Teaching method and system based on cloud desktop

Abstract

The invention discloses a teaching method and system based on a cloud desktop. The method comprises the following steps: acquiring teaching resource information applied to the cloud desktop by a student; acquiring data information of a student; based on the data information of the student, judging whether teaching resource information applied to the cloud desktop by the student accords with a preset specification, and if yes, allowing the student to use the corresponding teaching resource information; if not, the student is not allowed to use the corresponding teaching resource information, and the corresponding teaching resource information is matched according to the data information of the student; and sending the adaptive teaching resource information to the student end for selection. Interaction between teachers and students is achieved through the cloud desktop, and the students are prevented from being afraid of directly facing the teachers; besides, the students can complete learning targets according to own conditions, and passive learning is converted into active learning, so that the learning enthusiasm of the students is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of online teaching, and more specifically, to a teaching method and system based on a cloud desktop. Background Art

[0002] With the popularization of mobile Internet, students and teachers have an increasingly strong demand for obtaining teaching resources and conducting teaching activities anytime and anywhere; cloud desktops support access from multiple terminal devices. Whether in the classroom, at home or outdoors, as long as there is a network connection, you can access familiar teaching desktops and resources, breaking the limitations of time and space.

[0003] The traditional teaching method is relatively simple, often mainly based on teacher lectures. Students passively accept knowledge and lack opportunities for active participation and exploration, making it difficult to cultivate students' innovative thinking and practical ability. In addition, the traditional teaching method is often one-size-fits-all and cannot fully take into account the learning progress, interests and abilities of each student, resulting in some students not being able to keep up with the decoupling of teaching, while the potential of some students has not been fully tapped. Summary of the invention

[0004] In order to solve at least one of the above technical problems, the present invention proposes a teaching method and system based on a cloud desktop, which can enable students to avoid the fear of facing the teacher directly; in addition, it allows students to complete learning goals according to their own circumstances, turning passive learning into active learning, thereby improving students' enthusiasm for learning.

[0005] A first aspect of the present invention provides a teaching method based on a cloud desktop, comprising:

[0006] Obtain the teaching resource information that students apply for from the cloud desktop;

[0007] Obtain students’ information;

[0008] Based on the student's profile information, determine whether the teaching resource information applied by the student to the cloud desktop meets the preset regulations. If so, allow the student to use the corresponding teaching resource information;

[0009] If not, the student will not be allowed to use the corresponding teaching resource information, and the appropriate teaching resource information will be matched according to the student's profile information;

[0010] The appropriate teaching resource information is sent to the students for selection.

[0011] In this solution, the steps of judging whether the teaching resource information applied by the student to the cloud desktop meets the preset requirements based on the student's profile information specifically include:

[0012] The teaching resource information applied by the students to the cloud desktop is set as the teaching resource application information;

[0013] Extract the teaching application chapters and the difficulty levels of the corresponding teaching application chapters in the teaching resource application information;

[0014] According to the student's profile information, determine whether the student is logging in for the first time. If so, determine whether the teaching application chapter in the teaching resource application information is the first chapter of the corresponding subject; if so, determine whether the difficulty level of the corresponding teaching application chapter is the initial difficulty level of the corresponding teaching chapter. If so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations;

[0015] If it is not the first time logging in, extract the current teaching chapter and the corresponding difficulty level of the current teaching chapter from the student's information; obtain the learning assessment score of the corresponding student in the current teaching chapter based on the student's information; determine the recommended difficulty level range of the next teaching chapter for the corresponding student based on the learning assessment score of the corresponding student in the current teaching chapter and the corresponding difficulty level of the current teaching chapter; determine whether the teaching application chapter in the teaching resource application information is the next teaching chapter of the current teaching chapter; if so, determine whether the difficulty level of the corresponding teaching application chapter is within the recommended difficulty level range, and if so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations.

[0016] In this solution, the step of obtaining the learning assessment score of the corresponding student in the current teaching chapter according to the student's information specifically includes:

[0017] According to the student's information, obtain the corresponding student's study time and test score in non-current teaching chapters;

[0018] Divide the learning time and test scores of the corresponding students in non-current teaching chapters according to the teaching chapters to obtain the learning time and test scores of different teaching chapters;

[0019] Multiply the study time of different teaching chapters by the preset difficulty level coefficient of the corresponding teaching chapter, and then add them up to get the total effective study time of the corresponding students;

[0020] The test scores of different teaching chapters are accumulated to obtain the total test score of the corresponding students;

[0021] Divide the total test score of the corresponding student by the total effective learning time of the corresponding student to obtain the scoring coefficient of the corresponding student;

[0022] Get the learning time of the corresponding students in the current teaching chapter;

[0023] Multiply the corresponding student's learning time in the current teaching chapter by the preset difficulty level coefficient of the current teaching chapter, and then multiply it by the corresponding student's scoring coefficient to obtain the corresponding student's learning evaluation score in the current teaching chapter.

[0024] In this solution, after obtaining the learning evaluation score of the corresponding student in the current teaching chapter, it also includes:

[0025] Obtaining historical learning material information of other students within a preset first time period, wherein the historical learning material information at least includes the teaching chapters of historical learning, the time value of historical learning, the test scores in the process of historical learning, and the historical learning evaluation scores;

[0026] According to the student's information, the basic information and learning information of the current student are obtained, and the learning information of the current student at least includes the teaching chapter studied by the current student, the time value of the current student's study and the test score of the current student in the learning process;

[0027] Compare and analyze the history learning chapters of any other student within the preset first time period with the history learning chapters of the current student. If they are the same, the history learning material information of the corresponding other student will be saved; if they are different, the history learning material information of the corresponding other student will be deleted;

[0028] The difference between the historical learning time value of any other student within the preset first time period and the learning time value of the current student is calculated to obtain a first learning time difference. If the first learning time difference is less than or equal to the preset first time threshold, the historical learning data information of the corresponding other students is saved; if the first learning time difference is greater than the preset first time threshold, the historical learning data information of the corresponding other students is deleted;

[0029] Calculate the difference between the test score of any other student in the historical learning process within the preset first time period and the test score of the current student to obtain a first test score difference; if the first test score difference is less than or equal to the preset first score threshold, save the historical learning data information of the corresponding other students; if the first test score difference is greater than the preset first score threshold, delete the historical learning data information of the corresponding other students;

[0030] After traversing all the historical learning information of other students, obtain the historical learning information of the remaining other students;

[0031] Calculate the difference between the historical learning assessment score and the test score in the historical learning process of the same student in the remaining historical learning data information of other students, and obtain the historical prediction score difference of the corresponding student;

[0032] Traverse the historical learning information of all other students and obtain the historical prediction score difference set;

[0033] Calculate the average value of the historical prediction score differences in the historical prediction score difference set to obtain a revised learning evaluation score;

[0034] The revised value of the learning assessment score is added to the current student's learning assessment score in the current teaching chapter to obtain the revised value of the corresponding student's learning assessment score in the current teaching chapter.

[0035] In this solution, the steps of determining the recommended difficulty level range for the next teaching chapter for the corresponding student specifically include:

[0036] When the learning assessment score of the corresponding student in the current teaching chapter is within the preset score range, the recommended difficulty level range for the corresponding student in the next teaching chapter is the recommended difficulty level of the current teaching chapter;

[0037] When the learning assessment score of the corresponding student in the current teaching chapter is less than the preset score range, the minimum value in the preset score range is extracted, and the learning assessment score of the corresponding student in the current teaching chapter is subtracted from the minimum value in the preset score range to obtain a second score difference, and the first revised value of the difficulty level of the next teaching chapter is determined according to the preset second score range in which the second score difference falls; the first revised value of the difficulty level of the next teaching chapter is subtracted from the difficulty level of the current teaching chapter to obtain the maximum value in the recommended difficulty level range for the corresponding student in the next teaching chapter, and then the first revised value of the difficulty level of the next teaching chapter is subtracted from the minimum value in the recommended difficulty level range for the corresponding student in the current teaching chapter to obtain the minimum value in the recommended difficulty level range for the corresponding student in the next teaching chapter;

[0038] When the corresponding student's learning assessment score in the current teaching chapter is greater than the preset score range, the maximum value in the preset score range is extracted, and the third score difference is obtained by subtracting the maximum value in the preset score range from the corresponding student's learning assessment score in the current teaching chapter. According to the preset third score range in which the third score difference falls, the second revised value of the difficulty level of the next teaching chapter is determined; the difficulty level of the current teaching chapter is added to the second revised value of the difficulty level of the next teaching chapter to obtain the maximum value in the recommended difficulty level range for the corresponding student in the next teaching chapter, and the difficulty level of the current teaching chapter is set to the minimum value in the recommended difficulty level range for the next teaching chapter.

[0039] This plan also includes:

[0040] Get the student's learning time and test score in the current teaching chapter;

[0041] If the student's study time value in the current teaching chapter is greater than or equal to the preset study time threshold or the student's test score in the current teaching chapter is greater than or equal to the preset test score threshold, the corresponding student is allowed to apply for teaching resources for the next teaching chapter;

[0042] If the student's study time value in the current teaching chapter is less than the preset study time threshold and the student's test score in the current teaching chapter is less than the preset test score threshold, the corresponding student will not be allowed to apply for teaching resources for the next teaching chapter.

[0043] This plan also includes:

[0044] Get the current time node;

[0045] According to the current time node, query the preset learning progress table to obtain the learning progress value of the current teaching chapter theory completion;

[0046] Divide the student's learning time value in the current teaching chapter by the theoretical completed learning time value of the current teaching chapter to obtain the current student's actual completed learning progress value;

[0047] Subtract the actual learning progress value of the current student from the theoretical learning progress value of the current teaching chapter to get the learning progress difference;

[0048] If the learning progress difference is less than or equal to the preset learning progress difference threshold, the learning prompt information is triggered and sent to the corresponding student terminal.

[0049] A second aspect of the present invention provides a teaching system based on a cloud desktop, comprising a memory and a processor, wherein a teaching method program based on a cloud desktop is stored in the memory, and when the teaching method program based on the cloud desktop is executed by the processor, the following steps are implemented:

[0050] Obtain the teaching resource information that students apply for from the cloud desktop;

[0051] Obtain students’ information;

[0052] Based on the student's profile information, determine whether the teaching resource information applied by the student to the cloud desktop meets the preset regulations. If so, allow the student to use the corresponding teaching resource information;

[0053] If not, the student will not be allowed to use the corresponding teaching resource information, and the appropriate teaching resource information will be matched according to the student's profile information;

[0054] The appropriate teaching resource information is sent to the students for selection.

[0055] In this solution, the steps of judging whether the teaching resource information applied by the student to the cloud desktop meets the preset requirements based on the student's profile information specifically include:

[0056] The teaching resource information applied by the students to the cloud desktop is set as the teaching resource application information;

[0057] Extract the teaching application chapters and the difficulty levels of the corresponding teaching application chapters in the teaching resource application information;

[0058] According to the student's profile information, determine whether the student is logging in for the first time. If so, determine whether the teaching application chapter in the teaching resource application information is the first chapter of the corresponding subject; if so, determine whether the difficulty level of the corresponding teaching application chapter is the initial difficulty level of the corresponding teaching chapter. If so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations;

[0059] If it is not the first time logging in, extract the current teaching chapter and the corresponding difficulty level of the current teaching chapter from the student's information; obtain the learning assessment score of the corresponding student in the current teaching chapter based on the student's information; determine the recommended difficulty level range of the next teaching chapter for the corresponding student based on the learning assessment score of the corresponding student in the current teaching chapter and the corresponding difficulty level of the current teaching chapter; determine whether the teaching application chapter in the teaching resource application information is the next teaching chapter of the current teaching chapter; if so, determine whether the difficulty level of the corresponding teaching application chapter is within the recommended difficulty level range, and if so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations.

[0060] In this solution, the step of obtaining the learning assessment score of the corresponding student in the current teaching chapter according to the student's information specifically includes:

[0061] According to the student's information, obtain the corresponding student's study time and test score in non-current teaching chapters;

[0062] Divide the learning time and test scores of the corresponding students in non-current teaching chapters according to the teaching chapters to obtain the learning time and test scores of different teaching chapters;

[0063] Multiply the study time of different teaching chapters by the preset difficulty level coefficient of the corresponding teaching chapter, and then add them up to get the total effective study time of the corresponding students;

[0064] The test scores of different teaching chapters are accumulated to obtain the total test score of the corresponding students;

[0065] Divide the total test score of the corresponding student by the total effective learning time of the corresponding student to obtain the scoring coefficient of the corresponding student;

[0066] Get the learning time of the corresponding students in the current teaching chapter;

[0067] Multiply the corresponding student's learning time in the current teaching chapter by the preset difficulty level coefficient of the current teaching chapter, and then multiply it by the corresponding student's scoring coefficient to obtain the corresponding student's learning evaluation score in the current teaching chapter.

[0068] The present invention discloses a teaching method and system based on a cloud desktop, which realizes the interaction between teachers and students through the cloud desktop, so that students can avoid the fear of facing the teacher directly; in addition, students can complete learning goals according to their own situation, turning passive learning into active learning, thereby improving students' enthusiasm for learning. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 A flow chart of a teaching method based on a cloud desktop of the present invention is shown;

[0070] Figure 2 A flow chart showing the present invention for calculating the learning evaluation score of a student in the current teaching chapter;

[0071] Figure 3 A block diagram of a cloud desktop-based teaching system of the present invention is shown. DETAILED DESCRIPTION

[0072] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0074] Figure 1 A flow chart of a cloud desktop-based teaching method of the present invention is shown.

[0075] like Figure 1 As shown, the present invention discloses a teaching method based on a cloud desktop, comprising:

[0076] S101, obtaining the teaching resource information applied by the student from the cloud desktop;

[0077] S102, obtaining student information;

[0078] S103, based on the student's profile information, determining whether the teaching resource information applied by the student to the cloud desktop meets the preset regulations, and if so, allowing the student to use the corresponding teaching resource information;

[0079] S104, if not, the student is not allowed to use the corresponding teaching resource information, and the appropriate teaching resource information is matched according to the student's profile information;

[0080] S105, sending the appropriate teaching resource information to the student end for selection.

[0081] According to an embodiment of the present invention, the student's profile information includes the student's basic profile information and learning profile information. The student's basic profile information includes the corresponding student's name, student number, grade and other information; the student plans his or her own learning progress according to his or her own learning ability and learning goals, and applies for teaching resources suitable for himself or herself, thereby improving learning efficiency.

[0082] It can be understood that the teaching resources of the cloud desktop can be divided into different subjects. Each subject has multiple chapters, and the same chapter has teaching materials of different difficulty levels for students to choose from. When students apply for teaching resources, the recognition system in the cloud desktop will evaluate the student's information to determine whether the teaching resources applied for by the student meet the preset regulations, to prevent the students from applying for teaching resources with too high a difficulty level and undermining their self-confidence, and at the same time, to prevent the students from applying for teaching resources with too low a difficulty level and wasting their time.

[0083] According to an embodiment of the present invention, the step of judging whether the teaching resource information applied by the student to the cloud desktop meets the preset requirements based on the student's profile information specifically includes:

[0084] The teaching resource information applied by the students to the cloud desktop is set as the teaching resource application information;

[0085] Extract the teaching application chapters and the difficulty levels of the corresponding teaching application chapters in the teaching resource application information;

[0086] According to the student's profile information, determine whether the student is logging in for the first time. If so, determine whether the teaching application chapter in the teaching resource application information is the first chapter of the corresponding subject; if so, determine whether the difficulty level of the corresponding teaching application chapter is the initial difficulty level of the corresponding teaching chapter. If so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations;

[0087] If it is not the first time logging in, extract the current teaching chapter and the corresponding difficulty level of the current teaching chapter from the student's information; obtain the learning assessment score of the corresponding student in the current teaching chapter based on the student's information; determine the recommended difficulty level range of the next teaching chapter for the corresponding student based on the learning assessment score of the corresponding student in the current teaching chapter and the corresponding difficulty level of the current teaching chapter; determine whether the teaching application chapter in the teaching resource application information is the next teaching chapter of the current teaching chapter; if so, determine whether the difficulty level of the corresponding teaching application chapter is within the recommended difficulty level range, and if so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations.

[0088] It should be noted that the higher the difficulty level of the teaching application chapter, the higher the difficulty coefficient of the corresponding teaching chapter. The contents of the teaching chapters of the same chapter but different difficulty levels cover all the contents of the corresponding chapters in the textbook, and only differ in extracurricular extension, degree of detail of the teaching, etc. When the student logs in for the first time, it means that the current student has just started learning, and because there is no learning material information for the corresponding student, the corresponding student can only apply for the first chapter of the corresponding subject and the difficulty level is the initial difficulty level. The initial difficulty level is greater than the first difficulty level, such as the second difficulty level; if it is not the first login, a judgment will be made based on the corresponding student's learning material to determine the learning assessment score of the currently studied teaching chapter, and then a judgment will be made.

[0089] Furthermore, if the student is inserted into the study midway, the teacher can manually determine the teaching resource information applied for by the student.

[0090] Figure 2 A flow chart of the present invention for calculating the learning evaluation score of a student in the current teaching chapter is shown.

[0091] like Figure 2 As shown, the step of obtaining the learning evaluation score of the corresponding student in the current teaching chapter according to the student's information specifically includes:

[0092] S201, according to the student's information, obtaining the learning time and test score of the corresponding student in the non-current teaching chapter;

[0093] S202, dividing the learning time and test scores of the corresponding students in non-current teaching chapters according to the teaching chapters, and obtaining the learning time and test scores of different teaching chapters;

[0094] S203, multiplying the learning time of different teaching chapters by the preset difficulty level coefficient of the corresponding teaching chapter, and then accumulating them to obtain the total effective learning time of the corresponding students;

[0095] S204, accumulating the test scores of different teaching chapters to obtain the total test score of the corresponding student;

[0096] S205, dividing the total test score of the corresponding student by the total effective learning time of the corresponding student to obtain the scoring coefficient of the corresponding student;

[0097] S206, obtaining the learning time of the corresponding student in the current teaching chapter;

[0098] S207, multiplying the learning time of the corresponding student in the current teaching chapter by the preset difficulty level coefficient of the current teaching chapter, and then multiplying it by the scoring coefficient of the corresponding student to obtain the learning evaluation score of the corresponding student in the current teaching chapter.

[0099] It should be noted that after completing each teaching chapter, students will be given simple tests in turn to determine the students' achievements at that stage and obtain the test scores for the corresponding teaching chapters. When a teaching chapter has not been completed, the students' achievements at that stage can be predicted based on their study time at the corresponding teaching chapters to determine the learning evaluation scores for the current teaching chapters.

[0100] According to an embodiment of the present invention, after obtaining the learning evaluation score of the corresponding student in the current teaching chapter, the method further includes:

[0101] Obtaining historical learning material information of other students within a preset first time period, wherein the historical learning material information at least includes the teaching chapters of historical learning, the time value of historical learning, the test scores in the process of historical learning, and the historical learning evaluation scores;

[0102] According to the student's information, the basic information and learning information of the current student are obtained, and the learning information of the current student at least includes the teaching chapter studied by the current student, the time value of the current student's study and the test score of the current student in the learning process;

[0103] Compare and analyze the history learning chapters of any other student within the preset first time period with the history learning chapters of the current student. If they are the same, the history learning material information of the corresponding other student will be saved; if they are different, the history learning material information of the corresponding other student will be deleted;

[0104] The difference between the historical learning time value of any other student within the preset first time period and the learning time value of the current student is calculated to obtain a first learning time difference. If the first learning time difference is less than or equal to the preset first time threshold, the historical learning data information of the corresponding other students is saved; if the first learning time difference is greater than the preset first time threshold, the historical learning data information of the corresponding other students is deleted;

[0105] Calculate the difference between the test score of any other student in the historical learning process within the preset first time period and the test score of the current student to obtain a first test score difference; if the first test score difference is less than or equal to the preset first score threshold, save the historical learning data information of the corresponding other students; if the first test score difference is greater than the preset first score threshold, delete the historical learning data information of the corresponding other students;

[0106] After traversing all the historical learning information of other students, obtain the historical learning information of the remaining other students;

[0107] Calculate the difference between the historical learning assessment score and the test score in the historical learning process of the same student in the remaining historical learning data information of other students, and obtain the historical prediction score difference of the corresponding student;

[0108] Traverse the historical learning information of all other students and obtain the historical prediction score difference set;

[0109] Calculate the average value of the historical prediction score differences in the historical prediction score difference set to obtain a revised learning evaluation score;

[0110] The revised value of the learning assessment score is added to the current student's learning assessment score in the current teaching chapter to obtain the revised value of the corresponding student's learning assessment score in the current teaching chapter.

[0111] It should be noted that the one-to-one comparative analysis of the teaching chapters of history learning of any other student within the preset first time period and the teaching chapters studied by the current student is based on the conditions of the same subject and the same teaching chapters. For example, if the fifth chapter of the mathematics subject and the third difficulty level are selected at the same time, the teaching chapter studied by the current student and the teaching chapter of the history learning of the corresponding other students will be the same; if the current student selects the fifth chapter of the mathematics subject and the first difficulty level, and the corresponding other student selects the fifth chapter of the mathematical science subject and the third difficulty level, then they will be set to be different.

[0112] Furthermore, if the current student has only completed one chapter of a subject, the corresponding student has only one test score in the corresponding subject, and the difference calculation is performed based on the current student's only test score and the test scores of other students in the corresponding chapter of the corresponding subject; if the current student has completed multiple chapters in a single subject, the difference calculation is performed based on the test scores of the same teaching chapter to obtain the test score difference for each teaching chapter, and then the test score differences of all teaching chapters are averaged to obtain the corresponding first test score difference.

[0113] According to an embodiment of the present invention, the step of determining a recommended difficulty level range for the next teaching section for the corresponding student specifically includes:

[0114] When the learning assessment score of the corresponding student in the current teaching chapter is within the preset score range, the recommended difficulty level range for the corresponding student in the next teaching chapter is the recommended difficulty level of the current teaching chapter;

[0115] When the learning assessment score of the corresponding student in the current teaching chapter is less than the preset score range, the minimum value in the preset score range is extracted, and the learning assessment score of the corresponding student in the current teaching chapter is subtracted from the minimum value in the preset score range to obtain a second score difference, and the first revised value of the difficulty level of the next teaching chapter is determined according to the preset second score range in which the second score difference falls; the first revised value of the difficulty level of the next teaching chapter is subtracted from the difficulty level of the current teaching chapter to obtain the maximum value in the recommended difficulty level range for the corresponding student in the next teaching chapter, and then the first revised value of the difficulty level of the next teaching chapter is subtracted from the minimum value in the recommended difficulty level range for the corresponding student in the current teaching chapter to obtain the minimum value in the recommended difficulty level range for the corresponding student in the next teaching chapter;

[0116] When the corresponding student's learning assessment score in the current teaching chapter is greater than the preset score range, the maximum value in the preset score range is extracted, and the third score difference is obtained by subtracting the maximum value in the preset score range from the corresponding student's learning assessment score in the current teaching chapter. According to the preset third score range in which the third score difference falls, the second revised value of the difficulty level of the next teaching chapter is determined; the difficulty level of the current teaching chapter is added to the second revised value of the difficulty level of the next teaching chapter to obtain the maximum value in the recommended difficulty level range for the corresponding student in the next teaching chapter, and the difficulty level of the current teaching chapter is set to the minimum value in the recommended difficulty level range for the next teaching chapter.

[0117] It should be noted that due to external or personal reasons, students may have different learning states at different learning stages. Therefore, the difficulty level of the teaching materials is adjusted in real time according to the students' learning states. The students' learning states are measured by the learning assessment scores of the corresponding students. The higher the learning assessment scores, the better the learning states of the corresponding students. The better the learning states, the higher the difficulty level of the teaching chapters that the corresponding students can accept, thereby improving learning efficiency. Based on the preset second base number, the preset second score range is divided to determine different preset second score ranges. For example, if the preset second base number is 10 points, the preset second score range can be divided into: (0, 10], (10, 20], ... and so on, and each preset second score range corresponds to a first revised value of the difficulty level, wherein the larger the value in the preset second score range, the larger the corresponding first revised value of the difficulty level; based on the preset third base, the preset third score range is divided to determine different preset third score ranges. For example, if the preset third base is 8 points, the preset third score range can be divided into (0, 8], (8, 16], ... and so on, and each preset third score range corresponds to a second revised value of the difficulty level, wherein the larger the value in the preset third score range, the larger the corresponding second revised value of the difficulty level.

[0118] It is understood that when students have completed a teaching chapter or have spent a certain amount of time studying the corresponding teaching chapter, they can apply for the next teaching chapter; set the recommended difficulty level range of the teaching chapter to Where L n Indicates the teaching chapter n, Indicates the minimum value in the range of recommended difficulty levels corresponding to the nth chapter of the teaching. Indicates the maximum value in the range of recommended difficulty levels corresponding to the nth chapter of the teaching. When L1=1, k0 represents the initial difficulty level of the first chapter of the course. If the student's learning assessment score in the first chapter of the course is within the preset score range, the recommended difficulty level for the student in the second chapter of the course is If the student's learning assessment score in the first chapter of the teaching is less than the preset score range, the recommended difficulty level for the next chapter is Among them When it is less than 1, The result is set to 1, when When it is less than 1, The result is set to 1, where k1 represents the first revised value of the difficulty level. Indicates the difficulty level selected by the student in the first chapter of the teaching; if the student's learning assessment score in the first chapter of the teaching is greater than the preset score range, the recommended difficulty level for the next chapter is Where k2 represents the second revised value of the difficulty level.

[0119] According to an embodiment of the present invention, it also includes:

[0120] Get the student's learning time and test score in the current teaching chapter;

[0121] If the student's study time value in the current teaching chapter is greater than or equal to the preset study time threshold or the student's test score in the current teaching chapter is greater than or equal to the preset test score threshold, the corresponding student is allowed to apply for teaching resources for the next teaching chapter;

[0122] If the student's study time value in the current teaching chapter is less than the preset study time threshold and the student's test score in the current teaching chapter is less than the preset test score threshold, the corresponding student will not be allowed to apply for teaching resources for the next teaching chapter.

[0123] According to an embodiment of the present invention, it also includes:

[0124] Get the current time node;

[0125] According to the current time node, query the preset learning progress table to obtain the learning progress value of the current teaching chapter theory completion;

[0126] Divide the student's learning time value in the current teaching chapter by the theoretical completed learning time value of the current teaching chapter to obtain the current student's actual completed learning progress value;

[0127] Subtract the actual learning progress value of the current student from the theoretical learning progress value of the current teaching chapter to get the learning progress difference;

[0128] If the learning progress difference is less than or equal to the preset learning progress difference threshold, the learning prompt information is triggered and sent to the corresponding student terminal.

[0129] It should be noted that the preset learning progress table stores the theoretical completion learning progress values ​​of various subjects at different time nodes. For example, the theoretical completion learning progress value of the second chapter of subject A on Friday of the third week is 100%.

[0130] According to an embodiment of the present invention, it also includes:

[0131] When students study through the cloud desktop, if they have doubts about the knowledge points in the teaching chapter, the knowledge points in the current teaching chapter will be marked;

[0132] Get the number of times the same knowledge point is marked;

[0133] If the number of times the same knowledge point is marked is greater than the preset first number threshold, the live teaching time information is triggered;

[0134] The live teaching time information is sent to a preset teacher terminal for confirmation. If confirmed, the corresponding live teaching time information is sent to the student terminal that marks the knowledge point;

[0135] If the preset lecturer end does not confirm, then extract the live teaching time information set by the preset lecturer end and send it to the student end that marked the knowledge point;

[0136] If the number of times the same knowledge point is marked is less than or equal to the preset first number threshold, the recorded teaching information is triggered;

[0137] The recorded lecture information is sent to the preset teacher's terminal for a special explanation of the knowledge point.

[0138] It should be noted that when students have resolved their doubts about the corresponding knowledge point through special topic explanations, they can cancel the mark of the knowledge point.

[0139] Furthermore, if there is a special lecture on the knowledge point of the current teaching chapter by the lecturer, the special lecture on the corresponding knowledge point will be displayed.

[0140] Furthermore, a discussion group is constructed based on the identified knowledge point, and an invitation code is generated, and the invitation code is sent to a user terminal selected by the student to jointly discuss the identified knowledge point.

[0141] It should be noted that the constructed discussion group can also be set to be visible to all other students and instructors, so that other students who have doubts about the knowledge point can join in the discussion, make friends through questions, and open up students' thinking and make friends.

[0142] Figure 3 A block diagram of a cloud desktop-based teaching system of the present invention is shown.

[0143] like Figure 2 As shown, the second aspect of the present invention provides a teaching system 3 based on a cloud desktop, including a memory 31 and a processor 32, wherein the memory stores a teaching method program based on a cloud desktop, and when the teaching method program based on a cloud desktop is executed by the processor, the following steps are implemented:

[0144] Obtain the teaching resource information that students apply for from the cloud desktop;

[0145] Obtain students’ information;

[0146] Based on the student's profile information, determine whether the teaching resource information applied by the student to the cloud desktop meets the preset regulations. If so, allow the student to use the corresponding teaching resource information;

[0147] If not, the student will not be allowed to use the corresponding teaching resource information, and the appropriate teaching resource information will be matched according to the student's profile information;

[0148] The appropriate teaching resource information is sent to the students for selection.

[0149] In this solution, the steps of judging whether the teaching resource information applied by the student to the cloud desktop meets the preset requirements based on the student's profile information specifically include:

[0150] The teaching resource information applied by the students to the cloud desktop is set as the teaching resource application information;

[0151] Extract the teaching application chapters and the difficulty levels of the corresponding teaching application chapters in the teaching resource application information;

[0152] According to the student's profile information, determine whether the student is logging in for the first time. If so, determine whether the teaching application chapter in the teaching resource application information is the first chapter of the corresponding subject; if so, determine whether the difficulty level of the corresponding teaching application chapter is the initial difficulty level of the corresponding teaching chapter. If so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations;

[0153] If it is not the first time logging in, extract the current teaching chapter and the corresponding difficulty level of the current teaching chapter from the student's information; obtain the learning assessment score of the corresponding student in the current teaching chapter based on the student's information; determine the recommended difficulty level range of the next teaching chapter for the corresponding student based on the learning assessment score of the corresponding student in the current teaching chapter and the corresponding difficulty level of the current teaching chapter; determine whether the teaching application chapter in the teaching resource application information is the next teaching chapter of the current teaching chapter; if so, determine whether the difficulty level of the corresponding teaching application chapter is within the recommended difficulty level range, and if so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations.

[0154] In this solution, the step of obtaining the learning assessment score of the corresponding student in the current teaching chapter according to the student's information specifically includes:

[0155] According to the student's information, obtain the corresponding student's study time and test score in non-current teaching chapters;

[0156] Divide the learning time and test scores of the corresponding students in non-current teaching chapters according to the teaching chapters to obtain the learning time and test scores of different teaching chapters;

[0157] Multiply the study time of different teaching chapters by the preset difficulty level coefficient of the corresponding teaching chapter, and then add them up to get the total effective study time of the corresponding students;

[0158] The test scores of different teaching chapters are accumulated to obtain the total test score of the corresponding students;

[0159] Divide the total test score of the corresponding student by the total effective learning time of the corresponding student to obtain the scoring coefficient of the corresponding student;

[0160] Get the learning time of the corresponding students in the current teaching chapter;

[0161] Multiply the corresponding student's learning time in the current teaching chapter by the preset difficulty level coefficient of the current teaching chapter, and then multiply it by the corresponding student's scoring coefficient to obtain the corresponding student's learning evaluation score in the current teaching chapter.

[0162] The present invention discloses a teaching method and system based on a cloud desktop, which realizes the interaction between teachers and students through the cloud desktop, so that students can avoid the fear of facing the teacher directly; in addition, students can complete learning goals according to their own situation, turning passive learning into active learning, thereby improving students' enthusiasm for learning.

[0163] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0164] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0165] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0166] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks or optical disks, and other media that can store program codes.

[0167] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A teaching method based on cloud desktop, characterized in that: include: Obtain the teaching resource information that students apply for from the cloud desktop; Obtain students’ information; Based on the student's profile information, determine whether the teaching resource information applied by the student to the cloud desktop meets the preset regulations. If so, allow the student to use the corresponding teaching resource information; If not, the student will not be allowed to use the corresponding teaching resource information, and the appropriate teaching resource information will be matched according to the student's profile information; The appropriate teaching resource information is sent to the students for selection.

2. A cloud desktop-based teaching method according to claim 1, characterized in that: The step of judging whether the teaching resource information applied by the student to the cloud desktop meets the preset requirements based on the student's profile information specifically includes: The teaching resource information applied by the students to the cloud desktop is set as the teaching resource application information; Extract the teaching application chapters and the difficulty levels of the corresponding teaching application chapters in the teaching resource application information; According to the student's profile information, determine whether the student is logging in for the first time. If so, determine whether the teaching application chapter in the teaching resource application information is the first chapter of the corresponding subject; if so, determine whether the difficulty level of the corresponding teaching application chapter is the initial difficulty level of the corresponding teaching chapter. If so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations; If it is not the first time logging in, extract the current teaching chapter and the corresponding difficulty level of the current teaching chapter from the student's information; obtain the learning assessment score of the corresponding student in the current teaching chapter based on the student's information; determine the recommended difficulty level range of the next teaching chapter for the corresponding student based on the learning assessment score of the corresponding student in the current teaching chapter and the corresponding difficulty level of the current teaching chapter; determine whether the teaching application chapter in the teaching resource application information is the next teaching chapter of the current teaching chapter; if so, determine whether the difficulty level of the corresponding teaching application chapter is within the recommended difficulty level range, and if so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations.

3. The cloud desktop-based teaching method according to claim 2, characterized in that: The step of obtaining the learning evaluation score of the corresponding student in the current teaching chapter according to the student's information specifically includes: According to the student's information, obtain the corresponding student's study time and test score in non-current teaching chapters; Divide the learning time and test scores of the corresponding students in non-current teaching chapters according to the teaching chapters to obtain the learning time and test scores of different teaching chapters; Multiply the study time of different teaching chapters by the preset difficulty level coefficient of the corresponding teaching chapter, and then add them up to get the total effective study time of the corresponding students; The test scores of different teaching chapters are accumulated to obtain the total test score of the corresponding students; Divide the total test score of the corresponding student by the total effective learning time of the corresponding student to obtain the scoring coefficient of the corresponding student; Get the learning time of the corresponding students in the current teaching chapter; Multiply the corresponding student's learning time in the current teaching chapter by the preset difficulty level coefficient of the current teaching chapter, and then multiply it by the corresponding student's scoring coefficient to obtain the corresponding student's learning evaluation score in the current teaching chapter.

4. The cloud desktop-based teaching method according to claim 3, characterized in that: After obtaining the learning evaluation score of the corresponding student in the current teaching chapter, it also includes: Obtaining historical learning material information of other students within a preset first time period, wherein the historical learning material information at least includes the teaching chapters of historical learning, the time value of historical learning, the test scores in the process of historical learning, and the historical learning evaluation scores; According to the information of the student, the basic information and learning information of the current student are obtained, and the learning information of the current student at least includes the teaching chapter studied by the current student, the time value of the current student's study and the test score of the current student in the learning process; Compare and analyze the history learning chapters of any other student within the preset first time period with the history learning chapters of the current student. If they are the same, the history learning material information of the corresponding other student will be saved; if they are different, the history learning material information of the corresponding other student will be deleted; The difference between the historical learning time value of any other student within the preset first time period and the learning time value of the current student is calculated to obtain a first learning time difference. If the first learning time difference is less than or equal to the preset first time threshold, the historical learning data information of the corresponding other students is saved; if the first learning time difference is greater than the preset first time threshold, the historical learning data information of the corresponding other students is deleted; Calculate the difference between the test score of any other student in the historical learning process within the preset first time period and the test score of the current student to obtain a first test score difference; if the first test score difference is less than or equal to the preset first score threshold, save the historical learning data information of the corresponding other students; if the first test score difference is greater than the preset first score threshold, delete the historical learning data information of the corresponding other students; After traversing all the historical learning information of other students, obtain the historical learning information of the remaining other students; Calculate the difference between the historical learning assessment score and the test score in the historical learning process of the same student in the historical learning data information of the remaining other students to obtain the historical prediction score difference of the corresponding student; Traverse the historical learning information of all other students and obtain the historical prediction score difference set; Calculate the average value of the historical prediction score differences in the historical prediction score difference set to obtain a revised learning evaluation score; The revised value of the learning assessment score is added to the current student's learning assessment score in the current teaching chapter to obtain the revised value of the corresponding student's learning assessment score in the current teaching chapter.

5. The cloud desktop-based teaching method according to claim 2, characterized in that: The step of determining the recommended difficulty level range for the next teaching chapter for the corresponding student specifically includes: When the learning assessment score of the corresponding student in the current teaching chapter is within the preset score range, the recommended difficulty level range for the corresponding student in the next teaching chapter is the recommended difficulty level of the current teaching chapter; When the learning assessment score of the corresponding student in the current teaching chapter is less than the preset score range, the minimum value in the preset score range is extracted, and the learning assessment score of the corresponding student in the current teaching chapter is subtracted from the minimum value in the preset score range to obtain a second score difference, and the first revised value of the difficulty level of the next teaching chapter is determined according to the preset second score range in which the second score difference falls; the first revised value of the difficulty level of the next teaching chapter is subtracted from the difficulty level of the current teaching chapter to obtain the maximum value in the recommended difficulty level range for the corresponding student in the next teaching chapter, and then the first revised value of the difficulty level of the next teaching chapter is subtracted from the minimum value in the recommended difficulty level range for the corresponding student in the current teaching chapter to obtain the minimum value in the recommended difficulty level range for the corresponding student in the next teaching chapter; When the corresponding student's learning assessment score in the current teaching chapter is greater than the preset score range, the maximum value in the preset score range is extracted, and the third score difference is obtained by subtracting the maximum value in the preset score range from the corresponding student's learning assessment score in the current teaching chapter. According to the preset third score range in which the third score difference falls, the second revised value of the difficulty level of the next teaching chapter is determined; the difficulty level of the current teaching chapter is added to the second revised value of the difficulty level of the next teaching chapter to obtain the maximum value in the recommended difficulty level range for the corresponding student in the next teaching chapter, and the difficulty level of the current teaching chapter is set to the minimum value in the recommended difficulty level range for the next teaching chapter.

6. The cloud desktop-based teaching method according to claim 1, characterized in that: Also includes: Get the student's learning time and test score in the current teaching chapter; If the student's study time value in the current teaching chapter is greater than or equal to the preset study time threshold or the student's test score in the current teaching chapter is greater than or equal to the preset test score threshold, the corresponding student is allowed to apply for teaching resources for the next teaching chapter; If the student's study time value in the current teaching chapter is less than the preset study time threshold and the student's test score in the current teaching chapter is less than the preset test score threshold, the corresponding student will not be allowed to apply for teaching resources for the next teaching chapter.

7. The cloud desktop-based teaching method according to claim 6, characterized in that: Also includes: Get the current time node; According to the current time node, query the preset learning progress table to obtain the learning progress value of the current teaching chapter theory completion; Divide the student's learning time value in the current teaching chapter by the theoretical completed learning time value of the current teaching chapter to obtain the current student's actual completed learning progress value; Subtract the actual learning progress value of the current student from the theoretical learning progress value of the current teaching chapter to get the learning progress difference; If the learning progress difference is less than or equal to the preset learning progress difference threshold, the learning prompt information is triggered and sent to the corresponding student terminal.

8. A teaching system based on cloud desktop, characterized in that: The invention comprises a memory and a processor, wherein a teaching method program based on a cloud desktop is stored in the memory, and the teaching method program based on a cloud desktop is executed by the processor to implement the following steps: Obtain the teaching resource information that students apply for from the cloud desktop; Obtain students’ information; Based on the student's profile information, determine whether the teaching resource information applied by the student to the cloud desktop meets the preset regulations. If so, allow the student to use the corresponding teaching resource information; If not, the student will not be allowed to use the corresponding teaching resource information, and the appropriate teaching resource information will be matched according to the student's profile information; The appropriate teaching resource information is sent to the students for selection.

9. The cloud desktop-based teaching system according to claim 8, characterized in that: The step of judging whether the teaching resource information applied by the student to the cloud desktop meets the preset requirements based on the student's profile information specifically includes: The teaching resource information applied by the students to the cloud desktop is set as the teaching resource application information; Extract the teaching application chapters and the difficulty levels of the corresponding teaching application chapters in the teaching resource application information; According to the student's profile information, determine whether the student is logging in for the first time. If so, determine whether the teaching application chapter in the teaching resource application information is the first chapter of the corresponding subject; if so, determine whether the difficulty level of the corresponding teaching application chapter is the initial difficulty level of the corresponding teaching chapter. If so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations; If it is not the first time logging in, extract the current teaching chapter and the corresponding difficulty level of the current teaching chapter from the student's information; obtain the learning assessment score of the corresponding student in the current teaching chapter based on the student's information; determine the recommended difficulty level range of the next teaching chapter for the corresponding student based on the learning assessment score of the corresponding student in the current teaching chapter and the corresponding difficulty level of the current teaching chapter; determine whether the teaching application chapter in the teaching resource application information is the next teaching chapter of the current teaching chapter; if so, determine whether the difficulty level of the corresponding teaching application chapter is within the recommended difficulty level range, and if so, the teaching resource information applied by the student to the cloud desktop meets the preset regulations.

10. A cloud desktop-based teaching system according to claim 9, characterized in that: The step of obtaining the learning evaluation score of the corresponding student in the current teaching chapter according to the student's information specifically includes: According to the student's information, obtain the corresponding student's study time and test score in non-current teaching chapters; Divide the learning time and test scores of the corresponding students in non-current teaching chapters according to the teaching chapters to obtain the learning time and test scores of different teaching chapters; Multiply the study time of different teaching chapters by the preset difficulty level coefficient of the corresponding teaching chapter, and then add them up to get the total effective study time of the corresponding students; The test scores of different teaching chapters are accumulated to obtain the total test score of the corresponding students; Divide the total test score of the corresponding student by the total effective learning time of the corresponding student to obtain the scoring coefficient of the corresponding student; Get the learning time of the corresponding students in the current teaching chapter; Multiply the corresponding student's learning time in the current teaching chapter by the preset difficulty level coefficient of the current teaching chapter, and then multiply it by the corresponding student's scoring coefficient to obtain the corresponding student's learning evaluation score in the current teaching chapter.

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