CN111143750B - University computer class course management platform based on fragmented learning - Google Patents
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Abstract
The invention relates to a university computer class course management platform based on fragmented learning, which comprises a subjective question automatic judging function system, an intelligent recommended teaching resource function system, a user result interactive sharing function system and a professional route planning learning function system. The invention has reasonable concept, integrates four functions of automatic evaluation of subjective questions, intelligent recommendation of teaching resources, achievement sharing of users and professional route planning and learning, contributes to post-school learning and quantitative evaluation of teachers on students, and provides the most convenient and effective fragmented learning service for vast learners.
Description
Technical Field
The invention relates to a course management platform, in particular to a university computer-class course management platform based on fragmented learning.
Background
With the rapid development of the internet, people often face the current situation of learning but do not have enough time. Our research takes advantage of the small amount of time. Fragmentation analysis means that the whole is broken into parts; fragmented learning is to go from "deconstructing" to knowledge "construction" of the whole of the content of learning, the concept of which is to use the word "fragmentation" to visually describe the abstract process. The process is that the treatment is performed step by step from shallow to deep and from outside to inside with rhythm. At present, most fragmented learning mobile terminals in the society mostly perform extracurricular learning on English, and a fragmented learning platform aiming at computer professional learning courses (C language programming, java programming, database principle and application, operating system principle and the like) of college students does not appear yet. As for the admire class learning platform well-skilled in the art, the main mode is to replace the prior field learning, change all course contents into online learning, is not in line with the existing basic education of the subject, and is mainly used for the complete learning of non-professional established courses.
Disclosure of Invention
Aiming at the problems in the background technology, the invention provides a university computer class course management platform based on fragmented learning, which has reasonable conception, integrates four functions of automatic evaluation of subjective questions, intelligent recommendation of teaching resources, achievement sharing of users and professional route planning and learning, is dedicated to post-school learning and quantitative evaluation of teachers on students, and provides the most convenient and effective fragmented learning service for vast learners.
The technical scheme of the invention is as follows:
the university computer class course management platform based on fragmented learning comprises a subjective question automatic judging function system, an intelligent recommended teaching resource function system, a user achievement interactive sharing function system and a professional route planning and learning function system; the automatic subjective question evaluation functional system is based on artificial intelligence, automatically divides words by a maximum forward matching method, matches keywords with an established word bank, performs fuzzy matching on sentence division processing, grammar similarity and patterns by adopting a dynamic programming algorithm so as to achieve accurate simulation of manual scoring, realizes automatic evaluation of subjective questions, calculates comprehensive scores of students and analyzes the scores to realize evaluation of learning conditions of the students; the intelligent recommendation teaching resource function system is used for recommending the most appropriate learning materials for the user so as to avoid excessive time waste for selecting the learning materials or low-grade materials and achieve the purpose of fully utilizing fragmentation time for learning; the user achievement interactive sharing function system is characterized in that a user innovation achievement builds a discourse type interactive communication platform by relying on cloud computing, a plurality of special areas are arranged, different subjects are placed under different special areas, and information acquisition of users and management of administrators are facilitated; the professional route planning learning function system is used for providing a basis for the design and development of professional route planning learning.
The university computer class course management platform based on fragmented learning, wherein: the subjective question automatic evaluation functional system adopts a dynamic programming algorithm to carry out fuzzy matching on the similarity and the mode of the clauses, the grammar and the sentence which are processed, adopts a Monte Carlo algorithm to calculate the comprehensive score of the student and uses a big data cloud technology to analyze the score to realize the evaluation of the learning condition of the student; the automatic subjective question evaluation functional system comprises an automatic subjective question evaluation storage unit, an online evaluation unit of a compiling language and an SQL evaluation unit; the subjective question automatic evaluation storage unit is used for storing the correctness and the error condition of the work source program submitted by the students, and the stored work source program submitted by the students, the preset running time, the test data provided by the teacher and the test result data corresponding to the test data; the on-line question judging unit of the compiling type language adopts a complex algorithm to automatically judge the questions needing to be compiled of C language, C + +, java; the SQL question judging unit is based on a docker container, adopts a shortest editing distance algorithm to automatically judge the SQL sentences written by students, and the subjective question judging units of other computer learning courses are graded on line by teachers.
The university computer class course management platform based on fragmented learning comprises a subjective question automatic judging function system and a subjective question automatic judging function system, wherein the subjective question automatic judging function system comprises the following working procedures: firstly, compiling a job source program submitted by the automatic subjective question judging function system, and if the compiling system outputs wrong information, indicating that the job submitted by the student has a compiling error; secondly, the test data is redirected to input data, an executable file generated by compiling a homework source program submitted by a student is executed, the output result of the program is redirected to a specific file for further processing in the next step, and if the output result is overtime, the process is terminated and ended; then, comparing the output result file with the test result file, if the output result file is the same as the test result file, outputting the correct answer and finishing; and finally, comparing the result file and the test result after providing a space and a carriage return character, if the result file and the test result are the same, outputting an answer with a wrong format and ending, otherwise, outputting an answer with a wrong format and ending.
The university computer class course management platform based on fragmented learning, wherein: the intelligent recommended teaching resource function system is based on a recommendation algorithm of contents and a collaborative filtering recommendation algorithm under the background of big data, and adopts a mixed recommendation algorithm to recommend the most appropriate learning materials for the user; the intelligent recommended teaching resource function system comprises a user behavior model unit and a group user model unit; the user behavior model unit is used for establishing a user behavior model, namely establishing an individual vector model as an interface between a user and a resource according to contents browsed by the user, performing big data analysis on the behavior of the user, and pushing related contents suitable for the user to the user; the group user model unit is used for adding a group user model on the individual user model, namely similar individual users are classified according to interests according to a clustering algorithm to generate group users, the interests of the grouped group users are the integration of the interests of a plurality of similar individual users, and the individual users in the group users can realize concept expansion by inheriting the interests of the group users, so that the recall ratio is improved.
The university computer class course management platform based on fragmented learning, wherein: the intelligent recommended teaching resource function system can also provide users with interest similarity obtained by clustering for collaborative learning or for network administrators to improve services, automatically record the personalized access of the users to resources, dynamically adjust the behavior model of the users through the response ratio algorithm, and further adjust the vector model of the users, thereby realizing the update and storage of the personalized features of the users.
The university computer class course management platform based on fragmented learning, wherein: the user result interactive sharing function system comprises a user post issuing unit and an uploading learning material unit; the user post issuing unit is used for issuing related posts in different regions by a user, the related posts can be discussed by other users after the verification of an administrator is passed, the posts can be scored by other users, the user achievement interactive sharing function system can push essence posts to users with related interests, and the users can also add other users as friends, so that more sufficient communication is performed; the learning data uploading unit is used for the user to upload learning resources in different special areas, and the learning resources can be used by other users after being checked by an administrator.
The university computer class course management platform based on fragmented learning, wherein: the professional route planning learning functional system is a page synthesis algorithm for performing dynamic generation algorithm and personalized learning of a professional route planning learning path on big data by relying on a planning algorithm, and provides a basis for design and development of professional route planning learning; the professional route planning learning function system comprises a dynamic generation algorithm unit of a professional route planning learning path; the dynamic generation algorithm unit is used for recording the learning condition of the user and analyzing the degree of mastering related knowledge points of the user according to the knowledge structure of the course, generating an individualized knowledge state diagram based on a big data algorithm, and generating a professional route planning learning function based on the knowledge state diagram and the knowledge structure in cooperation with a complex algorithm.
The university computer class course management platform based on fragmented learning, wherein: the dynamic generation algorithm unit comprises an individualized evaluation algorithm, a big data analysis algorithm and a dynamic path planning algorithm; the personalized evaluation algorithm is used for evaluating the learning behaviors of students with different learning characteristics; the big data analysis algorithm is used for analyzing the mastering degree of students on the related knowledge points according to the learning behaviors of a large number of students; the dynamic path planning algorithm is used for performing dynamic path planning according to the current mastery degree of the knowledge points by the students, and recommending the optimal learning path under the current state for the students.
Has the advantages that:
the university computer class course management platform based on fragmented learning is reasonable in concept, integrates four functions of automatic subjective question evaluation, intelligent recommended teaching resources, achievement sharing of users and professional route planning and learning, contributes to post-school learning and quantitative evaluation of teachers on students, and provides the most convenient and most effective fragmented learning service for vast learners; meanwhile, the invention divides the learned course knowledge point into a plurality of stages, each stage is provided with a plurality of PPTs, short learning videos or technical articles to guide students to carry out the repair, the consolidation and the review of the learned course, and when the learning is finished without fragmentized resources, a test question bank aiming at the resources is provided, after the resource test is carried out, the review of the next resource can be carried out, and finally, the system calculates the ordinary score of the student according to the proportion of the score occupied by each resource.
The concrete advantages are shown in the following aspects:
(1) A set of fragmented learning resource management platform based on university computer class courses is established
In the existing teaching mode, most examinations are performed to obtain a grade through end-of-term examinations, and no strict quantitative scheme is provided for the examination of ordinary grades, so that teachers can make more random examinations on ordinary grades, students cannot firmly grasp knowledge points of courses, and the end-of-term assault review is mainly performed. Establishing a fragment learning resource management platform, and setting corresponding knowledge points and stages according to the types of courses, wherein a plurality of knowledge points correspond to the lower part of one stage; when fragmented resources are established, short videos, ppt and blog articles can be established, the short videos, the ppt and the blog articles are mainly used for consolidating and reviewing learning contents after class, a knowledge point is reached, so that the whole course is mastered, a corresponding assessment scheme needs to be set for the established fragmented resources, namely, after the knowledge point is learned, knowledge verification needs to be carried out, and the review condition of students is checked through modes of selecting, judging, filling in blank and programming questions. And setting the assessment sequence of the resources on the platform, allowing students to review the resources step by step, and defining the assessment time of the resources on the platform, so that the students finish the appointed resource learning within the appointed time. If the student does not finish the study of the resource within the appointed time, the score of the student in the course is counted as failing, and the student cannot take the end-of-term examination, so as to standardize and remind the student of an active study mode.
(2) A set of fragmented learning and assessment schemes based on university computer class courses is established
The score proportion of the current computer class courses of universities is the proportion of the ordinary times to the examination 2; the major games are put on end-of-term examinations, most colleges and universities begin to adjust the proportion of ordinary times and examinations along with the popularization of the engineering education mode, some colleges and universities are adjusted to 7,6; setting up the necessary and optional contents of resources in advance, and setting up the corresponding proportion; for the necessary repair content, the assessment sequence and the assessment time of the resources need to be set, for the optional repair content, the assessment time and the assessment content only need to be set, and in addition, the optional repair content accounts for 20% of the proportion of the ordinary achievement.
(3) Changes the current situation that no quantitative index exists in the usual performance examination and the examination quality cannot be monitored
The conventional ordinary performance examination basically takes homework, attendance, experimental reports and other contents as examination requirements, the completed contents are the same, the problem contents of each student are different, and the examination points are the same, so that students can copy each other when completing the homework after class, and teachers can not actually master the learning states of the students; through the management platform, teachers can establish a special question bank of the course in advance, different questions are set for the same knowledge point to carry out examination, so that when students finish learning resources, the examined knowledge points are the same, but the questions of each person are different, and a function of multi-time examination is provided, and the students can carry out multi-time examination until the students reach satisfactory scores; the examination questions of the same student are different when the same resource is examined every time, and the condition of complete question brushing is avoided. When students conduct self-test, the examination time and video collection are set so as to ensure that the students can finish the examination independently in the set time, teachers can call the monitoring videos at any time to review, and when cheating is found, the grades of the courses are directly cancelled.
(4) Provides a fragmentation interactive communication platform for students and teachers
Interactive communication is an indispensable link in designing this examination scheme, the mode of having lessons in the past is basically after having lessons, and the communication with mr is very few, now through when fragmentation resource study, can directly ask questions to this resource under the resource, when the teacher received this question, can receive the propelling movement message, can in time know the problem that the student met when studying after class, and in time reply in the platform, student and teacher can communicate many times, in order to reach the purpose of being close to the problem. Any teacher can disclose typical interactive records to form a common problem set, and can help students with the same problems in the learning process and frequently see the problems and master knowledge points skillfully. The common problem set can be stored for a long time, so that the common problem set is convenient for later students to check.
(5) Provides a pure question bank exercise mode, establishes a set of special question bank system based on knowledge points
The study after class has many ways, the general scheme is that the study knowledge points are consolidated by reading books, the resource platform is fragmented, and a set of special question banks based on the knowledge points are established to divide the question banks into various categories, namely an exercise question bank, a resource assessment special question bank and an examination special question bank. The question bank is associated on the basis of the knowledge points, and one question can correspond to a plurality of knowledge points for comprehensive assessment. The question banks are divided into various types, so that the question banks can be different when students practice, examine and take examinations, but the examination knowledge points are the same, and the mode that the students memorize hard backs by brushing questions is avoided.
Drawings
FIG. 1 is a tree diagram of the structure of a university computer class course management platform based on fragmented learning according to the present invention;
FIG. 2 is a flow chart of the work flow of the subjective question automatic judgment function system of the university computer class course management platform based on fragmented learning according to the present invention;
FIG. 3 is a flowchart of the intelligent teaching resource recommendation function system of the university computer class course management platform based on fragmented learning according to the present invention;
FIG. 4 is a flowchart of the user result interactive sharing function system of the university computer class course management platform based on fragmented learning according to the present invention;
FIG. 5 is a flowchart of the work flow of the professional routing learning function system of the university computer class course management platform based on fragmented learning according to the present invention;
FIG. 6 is a schematic diagram of the automatic subjective-question evaluation storage unit of the automatic subjective-question evaluation function system of the university computer class course management platform based on fragmented learning according to the present invention;
fig. 7 is a working principle diagram of a dynamic generation algorithm unit of the professional route planning learning function system of the university computer class course management platform based on fragmented learning according to the invention.
Detailed Description
As shown in fig. 1, the university computer class course management platform based on fragmented learning of the present invention includes a subjective question automatic evaluation function system 1, an intelligent recommended teaching resource function system 2, a user achievement interactive sharing function system 3, and a professional route planning learning function system 4.
The automatic subjective question evaluation functional system 1 is based on artificial intelligence, automatically divides words by a maximum forward matching method, matches keywords with an established word bank, performs fuzzy matching on sentence division processing, grammar similarity and patterns by adopting a dynamic programming algorithm, so as to achieve accurate simulation of manual scoring and realize automatic evaluation of subjective questions, and calculates comprehensive scores of students by adopting a Monte Carlo algorithm and analyzes the scores by using a big data cloud technology to realize evaluation of learning conditions of the students.
The automatic subjective question evaluation functional system 1 includes an automatic subjective question evaluation storage unit 10, an online evaluation unit 11 of a compiled language, and an SQL evaluation unit 12.
As shown in fig. 6, the subjective-subject automatic evaluation storage unit 10 is used to store correctness and error conditions of the source program submitted by students, which stores the source program submitted by students, a preset running time, test data provided by teachers, and test result data corresponding to the test data.
The online question judging unit 11 of the compiling type language adopts a complex algorithm to automatically judge the questions needing to be compiled of C language, C + +, java. The SQL question deciding unit 12 automatically decides the question of the SQL statement written by the student based on the docker container by using the shortest editing distance algorithm.
As shown in fig. 2, the work flow of the subjective question automatic evaluation function system 1 is:
firstly, compiling the job source program submitted by the automatic subjective question judging functional system 1, and if the compiling system outputs error information, indicating that the job submitted by the student has compiling error; secondly, the test data is redirected to input data, an executable file generated by compiling a homework source program submitted by a student is executed, and an output result of the program is redirected to a specific file for further processing in the next step; if overtime, the process is stopped and ended; thirdly, comparing the output result file with the test result file (standard answer), and if the output result file is the same as the test result file, outputting the correct answer and ending the operation; and finally, comparing the result file and the test result after providing a space and a carriage return character, if the result file and the test result are the same, outputting an answer with a wrong format and ending, otherwise, outputting an answer with a wrong format and ending.
The intelligent recommendation teaching resource function system 2 recommends the most appropriate learning materials for the user by using a content recommendation algorithm and a collaborative filtering recommendation algorithm based on a big data background and adopting a mixed recommendation algorithm (such as an algorithm of association, clustering, classification, regression, matrix decomposition, a neural network, a graph model and the like), so that excessive time waste is avoided, and the learning materials or low-grade materials are selected, thereby fully utilizing fragmentation time to learn.
The intelligent recommended teaching resource function system 2 includes a user behavior model unit 21 and a group user model unit 22. The user behavior model unit 21 is configured to build a user behavior model, that is, according to contents browsed by a user, an individual vector model is built as an interface between the user and a resource, big data analysis is performed on the behavior of the user, and relevant contents suitable for the user are pushed to the user. The group user model unit 22 is configured to add a group user model to the individual user model, and classify similar individual users into group users according to interests according to a clustering algorithm, so that after grouping, the interests of the group users are the synthesis of the interests of a plurality of similar individual users, and the individual users in the group can implement concept expansion by inheriting the interests of the group users, so that the recall ratio is improved.
The intelligent recommended teaching resource function system 2 can also provide the users with interest similarity obtained by clustering for collaborative learning or for network administrators to improve services; the intelligent recommendation teaching resource function system 2 automatically records the personalized access of the user to the resources, dynamically adjusts the behavior model of the user through the response ratio algorithm, and further adjusts the vector model of the user, thereby realizing the update and the storage of the personalized features of the user.
As shown in fig. 4, the user achievement interactive sharing functional system 3 is a system in which a user innovation achievement depends on cloud computing, a jar type interactive communication platform is built according to the characteristics of high reliability, virtualization and strong expansion, a plurality of special areas are arranged, different subjects are placed in different special areas, information of a user can be conveniently obtained, and meanwhile, management of an administrator is facilitated; based on the user achievement interactive sharing function system 3, the user can add a plurality of functions which cannot be realized on a message board system, and also realize extremely strong information interactivity of users from different places, and the user can make friends with wide view and expand the social surface of the user while obtaining the information required by the user.
The user result interactive sharing function system 3 comprises a user posting unit 31 and an uploading learning material unit 32.
The user post issuing unit 31 is used for a user to issue related posts in different regions, the posts can be discussed by other users after the audit of the administrator is passed, the posts can be scored by other users, the user achievement interactive sharing function system 3 pushes the essence posts to users with related interests, and the user can add other users as friends, so that more sufficient communication can be performed. The user post issuing unit 31 includes functions of user browsing, post issuing, user message leaving, and background auditing.
The learning material uploading unit 32 is used for users to upload learning resources in different areas, and the learning resources can be used by other users after being checked by the administrator. The learning material uploading unit 32 includes a learning material uploading function and a background auditing function.
As shown in fig. 3, the professional route planning learning functional system 4 performs a dynamic generation algorithm of a professional route planning learning path and a page synthesis algorithm of personalized learning on the basis of a big data planning algorithm, and provides a basis for the design and development of professional route planning learning; the students are advocated to be used as main bodies in professional route planning learning, the personalized learning of the students is used as a characteristic in intelligent professional route planning learning, and the organization of the domain knowledge and the intelligent navigation are basic problems for realizing the personalized learning in the intelligent professional route planning learning.
The professional route planning learning function system 4 includes a dynamic generation algorithm unit 41 of a professional route planning learning path; as shown in fig. 7, the dynamic generation algorithm unit 41 is configured to record the learning condition of the user according to the course knowledge structure, analyze the degree of mastering the relevant knowledge points, generate an individualized knowledge state diagram based on a big data algorithm, and generate a professional route planning learning function based on the knowledge state diagram and the knowledge structure in cooperation with a complex algorithm. The evaluation algorithm of different feature learning objects is as follows: firstly, the curriculum field experts define the weight of each relation, and then the field experts define different evaluation methods for students with different characteristics according to the curriculum learning characteristics and the learning method thereof.
The dynamic generation algorithm unit 41 includes a personalized evaluation algorithm, a big data analysis algorithm, and a dynamic path planning algorithm; the personalized evaluation algorithm is used for evaluating the learning behaviors of students with different learning characteristics; the big data analysis algorithm is used for analyzing the mastering degree of students on the related knowledge points according to the learning behaviors of a large number of students; the dynamic path planning algorithm is used for carrying out dynamic path planning according to the current mastery degree of the students on the knowledge points, and recommending the optimal learning path under the current state for the students.
The invention has reasonable concept, integrates four functions of automatic evaluation of subjective questions, intelligent recommendation of teaching resources, achievement sharing of users and professional route planning learning, is dedicated to learning after class and quantitative assessment of teachers on students, and provides most convenient and most effective fragmented learning service for vast learners.
Claims (7)
1. A university computer class course management platform based on fragmented learning, characterized in that: the management platform comprises a subjective question automatic evaluation function system, an intelligent recommended teaching resource function system, a user result interactive sharing function system and a professional route planning and learning function system;
the automatic subjective question judging functional system adopts a dynamic programming algorithm to carry out fuzzy matching on sentence division processing, grammar similarity and patterns, adopts a Monte Carlo algorithm to calculate comprehensive scores of students and uses a big data cloud technology to analyze the scores to realize the evaluation of the learning conditions of the students, and the working flow of the automatic subjective question judging functional system is as follows: firstly, compiling the job source program submitted by the automatic subjective question judging function system, and if the compiling system has error information output, indicating that the job submitted by the student has compiling error; secondly, test data is redirected to input data, an executable file generated by compiling a job source program submitted by a student is executed, an output result of the program is redirected to a specific file for further processing in the next step, and if the output result is overtime, the process is terminated and ended; then, comparing the output result file with the test result file, if the output result file is the same as the test result file, outputting the correct answer and finishing; finally, the result file and the test result are compared after a space and a carriage return character are provided, if the result file and the test result are the same, an output answer format is wrong and is finished, otherwise, the output answer is wrong and is finished, and then the comprehensive score of the student is calculated and analyzed to realize the evaluation of the learning condition of the student;
the intelligent recommendation teaching resource function system is used for recommending the most appropriate learning materials for the user so as to avoid excessive time waste for selecting the learning materials or low-grade materials and achieve the purpose of fully utilizing fragmentation time for learning;
the user achievement interactive sharing function system is characterized in that a user innovation achievement builds a discourse type interactive communication platform by relying on cloud computing, a plurality of special areas are arranged, different subjects are placed under different special areas, and information acquisition of users and management of administrators are facilitated;
the professional route planning learning function system is used for providing a basis for the design and development of professional route planning learning.
2. The fragmented learning-based university computer-like course management platform of claim 1, wherein: the subjective question automatic evaluation functional system adopts a dynamic programming algorithm to carry out fuzzy matching on the sentence division processing, the grammar similarity and the mode, adopts a Monte Carlo algorithm to calculate the comprehensive score of the student and uses a big data cloud technology to analyze the score to realize the evaluation of the learning condition of the student;
the automatic subjective question judging functional system comprises an automatic subjective question judging storage unit, an online compiling language question judging unit and an SQL question judging unit;
the subjective question automatic evaluation storage unit is used for storing the correctness and the error condition of the work source program submitted by the students, and the stored work source program submitted by the students, the preset running time, the test data provided by the teacher and the test result data corresponding to the test data;
the online question judging unit of the compiling type language automatically judges questions needing compiling of C language, C + +, java;
the SQL question judging unit is based on a docker container, adopts a shortest editing distance algorithm to automatically judge the SQL sentences written by students, and the subjective question judging units of other computer learning courses are graded on line by teachers.
3. The fragmented learning-based university computer-like course management platform of claim 1, wherein: the intelligent recommended teaching resource function system is based on a content recommendation algorithm and a collaborative filtering recommendation algorithm under a big data background, and adopts a mixed recommendation algorithm to recommend the most appropriate learning materials for the user; the intelligent recommended teaching resource function system comprises a user behavior model unit and a group user model unit;
the user behavior model unit is used for establishing a user behavior model, namely establishing an individual vector model as an interface between a user and a resource according to the content browsed by the user, carrying out big data analysis on the behavior of the user and pushing related content suitable for the user;
the group user model unit is used for adding a group user model on the individual user model, namely similar individual users are classified according to interests according to a clustering algorithm to generate group users, the interests of the grouped group users are the integration of the interests of a plurality of similar individual users, and the individual users in the group users can realize concept expansion by inheriting the interests of the group users, so that the recall ratio is improved.
4. The university computer-like course management platform based on fragmented learning according to claim 1 or 3, characterized in that: the intelligent recommended teaching resource function system can also provide users with interest similarity obtained by clustering for collaborative learning or for network administrators to improve services, automatically record the personalized access of the users to resources, dynamically adjust the behavior model of the users through a response ratio algorithm, and further adjust the vector model of the users, thereby realizing the updating and storage of the personalized features of the users.
5. The university computer-like course management platform based on fragmented learning of claim 1, wherein: the user result interactive sharing function system comprises a user post issuing unit and an uploading learning material unit;
the user post issuing unit is used for issuing related posts in different regions by a user, the posts can be discussed by other users after the audit of an administrator is passed, the posts can be scored by the other users, the user achievement interactive sharing function system can push the essence posts to users with related interests, and the users can also add other users as friends, so that more sufficient communication can be performed;
the learning data uploading unit is used for the user to upload learning resources in different special areas, and the learning resources can be used by other users after being checked by an administrator.
6. The university computer-like course management platform based on fragmented learning of claim 1, wherein: the professional route planning learning function system is a page synthesis algorithm for performing dynamic generation algorithm and personalized learning of a professional route planning learning path on big data by relying on a planning algorithm, and provides a basis for design and development of professional route planning learning;
the professional route planning learning function system comprises a dynamic generation algorithm unit of a professional route planning learning path; the dynamic generation algorithm unit is used for recording the learning condition of the user and analyzing the degree of mastering related knowledge points of the user according to the knowledge structure of the course, generating an individualized knowledge state diagram based on a big data algorithm, and generating a professional route planning learning function based on the knowledge state diagram and the knowledge structure in cooperation with a complex algorithm.
7. The university computer-like course management platform based on fragmented learning of claim 6, wherein: the dynamic generation algorithm unit comprises an individualized evaluation algorithm, a big data analysis algorithm and a dynamic path planning algorithm; the personalized evaluation algorithm is used for evaluating the learning behaviors of students with different learning characteristics; the big data analysis algorithm is used for analyzing the mastering degree of the students on the related knowledge points according to the learning behaviors of a large number of students; the dynamic path planning algorithm is used for carrying out dynamic path planning according to the current mastery degree of the students on the knowledge points, and recommending the optimal learning path under the current state for the students.
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