A digital-based teaching resource sharing system and method

Abstract

The application discloses a kind of teaching resource sharing system and method based on digitization, it is related to educational resource sharing technical field;The present application carries out multidimensional evaluation to the prepared resource before recommendation, extracts user evaluation data to determine user feedback index, considers the feedback of user to teaching resource;Obtain the user reliable index of uploader information, evaluate the reliability of resource creator;Calculate resource time limit index, guarantee the timeliness of recommended resource, this makes evaluation more comprehensive, provide basis for personalized recommendation, and consider the feedback approval preference of user, uploader approval preference and content timeliness preference, calculate the sharing evaluation index of teaching resource according to different preference, and according to sharing evaluation index, the push of teaching resource is carried out to user, solve the problem that user feedback data and uploader data etc. in prior art are not fully considered, and the personalized needs of user cannot be met.

Description

Technical Field

[0001] This invention relates to the field of educational resource sharing technology, specifically to a digital teaching resource sharing system and method. Background Technology

[0002] With the rapid development of information technology, the education field is also undergoing continuous digital transformation. Traditional teaching models rely on limited textbooks and individual teachers' knowledge reserves, resulting in relatively scarce teaching resources that are difficult to share widely.

[0003] However, existing teaching resource sharing systems still have the following shortcomings in practical applications:

[0004] The recommendation function of existing teaching resource sharing systems is relatively simple, mainly based on users' search history or popular resources. It does not fully consider user feedback data and uploader data of teaching resources, and cannot meet users' personalized needs.

[0005] In addition, existing sharing platforms lack sufficient incentives for users to participate in resource sharing, failing to fully mobilize users' enthusiasm. Users who upload high-quality resources do not receive enough recognition and rewards, resulting in many users lacking the motivation to share.

[0006] To address this, a digital-based teaching resource sharing system and method are proposed. Summary of the Invention

[0007] The purpose of this invention is to address the problems mentioned in the background art by proposing a digital teaching resource sharing system and method.

[0008] The objective of this invention can be achieved through the following technical solution: a digital-based teaching resource sharing system, comprising:

[0009] Resource Management Module: Identifies the teaching resources uploaded by users, identifies the subject, grade, and teaching type of the teaching resources, and categorizes them into the corresponding storage areas; teaching types include courseware, videos, and documents;

[0010] Resource recommendation module: After the user enters the subject, grade and teaching type of the required teaching resources, a search signal is triggered to extract each group of teaching resources that meet the user's input requirements and record them as reserve resources. After the resource evaluation of each group of reserve resources is processed, they are pushed to the user. After the push is completed, the user selects the teaching resources he / she needs from each group of reserve resources. After the selection is completed, the download count of the corresponding teaching resource is incremented by one.

[0011] Shared Incentive Module: A user incentive mechanism is pre-built, and the user's shared activity value is updated in real time according to the user incentive mechanism. When the user's shared activity value reaches the corresponding set reference value, a redemption signal is triggered and pushed to the user.

[0012] As a preferred embodiment of the present invention, the specific steps of the resource assessment process are as follows:

[0013] User evaluation data for each group of preparatory resources was extracted and keyword matching was performed to determine the user feedback index Uy for each group of preparatory resources.

[0014] Obtain the user type, number of uploaded resources, and number of downloads of the uploaders corresponding to each group of preparatory resources, and determine the user reliability index Ut of each group of preparatory resources after processing;

[0015] Extract the time of the most recent update of each group of reserve resources from the current time point, and calculate the time difference between the most recent update time and the current time point to obtain the resource timeliness index Ur of each group of reserve resources;

[0016] The user feedback index Uy, user reliability index Ut, and resource timeliness index Ur of each group of preparatory resources are obtained and pushed to the user. After the user determines their preferences, the resources are further evaluated and pushed to the user. Preferences include feedback approval preference, uploader approval preference, and content timeliness preference, and are represented by numbers a, b, and c.

[0017] Based on the preferences determined by the users, the user feedback index Uy, user reliability index Ut, and resource timeliness index Ur of each group of preparatory resources are substituted into the corresponding formulas for weighted calculation to obtain the shared evaluation index Ue of each group of preparatory resources.

[0018] Extract the shared evaluation index Ue of each group of preparatory resources, and sort the preparatory resources of each group from largest to smallest according to the size of the shared evaluation index Ue. After sorting, push the results to the user.

[0019] In a preferred embodiment of the present invention, the user feedback index Uy of each group of preparatory resources is determined as follows:

[0020] Preset each set of keywords corresponding to user comments, input each set of keywords into the user comment data in each set of preparatory resources for matching. If a set of user comment data in a preparatory resource successfully matches a preset keyword, the experience score of the corresponding preparatory resource is incremented by one. After the matching is completed, the final experience score of each set of preparatory resources is obtained and recorded as the number of times the user is satisfied.

[0021] Count the number of shares and the number of users commenting on each group of preparatory resources; calculate the percentage of satisfaction and sharing counts for each group of preparatory resources in the total number of users commenting, thus obtaining the satisfaction ratio and sharing ratio for each group of preparatory resources;

[0022] The satisfaction ratio and sharing ratio of each group of preparatory resources are multiplied by the corresponding set weight coefficients, and then summed to obtain the user feedback index Uy of each group of preparatory resources.

[0023] In a preferred embodiment of the present invention, the user reliability index Ut of each group of preparatory resources is determined as follows:

[0024] Obtain the user type of the uploader corresponding to each group of preparatory resources, including education experts, senior teachers, and in-service teachers; set a basic quality score for each user type to determine the basic quality score of each group of preparatory resources;

[0025] The number of uploaded resources and downloads by each group of resource uploaders are counted and formed into data pairs. The intervals corresponding to each data pair are preset, and each data pair interval corresponds to a value-added coefficient. The interval of each data pair includes a range of uploaded resource quantity and a range of download quantity. The data pairs of each group of resource uploaders are matched with the intervals of each data pair to determine the value-added coefficient of each group of resource uploaders.

[0026] Multiply the base value score of each group of preparatory resources by the corresponding value addition coefficient to obtain the user reliability index Ut of each group of preparatory resources.

[0027] In a preferred embodiment of the present invention, the shared evaluation index Ue of each group of preparatory resources is obtained as follows:

[0028] The formula is expressed as Uy 及格 、Ut 及格 Ur 参考 These are the preset passing feedback index, passing reliability index, and reference timeliness index, respectively; α1, α2, and α3 are the weighting factors affecting the user feedback index Uy, user reliability index Ut, and resource timeliness index Ur under the user's determined feedback approval preference; β1, β2, and β3 are the weighting factors affecting the user feedback index Uy, user reliability index Ut, and resource timeliness index Ur under the user's determined uploader approval preference; η1, η2, and η3 are the weighting factors affecting the user feedback index Uy, user reliability index Ut, and resource timeliness index Ur under the user's determined content timeliness preference.

[0029] As a preferred embodiment of the present invention, the process of constructing the user incentive mechanism is as follows:

[0030] Various incentive behaviors are pre-set, including resource uploading, resource downloading, user rating, and resource sharing;

[0031] The number of various incentive behaviors of users within a set time window is counted, and corresponding weight coefficients are set. The number of various incentive behaviors of users within the set time window is multiplied by the corresponding weight coefficients, and then the sum is obtained to obtain the user's activity evaluation index within the set time window.

[0032] The system presets four index ranges corresponding to the activity assessment index, and sets an activity level for each index range. The activity levels include Bronze, Silver, Gold, and Diamond, and each activity level corresponds to a set of activity reward points. After determining the user's activity level, the corresponding activity reward points are added to the user's current shared activity value and then updated.

[0033] In a preferred embodiment of the present invention, the process of constructing the user incentive mechanism further includes:

[0034] Obtain the user feedback index Uy of the teaching resources uploaded by the user within the set time window, set the value range of each group of indexes corresponding to the user feedback index Uy, and set a resource contribution score for each group of indexes; determine the resource contribution score of the teaching resources uploaded by the user within the set time window, add the corresponding resource contribution score to the user's current shared activity value and update it.

[0035] In a preferred embodiment of the present invention, if the number of teaching resources uploaded by a user is greater than one, the resource contribution score of each group of teaching resources uploaded within the set time window is determined and accumulated, and the accumulated value is added to the user's current shared activity value and then updated.

[0036] A digital-based method for sharing teaching resources includes:

[0037] Resource Management: After users complete registration and upload teaching resources, the system identifies the uploaded teaching resources, determines their corresponding subject, grade, and teaching type, and categorizes them into the corresponding storage areas.

[0038] Resource Recommendation: After the user enters the subject, grade and teaching type of the required teaching resources, a search signal is triggered to extract each group of teaching resources that meet the user's input requirements and record them as reserve resources. After the resource evaluation of each group of reserve resources is processed, they are pushed to the user. After the push is completed, the user selects the teaching resources he / she needs from each group of reserve resources.

[0039] User Incentives: A user incentive mechanism is pre-built, and the user's shared activity value is updated in real time according to the user incentive mechanism. When the user's shared activity value reaches the corresponding set reference value, a redemption signal is triggered and pushed to the user.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] This invention conducts multi-dimensional evaluations of preparatory resources before recommendation, extracts user evaluation data to determine a user feedback index, considers user feedback on teaching resources, obtains uploader information to derive a user reliability index, assesses the reliability of resource creators, and calculates a resource timeliness index to ensure the timeliness of recommended resources. This makes the evaluation more comprehensive, provides a basis for personalized recommendations, and considers user feedback approval preferences, uploader approval preferences, and content timeliness preferences. Based on different preferences, a shared evaluation index of teaching resources is calculated, and teaching resources are pushed to users based on the shared evaluation index. This solves the problem in existing technologies that do not fully consider user feedback data and uploader data of teaching resources, and thus cannot meet users' personalized needs.

[0042] This invention allows users to change their preferences after receiving recommendation results and push them again. If users are not satisfied with the current recommendations, they can adjust their preferences, recalculate the shared evaluation index, and push the recommendations in a different order, ensuring that the recommendation results better meet the user's needs.

[0043] This invention triggers a redemption signal when a user's shared activity value reaches a set reference value, reminding the user to redeem goods, allowing users to truly feel the value of participating in resource sharing and maintain their enthusiasm. Attached Figure Description

[0044] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0045] Figure 1 This is a schematic diagram of the principle of the present invention;

[0046] Figure 2 This is a flowchart of the present invention. Detailed Implementation

[0047] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Example 1

[0049] Please see Figure 1 As shown, a digital teaching resource sharing system includes a resource management module, a resource recommendation module, and a sharing incentive module.

[0050] The resource management module is used to identify the teaching resources uploaded by users, identify the subject, grade, and teaching type of the teaching resources, and classify them into the corresponding storage areas; teaching types include courseware, videos, and documents;

[0051] It should be noted that after classification, natural language processing technology can be used to automatically label teaching resources and extract keywords, making it convenient for users to quickly search and determine the subject (such as Chinese, mathematics, physics, etc.), grade (lower elementary, upper elementary, junior high, senior high, etc.), and teaching type (courseware, video, document) of the resources, and store them in the corresponding areas. This classification and storage method is similar to the partitioning of different categories of books in a library, which greatly improves the orderliness of resource management and facilitates subsequent retrieval and access.

[0052] For teaching resources uploaded by users, they are first evaluated by reviewers. Once the evaluation is passed, they are then identified and categorized. A resource update interval is set, and expired or invalid resources are deleted after the set interval is reached. For example, some courseware accompanying older versions of textbooks becomes inapplicable as the textbooks are updated, and will be deleted when the update interval is reached. At the same time, users are encouraged to upload the latest teaching resources to maintain the timeliness and practicality of the resource library, ensuring that users always have access to the latest and most useful teaching materials.

[0053] The resource recommendation module is used to trigger a search signal after the user enters the subject, grade and teaching type of the required teaching resources. It extracts each group of teaching resources that meet the user's input requirements and records them as reserve resources. After the resource evaluation of each group of reserve resources is processed, they are pushed to the user. After the push is completed, the user selects the teaching resources he / she needs from each group of reserve resources. After the selection is completed, the download count of the corresponding teaching resource is incremented by one.

[0054] The specific steps of resource assessment and processing are as follows:

[0055] Preset keywords for each set of user reviews; keywords include strong practicality, rich examples, and clear content; input the preset keywords into the user review data of each set of preparatory resources for matching. If a set of user review data of a preparatory resource successfully matches a preset keyword, the experience score of the corresponding preparatory resource is incremented by one. After the matching is completed, obtain the final experience score of each set of preparatory resources and record it as the number of times you are satisfied.

[0056] It should be noted that if the number of keywords matching the content of a group of user reviews exceeds one, the experience score will still be increased by one to avoid data inaccuracy caused by a group of users manipulating reviews.

[0057] Count the number of shares and the number of users commenting on each group of preparatory resources; calculate the percentage of satisfaction and sharing counts for each group of preparatory resources in the total number of users commenting, thus obtaining the satisfaction ratio and sharing ratio for each group of preparatory resources;

[0058] The satisfaction ratio and sharing ratio of each group of preparatory resources are multiplied by the corresponding set weight coefficients, and then summed to obtain the user feedback index Uy of each group of preparatory resources;

[0059] It should be noted that by pre-setting keywords related to user experience and matching them with user review data, valuable information can be extracted from actual user feedback, and users' experience with teaching resources can be objectively evaluated. The experience rating setting allows the performance of resources in terms of user experience to be quantified, avoiding the limitations of subjective judgment, and enabling users to more accurately understand their satisfaction with resources when selecting them.

[0060] Obtain the user type of the uploader corresponding to each group of preparatory resources, including education experts, senior teachers, and in-service teachers; set a basic quality score for each user type; the basic quality score of education experts > the basic quality score of senior teachers > the basic quality score of in-service teachers; thus determine the basic quality score of each group of preparatory resources.

[0061] The number of uploaded resources and downloads by each group of resource uploaders are counted and formed into data pairs. Each data pair is assigned a corresponding interval, and each interval corresponds to a value-added coefficient. The value-added coefficient ranges from 0.975 to 1.118. The data pairs of each group of resource uploaders are matched with their respective intervals to determine the value-added coefficient for each group of resource uploaders.

[0062] Multiply the base value score of each group of pre-reserved resources by the corresponding value addition coefficient to obtain the user reliability index Ut of each group of pre-reserved resources;

[0063] It should be noted that by calculating and applying the user reliability index, teaching resources can be better managed and organized, and high-quality resources can be pushed to users more accurately. For users, it is easier to find resources from reliable creators and that are popular, thereby improving learning and teaching efficiency.

[0064] Extract the time of the most recent update of each group of reserve resources from the current time point, and calculate the time difference between the most recent update time and the current time point to obtain the resource timeliness index Ur of each group of reserve resources;

[0065] It should be noted that newer teaching resources are more closely aligned with actual educational situations;

[0066] The user feedback index Uy, user reliability index Ut, and resource timeliness index Ur of each group of preparatory resources are obtained and pushed to the user. After the user determines their preferences, the resources are further evaluated and pushed to the user. Preferences include feedback approval preference, uploader approval preference, and content timeliness preference, and are represented by numbers a, b, and c.

[0067] Based on the preferences determined by the users, the user feedback index Uy, user reliability index Ut, and resource timeliness index Ur of each group of preparatory resources are substituted into the corresponding formulas for weighted calculation to obtain the shared evaluation index Ue of each group of preparatory resources.

[0068] The formula is expressed as Uy 及格 、Ut 及格 Ur 参考 These are the preset passing feedback index, passing reliability index, and reference timeliness index, respectively; α1, α2, and α3 are the weighting factors affecting the user feedback index Uy, user reliability index Ut, and resource timeliness index Ur under the user's determined feedback approval preference; β1, β2, and β3 are the weighting factors affecting the user feedback index Uy, user reliability index Ut, and resource timeliness index Ur under the user's determined uploader approval preference; η1, η2, and η3 are the weighting factors affecting the user feedback index Uy, user reliability index Ut, and resource timeliness index Ur under the user's determined content timeliness preference;

[0069] It should be noted that by taking into account different user preferences and using different weighting factors to calculate the corresponding index, the subsequent push results of teaching resources can be generated according to the user's personalized preferences.

[0070] For example, for users who value feedback from other users (feedback approval preference), the user feedback index will be given a higher weight when calculating the sharing evaluation index, and teaching resources that perform well in this aspect will be recommended first; while for users who value the qualifications of resource creators (uploader approval preference), the role of the user reliability index will be highlighted. This personalized evaluation method can better meet the diverse needs of users and improve user satisfaction with resources.

[0071] Extract the shared evaluation index Ue of each group of preparatory resources, and sort the preparatory resources of each group from largest to smallest according to the size of the shared evaluation index Ue. After sorting, push the results to the user.

[0072] It should be noted that after receiving the push notification, users can go back to the previous step to change their preferences and then receive a new notification.

[0073] The shared incentive module is used to pre-build a user incentive mechanism and update the user's shared activity value in real time according to the user incentive mechanism; the shared activity value is initially 0 after registration; when the user's shared activity value reaches the corresponding set reference value, a redemption signal is triggered and pushed to the user;

[0074] It should be noted that triggering the redemption signal indicates that the user's shared activity value can be used to redeem some items, reminding the user to redeem them in time.

[0075] The process of building a user incentive mechanism is as follows:

[0076] Various incentive behaviors are pre-set, including resource uploading, resource downloading, user rating, and resource sharing;

[0077] The number of various incentive behaviors of users within a set time window is counted, and corresponding weight coefficients are set. The number of various incentive behaviors of users within the set time window is multiplied by the corresponding weight coefficients, and then the sum is obtained to obtain the user's activity evaluation index within the set time window.

[0078] The system presets four index ranges corresponding to the activity assessment index, and assigns an activity level to each index range. The activity levels include Bronze, Silver, Gold, and Diamond, with a higher activity assessment index increasing the likelihood of reaching the Diamond activity level. Each activity level corresponds to a set of activity reward points, which can be set to 2, 4, 6, or 8. After determining a user's activity level, the corresponding activity reward points are added to the user's current shared activity value and then updated.

[0079] It should be noted that various incentive mechanisms, such as resource uploading, resource downloading, user reviews, and resource sharing, are clearly set up so that users know how to earn rewards. This encourages users to participate more in the sharing of teaching resources. In order to earn more activity reward points, users will be more proactive in uploading high-quality teaching resources, increasing the richness of the resources; or they will carefully review the resources they have used, providing references for other users, and at the same time improving the quality of the platform's resources.

[0080] Get the user feedback index Uy of the teaching resources uploaded by users within a set time window, set the value range of each group of indexes corresponding to the user feedback index Uy, and set each group of indexes to correspond to a resource contribution point; the resource contribution point range is set from 1 to 10, and the higher the user feedback index Uy, the higher the resource contribution point will be.

[0081] Determine the resource contribution points of the teaching resources uploaded by the user within the set time window, add the corresponding resource contribution points to the user's current shared activity value and update it;

[0082] If a user uploads more than one set of teaching resources, the resource contribution score of each set of teaching resources uploaded within the set time window is determined and accumulated. The accumulated value is then added to the user's current shared activity value and updated.

[0083] It should be noted that the user feedback index Uy is obtained by obtaining the user feedback index of teaching resources uploaded by users within a set time window. In the process of calculating the user feedback index Uy, only the user evaluation data and user analysis data newly added within the set time window are considered.

[0084] The quality of teaching resources uploaded by users is measured by a user feedback index, and corresponding resource contribution points are awarded based on this index. The higher the user feedback index, the more resource contribution points are awarded. This motivates users to strive to upload high-quality, practical teaching resources that can meet the needs of other users in order to obtain higher points, thus ensuring the quality of teaching resource sharing. This encourages users to spend more time and energy to improve courseware content and optimize the way teaching videos are presented, thereby improving the overall quality of teaching resources.

[0085] Example 2

[0086] Please see Figure 2 As shown, Embodiment 1 of this application provides a digital teaching resource sharing system, and Embodiment 2 of this application proposes a digital teaching resource sharing method. Embodiment 2 is merely a preferred embodiment of Embodiment 1, and its implementation will not affect the individual implementation of Embodiment 1.

[0087] Specifically, the difference in the digital-based teaching resource sharing method provided in Embodiment 2 of this application lies in that it includes:

[0088] Resource Management: After users complete registration and upload teaching resources, the system identifies the uploaded teaching resources, determines their corresponding subject, grade, and teaching type, and categorizes them into the corresponding storage areas.

[0089] Resource Recommendation: After the user enters the subject, grade and teaching type of the required teaching resources, a search signal is triggered to extract each group of teaching resources that meet the user's input requirements and record them as reserve resources. After the resource evaluation of each group of reserve resources is processed, they are pushed to the user. After the push is completed, the user selects the teaching resources he / she needs from each group of reserve resources.

[0090] User Incentives: A user incentive mechanism is pre-built, and the user's shared activity value is updated in real time according to the user incentive mechanism. When the user's shared activity value reaches the corresponding set reference value, a redemption signal is triggered and pushed to the user.

[0091] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A digitization-based teaching resource sharing system, characterized by, Comprise: Resource management module: identify the user uploaded teaching resources, identify the subject, grade and teaching type corresponding to the teaching resources and classified into the corresponding storage area; teaching type includes courseware, video and documents; Resource recommendation module: after the user inputs the required teaching resources of the subject, grade and teaching type, trigger retrieval signaling, extract each group of teaching resources that meet the user input requirements as preliminary resources, and push the preliminary resources to the user after resource evaluation processing, after the completion of the push, the user selects the required teaching resources from the preliminary resources, and the download count of the corresponding teaching resources is increased by one; The specific steps of resource evaluation processing are: Extract the user evaluation data of each group of preliminary resources, and determine the user feedback index Uy of each group of preliminary resources after keyword matching processing; Get the user type, resource quantity and download count of each group of preliminary resources corresponding to the uploader, and determine the user reliability index Ut of each group of preliminary resources after processing; Extract the time of the nearest last update of each group of preliminary resources from the current time point, and calculate the time difference between the last update time and the current time point to get the resource timeliness index Ur of each group of preliminary resources; Get the user feedback index Uy, user reliability index Ut and resource timeliness index Ur of each group of preliminary resources, and push them to the user, and further evaluate and push them to the user after the user determines the preference; preference includes feedback approval preference, uploader approval preference and content timeliness preference, and is represented by numbers a, b and c; Based on the user-determined preferences, the user feedback index Uy, the user reliability index Ut, and the resource timeliness index Ur of each group of preliminary resources are substituted into the formula After the weighted calculation, the sharing evaluation index Ue of each group of preliminary resources is obtained; are respectively a preset passing feedback index, a passing reliability index, and a reference timeliness index; 、 、 are the influence weight factors of the user feedback index Uy, the user reliability index Ut, and the resource timeliness index Ur determined by the user under the feedback approval preference; 、 、 are the influence weight factors of the user feedback index Uy, the user reliability index Ut, and the resource timeliness index Ur determined by the user under the uploader approval preference; 、 、 are the influence weight factors of the user feedback index Uy, the user reliability index Ut, and the resource timeliness index Ur determined by the user under the content timeliness preference; Extract the sharing evaluation index Ue of each group of preliminary resources, and sort each group of preliminary resources from large to small according to the size of the sharing evaluation index Ue, and push them to the user after sorting is completed; Shared incentive module: pre-construct user incentive mechanism, and update the user's sharing activity value in real time according to the user incentive mechanism, when the user's sharing activity value reaches the corresponding set reference value, trigger the exchange signaling and push it to the user.

2. The digital-based teaching resource sharing system according to claim 1, wherein, Determine the user feedback index Uy of each group of preliminary resources, specifically: Preset each group of keywords corresponding to user comments, input each group of preset keywords into user comment data in each group of preliminary resources for matching, if a group of user comment data corresponding to the preliminary resource matches the preset keyword successfully, the experience score of the corresponding preliminary resource is increased by one, and the final experience score of each group of preliminary resources is obtained after matching is completed, recorded as the number of times of satisfaction; Statistical analysis of the number of shares and the number of comment users of each group of preliminary resources; Calculate the proportion of the number of times of satisfaction and the number of shares in the number of comment users of each group of preliminary resources respectively, so as to obtain the satisfaction ratio and the sharing ratio of each group of preliminary resources; Multiply the satisfaction ratio and the sharing ratio of each group of preliminary resources by the corresponding set weight coefficient respectively, and then sum to get the user feedback index Uy of each group of preliminary resources.

3. The digital-based teaching resource sharing system according to claim 1, wherein, Determine the user reliability index Ut of each group of preliminary resources, specifically: Get the user type of the uploader corresponding to each group of preliminary resources, wherein the user type includes education experts, Senior teachers and in-service teachers; set different user types to correspond to a basic gold content score respectively, so as to determine the basic gold content score of each group of preliminary resources; Statistics of each group of preparatory resource uploaders upload resource quantity and download, and constitute a pair of data; Preset data pair corresponding to each group of data pair interval, each group of data pair interval corresponds to a gold content additional coefficient, and each group of data pair interval includes an upload resource quantity range and download range; The data pairs of each group of preparatory resources are matched with the intervals of each group of data pairs to determine the gold content additional coefficient of each group of preparatory resources; Multiply the basic gold content score of each group of preparatory resources determined and the corresponding gold content additional coefficient to obtain the user reliability index Ut of each group of preparatory resources.

4. The digital-based teaching resource sharing system according to claim 1, wherein, The construction process of user incentive mechanism is: Pre-set various incentive behaviors, including resource uploading, resource downloading, user evaluation and resource sharing; Statistics of the number of each type of incentive behavior of the user in the set time window, and set the corresponding weight coefficient, multiply the number of each type of incentive behavior of the user in the set time window by the corresponding weight coefficient, and then sum to obtain the active evaluation index of the user in the set time window; Pre-set the interval of four groups of index corresponding to the active evaluation index, and set each group of index interval to correspond to an active level respectively. The active level includes bronze, silver, gold and diamond, and different active levels correspond to a group of active reward points respectively; After determining the active level of the user, the corresponding active reward points are added to the current shared active value of the user and updated.

5. The digital-based teaching resource sharing system according to claim 4, wherein, The construction process of user incentive mechanism also includes: Obtain the user feedback index Uy of the uploaded teaching resources of the user in the set time window, set the index value range corresponding to each group of index Uy, and set each group of index value range to correspond to a resource contribution point respectively; Determine the resource contribution point of the uploaded teaching resources of the user in the set time window, add the corresponding resource contribution point to the current shared active value of the user and update.

6. The digital-based teaching resource sharing system according to claim 5, wherein, If the number of uploaded teaching resources of the user is greater than one, determine the resource contribution points of each group of teaching resources uploaded in the set time window and add them, and add the added value to the current shared active value of the user and update.

7. A method for sharing digitalized teaching resources, applied to the system for sharing digitalized teaching resources as claimed in any one of claims 1-6, characterized in that, It includes: Resource management: after the user completes the registration and uploads the teaching resources, the user uploads the teaching resources, identifies the corresponding subject, grade and teaching type of the teaching resources, and classifies them into the corresponding storage area; Resource recommendation: after the user inputs the required teaching resources, the subject, grade and teaching type, trigger the retrieval signal, extract each group of teaching resources that meet the user's input requirements as preparatory resources, and push the preparatory resources to the user after resource evaluation processing, and the user selects the required teaching resources from the preparatory resources; User incentive: pre-construct the user incentive mechanism, and update the shared active value of the user in real time according to the user incentive mechanism, and when the shared active value of the user reaches the corresponding set reference value, trigger the exchange signal and push it to the user.

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