CN113065986A - Educational resource generation method based on intelligent interaction - Google Patents
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Abstract
The invention provides an educational resource generation method based on intelligent interaction, which comprises the following steps: acquiring user identity information, and verifying the user identity information; determining a mapping relation between the user and a preset interactive function item in the education platform based on the verification result, and determining a target interactive option of the user according to the mapping relation; explaining the education content of the target interaction option to the user based on a preset interaction rule, and capturing the learning data of the user in real time; analyzing and processing the learning data of the user, and determining knowledge points corresponding to the knowledge blind areas of the user; and searching a corresponding solution from a preset database according to the knowledge points corresponding to the knowledge blind areas, and analyzing and explaining the solution to the user. Through the intelligent interaction mode, arouse child enthusiasm and enthusiasm to study, let child independently think in intelligent interaction, analyze the explanation and save the knowledge blind area to child's knowledge blind area in the learning process simultaneously to confirm corresponding education resources.
Description
Technical Field
The invention relates to the technical field of cloud information interaction and data processing, in particular to an educational resource generation method based on intelligent interaction.
Background
At present, the traditional education system only integrates communication between teachers and students, the communication is more realized by depending on a third-party platform, and the operation process has no real-time performance, is not direct and is not flexible; more importantly, the traditional education system can not arouse the learning interest of students, and meanwhile, the teaching process is single; moreover, the traditional education system can not process the information, and the processing capacity and the reliability are limited;
therefore, the invention provides an educational resource generation method based on intelligent interaction, which is used for exploring knowledge through interaction modes such as science popularization animation, Chinese-English bilingual explanation, knowledge competition and the like, exciting enthusiasm and enthusiasm of children for learning, enabling the children to independently think in intelligent interaction, self-help learning and enjoying the interest of exploring the world.
Disclosure of Invention
The invention provides an educational resource generation method based on intelligent interaction, which is used for exciting enthusiasm and enthusiasm of children for learning in an intelligent interaction mode, enabling the children to independently think in the intelligent interaction, analyzing and explaining knowledge blind areas of the children in the learning process and storing the knowledge blind areas, and accordingly determining corresponding educational resources.
The invention provides an educational resource generation method based on intelligent interaction, which comprises the following steps:
step 1: acquiring user identity information, and verifying the user identity information;
step 2: determining a mapping relation between the user and a preset interactive function item in the education platform based on the verification result, and determining a target interactive option of the user according to the mapping relation;
and step 3: explaining the education content of the target interaction option to a user based on a preset interaction rule, and capturing learning data of the user in real time;
and 4, step 4: analyzing and processing the learning data of the user, and determining knowledge points corresponding to the knowledge blind areas of the user;
and 5: and searching a corresponding solution from a preset database according to the knowledge points corresponding to the knowledge blind areas, and analyzing and explaining the solution to the user in a preset explanation mode.
Preferably, in step 1, obtaining user identity information and verifying the user identity information includes:
acquiring login information of a user terminal, wherein the login information comprises an account number of a user and ID information of the user terminal;
judging whether the login information is in a preset user database;
if not, judging that the user is a new user, and performing registration operation;
otherwise, comparing the login information with the data stub when the user registers to obtain the matching degree of the login information and the data stub when the user registers;
and comparing the matching degree with a preset matching degree, finishing the verification of the login information of the user when the matching degree is greater than or equal to the preset matching degree, and determining the identity information of the user corresponding to the login information based on a preset user database.
Preferably, in step 2, determining a mapping relationship between a user and a preset interactive function item in an education platform, and determining a target interactive option of the user according to the mapping relationship, the method for generating educational resources based on intelligent interaction includes:
acquiring historical learning record data of a user, and obtaining a corresponding relation between the user and at least one preset interactive function item in preset interactive function items in an education platform according to the historical data;
determining the mapping direction of the user and a preset interactive function item according to the corresponding relation, and establishing a mapping relation tree between the user and the preset interactive function item according to the mapping direction;
determining a mapping relation between the user and a preset interactive function item in an education platform based on the mapping relation tree;
determining completed interactive function items, ongoing interactive function items and non-ongoing interactive function items in preset interactive function items in the user and the education platform based on the mapping relation;
and the ongoing interactive function item is the target interactive option of the user.
Preferably, in step 3, the method for generating educational resources based on intelligent interaction explains the educational content of the target interaction option to the user, and captures learning data of the user in real time, and includes:
the method comprises the steps that an interactive execution instruction sent by a user is obtained, and after the interactive execution instruction is received by an education platform, an interactive interface between the user and the education platform is divided into a speaker information issuing interface and a student information issuing interface;
the education platform explains education contents to users based on the information issuing interface of the interphones;
wherein the explanation comprises a Chinese-English bilingual explanation and an animation explanation;
meanwhile, learning state data of students listening to and speaking education contents and interaction data of the education platform are collected in real time based on the student information publishing interface, and capturing of learning data of users is completed.
Preferably, in step 4, the method for generating educational resources based on intelligent interaction, which analyzes and processes the learning data of the user to determine knowledge points corresponding to the user knowledge dead zones, includes:
placing the learning data of the user in a preset coordinate system, and obtaining a coordinate point of the learning data of the user based on the preset coordinate system;
according to the coordinate points of the learning data of the user, performing data fitting in the preset coordinate system, drawing a learning data fitting curve of the user, and meanwhile, determining outlier data according to the learning data fitting curve of the user;
deleting the outlier data to obtain standard learning data of the user;
dividing the standard data into M data segments with fixed length, and extracting the offset value of each data segment;
classifying the data segments to obtain data segment type values corresponding to the data segments and the offset values, and extracting feature data in the data segments based on the data segment type values;
constructing a feature data classification model, and classifying the standard learning data of the user based on the feature data to obtain a target classification result;
determining the knowledge field to which the learning data of each type of user belongs based on the target classification result, and determining achievement information of a knowledge point corresponding to a target interaction option by the user based on the knowledge field;
associating the achievement information of the knowledge field and the knowledge points to a preset achievement database, wherein the average achievement information of the knowledge points corresponding to the target interaction option is stored in the preset achievement database;
comparing the achievement information of the knowledge points corresponding to the target interaction option of the user with the average achievement information of the knowledge points corresponding to the target interaction option to finish the evaluation of the current learning effect of the user;
determining a knowledge point area which is not mastered by the user in the target interaction option based on the evaluation result to obtain a knowledge blind area of the user;
acquiring meta-knowledge points in the knowledge blind area, and constructing a knowledge graph;
and determining a basic knowledge point combination having a dependency relationship with the meta knowledge points based on the knowledge graph to obtain knowledge points corresponding to the user knowledge dead zones.
Preferably, in step 5, searching a corresponding solution from a preset database according to a knowledge point corresponding to the blind knowledge area, and parsing and explaining the solution to a user in a preset explanation manner, the method for generating educational resources based on intelligent interaction includes:
acquiring knowledge points corresponding to the knowledge blind areas, and performing name vectorization processing on the knowledge points based on a pre-trained knowledge point name matching model to obtain name matching vectors corresponding to the knowledge points;
determining a field corresponding relation between a name matching vector corresponding to the knowledge point and a preset solution knowledge point standard name vector table based on a preset solution knowledge point standard name vector table, and determining similarity between corresponding fields;
when the similarity is greater than or equal to a preset similarity, determining a solution of a knowledge point corresponding to the knowledge dead zone;
wherein the solution comprises a plurality of interpretation steps;
and determining a weight value of each explanation step based on a preset algorithm, and pushing the solutions to the user according to the descending order of the weight values.
Preferably, the method for generating educational resources based on intelligent interaction, which determines the solution of the knowledge points corresponding to the knowledge dead zones, further comprises:
acquiring a solution of a knowledge point corresponding to the knowledge blind area and configuration parameters of the solution;
the configuration parameters comprise storage mode types corresponding to the solutions;
determining a target storage area based on the storage mode type, and determining a capacity value of the target storage area;
determining the byte value of the solution based on a preset algorithm, and judging the byte value of the solution and the capacity value of the target storage area;
storing the solution to the target storage area based on the storage mode type when a byte value of the solution is less than or equal to a capacity value of the target storage area.
Preferably, the method for generating educational resources based on intelligent interaction, which analyzes and processes the learning data of the user, determines knowledge points corresponding to knowledge blind areas of the user, and searches corresponding solutions from a preset database according to the knowledge points corresponding to the knowledge blind areas, further comprises:
acquiring the number of knowledge points corresponding to the knowledge blind area, calculating and determining the interaction accuracy of the user for the knowledge blind area according to the number of the knowledge points corresponding to the knowledge blind area, and calculating and finding the effective value of the corresponding solution according to the interaction accuracy, wherein the specific steps comprise:
and calculating and determining the interaction accuracy of the user for the knowledge blind area according to the following formula:
wherein alpha represents the interaction accuracy of the user for the knowledge blind area, and the value range is (0, 1); gamma represents the value of the knowledge points which are not mastered by the user in the target interaction option; δ represents the magnitude of all knowledge points involved in the target interaction option; sigma represents the area value of the knowledge blind area in the target interaction option knowledge graph; tau represents the total area value of the knowledge graph in the target interaction option; mu represents the average difficulty coefficient of the knowledge points of the knowledge dead zone, and the value range is (0.4, 0.6); p is a radical of1Representing the number of associated knowledge points between the knowledge points which are not mastered by the user in the target interaction option and the remaining knowledge points excluding the knowledge points which are not mastered in all the knowledge points involved in the target interaction option; p is a radical of2Representing the number of irrelevant knowledge points between the knowledge points which are not mastered by the user in the target interaction option and the rest knowledge points except the knowledge points which are not mastered in all the knowledge points involved in the target interaction option; p is a radical of1+p2＝δ；
According to the interaction accuracy, searching a corresponding solution, and meanwhile, calculating an effective value of the searched solution according to the following formula:
wherein β represents a valid value for finding a corresponding solution;
the capability factor representing the capability of the user to receive the solution is in a value range of (0.6, 0.8); xi represents the found solution and knowledge blindnessMatching degree values of the knowledge points corresponding to the regions; theta represents the feasibility rate of the solution, and the value range is (0, 1);
the method comprises the steps of representing the applicability rate of a solution to knowledge points of knowledge dead zones, wherein the value range is (0, 1); omega represents the number value of the knowledge points in the solvable knowledge blind area corresponding to the solution;
comparing the calculated effective value with a preset effective value;
if the effective value obtained by calculation is smaller than the preset effective value, judging that the searched corresponding solution is unqualified, marking a final blind area from the knowledge blind area, and performing tabulation output display on the knowledge points corresponding to the final blind area;
otherwise, judging that the searched corresponding solution is qualified, and outputting and displaying the solution and the solution process of the solution points which are not mastered.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of an educational resource generation method based on intelligent interaction in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1:
the embodiment provides an educational resource generation method based on intelligent interaction, as shown in fig. 1, including:
step 1: acquiring user identity information, and verifying the user identity information;
step 2: determining a mapping relation between the user and a preset interactive function item in the education platform based on the verification result, and determining a target interactive option of the user according to the mapping relation;
and step 3: explaining the education content of the target interaction option to a user based on a preset interaction rule, and capturing learning data of the user in real time;
and 4, step 4: analyzing and processing the learning data of the user, and determining knowledge points corresponding to the knowledge blind areas of the user;
and 5: and searching a corresponding solution from a preset database according to the knowledge points corresponding to the knowledge blind areas, and analyzing and explaining the solution to the user in a preset explanation mode.
In this embodiment, the preset interactive function item is a learning item that the user is allowed to learn by the education platform, and may be, for example, exploring the submarine world, exploring the universe world, and the like.
In this embodiment, the mapping relationship refers to an association relationship between a user and a preset interactive function item, where one preset interactive function item may correspond to one user, or multiple preset interactive function items may correspond to one user.
In this embodiment, the target interactive option means that it is determined from a plurality of preset interactive function items that the user is learning.
In this embodiment, the preset interaction rule is set in advance, and may be a variety of rules such as science popularization animation, human online knowledge competition, and chinese-english bilingual explanation.
In this embodiment, the preset database is obtained through multiple sets of training, and the solutions corresponding to the multiple knowledge points are stored inside the preset database.
The beneficial effects of the above technical scheme are: through the intelligent interaction mode, arouse child enthusiasm and enthusiasm to study, let child independently think in intelligent interaction, analyze the explanation and save the knowledge blind area to child's knowledge blind area in the learning process simultaneously to confirm corresponding education resources.
Example 2:
on the basis of the foregoing embodiment 1, this embodiment provides an educational resource generation method based on intelligent interaction, where in step 1, obtaining user identity information, and verifying the user identity information includes:
acquiring login information of a user terminal, wherein the login information comprises an account number of a user and ID information of the user terminal;
judging whether the login information is in a preset user database;
if not, judging that the user is a new user, and performing registration operation;
otherwise, comparing the login information with the data stub when the user registers to obtain the matching degree of the login information and the data stub when the user registers;
and comparing the matching degree with a preset matching degree, finishing the verification of the login information of the user when the matching degree is greater than or equal to the preset matching degree, and determining the identity information of the user corresponding to the login information based on a preset user database.
In this embodiment, the data stub refers to basic information filled in by the user at the time of registration, including name, gender, age, and the like.
In this embodiment, the preset matching degree is set in advance, and is used to measure the matching degree between the login information and the data stub when the user registers, so as to determine the identity information of the user.
The beneficial effects of the above technical scheme are: by acquiring the identity information of the user and verifying the identity of the user, the learning data corresponding to the user can be accurately grasped according to the interactive content of the user, so that a solution suitable for the user when the user encounters a problem in the learning process can be conveniently provided for the user.
Example 3:
on the basis of the foregoing embodiment 1, this embodiment provides an educational resource generation method based on intelligent interaction, where in step 2, determining a mapping relationship between a user and a preset interactive function item in an educational platform, and determining a target interaction option of the user according to the mapping relationship, includes:
acquiring historical learning record data of a user, and obtaining a corresponding relation between the user and at least one preset interactive function item in preset interactive function items in an education platform according to the historical data;
determining the mapping direction of the user and a preset interactive function item according to the corresponding relation, and establishing a mapping relation tree between the user and the preset interactive function item according to the mapping direction;
determining a mapping relation between the user and a preset interactive function item in an education platform based on the mapping relation tree;
determining completed interactive function items, ongoing interactive function items and non-ongoing interactive function items in preset interactive function items in the user and the education platform based on the mapping relation;
and the ongoing interactive function item is the target interactive option of the user.
In this embodiment, the mapping direction is used to determine the mapping direction of the mapping party and the mapped party, for example, the results of a mapping B and B mapping a are different.
In this embodiment, the mapping relationship tree is used to record an association relationship between a user and an interactive function item, and the interaction relationship between a plurality of interactive function items and the same user is stored inside the mapping relationship tree.
In this embodiment, the mapping relationship refers to an association relationship between a user and a preset interactive function item, where one preset interactive function item may correspond to one user, or multiple preset interactive function items may correspond to one user.
The beneficial effects of the above technical scheme are: by determining the mapping relation between the user and the preset interactive function items and accurately determining the target interactive function selection type of the user according to the mapping relation, the education platform can conveniently and accurately master the current learning data of the user according to the target interactive function selection, and determine the corresponding knowledge blind area according to the learning data, thereby determining the corresponding education resources.
Example 4:
on the basis of the foregoing embodiment 1, this embodiment provides an educational resource generation method based on intelligent interaction, and in step 3, the method for explaining the educational content of the target interaction option to the user and capturing learning data of the user in real time includes:
the method comprises the steps that an interactive execution instruction sent by a user is obtained, and after the interactive execution instruction is received by an education platform, an interactive interface between the user and the education platform is divided into a speaker information issuing interface and a student information issuing interface;
the education platform explains education contents to users based on the information issuing interface of the interphones;
wherein the explanation comprises a Chinese-English bilingual explanation and an animation explanation;
meanwhile, learning state data of students listening to and speaking education contents and interaction data of the education platform are collected in real time based on the student information publishing interface, and capturing of learning data of users is completed.
In this embodiment, the interactive execution instruction refers to an instruction sent by the user to the education platform, and the education platform starts to push the education content after receiving the instruction.
In this embodiment, the presenter information distribution interface refers to an interface used by an education platform terminal to push education, for example, in a line course, a teacher is a main body.
In this embodiment, the student information publishing interface refers to an interface through which students listen to the information sent by the education platform and display their learning states.
The beneficial effects of the above technical scheme are: the education content is pushed to the user, the learning data of the user are acquired in real time, the learning data of the user can be analyzed conveniently, and the place where the user is not firmly mastered with the knowledge points is accurately determined, so that the education platform can determine the corresponding solution according to the knowledge blind area conveniently, corresponding education resources are generated, and pertinence of the education resources is improved.
Example 5:
on the basis of the foregoing embodiment 1, this embodiment provides a method for generating educational resources based on intelligent interaction, where in step 4, analyzing and processing the learning data of the user to determine knowledge points corresponding to user knowledge blind areas, and the method includes:
placing the learning data of the user in a preset coordinate system, and obtaining a coordinate point of the learning data of the user based on the preset coordinate system;
according to the coordinate points of the learning data of the user, performing data fitting in the preset coordinate system, drawing a learning data fitting curve of the user, and meanwhile, determining outlier data according to the learning data fitting curve of the user;
deleting the outlier data to obtain standard learning data of the user;
dividing the standard data into M data segments with fixed length, and extracting the offset value of each data segment;
classifying the data segments to obtain data segment type values corresponding to the data segments and the offset values, and extracting feature data in the data segments based on the data segment type values;
constructing a feature data classification model, and classifying the standard learning data of the user based on the feature data to obtain a target classification result;
determining the knowledge field to which the learning data of each type of user belongs based on the target classification result, and determining achievement information of a knowledge point corresponding to a target interaction option by the user based on the knowledge field;
associating the achievement information of the knowledge field and the knowledge points to a preset achievement database, wherein the average achievement information of the knowledge points corresponding to the target interaction option is stored in the preset achievement database;
comparing the achievement information of the knowledge points corresponding to the target interaction option of the user with the average achievement information of the knowledge points corresponding to the target interaction option to finish the evaluation of the current learning effect of the user;
determining a knowledge point area which is not mastered by the user in the target interaction option based on the evaluation result to obtain a knowledge blind area of the user;
acquiring meta-knowledge points in the knowledge blind area, and constructing a knowledge graph;
and determining a basic knowledge point combination having a dependency relationship with the meta knowledge points based on the knowledge graph to obtain knowledge points corresponding to the user knowledge dead zones.
In this embodiment, the preset coordinate system is used to determine the learning data of the user to a specific point, so as to facilitate clearing abnormal data in the learning data of the user.
In this embodiment, the coordinate point of the learning data refers to a specific coordinate value of each data field obtained after the learning data is placed in the coordinate system.
In this embodiment, the fitting curve of the learning data refers to connecting data points with high density in the learning data to obtain a data curve, which is used to represent the fitting degree of the data.
In this embodiment, the outlier data refers to data that deviates from the fitting curve of the learning data and has an abnormal influence on the learning data of the user.
In this embodiment, the standard learning data refers to data obtained by removing abnormal data in the user learning data, and the data can be directly used to analyze the learning effect of the user.
In this embodiment, the offset value refers to the degree to which each data segment is offset from the predetermined standard, and can be used to determine the type of the data.
In this embodiment, the feature data refers to a representative key data segment in the user learning data, and the category of the learning data can be accurately determined according to the feature data.
In this embodiment, the preset achievement database is set in advance, is obtained by training the learning achievements of a plurality of users, and stores the average achievement information corresponding to the target interaction option.
In this embodiment, the meta knowledge points refer to knowledge points having critical problems in the knowledge dead zone, for example, when calculating the angle of a triangle, the trigonometric function is the meta knowledge point.
In this embodiment, the basic knowledge point refers to other knowledge points derived from the meta knowledge point, and has a blood-related relationship with the meta knowledge point, for example, the trigonometric function is the meta knowledge point, and the other derived trigonometric functions are combined into the basic knowledge point.
The beneficial effects of the above technical scheme are: the learning scores of the users are cleaned, abnormal data in the learning scores are eliminated, the current learning effect of the users is evaluated according to the learning data of the users, the knowledge blind areas of the users are accurately determined, the knowledge points corresponding to the knowledge blind areas of the users are obtained according to the meta-knowledge points in the knowledge blind areas, the knowledge points corresponding to the knowledge blind areas of the users are accurately obtained, the solution that the education platform determines the corresponding solution according to the knowledge blind areas is improved, the education resources of the education platform are perfected, and convenience is brought to the determination of the corresponding education resources.
Example 6:
on the basis of the foregoing embodiment 1, this embodiment provides an educational resource generation method based on intelligent interaction, and in step 5, searching a corresponding solution from a preset database according to a knowledge point corresponding to the blind knowledge area, and parsing and explaining the solution to a user in a preset explanation manner, where the method includes:
acquiring knowledge points corresponding to the knowledge blind areas, and performing name vectorization processing on the knowledge points based on a pre-trained knowledge point name matching model to obtain name matching vectors corresponding to the knowledge points;
determining a field corresponding relation between a name matching vector corresponding to the knowledge point and a preset solution knowledge point standard name vector table based on a preset solution knowledge point standard name vector table, and determining similarity between corresponding fields;
when the similarity is greater than or equal to a preset similarity, determining a solution of a knowledge point corresponding to the knowledge dead zone;
wherein the solution comprises a plurality of interpretation steps;
and determining a weight value of each explanation step based on a preset algorithm, and pushing the solutions to the user according to the descending order of the weight values.
In this embodiment, the name vectorization processing refers to performing conversion calculation on data to obtain a vector mode corresponding to the data.
In this embodiment, the name matching vector refers to a vector obtained by vectorizing the name of the knowledge point, so as to calculate the similarity with the standard name vector according to the vector.
In this embodiment, the field correspondence refers to the correspondence between the knowledge point name vector and the data at the same position in the standard name vector, for example: name length correspondence, data content correspondence, etc.
In this embodiment, the weight value refers to the proportion of each step in the solution in all steps, and is used to represent the importance of the step.
The beneficial effects of the above technical scheme are: by searching the corresponding solution according to the knowledge blind area of the user, the knowledge points which are not well learned by the user can be analyzed and explained conveniently, the learning efficiency of the user is improved, the enthusiasm of the user for learning is stimulated conveniently, and the user can learn autonomously.
Example 7:
on the basis of the foregoing embodiment 6, this embodiment provides an educational resource generation method based on intelligent interaction, which is characterized in that, determining a solution of a knowledge point corresponding to the knowledge dead zone, further includes:
acquiring a solution of a knowledge point corresponding to the knowledge blind area and configuration parameters of the solution;
the configuration parameters comprise storage mode types corresponding to the solutions;
determining a target storage area based on the storage mode type, and determining a capacity value of the target storage area;
determining the byte value of the solution based on a preset algorithm, and judging the byte value of the solution and the capacity value of the target storage area;
storing the solution to the target storage area based on the storage mode type when a byte value of the solution is less than or equal to a capacity value of the target storage area.
In this embodiment, the configuration parameters refer to the type of the storage mode corresponding to the solution, the number of steps included in the solution, the amount of information, and the like.
In this embodiment, the target storage area refers to a storage area for storing the solution, and is a place selected from a plurality of storage areas where the solution is suitable for storage.
In this embodiment, the preset algorithm is set in advance, and is used to determine the byte value of the solution and the capacity value of the target storage area, which are obtained through multiple training.
The beneficial effects of the above technical scheme are: through preserving the solution that corresponds user knowledge blind area, the education platform of being convenient for carries out the comprehensive training to user's knowledge blind area, increases education resource bank of education platform, and the education platform of being convenient for generates corresponding education resource according to user knowledge blind area, has improved and has generated education resource efficiency and pertinence.
Example 8:
on the basis of the foregoing embodiment 1, this embodiment provides an educational resource generation method based on intelligent interaction, which analyzes and processes the learning data of the user, determines knowledge points corresponding to user knowledge blind areas, and searches for corresponding solutions from a preset database according to the knowledge points corresponding to the knowledge blind areas, and further includes:
acquiring the number of knowledge points corresponding to the knowledge blind area, calculating and determining the interaction accuracy of the user for the knowledge blind area according to the number of the knowledge points corresponding to the knowledge blind area, and calculating and finding the effective value of the corresponding solution according to the interaction accuracy, wherein the specific steps comprise:
and calculating and determining the interaction accuracy of the user for the knowledge blind area according to the following formula:
wherein alpha represents the interaction accuracy of the user for the knowledge blind area, and the value range is (0, 1); gamma represents the value of the knowledge points which are not mastered by the user in the target interaction option; δ represents the magnitude of all knowledge points involved in the target interaction option; sigma represents the area value of the knowledge blind area in the target interaction option knowledge graph; tau represents the total area value of the knowledge graph in the target interaction option; mu represents the average difficulty coefficient of the knowledge points of the knowledge dead zone, and the value range is (0.4, 0.6); p is a radical of1Representing the number of associated knowledge points between the knowledge points which are not mastered by the user in the target interaction option and the remaining knowledge points excluding the knowledge points which are not mastered in all the knowledge points involved in the target interaction option; p is a radical of2Representing the number of irrelevant knowledge points between the knowledge points which are not mastered by the user in the target interaction option and the rest knowledge points except the knowledge points which are not mastered in all the knowledge points involved in the target interaction option; p is a radical of1+p2＝δ；
According to the interaction accuracy, searching a corresponding solution, and meanwhile, calculating an effective value of the searched solution according to the following formula:
wherein β represents a valid value for finding a corresponding solution;
the capability factor representing the capability of the user to receive the solution is in a value range of (0.6, 0.8); xi represents the matching degree value of the searched solution and the knowledge point corresponding to the knowledge blind area; theta represents the feasibility rate of the solution, and the value range is (0, 1);
the method comprises the steps of representing the applicability rate of a solution to knowledge points of knowledge dead zones, wherein the value range is (0, 1); omega represents the number value of the knowledge points in the solvable knowledge blind area corresponding to the solution;
comparing the calculated effective value with a preset effective value;
if the effective value obtained by calculation is smaller than the preset effective value, judging that the searched corresponding solution is unqualified, marking a final blind area from the knowledge blind area, and performing tabulation output display on the knowledge points corresponding to the final blind area;
otherwise, judging that the searched corresponding solution is qualified, and outputting and displaying the solution and the solution process of the solution points which are not mastered.
In this embodiment, the capability factor is used to indicate the degree of capability of the user to receive the solution.
In this embodiment, the applicability refers to pertinence of the solution to the knowledge points corresponding to the knowledge dead zone, and is used to determine whether the solution can handle the knowledge point problem of the knowledge dead zone.
In this embodiment, the preset effective value is set in advance, and is used to determine whether the calculated effective value is qualified, which is an index for measuring the calculation result.
The beneficial effects of the above technical scheme are: the accuracy of the knowledge blind area is determined by calculating according to the number of the knowledge points corresponding to the knowledge blind area, the effective value of the corresponding solution is found by calculating according to the accuracy, when the accuracy is calculated, the ratio of the number of the knowledge points corresponding to the knowledge blind area to the number of all the knowledge points and the area value occupied by the knowledge blind area in the target interaction option knowledge map are related, so that the calculated accuracy can be obtained according to the calculated accuracy, the calculation accuracy is improved, when the effective value is calculated, the matching value, the feasibility rate of the solution and the capability factor of the user for receiving the solution are related, the calculation result is more accurate and reliable, the solution can effectively solve the knowledge blind area of the user, the solution efficiency of the knowledge blind area of the user is improved, and meanwhile, the accuracy of the education platform for generating education resources according to the knowledge blind area of the user is improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. An educational resource generation method based on intelligent interaction is characterized by comprising the following steps:
step 1: acquiring user identity information, and verifying the user identity information;
step 2: determining a mapping relation between the user and a preset interactive function item in the education platform based on the verification result, and determining a target interactive option of the user according to the mapping relation;
and step 3: explaining the education content of the target interaction option to a user based on a preset interaction rule, and capturing learning data of the user in real time;
and 4, step 4: analyzing and processing the learning data of the user, and determining knowledge points corresponding to the knowledge blind areas of the user;
and 5: and searching a corresponding solution from a preset database according to the knowledge points corresponding to the knowledge blind areas, and analyzing and explaining the solution to the user in a preset explanation mode.
2. The method for generating educational resources based on intelligent interaction according to claim 1, wherein the step 1 of obtaining user identity information and verifying the user identity information comprises:
acquiring login information of a user terminal, wherein the login information comprises an account number of a user and ID information of the user terminal;
judging whether the login information is in a preset user database;
if not, judging that the user is a new user, and performing registration operation;
otherwise, comparing the login information with the data stub when the user registers to obtain the matching degree of the login information and the data stub when the user registers;
and comparing the matching degree with a preset matching degree, finishing the verification of the login information of the user when the matching degree is greater than or equal to the preset matching degree, and determining the identity information of the user corresponding to the login information based on a preset user database.
3. The method for generating educational resources based on intelligent interaction according to claim 1, wherein in step 2, determining a mapping relationship between the user and a preset interactive function item in the educational platform, and determining the target interactive option of the user according to the mapping relationship comprises:
acquiring historical learning record data of a user, and obtaining a corresponding relation between the user and at least one preset interactive function item in preset interactive function items in an education platform according to the historical data;
determining the mapping direction of the user and a preset interactive function item according to the corresponding relation, and establishing a mapping relation tree between the user and the preset interactive function item according to the mapping direction;
determining a mapping relation between the user and a preset interactive function item in an education platform based on the mapping relation tree;
determining completed interactive function items, ongoing interactive function items and non-ongoing interactive function items in preset interactive function items in the user and the education platform based on the mapping relation;
and the ongoing interactive function item is the target interactive option of the user.
4. The method for generating educational resources based on intelligent interaction according to claim 1, wherein in step 3, the teaching of the educational content of the target interaction option to the user and the capturing of the learning data of the user in real time comprises:
the method comprises the steps that an interactive execution instruction sent by a user is obtained, and after the interactive execution instruction is received by an education platform, an interactive interface between the user and the education platform is divided into a speaker information issuing interface and a student information issuing interface;
the education platform explains education contents to users based on the information issuing interface of the interphones;
wherein the explanation comprises a Chinese-English bilingual explanation and an animation explanation;
meanwhile, learning state data of students listening to and speaking education contents and interaction data of the education platform are collected in real time based on the student information publishing interface, and capturing of learning data of users is completed.
5. The method for generating educational resources based on intelligent interaction according to claim 1, wherein in step 4, analyzing and processing the learning data of the user to determine knowledge points corresponding to user knowledge dead zones comprises:
placing the learning data of the user in a preset coordinate system, and obtaining a coordinate point of the learning data of the user based on the preset coordinate system;
according to the coordinate points of the learning data of the user, performing data fitting in the preset coordinate system, drawing a learning data fitting curve of the user, and meanwhile, determining outlier data according to the learning data fitting curve of the user;
deleting the outlier data to obtain standard learning data of the user;
dividing the standard data into M data segments with fixed length, and extracting the offset value of each data segment;
classifying the data segments to obtain data segment type values corresponding to the data segments and the offset values, and extracting feature data in the data segments based on the data segment type values;
constructing a feature data classification model, and classifying the standard learning data of the user based on the feature data to obtain a target classification result;
determining the knowledge field to which the learning data of each type of user belongs based on the target classification result, and determining achievement information of a knowledge point corresponding to a target interaction option by the user based on the knowledge field;
associating the achievement information of the knowledge field and the knowledge points to a preset achievement database, wherein the average achievement information of the knowledge points corresponding to the target interaction option is stored in the preset achievement database;
comparing the achievement information of the knowledge points corresponding to the target interaction option of the user with the average achievement information of the knowledge points corresponding to the target interaction option to finish the evaluation of the current learning effect of the user;
determining a knowledge point area which is not mastered by the user in the target interaction option based on the evaluation result to obtain a knowledge blind area of the user;
acquiring meta-knowledge points in the knowledge blind area, and constructing a knowledge graph;
and determining a basic knowledge point combination having a dependency relationship with the meta knowledge points based on the knowledge graph to obtain knowledge points corresponding to the user knowledge dead zones.
6. The method for generating educational resources based on intelligent interaction according to claim 1, wherein in step 5, the corresponding solution is searched from a preset database according to the knowledge points corresponding to the blind knowledge areas, and the solution is parsed and explained to the user in a preset explanation manner, which comprises:
acquiring knowledge points corresponding to the knowledge blind areas, and performing name vectorization processing on the knowledge points based on a pre-trained knowledge point name matching model to obtain name matching vectors corresponding to the knowledge points;
determining a field corresponding relation between a name matching vector corresponding to the knowledge point and a preset solution knowledge point standard name vector table based on a preset solution knowledge point standard name vector table, and determining similarity between corresponding fields;
when the similarity is greater than or equal to a preset similarity, determining a solution of a knowledge point corresponding to the knowledge dead zone;
wherein the solution comprises a plurality of interpretation steps;
and determining a weight value of each explanation step based on a preset algorithm, and pushing the solutions to the user according to the descending order of the weight values.
7. The method of claim 6, wherein determining the solution of the knowledge points corresponding to the blind knowledge areas further comprises:
acquiring a solution of a knowledge point corresponding to the knowledge blind area and configuration parameters of the solution;
the configuration parameters comprise storage mode types corresponding to the solutions;
determining a target storage area based on the storage mode type, and determining a capacity value of the target storage area;
determining the byte value of the solution based on a preset algorithm, and judging the byte value of the solution and the capacity value of the target storage area;
storing the solution to the target storage area based on the storage mode type when a byte value of the solution is less than or equal to a capacity value of the target storage area.
8. The method as claimed in claim 1, wherein the method for generating educational resources based on intelligent interaction comprises analyzing and processing the learning data of the user, determining knowledge points corresponding to the user's knowledge dead zones, and searching corresponding solutions from a preset database according to the knowledge points corresponding to the knowledge dead zones, further comprising:
acquiring the number of knowledge points corresponding to the knowledge blind area, calculating and determining the interaction accuracy of the user for the knowledge blind area according to the number of the knowledge points corresponding to the knowledge blind area, and calculating and finding the effective value of the corresponding solution according to the interaction accuracy, wherein the specific steps comprise:
and calculating and determining the interaction accuracy of the user for the knowledge blind area according to the following formula:
wherein alpha represents the interaction accuracy of the user for the knowledge blind area, and the value range is (0, 1); gamma represents the value of the knowledge points which are not mastered by the user in the target interaction option; δ represents the magnitude of all knowledge points involved in the target interaction option; sigma represents the area value of the knowledge blind area in the target interaction option knowledge graph; tau represents the total area value of the knowledge graph in the target interaction option; mu represents the average difficulty coefficient of the knowledge points of the knowledge dead zone, and the value range is (0.4, 0.6); p is a radical of1Representing the number of associated knowledge points between the knowledge points which are not mastered by the user in the target interaction option and the remaining knowledge points excluding the knowledge points which are not mastered in all the knowledge points involved in the target interaction option; p is a radical of2Representing the number of irrelevant knowledge points between the knowledge points which are not mastered by the user in the target interaction option and the rest knowledge points except the knowledge points which are not mastered in all the knowledge points involved in the target interaction option; p is a radical of1+p2＝δ；
According to the interaction accuracy, searching a corresponding solution, and meanwhile, calculating an effective value of the searched solution according to the following formula:
wherein β represents a valid value for finding a corresponding solution;
the capability factor representing the capability of the user to receive the solution is in a value range of (0.6, 0.8); xi represents the matching degree value of the searched solution and the knowledge point corresponding to the knowledge blind area; theta represents the feasibility of the solution and takes on valueThe range is (0, 1);
the method comprises the steps of representing the applicability rate of a solution to knowledge points of knowledge dead zones, wherein the value range is (0, 1); omega represents the number value of the knowledge points in the solvable knowledge blind area corresponding to the solution;
comparing the calculated effective value with a preset effective value;
if the effective value obtained by calculation is smaller than the preset effective value, judging that the searched corresponding solution is unqualified, marking a final blind area from the knowledge blind area, and performing tabulation output display on the knowledge points corresponding to the final blind area;
otherwise, judging that the searched corresponding solution is qualified, and outputting and displaying the solution and the solution process of the solution points which are not mastered.
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