and determining the question setting sequence positions of the first type of job questions and the second type of job questions in the job test paper specifically includes:
step S2031, determining first task difficulty characteristic values S1 of all the selected first type of task tasks and second task difficulty characteristic values S2 of all the second type of tasks by using the following formulas (1) - (2),
Figure FDA0003120498320000021
Figure FDA0003120498320000031
in the above formulas (1) to (2), αi1The title word space representing the i1 th first-type task accounts for the total title word space of all the first-type tasks, and the value range is (0, 1), alphai2The title word space representing the i2 th second-type task accounts is the ratio of the total title word space of all the second-type tasks, and the value range is (0, 1), beta0nRepresents the average task difficulty value, beta, corresponding to all the first type of task0mRepresenting the average task difficulty value corresponding to all the second type of task, n representing the total number of the first type of taskM represents the total number of the second type of job titles;
step S2032, determining a first layout position weight value of each first type of the homework and a second layout position weight value of each second type of the homework by using the following formulas (3) to (4); when the weight value of the first layout position of a certain first type of job topic is larger, the setting position of the certain first type of job topic in the whole layout area of all the first type of job topics is more backward; when the weighted value of the second layout position of a certain second type of operation task is larger, the setting position of the second type of operation task in the overall layout area is more back,
Figure FDA0003120498320000032
Figure FDA0003120498320000033
in the above formulas (3) to (4), Pi1The first layout weight, χ, representing the i1 th first type of job titlei1Indicates the ratio of the topic score of the i1 th first-type task to the total topic score of all the first-type tasks, and
Figure FDA0003120498320000034
ri1the ratio of the topic score of the i1 th first-class task to the total score of the operation evaluation paper is shown, and the value range is (0, 1), ri1maxRepresenting the ratio of the topic score of the first-class job topic with the highest topic score among all the first-class job topics to the total score of the job evaluation paper, Pi2Second layout position weight, χ, representing i2 th second type of job titlei2Indicates the ratio of the topic score of the i2 th second-type task to the total topic score of all second-type tasks
Figure FDA0003120498320000041
ri2Indicates the i2 thThe title value of the second kind of job title is in proportion to the total score of the job evaluation volume, and the value range is (0, 1), ri2maxShowing the proportion of the topic score of the second type of operation topic with the highest topic score in the total score of the operation evaluation volume in all the second type of operation topics;
when the weight value of the first layout position of a certain first type of job topic is larger, the setting position of the certain first type of job topic in the whole layout area of all the first type of job topics is more backward; when the weight value of a second layout position of a certain second type of operation topic is larger, the setting position of the second layout position of the certain second type of operation topic in the whole layout area is more back;
step S2033, using the following formula (5) to determine the verification values Y corresponding to the layout of all the task positions in the task test and review paper,
Figure FDA0003120498320000042
in the above-mentioned formula (5),
Figure FDA0003120498320000043
an average value of the weight values of the first layout positions representing all the jobs of the first kind,
Figure FDA0003120498320000044
the average value of the weight values of the second layout positions of all the second type of operation tasks is represented, a1 represents the floating change ratio value of the quantity of all difficult knowledge points contained in all the first type of operation tasks, the value range of the floating change ratio value is 0.01-0.05, a2 represents the floating change ratio value of the quantity of all the non-difficult knowledge points contained in all the second type of operation tasks, and the value range of the floating change ratio value is 0.02-0.04;
comparing the verification value Y with a preset verification threshold Y1, and if the verification value is greater than or equal to a preset verification threshold Y1, reserving the obtained operation test and evaluation paper; otherwise, deleting the obtained operation test paper.
5. The interactive teaching method based on virtual reality scene as claimed in claim 3, characterized in that: in step S3, the students' completed homework test paper is evaluated, so as to determine the answer results of all the homework questions in the homework test paper; according to the answer result, when the teaching of the corresponding course knowledge teaching link is adjusted in the subsequent virtual reality scene teaching, the method specifically comprises the following steps:
step S301, evaluating the homework test paper finished by the students so as to determine the correct/wrong condition of the answer result of each homework subject in the homework test paper finished by the students;
step S302, if the answer result of a certain task is correct, the teaching time of the corresponding course knowledge teaching link is reduced in the virtual reality scene teaching; if the answer result of a certain task is wrong, increasing the teaching time of a corresponding course knowledge teaching link in the subsequent virtual reality scene teaching;
step S303, regularly sending a reminding message to students in a course knowledge teaching link of subsequent virtual reality scene teaching when teaching is increased; the reminding message comprises voice content for reminding the current teaching progress of the student.
6. The interactive teaching system based on the virtual reality scene is characterized by comprising a student image shooting and analyzing module, a course knowledge identification module, an operation test and review paper generating module and a course teaching adjustment module; wherein,
the student image shooting and analyzing module is used for collecting student whole-body images corresponding to different course knowledge teaching links of students in a virtual reality scene; analyzing the whole body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link;
the course knowledge identification module is used for identifying the course knowledge related to the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body action state;
the operation examination and evaluation generating module is used for selecting a plurality of first type operation questions and a plurality of second type operation questions which respectively correspond to the difficult knowledge and the non-difficult knowledge from a preset operation question database so as to form corresponding operation examination and evaluation;
the course professor adjusting module is used for judging the homework test and evaluation paper finished by the students so as to determine answer results of all homework questions in the homework test and evaluation paper; and adjusting the teaching time of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching according to the answering result.
7. The interactive teaching system based on virtual reality scene of claim 6, wherein: the student image shooting and analyzing module is used for collecting student whole-body images corresponding to different course knowledge teaching links of students in a virtual reality scene; analyzing the whole-body image of the student to determine the corresponding body action state of the student in each course knowledge teaching link specifically comprises:
in each course knowledge teaching link carried out in a virtual reality scene, carrying out binocular shooting on students respectively so as to acquire corresponding binocular student whole body images; carrying out background noise filtering processing on the binocular student images;
generating a three-dimensional student whole-body image according to the image parallax of the binocular student whole-body image;
recognizing the head postures of the students in the three-dimensional student whole-body images;
and determining the corresponding head swing direction and head swing amplitude of the student in each course knowledge teaching link according to the head posture, and taking the corresponding head swing direction and head swing amplitude as the body action state.
8. The interactive teaching system based on virtual reality scene of claim 7, wherein: the course knowledge identification module is used for identifying the course knowledge related to the corresponding course knowledge teaching link as problematic knowledge and non-problematic knowledge according to the body action state, and specifically comprises the following steps:
judging whether the corresponding head swing direction of the student in each course knowledge teaching link is the left-right swing direction or not and the corresponding actual swing amplitude when the head swings left and right;
when the swing direction of the head of the student swings leftwards and the actual swing amplitude of the leftward swing is larger than a preset swing amplitude threshold value, identifying course knowledge related to a corresponding course knowledge teaching link as difficult knowledge; when the swing direction of the head of the student swings rightwards and the actual swing amplitude of the head swings rightwards is larger than a preset swing amplitude threshold value, identifying the course knowledge related to the corresponding course knowledge teaching link as non-problematic knowledge;
and the number of the first and second groups,
the operation examination and evaluation paper generation module is used for picking a plurality of first type operation questions and a plurality of second type operation questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset operation question database, so that the corresponding operation examination and evaluation paper is formed by the following steps:
selecting a plurality of first type operation questions and a plurality of second type operation questions which respectively have the same knowledge point key words with the difficult knowledge and the non-difficult knowledge from a preset operation question database; and selecting a specific number of first type of operation questions and second type of operation questions according to a preset operation question configuration proportion to jointly form a corresponding operation test and evaluation paper.
9. The interactive teaching system based on virtual reality scene of claim 8, wherein: the course professor adjusting module is used for judging the homework test and evaluation paper finished by the students so as to determine answer results of all homework questions in the homework test and evaluation paper; according to the answer result, when the teaching of the corresponding course knowledge teaching link is adjusted in the subsequent virtual reality scene teaching, the method specifically comprises the following steps:
judging the homework test paper finished by the student so as to determine the correct/wrong condition of the response result of each homework subject in the homework test paper finished by the student;
if the answer result of a certain task is correct, the teaching time of the corresponding course knowledge teaching link is reduced in the virtual reality scene teaching; if the answer result of a certain task is wrong, increasing the teaching time of a corresponding course knowledge teaching link in the subsequent virtual reality scene teaching;
in a course knowledge teaching link of subsequent virtual reality scene teaching, which is increased in teaching course, a reminding message is sent to students at regular time; the reminding message comprises voice content for reminding the current teaching progress of the student.
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