Interactive teaching method and system based on virtual reality scene

Abstract

The present invention provides an interactive teaching method and system based on a virtual reality scene. By collecting students' body movement states in different course knowledge teaching links in a virtual reality teaching scene, the course knowledge involved in the corresponding course knowledge teaching link is marked as difficult knowledge and non-difficult knowledge. In this way, the students' learning responses to different knowledge contents in the teaching process can be determined in real time, so as to facilitate the subsequent targeted selection of homework questions of different difficulty levels to form homework assessment papers, and according to the answer results of the students on the homework assessment papers, the weak links of the students' knowledge learning are determined, so as to adjust the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching. In this way, not only can the teaching content be adjusted intelligently and targetedly according to the learning abilities of different students, but also the learning efficiency and quality of the students in the virtual reality scene can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent teaching, and in particular to an interactive teaching method and system based on a virtual reality scene. Background Art

[0002] At present, virtual reality technology is widely used in intelligent teaching. Students can get an immersive class experience by wearing head-mounted virtual reality display devices. Class teaching in virtual reality scenes usually directly displays three-dimensional teaching course images to students. It does not interact with students in the virtual reality scene and collect students' behaviors and actions in the teaching process in a timely manner. This makes it impossible to adjust the course teaching content according to students' real-time reactions during the teaching process and remind students in a timely manner. It can be seen that the existing virtual reality teaching model cannot achieve interactive teaching with students, and cannot make intelligent and targeted adjustments to teaching content according to the learning abilities of different students, which greatly reduces students' learning efficiency and quality in virtual reality scenes. Summary of the invention

[0003] In view of the defects of the prior art, the present invention provides an interactive teaching method and system based on a virtual reality scene, which collects full-body images of students corresponding to different course knowledge teaching links in the virtual reality scene; analyzes the full-body images of students to determine the corresponding body movement states of students in each course knowledge teaching link; identifies the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body movement states; extracts a number of first-category homework questions and a number of second-category homework questions corresponding to difficult knowledge and non-difficult knowledge respectively from a preset homework question database, thereby forming a corresponding homework evaluation paper; finally, evaluates the homework evaluation paper completed by the students to determine the answer results of all homework questions in the homework evaluation paper; and adjusts the corresponding course knowledge teaching link in subsequent virtual reality scene teaching according to the answer results. Teaching hours; It can be seen that the interactive teaching method and system based on the virtual reality scene collects the body movement states of students in different course knowledge teaching links in the virtual reality teaching scene, and identifies the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge. In this way, the students' learning response to different knowledge contents in the teaching process can be determined in real time, so as to facilitate the subsequent targeted selection of homework questions of different difficulty levels to form homework evaluation papers, and determine the weak links of students' knowledge learning according to the answer results of the students' homework evaluation papers, so as to adjust the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching. In this way, not only can the teaching content be adjusted intelligently and targetedly according to the learning abilities of different students, but also the learning efficiency and quality of students in the virtual reality scene can be greatly improved.

[0004] The present invention provides an interactive teaching method based on a virtual reality scene, characterized in that it comprises the following steps:

[0005] Step S1, collecting full-body images of students corresponding to different course knowledge teaching links in a virtual reality scene; analyzing the full-body images of students to determine the corresponding body movement states of students in each course knowledge teaching link;

[0006] Step S2, according to the body movement state, marking the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge; extracting a number of first-category homework questions and a number of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset homework question database, so as to form a corresponding homework assessment paper;

[0007] Step S3, evaluating the homework assessment papers completed by the students, thereby determining the answer results of all homework questions in the homework assessment papers; and adjusting the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching according to the answer results;

[0008] Furthermore, in step S1, whole-body images of students corresponding to different course knowledge teaching links in the virtual reality scene are collected; and the whole-body images of students are analyzed to determine the body movement states of students corresponding to each course knowledge teaching link, specifically including:

[0009] Step S101, in each course knowledge teaching session in the virtual reality scene, students are photographed binocularly to obtain corresponding binocular student full-body images; and background noise filtering is performed on the binocular student images;

[0010] Step S102, generating a three-dimensional full-body image of the student according to the image parallax of the binocular full-body image of the student; and identifying the head posture of the student in the three-dimensional full-body image of the student;

[0011] Step S103, determining the head swing direction and head swing amplitude corresponding to the student in each course knowledge teaching session according to the head posture, and using this as the body movement state;

[0012] Further, in the step S2, according to the body movement state, the course knowledge involved in the corresponding course knowledge teaching link is identified as difficult knowledge and non-difficult knowledge; from the preset homework question database, a number of first-category homework questions and a number of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge are selected, so as to form a corresponding homework assessment paper, which specifically includes:

[0013] Step S201, determining whether the head swing direction corresponding to the student in each course knowledge teaching session is a left-right swing direction and the actual swing amplitude corresponding to the left-right swing of the head;

[0014] Step S202: when the student's head swing direction is to the left and the actual swing amplitude of the left swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as difficult knowledge; when the student's head swing direction is to the right and the actual swing amplitude of the right swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as non-difficult knowledge;

[0015] Step S203, extracting a number of first-category homework questions and a number of second-category homework questions that have the same knowledge point keywords as the difficult knowledge and the non-difficult knowledge respectively from the preset homework question database; and then selecting a specific number of first-category homework questions and second-category homework questions according to the preset homework question configuration ratio to form a corresponding homework assessment paper together;

[0016] Further, in step S203, according to the preset homework title configuration ratio, a specific number of first-category homework titles and second-category homework titles are selected to form a corresponding homework assessment paper. Specifically, a specific number of first-category homework titles and second-category homework titles are selected, and the position of the first-category homework titles and second-category homework titles in the homework assessment paper are determined. Specifically, the position of the title setting sequence of the first-category homework titles and the second-category homework titles in the homework assessment paper includes:

[0017] Step S2031, using the following formulas (1)-(2), determine the first question difficulty characteristic value S1 of all the selected first-category homework questions and the second question difficulty characteristic value S2 of all the selected second-category questions,

[0018]

[0019]

[0020] In the above formulas (1)-(2), α i1 It represents the proportion of the word count of the i1th first-category homework question to the total word count of all first-category homework questions, and its value range is (0, 1), α i2 It represents the proportion of the word count of the i2th second-category homework question in the total word count of all second-category homework questions, and its value range is (0, 1), β 0n represents the average difficulty value of all the first-category homework questions, β 0m represents the average difficulty value of all the second-category homework questions, n represents the total number of the first-category homework questions, and m represents the total number of the second-category homework questions;

[0021] Step S2032, using the following formulas (3)-(4), determine the first layout position weight value of each first-category homework question and the second layout position weight value of each second-category homework question; when the first layout position weight value of a first-category homework question is larger, its setting position in the overall layout area of ​​all first-category homework questions is closer to the back; when the second layout position weight value of a second-category homework question is larger, its setting position in the overall layout area of ​​all second-category homework questions is closer to the back,

[0022]

[0023]

[0024] In the above formulas (3)-(4), P i1 represents the first layout position weight value of the first type of homework question i1, i1 represents the proportion of the score of the i1th first-category homework question to the total score of all first-category homework questions, and r i1 represents the proportion of the score of the first type of homework question in the total score of the homework assessment paper, and its value range is (0, 1), r i1max It represents the proportion of the first-category homework question with the highest question score among all the first-category homework questions in the total score of the homework assessment paper, P i2 represents the second layout position weight value of the i2th second-category homework question, χ i2 represents the proportion of the score of the i2th second-category homework question to the total score of all second-category homework questions, and r i2 represents the proportion of the score of the second type of homework question in the total score of the homework assessment paper, and its value range is (0, 1), r i2max It indicates the proportion of the score of the second-category homework question with the highest score among all the second-category homework questions in the total score of the homework assessment paper;

[0025] When the first layout position weight value of a first-category homework question is larger, its setting position in the overall layout area of ​​all first-category homework questions is positioned further back; when the second layout position weight value of a second-category homework question is larger, its setting position in the overall layout area of ​​all second-category homework questions is positioned further back;

[0026] Step S2033, using the following formula (5), determine the verification value Y corresponding to the position layout of all homework questions in the homework assessment paper,

[0027]

[0028] In the above formula (5), Represents the average value of the first layout position weight of all first-category assignments. represents the average value of the second layout position weight value of all second-category homework questions, a1 represents the floating change ratio value of the number of all difficult knowledge points contained in all first-category homework questions, and its value range is 0.01-0.05, a2 represents the floating change ratio value of the number of all non-difficult knowledge points contained in all second-category homework questions, and its value range is 0.02-0.04;

[0029] The verification value Y is compared with a preset verification threshold value Y1. If the verification value is greater than or equal to the preset verification threshold value Y1, the obtained homework evaluation paper is retained; otherwise, the obtained homework evaluation paper is deleted;

[0030] Further, in step S3, the homework assessment paper completed by the student is evaluated to determine the answer results of all homework questions in the homework assessment paper; according to the answer results, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are adjusted specifically including:

[0031] Step S301, judging the homework assessment paper completed by the student, so as to determine the correctness / incorrectness of the answer results of each homework question in the homework assessment paper completed by the student;

[0032] Step S302: if the answer result of a certain homework question is correct, then the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are reduced; if the answer result of a certain homework question is wrong, then the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are increased;

[0033] Step S303, in the subsequent course knowledge teaching phase of the virtual reality scene teaching with increased teaching hours, a reminder message is regularly sent to the students; wherein the reminder message includes voice content that reminds the students of the current teaching progress.

[0034] The present invention also provides an interactive teaching system based on a virtual reality scene, characterized in that it includes a student image shooting and analysis module, a course knowledge identification module, a homework evaluation paper generation module and a course teaching adjustment module; wherein,

[0035] The student image shooting and analysis module is used to collect the student's full-body images corresponding to different course knowledge teaching links in the virtual reality scene; analyze the student's full-body images to determine the student's body movement state corresponding to each course knowledge teaching link;

[0036] The course knowledge identification module is used to identify the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body movement state;

[0037] The homework assessment paper generating module is used to extract a plurality of first-category homework questions and a plurality of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset homework question database, so as to form a corresponding homework assessment paper;

[0038] The course teaching adjustment module is used to judge the homework assessment papers completed by students, so as to determine the answer results of all homework questions in the homework assessment papers; according to the answer results, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are adjusted;

[0039] Furthermore, the student image shooting and analysis module is used to collect full-body images of students corresponding to different course knowledge teaching links in the virtual reality scene; analyze the full-body images of students to determine the corresponding body movement states of students in each course knowledge teaching link, specifically including:

[0040] In each course knowledge teaching session in the virtual reality scene, students are photographed binocularly to obtain corresponding binocular student full-body images; and background noise filtering is performed on the binocular student images;

[0041] Generating a three-dimensional full-body image of the student according to the image parallax of the binocular full-body image of the student; recognizing the head posture of the student in the three-dimensional full-body image of the student;

[0042] According to the head posture, determining the head swing direction and head swing amplitude corresponding to the student in each course knowledge teaching session, and using them as the body movement state;

[0043] Furthermore, the course knowledge identification module is used to identify the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body movement state, which specifically includes:

[0044] Determine whether the head swing direction of the students in each course knowledge teaching session is left-right swing direction and the actual swing amplitude when the head swings left-right;

[0045] When the student's head swing direction is to the left and the actual swing amplitude of the left swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as difficult knowledge; when the student's head swing direction is to the right and the actual swing amplitude of the right swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as non-difficult knowledge;

[0046] as well as,

[0047] The homework assessment paper generation module is used to extract a plurality of first-category homework questions and a plurality of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset homework question database, so as to form a corresponding homework assessment paper, specifically including:

[0048] From a preset homework question database, a number of first-category homework questions and a number of second-category homework questions having the same knowledge point keywords as the difficult knowledge and the non-difficult knowledge respectively are selected; and then, according to a preset homework question configuration ratio, a specific number of first-category homework questions and second-category homework questions are selected to form a corresponding homework assessment paper together;

[0049] Furthermore, the course teaching adjustment module is used to judge the homework assessment papers completed by students, so as to determine the answer results of all homework questions in the homework assessment papers; according to the answer results, the teaching hours of the corresponding course knowledge teaching link are adjusted in the subsequent virtual reality scene teaching, specifically including:

[0050] Evaluate the homework assessment papers completed by students to determine whether the students' answers to each homework question in the homework assessment papers are correct or incorrect;

[0051] If the answer to a homework question is correct, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching will be reduced; if the answer to a homework question is wrong, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching will be increased;

[0052] In the subsequent course knowledge teaching phase of the virtual reality scene teaching with increased teaching hours, reminder messages are sent to students at regular intervals; wherein the reminder messages include voice content that reminds students of the current teaching progress.

[0053] Compared with the prior art, the present invention provides an interactive teaching method and system based on a virtual reality scene to collect full-body images of students corresponding to different course knowledge teaching links in a virtual reality scene; analyze the full-body images of students to determine the corresponding body movement states of students in each course knowledge teaching link; identify the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body movement states; extract a number of first-category homework questions and a number of second-category homework questions corresponding to difficult knowledge and non-difficult knowledge respectively from a preset homework question database, thereby forming a corresponding homework evaluation paper; finally, judge the homework evaluation paper completed by the students to determine the answer results of all homework questions in the homework evaluation paper; according to the answer results, adjust the teaching of the corresponding course knowledge teaching link in subsequent virtual reality scene teaching. class hours; it can be seen that the interactive teaching method and system based on the virtual reality scene collects the body movement states of students in different course knowledge teaching links in the virtual reality teaching scene, and identifies the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge. In this way, the students' learning response to different knowledge contents in the teaching process can be determined in real time, so as to facilitate the subsequent targeted selection of homework questions of different difficulty levels to form homework evaluation papers, and determine the weak links in students' knowledge learning according to the answer results of the students' homework evaluation papers, so as to adjust the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching. In this way, not only can the teaching content be adjusted intelligently and targetedly according to the learning abilities of different students, but also the students' learning efficiency and quality in the virtual reality scene can be greatly improved.

[0054] 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 particularly pointed out in the written description, claims, and drawings.

[0055] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 A schematic diagram of the flow of the interactive teaching method based on virtual reality scene provided by the present invention.

[0058] Figure 2 This is a schematic diagram of the structure of the interactive teaching system based on virtual reality scene provided by the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] See also Figure 1 , is a flow chart of an interactive teaching method based on a virtual reality scene provided by an embodiment of the present invention. The interactive teaching method based on a virtual reality scene comprises the following steps:

[0061] Step S1, collecting full-body images of students corresponding to different course knowledge teaching links in a virtual reality scene; analyzing the full-body images of students to determine the corresponding body movement states of students in each course knowledge teaching link;

[0062] Step S2, according to the body movement state, marking the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge; extracting a number of first-category homework questions and a number of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset homework question database, so as to form a corresponding homework assessment paper;

[0063] Step S3, judging the homework assessment papers completed by the students, thereby determining the answer results of all homework questions in the homework assessment papers; according to the answer results, adjusting the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching.

[0064] The beneficial effect of the above technical solution is: the interactive teaching method based on virtual reality scene collects the body movement states of students in different course knowledge teaching links in the virtual reality teaching scene, and identifies the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge. In this way, the students' learning response to different knowledge content in the teaching process can be determined in real time, so as to facilitate the subsequent targeted selection of homework questions of different difficulty levels to form homework evaluation papers, and determine the weak links in students' knowledge learning based on the answer results of the students completing the homework evaluation papers, so as to adjust the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching. In this way, not only can the teaching content be adjusted intelligently and targetedly according to the learning abilities of different students, but also the learning efficiency and quality of students in the virtual reality scene can be greatly improved.

[0065] Preferably, in step S1, collecting the whole body images of the students corresponding to different course knowledge teaching links in the virtual reality scene; analyzing the whole body images of the students to determine the body movement states of the students corresponding to each course knowledge teaching link specifically includes:

[0066] Step S101, in each course knowledge teaching session in the virtual reality scene, students are photographed binocularly to obtain corresponding binocular student full-body images; and background noise filtering is performed on the binocular student images;

[0067] Step S102, generating a three-dimensional full-body image of the student according to the image parallax of the binocular full-body image of the student; and identifying the head posture of the student in the three-dimensional full-body image of the student;

[0068] Step S103, according to the head posture, determining the head swing direction and head swing amplitude corresponding to the student in each course knowledge teaching link, and taking this as the body movement state.

[0069] The beneficial effect of the above technical solution is that students learn different course knowledge in a virtual reality scene. During the learning process, students usually have questions about the knowledge content they are learning or have misunderstandings. At this time, students need to provide corresponding feedback to determine which knowledge content is difficult knowledge for students. In order to facilitate clear and rapid real-time analysis of students' reactions during the teaching process, the head posture of the students can be determined by taking a full-body image of the students and then analyzing the full-body image. In actual operation, students can be informed in advance that when students think that the current knowledge content is difficult knowledge during the teaching process, the student's head needs to perform a first type of action (such as swinging the head to the left by a preset amplitude). At the same time, when students think that the current knowledge content is non-difficult knowledge during the teaching process, the student's head needs to perform a second type of action (such as swinging the head to the right by a preset amplitude). In this way, the knowledge involved in the teaching process can be quickly and accurately distinguished according to the student's head action.

[0070] Preferably, in step S2, according to the body movement state, the course knowledge involved in the corresponding course knowledge teaching link is identified as difficult knowledge and non-difficult knowledge; from the preset homework question database, a number of first-category homework questions and a number of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge are selected, so as to form a corresponding homework assessment paper, which specifically includes:

[0071] Step S201, determining whether the head swing direction corresponding to the student in each course knowledge teaching session is a left-right swing direction and the actual swing amplitude corresponding to the left-right swing of the head;

[0072] Step S202: when the student's head swing direction is to the left and the actual swing amplitude of the left swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as difficult knowledge; when the student's head swing direction is to the right and the actual swing amplitude of the right swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as non-difficult knowledge;

[0073] Step S203, extracting a number of first-category homework questions and a number of second-category homework questions that have the same knowledge point keywords as the difficult knowledge and the non-difficult knowledge respectively from the preset homework question database; then selecting a specific number of first-category homework questions and second-category homework questions according to the preset homework question configuration ratio to jointly form a corresponding homework assessment paper.

[0074] The beneficial effect of the above technical solution is: by identifying the type of head movement of students during the teaching process, the different difficult and easy knowledge contents involved in the teaching process are calibrated. For example, in the course learning about calculus, when in the course knowledge teaching link of one-dimensional integration, the student's head swings to the right and the actual swing amplitude of the right swing is greater than the preset swing amplitude threshold. At this time, the knowledge corresponding to the one-dimensional integration is marked as non-difficult knowledge. When in the course knowledge teaching link of two-dimensional integration, the student's head swings to the left and the actual swing amplitude of the left swing is greater than the preset swing amplitude threshold. At this time, the knowledge corresponding to the two-dimensional integration is marked as difficult knowledge. Through the above method, different types of course knowledge can be quickly and accurately marked as difficult without affecting students' normal listening to the class.

[0075] In addition, after all course knowledge is marked as difficult knowledge and non-difficult knowledge, the corresponding homework questions can be selected from the preset homework question database by keyword matching. For example, for one-dimensional integral knowledge content marked as non-difficult knowledge, the keyword "one-dimensional integral" can be used to find homework questions related to one-dimensional integral in the preset homework question database, and this is used as the second type of homework question; for two-dimensional integral knowledge content marked as difficult knowledge, the keyword "two-dimensional integral" can be used to find homework questions related to two-dimensional integral in the preset homework question database, and this is used as the first type of homework question. Then, according to the ratio requirements between the number of subjective questions such as multiple-choice questions and objective questions such as calculation questions in the homework assessment paper as the preset homework question configuration ratio, the corresponding number of first-category homework questions and second-category homework questions are selected to form the homework assessment paper together, which can improve the comprehensive coverage of different knowledge contents in the homework assessment paper.

[0076] Preferably, in step S203, according to a preset homework title configuration ratio, a specific number of first-category homework titles and second-category homework titles are selected to form a corresponding homework assessment paper together. Specifically, a specific number of first-category homework titles and second-category homework titles are selected, and the position of the first-category homework titles and second-category homework titles in the homework assessment paper are determined. Specifically, the position of the title setting sequence of the first-category homework titles and the second-category homework titles in the homework assessment paper includes:

[0077] Step S2031, using the following formulas (1)-(2), determine the first question difficulty characteristic value S1 of all the selected first-category homework questions and the second question difficulty characteristic value S2 of all the selected second-category questions,

[0078]

[0079]

[0080] In the above formulas (1)-(2), α i1 It represents the proportion of the word count of the i1th first-category homework question to the total word count of all first-category homework questions, and its value range is (0, 1), α i2 It represents the proportion of the word count of the i2th second-category homework question in the total word count of all second-category homework questions, and its value range is (0, 1), β 0n represents the average difficulty value of all the first-category homework questions, β 0m represents the average difficulty value of all the second-category homework questions, n represents the total number of the first-category homework questions, and m represents the total number of the second-category homework questions;

[0081] Step S2032, using the following formulas (3)-(4), determine the first layout position weight value of each first-category homework question and the second layout position weight value of each second-category homework question; when the first layout position weight value of a first-category homework question is larger, its setting position in the overall layout area of ​​all first-category homework questions is closer to the back; when the second layout position weight value of a second-category homework question is larger, its setting position in the overall layout area of ​​all second-category homework questions is closer to the back,

[0082]

[0083]

[0084] In the above formulas (3)-(4), P i1 represents the first layout position weight value of the first type of homework question i1, i1 represents the proportion of the score of the i1th first-category homework question to the total score of all first-category homework questions, and ri1 represents the proportion of the score of the first type of homework question in the total score of the homework assessment paper, and its value range is (0, 1), r i1max It represents the proportion of the first-category homework question with the highest question score among all the first-category homework questions in the total score of the homework assessment paper, P i2 represents the second layout position weight value of the i2th second-category homework question, χ i2 represents the proportion of the score of the i2th second-category homework question to the total score of all second-category homework questions, and r i2 represents the proportion of the score of the second type of homework question in the total score of the homework assessment paper, and its value range is (0, 1), r i2max It indicates the proportion of the score of the second-category homework question with the highest score among all the second-category homework questions in the total score of the homework assessment paper;

[0085] In the homework assessment paper, the first category homework questions and the second category homework questions are set in two independent areas of the homework assessment paper respectively. The first category homework questions and the second category homework questions are not set crosswise in the homework test paper. When the first layout position weight value of a first category homework question is larger, its setting position in the overall layout area of ​​all first category homework questions is further back; when the second layout position weight value of a second category homework question is larger, its setting position in the overall layout area of ​​all second category homework questions is further back;

[0086] Step S2033, using the following formula (5), determine the verification value Y corresponding to the position layout of all homework questions in the homework assessment paper,

[0087]

[0088] In the above formula (5), Represents the average value of the first layout position weight of all first-category assignments. represents the average value of the second layout position weight value of all second-category homework questions, a1 represents the floating change ratio value of the number of all difficult knowledge points contained in all first-category homework questions, and its value range is 0.01-0.05. Since the number of difficult knowledge points contained in all first-category homework questions will change with the content of the first-category homework questions selected, when selecting the first-category homework questions, the number of difficult knowledge points contained in all first-category homework questions will be set to be higher than the preset difficult knowledge points number benchmark value, and a1 represents the number of all difficult knowledge points contained in all first-category homework questions compared to the preset difficult knowledge points number benchmark value. a2 represents the floating change ratio of the number of all non-difficult knowledge points contained in all second-category homework questions, and its value range is 0.02-0.04. Since the number of non-difficult knowledge points contained in all second-category homework questions will vary with the content of the second-category homework questions selected, when selecting the second-category homework questions, the number of non-difficult knowledge points contained in all second-category homework questions will be set to be higher than the preset non-difficult knowledge points number benchmark value, and a2 represents the floating change ratio of the number of all non-difficult knowledge points contained in all second-category homework questions compared to the preset non-difficult knowledge points number benchmark value;

[0089] The verification value Y is compared with the preset verification threshold value Y1. If the verification value is greater than or equal to the preset verification threshold value Y1, the obtained homework evaluation paper is retained; otherwise, the obtained homework evaluation paper is deleted, and after deleting the obtained homework test paper, the corresponding number of first-category homework questions and second-category homework questions are reselected, and the above steps S2031-S2033 are traversed again in sequence until the verification value is greater than or equal to the preset verification threshold value Y1.

[0090] The beneficial effect of the above technical solution is that since the first type of homework questions contain difficult knowledge points and the second type of homework questions contain non-difficult knowledge points, the first type of homework questions and the second type of homework questions are laid out independently in the homework test paper. The above formulas (1)-(2) can be used to quantitatively evaluate the overall difficulty of the first type of homework questions and the second type of homework questions, respectively, so as to obtain the corresponding difficulty characteristic value; then the above formulas (3)-(4) are used to determine the layout position weight values ​​of the first type of homework questions and the second type of homework questions, respectively, so that according to the ascending order of the layout position weight values, the corresponding layout setting position order of the first type of homework questions and the second type of homework questions in the homework test paper can be quickly determined, so as to preliminarily form the corresponding homework test paper. Finally, the above formula (5) is used to verify the homework test paper to determine whether the preliminarily formed homework test paper meets the corresponding homework question difficulty layout requirements, so that the final homework test paper can match the student homework needs to the greatest extent.

[0091] Preferably, in step S3, the homework assessment paper completed by the student is evaluated to determine the answer results of all homework questions in the homework assessment paper; and according to the answer results, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are adjusted specifically including:

[0092] Step S301, judging the homework assessment paper completed by the student, so as to determine the correctness / incorrectness of the answer results of each homework question in the homework assessment paper completed by the student;

[0093] Step S302: if the answer result of a certain homework question is correct, then the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are reduced; if the answer result of a certain homework question is wrong, then the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are increased;

[0094] Step S303, in the subsequent course knowledge teaching phase of the virtual reality scene teaching with increased teaching hours, a reminder message is regularly sent to the students; wherein the reminder message includes voice content that reminds the students of the current teaching progress.

[0095] The beneficial effect of the above technical solution is: by judging the correctness / error of the answer results of each homework question obtained by the homework assessment paper completed by the students, it is possible to accurately determine the degree of students' firm grasp of different knowledge contents in the teaching process. For example, if the correctness rate of the students' answers to the homework questions about one-dimensional integration is high, it means that the students have a high degree of firm grasp of the knowledge content of one-dimensional integration, and the error rate of the students' answers to the homework questions about two-dimensional integration is high, which means that the students have a low degree of firm grasp of the knowledge content of two-dimensional integration; at this time, in the subsequent virtual reality scene teaching, the teaching hours of the two-dimensional integration knowledge content can be increased, and the teaching hours of the one-dimensional integration knowledge content can be reduced; at the same time, it is also possible to send a voice message of the current two-dimensional integration knowledge content teaching progress to the students during the teaching of the two-dimensional integration knowledge content, wherein the two-dimensional integration knowledge content teaching progress can be but not limited to the number of knowledge chapters that have been taught and the number of knowledge chapters that have not been taught in the two-dimensional integration knowledge content.

[0096] See also Figure 2 , is a structural diagram of an interactive teaching system based on a virtual reality scene provided by an embodiment of the present invention. The interactive teaching system based on a virtual reality scene includes a student image shooting and analysis module, a course knowledge identification module, a homework evaluation paper generation module and a course teaching adjustment module; wherein,

[0097] The student image shooting and analysis module is used to collect the student's full-body images corresponding to different course knowledge teaching links in the virtual reality scene; analyze the student's full-body images to determine the student's body movement state corresponding to each course knowledge teaching link;

[0098] The course knowledge identification module is used to identify the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body movement state;

[0099] The homework assessment paper generating module is used to extract a plurality of first-category homework questions and a plurality of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset homework question database, so as to form a corresponding homework assessment paper;

[0100] The course teaching adjustment module is used to judge the homework assessment papers completed by students, so as to determine the answer results of all homework questions in the homework assessment papers; according to the answer results, the teaching hours of the corresponding course knowledge teaching links in the subsequent virtual reality scene teaching are adjusted.

[0101] The beneficial effect of the above technical solution is: the interactive teaching system based on the virtual reality scene collects the body movement states of students in different course knowledge teaching links in the virtual reality teaching scene, and identifies the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge. In this way, the students' learning response to different knowledge content in the teaching process can be determined in real time, so as to facilitate the subsequent targeted selection of homework questions of different difficulty levels to form homework evaluation papers, and determine the weak links in students' knowledge learning based on the answer results of the students completing the homework evaluation papers, so as to adjust the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching. In this way, not only can the teaching content be adjusted intelligently and targetedly according to the learning abilities of different students, but also the learning efficiency and quality of students in the virtual reality scene can be greatly improved.

[0102] Preferably, the student image shooting and analysis module is used to collect the student's full-body images corresponding to different course knowledge teaching links in the virtual reality scene; analyzing the student's full-body images to determine the student's body movement state corresponding to each course knowledge teaching link specifically includes:

[0103] In each course knowledge teaching session in the virtual reality scene, students are photographed binocularly to obtain the corresponding binocular student full-body images; and the binocular student images are subjected to background noise filtering;

[0104] Generate a three-dimensional full-body image of the student according to the image parallax of the binocular full-body image of the student; and recognize the head posture of the student in the three-dimensional full-body image of the student;

[0105] According to the head posture, the head swing direction and head swing amplitude corresponding to the students in each course knowledge teaching session are determined as the body movement state.

[0106] The beneficial effect of the above technical solution is that students learn different course knowledge in a virtual reality scene. During the learning process, students usually have questions about the knowledge content they are learning or have misunderstandings. At this time, students need to provide corresponding feedback to determine which knowledge content is difficult knowledge for students. In order to facilitate clear and rapid real-time analysis of students' reactions during the teaching process, the head posture of the students can be determined by taking a full-body image of the students and then analyzing the full-body image. In actual operation, students can be informed in advance that when students think that the current knowledge content is difficult knowledge during the teaching process, the student's head needs to perform a first type of action (such as swinging the head to the left by a preset amplitude). At the same time, when students think that the current knowledge content is non-difficult knowledge during the teaching process, the student's head needs to perform a second type of action (such as swinging the head to the right by a preset amplitude). In this way, the knowledge involved in the teaching process can be quickly and accurately distinguished according to the student's head action.

[0107] Preferably, the course knowledge identification module is used to identify the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body movement state, specifically including:

[0108] Determine whether the student's head swing direction in each course knowledge teaching session is left-right and the actual swing amplitude when the head swings left-right;

[0109] When the student's head swing direction is to the left and the actual swing amplitude of the left swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as difficult knowledge; when the student's head swing direction is to the right and the actual swing amplitude of the right swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as non-difficult knowledge;

[0110] as well as,

[0111] The homework assessment paper generation module is used to extract a number of first-category homework questions and a number of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset homework question database, so as to form a corresponding homework assessment paper, which specifically includes:

[0112] From the preset homework question database, select several first category homework questions and several second category homework questions that have the same knowledge point keywords as the difficult knowledge and the non-difficult knowledge respectively; then according to the preset homework question configuration ratio, select a specific number of first category homework questions and second category homework questions to jointly form the corresponding homework evaluation paper.

[0113] In addition, after all course knowledge is marked as difficult knowledge and non-difficult knowledge, the corresponding homework questions can be selected from the preset homework question database by keyword matching. For example, for one-dimensional integral knowledge content marked as non-difficult knowledge, the keyword "one-dimensional integral" can be used to find homework questions related to one-dimensional integral in the preset homework question database, and this is used as the second type of homework question; for two-dimensional integral knowledge content marked as difficult knowledge, the keyword "two-dimensional integral" can be used to find homework questions related to two-dimensional integral in the preset homework question database, and this is used as the first type of homework question. Then, according to the ratio requirements between the number of subjective questions such as multiple-choice questions and objective questions such as calculation questions in the homework assessment paper as the preset homework question configuration ratio, the corresponding number of first-category homework questions and second-category homework questions are selected to form the homework assessment paper together, which can improve the comprehensive coverage of different knowledge contents in the homework assessment paper.

[0114] Preferably, the course teaching adjustment module is used to judge the homework assessment papers completed by students, so as to determine the answer results of all homework questions in the homework assessment papers; according to the answer results, adjusting the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching specifically includes:

[0115] Evaluate the homework assessment papers completed by students to determine whether the students' answers to each homework question in the homework assessment papers are correct or incorrect;

[0116] If the answer to a homework question is correct, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching will be reduced; if the answer to a homework question is wrong, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching will be increased;

[0117] In the subsequent course knowledge teaching phase of the virtual reality scene teaching with increased teaching hours, reminder messages are sent to students at regular intervals; wherein the reminder messages include voice content that reminds students of the current teaching progress.

[0118] The beneficial effect of the above technical solution is: by judging the correctness / error of the answer results of each homework question obtained by the homework assessment paper completed by the students, it is possible to accurately determine the degree of students' firm grasp of different knowledge contents in the teaching process. For example, if the correctness rate of the students' answers to the homework questions about one-dimensional integration is high, it means that the students have a high degree of firm grasp of the knowledge content of one-dimensional integration, and the error rate of the students' answers to the homework questions about two-dimensional integration is high, which means that the students have a low degree of firm grasp of the knowledge content of two-dimensional integration; at this time, in the subsequent virtual reality scene teaching, the teaching hours of the two-dimensional integration knowledge content can be increased, and the teaching hours of the one-dimensional integration knowledge content can be reduced; at the same time, it is also possible to send a voice message of the current two-dimensional integration knowledge content teaching progress to the students during the teaching of the two-dimensional integration knowledge content, wherein the two-dimensional integration knowledge content teaching progress can be but not limited to the number of knowledge chapters that have been taught and the number of knowledge chapters that have not been taught in the two-dimensional integration knowledge content.

[0119] It can be seen from the contents of the above embodiments that the interactive teaching method and system based on virtual reality scenes collects students' body movement states in different course knowledge teaching links in the virtual reality teaching scene, and identifies the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge. In this way, students' learning responses to different knowledge contents in the teaching process can be determined in real time, so as to facilitate the subsequent targeted selection of homework questions of different difficulty levels to form homework assessment papers, and determine the weak links in students' knowledge learning based on the answer results of students completing the homework assessment papers, so as to adjust the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching. In this way, not only can the teaching content be adjusted intelligently and targetedly according to the learning abilities of different students, but also the learning efficiency and quality of students in the virtual reality scene can be greatly improved.

[0120] 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 fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An interactive teaching method based on virtual reality scenes, characterized in that: It includes the following steps: Step S1, collecting full-body images of students corresponding to different course knowledge teaching links in a virtual reality scene; analyzing the full-body images of students to determine the corresponding body movement states of students in each course knowledge teaching link; Step S2, according to the body movement state, marking the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge; extracting a number of first-category homework questions and a number of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset homework question database, so as to form a corresponding homework assessment paper; Step S3, evaluating the homework assessment papers completed by the students, thereby determining the answer results of all homework questions in the homework assessment papers; and adjusting the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching according to the answer results; Wherein, in the step S1, collecting the whole body images of the students corresponding to different course knowledge teaching links in the virtual reality scene; analyzing the whole body images of the students to determine the body movement states corresponding to the students in each course knowledge teaching link specifically includes: Step S101, in each course knowledge teaching session in the virtual reality scene, students are photographed binocularly to obtain corresponding binocular student full-body images; and background noise filtering is performed on the binocular student images; Step S102, generating a three-dimensional full-body image of the student according to the image parallax of the binocular full-body image of the student; and identifying the head posture of the student in the three-dimensional full-body image of the student; Step S103, according to the head posture, determine the head swing direction and head swing amplitude corresponding to the student in each course knowledge teaching link, and use this as the body movement state; wherein, in the step S2, according to the body movement state, the course knowledge involved in the corresponding course knowledge teaching link is identified as difficult knowledge and non-difficult knowledge; from the preset homework question database, select a number of first-category homework questions and a number of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge, respectively, to form a corresponding homework assessment paper, specifically including: Step S201, determining whether the head swing direction corresponding to the student in each course knowledge teaching session is a left-right swing direction and the actual swing amplitude corresponding to the left-right swing of the head; Step S202: when the student's head swing direction is to the left and the actual swing amplitude of the left swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as difficult knowledge; when the student's head swing direction is to the right and the actual swing amplitude of the right swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as non-difficult knowledge; Step S203, extracting a number of first-category homework questions and a number of second-category homework questions that have the same knowledge point keywords as the difficult knowledge and the non-difficult knowledge respectively from the preset homework question database; and then selecting a specific number of first-category homework questions and second-category homework questions according to the preset homework question configuration ratio to form a corresponding homework assessment paper together; Among them, in step S203, according to the preset homework title configuration ratio, a specific number of first-category homework titles and second-category homework titles are selected to form a corresponding homework assessment paper together. Specifically, a specific number of first-category homework titles and second-category homework titles are selected, and the position of the first-category homework titles and second-category homework titles in the homework assessment paper are determined. Specifically, the position of the title setting sequence of the first-category homework titles and the second-category homework titles in the homework assessment paper includes: Step S2031, using the following formulas (1)-(2), determine the first question difficulty characteristic value S1 of all the selected first-category homework questions and the second question difficulty characteristic value S2 of all the selected second-category questions, In the above formulas (1)-(2), α i1 It represents the proportion of the word count of the i1th first-category homework question to the total word count of all first-category homework questions, and its value range is (0, 1), α i2 It represents the proportion of the word count of the i2th second-category homework question in the total word count of all second-category homework questions, and its value range is (0, 1), β 0n represents the average difficulty value of all the first-category homework questions, β 0m represents the average difficulty value of all the second-category homework questions, n represents the total number of the first-category homework questions, and m represents the total number of the second-category homework questions; Step S2032, using the following formulas (3)-(4), determine the first layout position weight value of each first-category homework question and the second layout position weight value of each second-category homework question; when the first layout position weight value of a first-category homework question is larger, its setting position in the overall layout area of ​​all first-category homework questions is closer to the back; when the second layout position weight value of a second-category homework question is larger, its setting position in the overall layout area of ​​all second-category homework questions is closer to the back, In the above formulas (3)-(4), P i1 represents the first layout position weight value of the first type of homework question i1, i1 represents the proportion of the score of the i1th first-category homework question to the total score of all first-category homework questions, and r i1 represents the proportion of the score of the first type of homework question in the total score of the homework assessment paper, and its value range is (0, 1), r i1max It represents the proportion of the first-category homework question with the highest question score among all the first-category homework questions in the total score of the homework assessment paper, P i2 represents the second layout position weight value of the i2th second-category homework question, χ i2 represents the proportion of the score of the i2th second-category homework question to the total score of all second-category homework questions, and r i2 represents the proportion of the score of the second type of homework question in the total score of the homework assessment paper, and its value range is (0, 1), r i2max It indicates the proportion of the score of the second-category homework question with the highest score among all the second-category homework questions in the total score of the homework assessment paper; Step S2033, using the following formula (5), determine the verification value Y corresponding to the position layout of all homework questions in the homework assessment paper, In the above formula (5), Represents the average value of the first layout position weight of all first-category assignments. represents the average value of the second layout position weight value of all second-category homework questions, a1 represents the floating change ratio value of the number of all difficult knowledge points contained in all first-category homework questions, and its value range is 0.01-0.05, a2 represents the floating change ratio value of the number of all non-difficult knowledge points contained in all second-category homework questions, and its value range is 0.02-0.04; The verification value Y is compared with the preset verification threshold value Y1. If the verification value is greater than or equal to the preset verification threshold value Y1, the obtained homework evaluation paper is retained; otherwise, the obtained homework evaluation paper is deleted.

2. The interactive teaching method based on virtual reality scene as claimed in claim 1, characterized in that: In the step S3, the homework assessment paper completed by the student is evaluated to determine the answer results of all homework questions in the homework assessment paper; according to the answer results, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are adjusted specifically including: Step S301, judging the homework assessment paper completed by the student, so as to determine the correctness / incorrectness of the answer results of each homework question in the homework assessment paper completed by the student; Step S302: if the answer result of a certain homework question is correct, then the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are reduced; if the answer result of a certain homework question is wrong, then the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are increased; Step S303, in the subsequent course knowledge teaching phase of the virtual reality scene teaching with increased teaching hours, a reminder message is regularly sent to the students; wherein the reminder message includes voice content that reminds the students of the current teaching progress.

3. The interactive teaching system based on virtual reality scene is characterized by: It includes student image shooting and analysis module, course knowledge identification module, homework assessment paper generation module and course teaching adjustment module; among them, The student image shooting and analysis module is used to collect the student's full-body images corresponding to different course knowledge teaching links in the virtual reality scene; analyze the student's full-body images to determine the student's body movement state corresponding to each course knowledge teaching link; The course knowledge identification module is used to identify the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body movement state; The homework assessment paper generating module is used to extract a plurality of first-category homework questions and a plurality of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset homework question database, so as to form a corresponding homework assessment paper; The course teaching adjustment module is used to judge the homework assessment papers completed by students, so as to determine the answer results of all homework questions in the homework assessment papers; according to the answer results, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are adjusted; The student image shooting and analysis module is used to collect the whole-body images of students corresponding to different course knowledge teaching links in the virtual reality scene; analyzing the whole-body images of students to determine the corresponding body movement states of students in each course knowledge teaching link specifically includes: in each course knowledge teaching link in the virtual reality scene, binocularly shooting the students respectively to obtain the corresponding binocular whole-body images of students; and performing background noise filtering on the binocular student images; Generating a three-dimensional full-body image of the student according to the image parallax of the binocular full-body image of the student; recognizing a head posture of the student in the three-dimensional full-body image of the student; According to the head posture, determining the head swing direction and head swing amplitude corresponding to the student in each course knowledge teaching session, and using them as the body movement state; The course knowledge identification module is used to identify the course knowledge involved in the corresponding course knowledge teaching link as difficult knowledge and non-difficult knowledge according to the body movement state, and specifically includes: Determine whether the student's head swing direction in each course knowledge teaching session is left-right and the actual swing amplitude when the head swings left-right; When the student's head swing direction is to the left and the actual swing amplitude of the left swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as difficult knowledge; when the student's head swing direction is to the right and the actual swing amplitude of the right swing is greater than the preset swing amplitude threshold, the course knowledge involved in the corresponding course knowledge teaching link is marked as non-difficult knowledge; as well as, The homework assessment paper generation module is used to extract a plurality of first-category homework questions and a plurality of second-category homework questions corresponding to the difficult knowledge and the non-difficult knowledge respectively from a preset homework question database, so as to form a corresponding homework assessment paper, specifically including: From a preset homework question database, a number of first-category homework questions and a number of second-category homework questions having the same knowledge point keywords as the difficult knowledge and the non-difficult knowledge respectively are selected; and then, according to a preset homework question configuration ratio, a specific number of first-category homework questions and second-category homework questions are selected to form a corresponding homework assessment paper together; The step of selecting a specific number of first-category assignments and second-category assignments according to a preset assignment assignment configuration ratio to form a corresponding assignment evaluation paper specifically includes selecting a specific number of first-category assignments and second-category assignments, and determining the position of the first-category assignments and second-category assignments in the assignment evaluation paper. Specifically, the step of: Step S2031, using the following formulas (1)-(2), determine the first question difficulty characteristic value S1 of all the selected first-category homework questions and the second question difficulty characteristic value S2 of all the selected second-category questions, In the above formulas (1)-(2), α i1 It represents the proportion of the word count of the i1th first-category homework question to the total word count of all first-category homework questions, and its value range is (0, 1), α i2 It represents the proportion of the word count of the i2th second-category homework question in the total word count of all second-category homework questions, and its value range is (0, 1), β 0n represents the average difficulty value of all the first-category homework questions, β 0m represents the average difficulty value of all the second-category homework questions, n represents the total number of the first-category homework questions, and m represents the total number of the second-category homework questions; Step S2032, using the following formulas (3)-(4), determine the first layout position weight value of each first-category homework question and the second layout position weight value of each second-category homework question; when the first layout position weight value of a first-category homework question is larger, its setting position in the overall layout area of ​​all first-category homework questions is closer to the back; when the second layout position weight value of a second-category homework question is larger, its setting position in the overall layout area of ​​all second-category homework questions is closer to the back, In the above formulas (3)-(4), P i1 represents the first layout position weight value of the first type of homework question i1, i1 represents the proportion of the score of the i1th first-category homework question to the total score of all first-category homework questions, and r i1 represents the proportion of the score of the first type of homework question in the total score of the homework assessment paper, and its value range is (0, 1), r i1max It represents the proportion of the first-category homework question with the highest question score among all the first-category homework questions in the total score of the homework assessment paper, P i2 represents the second layout position weight value of the i2th second-category homework question, χ i2 represents the proportion of the score of the i2th second-category homework question to the total score of all second-category homework questions, and r i2 represents the proportion of the score of the second type of homework question in the total score of the homework assessment paper, and its value range is (0, 1), r i2max It indicates the proportion of the score of the second-category homework question with the highest score among all the second-category homework questions in the total score of the homework assessment paper; Step S2033, using the following formula (5), determine the verification value Y corresponding to the position layout of all homework questions in the homework assessment paper, In the above formula (5), Represents the average value of the first layout position weight of all first-category assignments. represents the average value of the second layout position weight value of all second-category homework questions, a1 represents the floating change ratio value of the number of all difficult knowledge points contained in all first-category homework questions, and its value range is 0.01-0.05, a2 represents the floating change ratio value of the number of all non-difficult knowledge points contained in all second-category homework questions, and its value range is 0.02-0.04; The verification value Y is compared with the preset verification threshold value Y1. If the verification value is greater than or equal to the preset verification threshold value Y1, the obtained homework evaluation paper is retained; otherwise, the obtained homework evaluation paper is deleted.

4. The interactive teaching system based on virtual reality scene as claimed in claim 3, characterized in that: The course teaching adjustment module is used to judge the homework assessment papers completed by students, so as to determine the answer results of all homework questions in the homework assessment papers; according to the answer results, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching are adjusted specifically including: Evaluate the homework assessment papers completed by students to determine whether the students' answers to each homework question in the homework assessment papers are correct or incorrect; If the answer to a homework question is correct, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching will be reduced; if the answer to a homework question is wrong, the teaching hours of the corresponding course knowledge teaching link in the subsequent virtual reality scene teaching will be increased; In the subsequent course knowledge teaching phase of the virtual reality scene teaching with increased teaching hours, reminder messages are sent to students at regular intervals; wherein the reminder messages include voice content that reminds students of the current teaching progress.

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