Multimedia teaching resource management method based on data interaction

Abstract

The invention relates to the technical field of teaching management, in particular to a multimedia teaching resource management method based on data interaction, and the method comprises the steps: extracting recommended teaching data of a multimedia platform, extracting historical watching teaching data of a student account end, and extracting data coding features of the recommended teaching data and the historical watching teaching data; obtaining data coding characteristics of the recommended teaching data and the historical watching teaching data, and performing matching degree calculation based on the data coding characteristics; and obtaining a teaching theme of the recommended teaching data according to a calculation result of the matching degree, calculating a learning expectation of the student for the recommended teaching data, and judging whether the recommended teaching data is pushed to the student or not. Whether the recommended teaching data meets the expectation of the student is judged according to the learning expectation of the student on the teaching content, the operability is good, the accuracy is high, and the calculation amount is small.

Description

Background Art

[0002] With the continuous advancement of information technology, the types and quantity of multimedia teaching resources have increased dramatically, including educational materials in various forms such as text, pictures, audio, and video. These resources not only enrich the teaching content, but also improve the teaching effect and learning quality. However, how to efficiently manage and utilize these resources has become an urgent problem to be solved. The introduction of data interaction technology provides new ideas and means for the management of multimedia teaching resources. The popularization of the Internet makes the sharing and transmission of multimedia teaching resources more convenient. Through the Internet, teachers can easily obtain and share various teaching resources, and students can also access these resources anytime and anywhere for learning. Data interaction technology plays a key role in this process, making the sharing and transmission of resources more efficient, accurate and reliable.

[0003] Problems in the existing technology: There are limitations in the existing methods for pushing multimedia teaching resources. For example, when processing large-scale data sets, the cost of calculation and storage is very high; at the same time, the content-based push algorithm cannot handle the relationship between information. These limitations affect the accuracy and effect of teaching resource push and affect students' learning experience. Summary of the invention

[0004] The main purpose of the present invention is to provide a multimedia teaching resource management method based on data interaction, which effectively solves the above-mentioned problems mentioned in the background technology.

[0005] The technical solution of the present invention is as follows:

[0006] A multimedia teaching resource management method based on data interaction is proposed, which includes the following steps:

[0007] S1. Extract the recommended teaching data from the multimedia platform, and at the same time extract the historical viewing teaching data from the student account, and extract the data encoding features of the recommended teaching data and the historical viewing teaching data;

[0008] S2, obtaining data encoding features of recommended teaching data and historically viewed teaching data, and performing matching calculation based on the data encoding features;

[0009] S3. According to the calculation result of the matching, the teaching topic of the recommended teaching data is obtained, the student's learning expectation for the recommended teaching data is calculated, and it is determined whether to push the recommended teaching data to the student.

[0010] A further improvement of the present invention is that S1 comprises the following specific steps:

[0011] S11, extracting the recommended teaching data of the multimedia platform, and extracting the historical viewing teaching data of the student account end, and encoding them using the LZ77 encoding technology to obtain the data encoding of the recommended teaching data of the multimedia platform and the historical viewing teaching data of the student account end;

[0012] S12. According to the sentence positions in the recommended teaching data and the historical viewing teaching data, the obtained data codes are segmented to form a recommended teaching data code segment set A and a historical viewing teaching data code segment set B, and different code segment sets C and identical code segment sets D are extracted from the recommended teaching data code segment set A and the historical viewing teaching data code segment set B, wherein the different code segment set C is the intersection of a set of code segments with different codes in the recommended teaching data code segment set A and the historical viewing teaching data code segment set B and the historical viewing teaching data code segment set B, and the identical code segment set D is the intersection of a set of code segments with the same codes in the recommended teaching data code segment set A and the historical viewing teaching data code segment set B and the historical viewing teaching data code segment set B.

[0013] A further improvement of the present invention is that S2 comprises the following specific steps:

[0014] S21, extracting different coding segment sets C and the same coding segment set D from the recommended teaching data coding segment set A and the historical viewing teaching data coding segment set B, and extracting the number of occurrences of a single element in the different coding segment set C and the same coding segment set D in the historical viewing teaching data of the user;

[0015] S22, substituting all elements in the recommended teaching data coding segment set A and all elements in the different coding segment set C and the same coding segment set D into the matching calculation formula, respectively calculating the matching of all elements of the recommended teaching data with the different coding segment set C and the same coding segment set D, the calculation formula is: where p1 i is the compatibility between element i in the recommended teaching data coding segment set A and different coding segment sets C, longc j is the length of the jth element in the different coding segment sets C, n is the number of elements in the different coding segment sets C, a i is the i-th element in the recommended teaching data coding segment set A, c j is the jth element in the set C of different coding segments, p2 i is the matching degree between element i in the recommended teaching data coding segment set A and the same coding segment set D, longd j is the jth element in the same coding segment set D, m is the number of elements in the same coding segment set D, d jis the jth element in the same coding segment set C.

[0016] A further improvement of the present invention is that the S2 further includes calculating the comprehensive compatibility of a single element in the recommended teaching data coding segment set A with elements in different coding segment sets C and the same coding segment set D, and the formula is: i =0.372p1 i +0.628p2 i , Pi is the comprehensive matching degree between the i-th element in the recommended teaching data coding segment set A and the historical viewing teaching data coding segment set B.

[0017] A further improvement of the present invention is that the specific content of obtaining the teaching theme of the recommended teaching data in S3 is: extracting the comprehensive compatibility of all elements in the recommended teaching data coding segment set A with the elements in different coding segment sets C and the same coding segment set D; arranging all elements in the recommended teaching data coding segment set A in descending order according to the size of the comprehensive compatibility, and taking the data coding segment of the first element in the sequence obtained after the arrangement as the teaching theme of the recommended teaching data.

[0018] A further improvement of the present invention is that S3 further includes:

[0019] S31, extracting the number of times the teaching topic of the recommended teaching data appears in the historical teaching data watched by the student, including the number of times it appears in the past week and the number of times it appears on the current day;

[0020] S32. Calculate students’ learning expectations for the recommended teaching data in the past week. The learning expectation calculation formula is: Among them, q1 is the student's learning expectation for the recommended teaching data in the past week, c is the number of times the teaching topic of the recommended teaching data appears in the student's historical viewing teaching data in the past week, and n is the total number of times all different teaching topics appear in the student's historical viewing teaching data in the past week;

[0021] S33 calculates the student's learning expectations for the recommended teaching data on that day. The learning expectation calculation formula is: Among them, q2 is the student's learning expectation for the recommended teaching data on that day, C is the number of times the teaching topic of the recommended teaching data information appears in the student's historical viewing teaching data on that day, and N is the total number of times all different teaching topics appear in the student's historical viewing teaching data on that day;

[0022] S34. When the sum of the student's learning expectations for the recommended teaching data in the past week and the student's learning expectations for the recommended teaching data on the current day is greater than the learning expectation threshold, the recommended teaching data is pushed to the student.

[0023] The technical effects of the present invention are as follows:

[0024] A multimedia teaching resource management method based on data interaction is constructed. The invention extracts the recommended teaching data of the multimedia platform and the historical viewing teaching data of the student account at the same time, extracts the data coding features of the recommended teaching data and the historical viewing teaching data; obtains the data coding features of the recommended teaching data and the historical viewing teaching data, and calculates the degree of matching based on the data coding features; obtains the teaching subject of the recommended teaching data according to the calculation result of the degree of matching, calculates the student's learning expectation for the recommended teaching data, and determines whether to push the recommended teaching data to the student. The invention determines whether the recommended teaching data meets the student's expectations based on the student's personal learning expectation for the teaching content, and has good operability, high accuracy, and low calculation amount. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0026] Figure 1 It is a flow chart of the multimedia teaching resource management method based on data interaction of the present invention. DETAILED DESCRIPTION

[0027] The present invention aims to propose a multimedia teaching resource management method based on data interaction, by extracting the recommended teaching data of the multimedia platform, and extracting the historical viewing teaching data of the student account end at the same time, extracting the data coding features of the recommended teaching data and the historical viewing teaching data; obtaining the data coding features of the recommended teaching data and the historical viewing teaching data, and calculating the degree of matching based on the data coding features; according to the calculation result of the degree of matching, obtaining the teaching subject of the recommended teaching data, calculating the student's learning expectations for the recommended teaching data, and judging whether to push the recommended teaching data to the student. Judging whether the recommended teaching data meets the student's expectations based on the student's personal learning expectations for the teaching content, the method has good operability, high accuracy, and low calculation amount.

[0028] Embodiment 1:

[0029] This embodiment proposes a multimedia teaching resource management method based on data interaction, such as Figure 1 As shown, the specific steps include:

[0030] S1. Extract the recommended teaching data from the multimedia platform, and at the same time extract the historical viewing teaching data from the student account, and extract the data encoding features of the recommended teaching data and the historical viewing teaching data;

[0031] S2, obtaining data encoding features of recommended teaching data and historically viewed teaching data, and performing matching calculation based on the data encoding features;

[0032] S3. According to the calculation result of the matching, the teaching topic of the recommended teaching data is obtained, the student's learning expectation for the recommended teaching data is calculated, and it is determined whether to push the recommended teaching data to the student.

[0033] In this embodiment, S1 includes the following specific steps:

[0034] S11, extracting the recommended teaching data of the multimedia platform, and extracting the historical viewing teaching data of the student account end, and encoding them using the LZ77 encoding technology to obtain the data encoding of the recommended teaching data of the multimedia platform and the historical viewing teaching data of the student account end;

[0035] S12. According to the sentence positions in the recommended teaching data and the historical viewing teaching data, the obtained data codes are segmented to form a recommended teaching data code segment set A and a historical viewing teaching data code segment set B, and different code segment sets C and identical code segment sets D are extracted from the recommended teaching data code segment set A and the historical viewing teaching data code segment set B, wherein the different code segment set C is the intersection of a set of code segments with different codes in the recommended teaching data code segment set A and the historical viewing teaching data code segment set B and the historical viewing teaching data code segment set B, and the identical code segment set D is the intersection of a set of code segments with the same codes in the recommended teaching data code segment set A and the historical viewing teaching data code segment set B and the historical viewing teaching data code segment set B.

[0036] In this embodiment, S2 includes the following specific steps:

[0037] S21, extracting different coding segment sets C and the same coding segment set D from the recommended teaching data coding segment set A and the historical viewing teaching data coding segment set B, and extracting the number of occurrences of a single element in the different coding segment set C and the same coding segment set D in the historical viewing teaching data of the user;

[0038] S22, substituting all elements in the recommended teaching data coding segment set A and all elements in the different coding segment set C and the same coding segment set D into the matching calculation formula, respectively calculating the matching of all elements of the recommended teaching data with the different coding segment set C and the same coding segment set D, the calculation formula is: where p1 i is the compatibility between element i in the recommended teaching data coding segment set A and different coding segment sets C, longc j is the length of the jth element in the different coding segment sets C, n is the number of elements in the different coding segment sets C, a i is the i-th element in the recommended teaching data coding segment set A, c jis the jth element in the set C of different coding segments, p2 i is the matching degree between element i in the recommended teaching data coding segment set A and the same coding segment set D, longd j is the jth element in the same coding segment set D, m is the number of elements in the same coding segment set D, d j is the jth element in the same coding segment set C.

[0039] In this embodiment, S2 also includes calculating the comprehensive compatibility of a single element in the recommended teaching data coding segment set A with elements in different coding segment sets C and the same coding segment set D, and the formula is: i =0.372p1 i +0.628p2 i , Pi is the comprehensive matching degree between the i-th element in the recommended teaching data coding segment set A and the historical viewing teaching data coding segment set B.

[0040] In this embodiment, the specific content of obtaining the teaching topic of the recommended teaching data in S3 is: extracting the comprehensive compatibility of all elements in the recommended teaching data coding segment set A with the elements in different coding segment sets C and the same coding segment set D; arranging all elements in the recommended teaching data coding segment set A in descending order according to the size of the comprehensive compatibility, and taking the data coding segment of the first element in the sequence obtained after the arrangement as the teaching topic of the recommended teaching data.

[0041] In this embodiment, S3 further includes:

[0042] S31, extracting the number of times the teaching topic of the recommended teaching data appears in the historical teaching data watched by the student, including the number of times it appears in the past week and the number of times it appears on the current day;

[0043] S32. Calculate students’ learning expectations for the recommended teaching data in the past week. The learning expectation calculation formula is: Among them, q1 is the student's learning expectation for the recommended teaching data in the past week, c is the number of times the teaching topic of the recommended teaching data appears in the student's historical viewing teaching data in the past week, and n is the total number of times all different teaching topics appear in the student's historical viewing teaching data in the past week;

[0044] S33 calculates the student's learning expectations for the recommended teaching data on that day. The learning expectation calculation formula is: Among them, q2 is the student's learning expectation for the recommended teaching data on that day, C is the number of times the teaching topic of the recommended teaching data information appears in the student's historical viewing teaching data on that day, and N is the total number of times all different teaching topics appear in the student's historical viewing teaching data on that day;

[0045] S34. When the sum of the student's learning expectations for the recommended teaching data in the past week and the student's learning expectations for the recommended teaching data on the current day is greater than the learning expectation threshold, the recommended teaching data is pushed to the student.

[0046] Embodiment 2:

[0047] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; the processor executes the above-mentioned multimedia teaching resource management method based on data interaction by calling the computer program stored in the memory.

[0048] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein at least one computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement the multimedia teaching resource management method based on data interaction provided by the above method embodiment. The electronic device may also include other components for realizing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface, so as to input and output data. This embodiment will not be described in detail here.

[0049] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present disclosure can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), and it can also be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0050] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0051] The present invention is described with reference to flowcharts and block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process or block in the flowchart and block diagram, as well as the combination of processes and blocks in the flowchart or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts. Figure 1 Process or multiple processes and boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0052] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 Process or multiple processes and boxes Figure 1 The steps for the functions specified in one or more boxes.

[0053] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

Claims

1. A multimedia teaching resource management method based on data interaction, characterized in that: The specific steps include: S1. Extract the recommended teaching data from the multimedia platform, and at the same time extract the historical viewing teaching data from the student account, and extract the data encoding features of the recommended teaching data and the historical viewing teaching data; S2, obtaining data encoding features of recommended teaching data and historically viewed teaching data, and performing matching calculation based on the data encoding features; S3. According to the calculation result of the matching, the teaching topic of the recommended teaching data is obtained, the student's learning expectation for the recommended teaching data is calculated, and it is determined whether to push the recommended teaching data to the student.

2. The multimedia teaching resource management method based on data interaction according to claim 1 is characterized in that: The S1 comprises the following specific steps: S11, extracting the recommended teaching data of the multimedia platform, and extracting the historical viewing teaching data of the student account end, and encoding them using the LZ77 encoding technology to obtain the data encoding of the recommended teaching data of the multimedia platform and the historical viewing teaching data of the student account end; S12. According to the sentence positions in the recommended teaching data and the historical viewing teaching data, the obtained data codes are segmented to form a recommended teaching data code segment set A and a historical viewing teaching data code segment set B, and different code segment sets C and identical code segment sets D are extracted from the recommended teaching data code segment set A and the historical viewing teaching data code segment set B, wherein the different code segment set C is the intersection of a set of code segments with different codes in the recommended teaching data code segment set A and the historical viewing teaching data code segment set B and the historical viewing teaching data code segment set B, and the identical code segment set D is the intersection of a set of code segments with the same codes in the recommended teaching data code segment set A and the historical viewing teaching data code segment set B and the historical viewing teaching data code segment set B.

3. The multimedia teaching resource management method based on data interaction according to claim 2 is characterized in that: The S2 comprises the following specific steps: S21, extracting different coding segment sets C and the same coding segment set D from the recommended teaching data coding segment set A and the historical viewing teaching data coding segment set B, and extracting the number of occurrences of a single element in the different coding segment set C and the same coding segment set D in the historical viewing teaching data of the user; S22, substituting all elements in the recommended teaching data coding segment set A and all elements in the different coding segment set C and the same coding segment set D into the matching calculation formula, respectively calculating the matching of all elements of the recommended teaching data with the different coding segment set C and the same coding segment set D, the calculation formula is: where p1 i is the compatibility between element i in the recommended teaching data coding segment set A and different coding segment sets C, longc j is the length of the jth element in the different coding segment sets C, n is the number of elements in the different coding segment sets C, a i is the i-th element in the recommended teaching data coding segment set A, c j is the jth element in the set C of different coding segments, p2 i is the matching degree between element i in the recommended teaching data coding segment set A and the same coding segment set D, longd j is the jth element in the same coding segment set D, m is the number of elements in the same coding segment set D, d j is the jth element in the same coding segment set C.

4. The multimedia teaching resource management method based on data interaction according to claim 3 is characterized in that: The S2 also includes calculating the comprehensive matching degree between a single element in the recommended teaching data coding segment set A and elements in different coding segment sets C and the same coding segment set D, the formula is: i =0.372p1 i +0.628p2 i , Pi is the comprehensive matching degree between the i-th element in the recommended teaching data coding segment set A and the historical viewing teaching data coding segment set B.

5. The multimedia teaching resource management method based on data interaction according to claim 4 is characterized in that: The specific content of obtaining the teaching topic of the recommended teaching data in S3 is: extracting the comprehensive compatibility of all elements in the recommended teaching data coding segment set A with the elements in different coding segment sets C and the same coding segment set D; arranging all elements in the recommended teaching data coding segment set A in descending order according to the size of the comprehensive compatibility, and taking the data coding segment of the first element in the sequence obtained after the arrangement as the teaching topic of the recommended teaching data.

6. The multimedia teaching resource management method based on data interaction according to claim 5 is characterized in that: The S3 further includes: S31, extracting the number of times the teaching topic of the recommended teaching data appears in the historical teaching data watched by the student, including the number of times it appears in the past week and the number of times it appears on the current day; S32. Calculate students’ learning expectations for the recommended teaching data in the past week. The learning expectation calculation formula is: Among them, q1 is the student's learning expectation for the recommended teaching data in the past week, c is the number of times the teaching topic of the recommended teaching data appears in the student's historical viewing teaching data in the past week, and n is the total number of times all different teaching topics appear in the student's historical viewing teaching data in the past week; S33 calculates the student's learning expectations for the recommended teaching data on that day. The learning expectation calculation formula is: Among them, q2 is the student's learning expectation for the recommended teaching data on that day, C is the number of times the teaching topic of the recommended teaching data information appears in the student's historical viewing teaching data on that day, and N is the total number of times all different teaching topics appear in the student's historical viewing teaching data on that day; S34. When the sum of the student's learning expectations for the recommended teaching data in the past week and the student's learning expectations for the recommended teaching data on the current day is greater than the learning expectation threshold, the recommended teaching data is pushed to the student.

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