CN109255998B - Student score diagnosis and promotion system - Google Patents
Student score diagnosis and promotion system Download PDFInfo
- Publication number
- CN109255998B CN109255998B CN201811247516.0A CN201811247516A CN109255998B CN 109255998 B CN109255998 B CN 109255998B CN 201811247516 A CN201811247516 A CN 201811247516A CN 109255998 B CN109255998 B CN 109255998B
- Authority
- CN
- China
- Prior art keywords
- module
- student
- training
- test
- ability
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000003745 diagnosis Methods 0.000 title claims abstract description 103
- 238000012360 testing method Methods 0.000 claims abstract description 189
- 238000012549 training Methods 0.000 claims abstract description 118
- 230000003930 cognitive ability Effects 0.000 claims abstract description 45
- 238000004458 analytical method Methods 0.000 claims abstract description 44
- 230000002996 emotional effect Effects 0.000 claims abstract description 35
- 239000000463 material Substances 0.000 claims abstract description 11
- 238000002360 preparation method Methods 0.000 claims abstract description 9
- 230000003997 social interaction Effects 0.000 claims abstract description 7
- 230000001149 cognitive effect Effects 0.000 claims description 22
- 230000008451 emotion Effects 0.000 claims description 13
- 230000006872 improvement Effects 0.000 claims description 13
- 238000007405 data analysis Methods 0.000 claims description 9
- 238000004891 communication Methods 0.000 claims description 7
- 238000004519 manufacturing process Methods 0.000 claims description 7
- 238000000034 method Methods 0.000 claims description 5
- 230000008569 process Effects 0.000 claims description 5
- 238000000605 extraction Methods 0.000 claims description 4
- 230000008450 motivation Effects 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 238000007619 statistical method Methods 0.000 claims description 4
- 230000003936 working memory Effects 0.000 claims description 4
- 208000019901 Anxiety disease Diseases 0.000 claims description 3
- 230000036506 anxiety Effects 0.000 claims description 3
- 238000013508 migration Methods 0.000 claims description 3
- 230000005012 migration Effects 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 claims description 3
- 230000019771 cognition Effects 0.000 abstract 1
- 230000001737 promoting effect Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 10
- 230000003993 interaction Effects 0.000 description 10
- 230000004044 response Effects 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 230000007786 learning performance Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000006998 cognitive state Effects 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003909 pattern recognition Methods 0.000 description 1
- 238000012797 qualification Methods 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000035484 reaction time Effects 0.000 description 1
- 230000009257 reactivity Effects 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
- G09B7/02—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Educational Administration (AREA)
- Educational Technology (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Electrically Operated Instructional Devices (AREA)
Abstract
A student score diagnosis and promotion system belongs to the field of education. The system comprises an information acquisition module, a structured question bank, an online test module, a special subject training module, a test paper acquisition module, an accurate analysis module, a task issuing module, a learning condition tracking module, an electronic lesson preparation module and a social interaction module. The structured question bank stores questions marked by the knowledge points as labels. The online testing module tests the knowledge level, problem solving capability, cognitive ability and emotional ability of the student by using the structured question bank, and forms an individualized diagnosis report through the accurate analysis module; the thematic training module performs the training in the four aspects according to the report content; the accurate analysis module analyzes the information according to the test paper acquisition module and the online test module to obtain diagnosis information; the learning situation tracking module is used for feeding back the learning situation to teachers and parents. According to the invention, psychological cognition factors and emotional ability are introduced, the ability promoting path is effectively planned, training materials are recommended, and the comprehensive ability of students is improved.
Description
Technical Field
The invention relates to the field of intelligent education, in particular to a student score diagnosis and promotion system.
Background
In the field of education, how to accurately and efficiently diagnose and test the knowledge mastery condition of a testee is a hot problem of research. Modern test theory requires that a test result not only can give a test score or a capability score, but also provides diagnostic information of a testee, such as a knowledge structure, cognitive deficiency and the like.
Compared with the traditional paper test mode, the paper test system has the characteristics of justice, safety and high efficiency by utilizing a computer network test platform. The network test method for instantly making questions according to the answer condition by carrying out instant statistical analysis on the answer condition of a tested person is called self-adaptive test, can ensure that the ability level which is as accurate as possible can be obtained by using the number of the questions as less as possible, and can quickly analyze the knowledge ability level of the tested person. At present, the theories for the adaptive test are mainly Item Response Theory (Item Response Theory) and Knowledge Space Theory (Knowledge Space Theory).
The self-adaptive test based on the project reaction theory mainly considers the measurement accuracy, and aims to distinguish students with different levels as much as possible, and the attention on the knowledge structure is insufficient, so that the knowledge structure and the cognitive defects of the students cannot be investigated. The knowledge space theory is proposed by Jean-Claude Falmagne in 1985, is a psychological theory for testing knowledge level and knowledge structure of students, and the score of the psychological theory represents sum quantification of the mastery degree of a testee on related knowledge points.
At present, most researches on learning and diagnosing models based on knowledge space theory pursue how to diagnose the knowledge state of a testee most quickly with the fewest questions, and the emphasis is on a self-adaptive question selection strategy.
The invention starts from the perspective of wrong problem root causes of students, introduces problem solving capability, cognitive capability and emotional capability to extend and expand the knowledge space theory so as to achieve the aims of accurately evaluating the comprehensive capability of the students, accurately planning capability improvement paths, accurately recommending capability training materials and the like.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a student score diagnosis and promotion system which introduces problem solving capability, cognitive capability and emotional capability to help students promote comprehensive capability on the basis of self-adaptive test based on knowledge space theory.
The invention is realized by the following technical scheme:
the invention relates to a student score diagnosis and promotion system, which comprises:
the information acquisition module is used for acquiring information of teachers, students and parents;
the structured question bank stores questions marked by the knowledge points as labels, and builds a knowledge network according to the logical relationship among the knowledge points;
the online testing module is used for carrying out self-adaptive testing on the knowledge level of the student by utilizing the structured question bank, testing the problem solving capability, the cognitive capability and the emotional capability of the student, and transmitting a testing result serving as a data source to the accurate analysis module;
the special training module is used for training the students in the aspects of knowledge level, problem solving capability, cognitive capability and emotional capability according to the personalized diagnosis reports of the students, and the training results are used as data sources to feed back the updating precision analysis module and are also used for receiving task training issued by teachers through the task issuing module;
the test paper acquisition module is used for collecting and counting the information of the test paper of each course for the teacher to use, wherein the information of the test paper of each course comprises subject information and the scoring condition of students on each subject;
and the accurate analysis module is used for modeling and analyzing to obtain personalized diagnosis reports about the knowledge level, the problem solving capability, the cognitive capability and the emotional capability according to the information obtained by the test paper acquisition module, the online test module and the special training module, wherein the personalized diagnosis reports comprise class diagnosis reports, student diagnosis reports and group diagnosis reports for teachers and parents to use. The personalized diagnosis report compares the student test results transversely and longitudinally to form accurate user portrait, a learning path and a cultivation suggestion.
The task issuing module is used for a teacher to issue class tasks, student tasks and group tasks related to the knowledge level, the problem solving capability, the cognitive capability and the emotional capability based on the user requirements and combined with the structured question bank, and is also used for parents to issue student tasks related to the knowledge level, the problem solving capability, the cognitive capability and the emotional capability based on the user requirements and combined with the structured question bank;
the study situation tracking module is used for tracking the test of the online test module, the training of the special training module and the result data of the personalized diagnosis report, and feeding the tracked result data of the test of the online test module, the training of the special training module and the personalized diagnosis report back to teachers and parents;
the electronic lesson preparation module is used for preparing an electronic teaching plan by a teacher;
and the social interaction module is used for providing question answering, state reminding and task reminding for teachers and students, providing communication for teachers and parents and providing a platform for communication among teachers.
Preferably, the information acquisition module includes:
the teacher information acquisition unit is used for acquiring the name, sex, age, study level, working age, school, class of any education and job in school of a teacher;
the student information acquisition unit is used for acquiring names, sexes, ages, schools, grades, classes, class jobs, household nationalities and family conditions of students;
and the parent information acquisition unit is used for acquiring the name, the sex, the age, the name of a child and the family condition of a parent.
Preferably, the structured question bank is formed by analyzing and extracting a plurality of knowledge points aiming at the teaching and assisting materials, building a knowledge network according to the logical relation among the knowledge points and carrying out knowledge point label identification on the collected questions according to the problem solving step.
Preferably, the online test module includes:
the knowledge level testing unit is used for carrying out self-adaptive testing on the knowledge levels of students, including knowledge point mastering conditions and knowledge structure mastering conditions;
the problem solving capability testing unit is used for testing the problem solving capability of the students, including problem representation, mode identification, problem solving migration and problem solving monitoring;
the cognitive ability testing unit is used for testing basic cognitive ability and advanced cognitive ability of students, wherein the basic cognitive ability comprises working memory, processing speed, attention, reaction force and cognitive style, and the advanced cognitive ability comprises logical thinking, geometric imagination, computing ability and statistical analysis;
and the emotional ability testing unit is used for testing the social emotional ability, motivation, self-effectiveness and mathematical anxiety of the students.
Preferably, the thematic training module comprises:
the knowledge level training unit is used for performing knowledge level training according to the knowledge level test result of the individual diagnosis report of the student and by combining the structured question bank and the task issuing module, and feeding back and updating the knowledge level training result to the accurate analysis module;
the problem solving ability training unit is used for training the problem solving ability according to the problem solving ability test result of the personalized diagnosis report of the student and by combining the structured question bank and the task issuing module, and feeding back and updating the problem solving ability training result to the accurate analysis module;
the cognitive ability training unit is used for carrying out cognitive ability training according to the cognitive ability test result of the personalized diagnosis report of the student and feeding back and updating the cognitive ability training result to the accurate analysis module;
the emotion ability training unit is used for performing emotion ability training according to the emotion ability test result of the personalized diagnosis report of the student and feeding back and updating the emotion ability training result to the accurate analysis module;
and the task training unit is used for receiving the class tasks, the student tasks and the group tasks issued by the task issuing module so as to train the tasks of the students.
Preferably, the test paper collecting module includes:
the acquisition unit is used for collecting and counting test paper of each test,
the extraction unit is used for extracting the test paper information of the previous test and sending the test paper information to the accurate analysis module;
the test paper information of the historical test comprises question information, the scoring condition of students on each question and a knowledge point label used for identifying the knowledge point of the question, wherein the question information comprises a question number, a question type, a question full score and an affiliated textbook version.
Preferably, the accurate analysis module includes:
the test paper information acquisition unit is used for acquiring the test paper information of the test paper acquisition module in the previous test;
the online test result acquisition unit is used for acquiring test result information of the student online test module;
the special subject training result acquisition unit is used for acquiring training result information of the student special subject training module;
the accurate analysis unit is used for modeling and analyzing to obtain class diagnosis reports, student diagnosis reports and group diagnosis reports according to the information obtained by the test paper information acquisition unit, the online test result acquisition unit and the special training result acquisition unit, so as to be used by teachers and parents;
the class diagnosis report comprises a class accurate portrait, a data analysis chart and class cultivation suggestions, the student diagnosis report comprises a student accurate portrait, a data analysis chart and student cultivation suggestions, and the group diagnosis report comprises a group accurate portrait, a data analysis chart and group cultivation suggestions.
Preferably, the task issuing module includes:
the study condition acquisition unit is used for acquiring a class diagnosis report, a student diagnosis report and a group diagnosis report of the accurate analysis module and taking the class diagnosis report, the student diagnosis report and the group diagnosis report as user requirements;
and the task issuing unit is used for the teacher to issue class tasks, student tasks and group tasks to the special subject training module based on the user requirements and combined with the structured question bank, and is also used for the parents to issue the student tasks to the special subject training module based on the user requirements and combined with the structured question bank.
Preferably, the learning situation tracking module comprises:
the first tracking unit is used for tracking the test data of the online test module and respectively sending the tracked test data to the teacher end and the family end;
the second tracking unit is used for tracking report data of the personalized diagnosis report and respectively sending the tracked report data to the teacher end and the household end;
and the third tracking unit is used for tracking the training result data of the thematic training module and sending the tracked training result data to the teacher end and the captain end.
Preferably, the electronic lesson preparation module comprises:
the teaching plan sharing unit is used for sharing teaching plans among teachers;
the teaching plan manufacturing unit is used for manufacturing a teaching model and recording a teaching video;
the teaching note recording unit is used for recording teaching notes;
and the teaching plan sending unit is used for sending the teaching plan related to the knowledge points related to the teaching process to the task publishing module, and the task publishing module publishes the learning or video task of the related teaching plan so as to complete the thematic training conforming to the teaching plan.
The invention has the following beneficial effects:
the student score diagnosis and promotion system provided by the invention is mainly used for comprehensively extracting and forming a native knowledge point system and a knowledge network according to domestic course standards and teaching and assisting materials for three main bodies, teachers, students and parents, is smaller in granularity, and is more favorable for accurately positioning the knowledge state of the students. Meanwhile, on the basis of self-adaptive testing, the invention further extracts advanced cognitive ability and problem solving ability related to mathematics, introduces basic cognitive ability and emotional ability, comprehensively analyzes knowledge state, ability state and emotional state of students, and effectively plans an ability improvement path, recommends training materials, helps students improve learning performance and improves comprehensive ability from the perspective of user requirements according to different psychological cognitive characteristics of the students.
Drawings
FIG. 1 is a block diagram of a system architecture of a student score diagnosis and promotion system according to the present invention;
FIG. 2 is a block diagram of an information collection module in the student achievement diagnosis and improvement system according to the present invention;
FIG. 3 is a block diagram of an on-line testing module in the student score diagnosis and promotion system according to the present invention;
FIG. 4 is a block diagram of a subject training module in the student achievement diagnosis and improvement system of the present invention;
FIG. 5 is a block diagram of a test paper collection module in the student achievement diagnosis and improvement system of the present invention;
FIG. 6 is a block diagram of a precision analysis module in the student score diagnosis and promotion system according to the present invention;
FIG. 7 is a block diagram of a task publishing module in the student achievement diagnosis and improvement system of the present invention;
FIG. 8 is a block diagram of a learning situation tracking module in the student achievement diagnosis and improvement system according to the present invention;
FIG. 9 is a block diagram of an electronic lesson preparation module in the student achievement diagnosis and improvement system according to the present invention;
fig. 10 is a block diagram illustrating a social interaction module in the student achievement diagnosis and improvement system according to the present invention.
Detailed Description
The following are specific embodiments of the present invention and are further described with reference to the drawings, but the present invention is not limited to these embodiments.
The prior knowledge space theory mainly has three problems:
1. the knowledge space theory needs to determine the test content in advance and prepare the related subjects to investigate the test content, and Dr. Jean-Claude Falmagne et al adopt foreign teaching standards and class time arrangement and are not suitable for domestic situations.
2. The knowledge space theory simply divides the knowledge mastering conditions of students, including mastering and non-mastering states, does not subdivide the application conditions of the students to knowledge points, the combined mastering conditions of the knowledge points and the application conditions in specific scenes, and does not consider the possibility of guessing and errors of the students in the test process. If the student is asked orally to inquire a triangular area formula, the student can quickly answer the result of multiplying the base by the height by dividing by two, but the division by two is easily ignored in the actual problem solving process, and the student does not reach the stage of freely applying the knowledge point (automatic processing); or when the students independently calculate the area of the triangle, the students can not make mistakes, but are easy to lose scores in the combined operation of the area of the graph, which indicates that the students have problems in the combined application of the knowledge points; or the students do not have problems in mastering, application and combined application of knowledge points, but the errors are easily caused by various other problems in an actual scene, and the errors are unified and careless in the traditional education concept.
3. The knowledge space theory plans the learning path of the student according to the relation between the knowledge points without considering the individual characteristics of problem solving ability, cognitive ability, emotional ability and the like of the student.
Aiming at the problems, the invention provides a student score diagnosis and promotion system which is suitable for the teaching standard of China.
Referring to fig. 1, the system of the invention comprises an information acquisition module, a structured question bank, an online test module, a special subject training module, a test paper acquisition module, an accurate analysis module, a task issuing module, a learning situation tracking module, an electronic lesson preparation module and a social interaction module. The information acquisition module gathers the information of teacher, student, head of a family tripartite, and the system is known student's study condition to this tripartite of oriented to accurate aassessment student's overall state.
As shown in fig. 2, the information collection module includes a teacher information collection unit, a student information collection unit, and a parent information collection unit. The teacher information acquisition unit faces the teacher end and is used for acquiring the demographic information of the teacher, including name, gender, age, study level, working age, school, class of preschool education, duties in school and the like. The on-school jobs comprise the jobs of the teachers in the lectures, the jobs of the teams and the leaders, the jobs of the class group leaders and the like. The student information acquisition unit faces the student end and is used for acquiring demographic information of students, including names, sexes, ages, schools, grades, classes, class jobs, household nationalities, family conditions and the like. The parent information acquisition unit faces the parental terminal and is used for acquiring the demographic information of parents, including names, sexes, ages, names of children, family conditions and the like. The system can acquire the teaching level and the qualification of a teacher by using the information acquisition module, can acquire the learning degree of students and the basic general situation of family education at the same time, and ensures that the system is real and reliable to use.
The structured question bank stores questions marked by using knowledge points as labels, and experts build a knowledge network according to the logical relationship among the knowledge points. Specifically, an expert analyzes and extracts the existing teaching auxiliary materials to form a knowledge point system, a knowledge point network is built according to the logical relationship between knowledge points and teaching key points, and meanwhile, the knowledge point system and the knowledge point network are expanded through an artificial intelligent machine learning method, so that various knowledge points are well divided and relevant questions of the knowledge points are matched, the problem that the existing knowledge space theory simply divides the knowledge points is solved, and the mastering condition of students on the knowledge points, particularly the combination of the tiny knowledge points and the knowledge points, is accurately evaluated. For example, the teaching auxiliary materials of the primary school grades from 1 to 6 are analyzed and extracted to form more than four kinds of thousands of knowledge points such as numbers, algebras, graphic geometry, statistical probability, comprehensive practice and the like, and the collected primary school mathematics questions are labeled according to detailed steps by using the knowledge points to form a huge structured question bank. The primary school mathematics questions can be provided by teachers or from teaching materials or collected through a network or developed autonomously.
Referring to fig. 3, the online testing module faces the student side and includes a knowledge level testing unit, a problem solving ability testing unit, a cognitive ability testing unit, and an emotional ability testing unit. The knowledge level testing unit utilizes the structured question bank to carry out self-adaptive testing on the knowledge level of the student, including knowledge point mastering conditions and knowledge structure mastering conditions. The problem solving capability testing unit is used for testing the problem solving capability of the student, including problem representation, pattern recognition, problem solving migration and problem solving monitoring. The cognitive ability testing unit is used for testing basic cognitive ability and advanced cognitive ability of students. The basic cognitive ability comprises the aspects of working memory, processing speed, attention, reaction force, cognitive style and the like. The working memory can be tested by testing the maximum unit block, such as several numbers and several groups of numbers, which the student can remember once. The testing of the machining speed may be accomplished by testing how fast or slow different cognitive operations are performed, such as the time required to rotate a geometric body to a certain position. The attention tests include tests of attention stability, which refers to the average time that a certain object can be continuously noticed, and attention span, which refers to the number of objects that can be simultaneously assigned attention. The test of the reactivity includes a simple reaction to test a response immediately and a selection of a reaction time. The cognitive style test is implemented by how to analyze the problem, such as independent thinking or combining other opinions, analyzing the problem globally or cutting in from clues. The test of the high-level cognitive ability refers to the test of the cognitive ability related to mathematics, including four aspects of logical thinking, geometric imagination, computing ability and statistical analysis. The emotional ability testing unit is used for testing the social emotional ability, motivation, self-effectiveness, mathematics anxiety and other aspects of the students. For example, senior students adopt a scale self-evaluation to realize a test, and the students report whether the content of the emotional ability test is met or not; and the students in the lower grades can select answers according with the actual responses according to the scenes through the situational tests.
As shown in fig. 4, the thematic training module faces the student side, and includes a knowledge level training unit, a problem solving ability training unit, a cognitive ability training unit, an emotional ability training unit, and a task training unit. The special training module is realized based on the online testing module, and the targeted training is improved according to the weak point condition of the student ability detected by the online testing module. For example, two students scoring the same on two rolls, the online test module can test to obtain that one student has poor mastery degree on the knowledge points, and the other student has weak advanced cognitive ability, and performs targeted training according to the test result to ensure the maximization of learning efficiency. The online testing module and the special topic training module are used for analyzing the answer condition of the student to the topic, namely, the answer condition is obtained based on wrong topic root cause analysis.
Specifically, the knowledge level training unit is used for performing knowledge level training according to the knowledge level test result of the personalized diagnosis report of the student and in combination with the structured question bank, feeding back the knowledge level training result to the accurate analysis module, and updating the knowledge level grade in the personalized diagnosis report in real time. And the problem solving capability training unit is used for training the problem solving capability according to the problem solving capability test result of the personalized diagnosis report of the student, combining the structured question bank and the task publishing module, feeding the problem solving capability training result back to the accurate analysis module, and immediately updating the problem solving capability grade in the personalized diagnosis report. And the cognitive ability training unit is used for carrying out cognitive ability training according to the cognitive ability test result of the personalized diagnosis report of the student, feeding back the cognitive ability training result to the accurate analysis module and updating the cognitive ability grade of the personalized diagnosis report in real time. And the emotion ability training unit is used for performing emotion ability training according to the emotion ability test result of the personalized diagnosis report of the student, feeding back the emotion ability training result to the accurate analysis module, and immediately updating the emotion ability training level in the personalized diagnosis report. The knowledge level grade, the problem solving capability grade, the cognitive capability grade and the emotional capability grade are determined by forming a general sample normal model according to the knowledge level, the problem solving capability, the cognitive capability and the emotional capability distribution in a general student sample, calculating the percentile of the student in the normal model and then determining which grade the student belongs to.
The special subject training module also comprises a task training unit which is used for receiving class tasks, student tasks and group tasks issued by the task issuing module so as to train the students on tasks. The result of task training includes learning condition and action data, learning condition mainly refers to what questions the question was done to, action data mainly refers to the time spent doing the question and other interactive behaviors, if feel can't do direct exit etc. accurate analysis module can carry out the renewal evaluation to student's each aspect according to student's learning condition and action data, if from doing the mistake to doing the right, show that student's mastery degree to knowledge point promotes to some extent. Tasks in addition to doing a question, there may be other forms of tasks such as a mini-game, a team collaborative project practice, getting home to say i love you with dad and mom, and so on.
As shown in fig. 5, the test paper collection module faces the teacher end and includes a collection unit and an extraction unit. The acquisition unit is used for collecting and counting test paper of each test. The test paper of each test can be a test paper of school test or a test paper from a network. The extraction unit is used for extracting the test paper information of the previous test and sending the test paper information to the accurate analysis module. The test paper information of the past times comprises question information, the scoring condition of students on each question and corresponding knowledge point labels printed on the questions by experts, wherein the question information comprises question numbers, question types, question full scores, affiliated textbook versions and the like.
As shown in fig. 6, the precision analysis module faces the teacher end and includes a test paper information obtaining unit, an online test result obtaining unit, a thematic training result obtaining unit, and a precision analysis unit. The test paper information acquisition unit is used for acquiring the test paper information of the test paper acquisition module in the previous test. The accurate analysis module obtains an individualized diagnosis report after analysis, and the content of the individualized diagnosis report comprises transverse and longitudinal comparison of student test results, accurate user image, learning path and training suggestion. And the online test result acquisition unit is used for acquiring the test result information of the student online test module. And the special training result acquisition unit is used for acquiring training result information of the student special training module. The accurate analysis unit is used for modeling and analyzing to obtain personalized diagnosis reports according to the information obtained by the test paper information obtaining unit, the online test result obtaining unit and the special training result obtaining unit, and the personalized diagnosis reports comprise class diagnosis reports, student diagnosis reports and group diagnosis reports. The class diagnosis report comprises a class accurate portrait, a data analysis chart and class cultivation suggestions, the student diagnosis report comprises a student accurate portrait, a data analysis chart and student cultivation suggestions, and the group diagnosis report comprises a group accurate portrait, a data analysis chart and group cultivation suggestions. The group can divide students into the following according to the grade: the preferential equal student population and the poor equal student population, or the populations can be divided into the following groups according to the mastery conditions of different knowledge points: populations with poor geometric abilities, poor statistical abilities, etc., or the populations may be divided according to different cognitive abilities: groups with better basic cognitive ability, groups with better advanced cognitive ability and the like, or the groups can be divided into the following groups according to different emotional abilities: groups with better learning motivation, groups with poorer self-potency feeling and the like, or the groups can be divided into the following groups according to the common expression of knowledge level and cognitive ability: populations of basal types, etc. On the basis of examination paper collection module, accurate analysis module can accumulate, model the model, handle and the analysis to data, provides the categorised diagnosis report of different main parts respectively, and the help teacher knows the whole condition of the class of religion more comprehensively accurately, including the contrast condition of each student's condition and all students of class in the class to in time adjust the teaching scheme, reach the effect of executing the teaching according to the circumstances.
As shown in fig. 7, the task issuing module faces the teacher end and the parent end, and includes a learning situation acquiring unit and a task issuing unit. The study condition acquisition unit is used for acquiring class diagnosis reports, student diagnosis reports and group diagnosis reports of the precise analysis module and taking the class diagnosis reports, the student diagnosis reports and the group diagnosis reports as user requirements. The task issuing unit can issue class tasks or group tasks or student tasks by using the structured question bank and an accurate recommendation algorithm based on user requirements according to an analysis result of the accurate analysis module, and can issue student tasks by using the structured question bank and the accurate recommendation algorithm based on the user requirements, so that students can be helped to perform targeted ability tutoring training.
As shown in fig. 8, the learning context tracking module faces to a teacher end, a student end and a parent end, and includes a first tracking unit, a second tracking unit and a third tracking unit. And the first tracking unit is used for tracking the test data of the online test module and respectively sending the tracked test data to the teacher end and the family end. The test data comprises test result data and behavior data of knowledge level, problem solving ability, cognitive ability and emotional ability. And the second tracking unit is used for tracking report data of the personalized diagnosis report, including newly generated report data and updated report data, and respectively sending the tracked report data to the teacher end and the household end. And the third tracking unit is used for tracking the training result data of the thematic training module and sending the tracked training result data to the teacher end and the captain end. The training result data comprises training result data of knowledge level, problem solving ability, cognitive ability and emotional ability and behavior data. The student situation tracking module facing the student end is used for collecting the testing and training results of the online testing module and the thematic training module, and the results are fed back to the student situation tracking module facing the teacher end and the student situation tracking module facing the chief end in real time through the testing and training results, so that the teacher can accurately master the learning dynamics of students, and parents can know the recent online testing, thematic training and other conditions of the students.
As shown in fig. 9, the electronic lesson preparation module faces to the teacher end and is used for preparing an electronic teaching plan by the teacher. The electronic lesson preparation module comprises a teaching plan sharing unit, a teaching plan manufacturing unit, a teaching note recording unit and a teaching plan sending unit. The teaching plan sharing unit is used for teachers to share teaching plans, and the teachers share the manufactured teaching plans on the system for other teachers to use and refer. And the teaching plan manufacturing unit is used for manufacturing teaching models and recording teaching videos. And the teaching note recording unit is used for recording teaching notes. The above units provide accurate recommendations for teaching materials. The teaching plan sending unit is used for sending teaching plans related to knowledge points in the teaching process to the task issuing module, and requiring students to complete tasks of learning or video watching of the related teaching plans so as to complete thematic training conforming to the teaching plans.
As shown in fig. 10, the social interaction module faces the teacher end, the student end, and the master end, and is configured to provide question answering, status reminding, and task reminding for the teacher and the students, provide communication for the teacher and the parents, and provide a platform for communication among the teachers. The social interaction module comprises a teacher interaction unit, a teacher and student interaction unit, a teacher and parent interaction unit, a student interaction unit and a parent interaction unit. The teacher interaction unit is used for communicating and communicating academies among a plurality of teachers, sharing the results of teaching, and seeking help to the problem of hot points and difficulties so as to perfect a teaching scheme and a teaching means. The teacher and student interaction unit is used for helping the teacher to consult and answer questions, remind the student to pre-study and do homework, and remind the teacher of abnormal states of the student, including learning states, emotional states, cognitive states and the like. The teacher and parent interaction unit is used for the teacher to communicate with the parents to study the situation in school and at home. The student interaction unit is used for informing the difficult and difficult problems of the inter-student ditches and participating in project practice activities in team cooperation and the like. The parent interaction unit is used for communication among a plurality of parents so as to urge students to learn well at home and perfect the good education state of the family.
On the basis of self-adaptive testing based on knowledge space theory, advanced cognitive ability and problem solving ability related to mathematics are further extracted, basic cognitive ability and emotional ability are introduced, knowledge states, ability states and emotional states of students are comprehensively analyzed, and according to different psychological cognitive characteristics of the students, ability improvement paths are effectively planned, training materials are recommended, and the students are helped to improve learning performance and comprehensive ability. It will be appreciated by persons skilled in the art that the embodiments of the invention described above and shown in the drawings are given by way of example only and are not limiting of the invention. The objects of the present invention have been fully and effectively accomplished. The functional and structural principles of the present invention have been shown and described in the examples, and any variations or modifications of the embodiments of the present invention may be made without departing from the principles.
Claims (7)
1. A student performance diagnostic enhancement system, comprising:
the information acquisition module is used for acquiring information of teachers, students and parents;
the structured question bank stores questions marked by the knowledge points as labels, and builds a knowledge network according to the logical relationship among the knowledge points;
the online testing module is used for carrying out self-adaptive testing on the knowledge level of the student by utilizing the structured question bank, testing the problem solving capability, the cognitive capability and the emotional capability of the student, and transmitting a testing result serving as a data source to the accurate analysis module; the online test module comprises:
the knowledge level testing unit is used for carrying out self-adaptive testing on the knowledge levels of students, including knowledge point mastering conditions and knowledge structure mastering conditions;
the problem solving capability testing unit is used for testing the problem solving capability of the students, including problem representation, mode identification, problem solving migration and problem solving monitoring;
the cognitive ability testing unit is used for testing basic cognitive ability and advanced cognitive ability of students, wherein the basic cognitive ability comprises working memory, processing speed, attention, reaction force and cognitive style, and the advanced cognitive ability comprises logical thinking, geometric imagination, computing ability and statistical analysis;
the emotional ability testing unit is used for testing the emotional ability of the students about social emotional ability, motivation, self-effectiveness feeling and mathematic anxiety;
the special training module is used for training the students in the aspects of knowledge level, problem solving capability, cognitive capability and emotional capability according to the personalized diagnosis reports of the students, and the training results are used as data sources to feed back the updating precision analysis module and are also used for receiving task training issued by teachers and parents through the task issuing module; the thematic training module comprises:
the knowledge level training unit is used for performing knowledge level training according to the knowledge level test result of the individual diagnosis report of the student and by combining the structured question bank and the task issuing module, and feeding back and updating the knowledge level training result to the accurate analysis module;
the problem solving ability training unit is used for training the problem solving ability according to the problem solving ability test result of the personalized diagnosis report of the student and by combining the structured question bank and the task issuing module, and feeding back and updating the problem solving ability training result to the accurate analysis module;
the cognitive ability training unit is used for carrying out cognitive ability training according to the cognitive ability test result of the personalized diagnosis report of the student and feeding back and updating the cognitive ability training result to the accurate analysis module;
the emotion ability training unit is used for performing emotion ability training according to the emotion ability test result of the personalized diagnosis report of the student and feeding back and updating the emotion ability training result to the accurate analysis module;
the task training unit is used for receiving class tasks, student tasks and group tasks issued by the task issuing module so as to train the tasks of the students;
the test paper acquisition module is used for collecting and counting the information of the test paper of each course for the teacher to use, wherein the information of the test paper of each course comprises subject information and the scoring condition of students on each subject;
the accurate analysis module is used for modeling and analyzing to obtain personalized diagnosis reports about knowledge level, problem solving capability, cognitive ability and emotional ability according to the information obtained by the test paper acquisition module, the online test module and the special training module, wherein the personalized diagnosis reports comprise class diagnosis reports, student diagnosis reports and group diagnosis reports for teachers and parents to use; the accurate analysis module includes:
the test paper information acquisition unit is used for acquiring the test paper information of the test paper acquisition module in the previous test;
the online test result acquisition unit is used for acquiring test result information of the student online test module;
the special subject training result acquisition unit is used for acquiring training result information of the student special subject training module;
the accurate analysis unit is used for modeling and analyzing to obtain class diagnosis reports, student diagnosis reports and group diagnosis reports according to the information obtained by the test paper information acquisition unit, the online test result acquisition unit and the special training result acquisition unit, so as to be used by teachers and parents;
the class diagnosis report comprises a class accurate portrait, a data analysis chart and class cultivation suggestions, the student diagnosis report comprises a student accurate portrait, a data analysis chart and student cultivation suggestions, and the group diagnosis report comprises a group accurate portrait, a data analysis chart and group cultivation suggestions;
the task issuing module is used for a teacher to issue class tasks, student tasks and group tasks related to the knowledge level, the problem solving capability, the cognitive capability and the emotional capability based on the user requirements and combined with the structured question bank, and is also used for parents to issue student tasks related to the knowledge level, the problem solving capability, the cognitive capability and the emotional capability based on the user requirements and combined with the structured question bank;
the study situation tracking module is used for tracking the test of the online test module, the training of the special training module and the result data of the personalized diagnosis report, and feeding the tracked result data of the test of the online test module, the training of the special training module and the personalized diagnosis report back to teachers and parents;
the electronic lesson preparation module is used for preparing an electronic teaching plan by a teacher;
and the social interaction module is used for providing question answering, state reminding and task reminding for teachers and students, providing communication for teachers and parents and providing a platform for communication among teachers.
2. The student achievement diagnosis and improvement system of claim 1, wherein the information collection module comprises:
the teacher information acquisition unit is used for acquiring the name, sex, age, study level, working age, school, class of any education and job in school of a teacher;
the student information acquisition unit is used for acquiring names, sexes, ages, schools, grades, classes, class jobs, household nationalities and family conditions of students;
and the parent information acquisition unit is used for acquiring the name, the sex, the age, the name of a child and the family condition of a parent.
3. The student achievement diagnosis and promotion system of claim 1, wherein the structured question bank is formed by constructing a knowledge network according to logical relations among knowledge points and performing knowledge point label identification on collected questions according to question solving steps after analyzing and extracting a plurality of knowledge points aiming at teaching and assisting materials.
4. The student achievement diagnosis and improvement system of claim 1, wherein the test paper collection module comprises:
the acquisition unit is used for collecting and counting test paper of the previous test;
the extraction unit is used for extracting the test paper information of the previous test and sending the test paper information to the accurate analysis module;
the test paper information of the historical test comprises question information, the scoring condition of students on each question and a knowledge point label used for identifying the knowledge point of the question, wherein the question information comprises a question number, a question type, a question full score and an affiliated textbook version.
5. The student achievement diagnosis and improvement system of claim 1, wherein the task issuing module comprises:
the study condition acquisition unit is used for acquiring a class diagnosis report, a student diagnosis report and a group diagnosis report of the accurate analysis module and taking the class diagnosis report, the student diagnosis report and the group diagnosis report as user requirements;
and the task issuing unit is used for the teacher to issue class tasks, student tasks and group tasks to the special subject training module based on the user requirements and in combination with the structured question bank, and is also used for the parents to issue the student tasks to the special subject training module based on the user requirements and in combination with the structured question bank.
6. The student achievement diagnosis and promotion system of claim 1, wherein the learning situation tracking module comprises:
the first tracking unit is used for tracking the test data of the online test module and respectively sending the tracked test data to the teacher end and the family end;
the second tracking unit is used for tracking report data of the personalized diagnosis report and respectively sending the tracked report data to the teacher end and the household end;
a third tracking unit for tracking the training result data of the thematic training module,
and the tracked training result data is sent to the teacher end and the family end.
7. The student achievement diagnosis and promotion system of claim 1, wherein the electronic lesson preparation module comprises:
the teaching plan sharing unit is used for sharing teaching plans among teachers;
the teaching plan manufacturing unit is used for manufacturing a teaching model and recording a teaching video;
the teaching note recording unit is used for recording teaching notes;
and the teaching plan sending unit is used for sending the teaching plan related to the knowledge points related to the teaching process to the task publishing module, and the task publishing module publishes the learning or video watching task of the related teaching plan so as to complete the thematic training conforming to the teaching plan.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811247516.0A CN109255998B (en) | 2018-10-25 | 2018-10-25 | Student score diagnosis and promotion system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811247516.0A CN109255998B (en) | 2018-10-25 | 2018-10-25 | Student score diagnosis and promotion system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109255998A CN109255998A (en) | 2019-01-22 |
| CN109255998B true CN109255998B (en) | 2021-04-13 |
Family
ID=65045724
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811247516.0A Active CN109255998B (en) | 2018-10-25 | 2018-10-25 | Student score diagnosis and promotion system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109255998B (en) |
Families Citing this family (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109754659A (en) * | 2019-03-14 | 2019-05-14 | 四川米图优图教育信息咨询服务有限公司 | A kind of culture process and intelligent tutoring auxiliary system |
| CN110070232B (en) * | 2019-04-28 | 2021-06-18 | 东北大学 | Method for multi-dimensional student score prediction by introducing teacher teaching style |
| CN110021208A (en) * | 2019-05-16 | 2019-07-16 | 上海乂学教育科技有限公司 | For the efficient training method and system of English Reading topic |
| CN110490467A (en) * | 2019-08-22 | 2019-11-22 | 常州易学网络科技有限公司 | A kind of students in middle and primary schools' school work capability comparison method and system |
| CN110598777B (en) * | 2019-09-03 | 2022-12-27 | 中国科学院深圳先进技术研究院 | Data processing method and system based on end cloud cooperation |
| CN110718105B (en) * | 2019-10-10 | 2021-12-07 | 江苏曲速教育科技有限公司 | Personalized personal vacation exercise book, generation method and use method |
| CN110807173A (en) * | 2019-10-15 | 2020-02-18 | 广州摩翼信息科技有限公司 | Studying situation analysis method and device, computer equipment and storage medium |
| CN110930033A (en) * | 2019-11-25 | 2020-03-27 | 南昌航空大学 | Method for presenting college student English reading cognitive diagnosis report |
| CN110728868A (en) * | 2019-11-27 | 2020-01-24 | 墨子(深圳)人工智能技术有限公司 | Intelligent device for learning training and implementation method |
| CN111179664A (en) * | 2020-01-20 | 2020-05-19 | 安徽明思科技有限公司 | Innovative ability evaluation system for artificial intelligence education |
| CN111739366B (en) * | 2020-07-21 | 2022-05-24 | 山东培立优教育科技有限公司 | Self-adaptive pre-examination sprint online learning method and system based on self-consistency system |
| CN112419824A (en) * | 2020-12-01 | 2021-02-26 | 青岛凌鼎智能科技有限公司 | Interactive fire control simulation training system |
| CN112614391A (en) * | 2020-12-22 | 2021-04-06 | 贵州树精英教育科技有限责任公司 | Learning promotion system based on ability level |
| CN112686462A (en) * | 2021-01-06 | 2021-04-20 | 广州视源电子科技股份有限公司 | Student portrait-based anomaly detection method, device, equipment and storage medium |
| CN113240961A (en) * | 2021-05-19 | 2021-08-10 | 江苏博而雅教育科技有限公司 | Training system and method for improving problem solving ability based on deep learning |
| CN113254629B (en) * | 2021-06-07 | 2022-07-26 | 重庆第二师范学院 | Learning content recommendation method and system based on artificial intelligence |
| CN114358425A (en) * | 2022-01-06 | 2022-04-15 | 杭州数理大数据技术有限公司 | Test question selection method and device, electronic equipment and storage medium |
| CN116504271B (en) * | 2023-05-15 | 2024-03-19 | 杭州企智互联科技有限公司 | Operation release management system for intelligent campus |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003009474A2 (en) * | 2001-07-18 | 2003-01-30 | Wireless Generation, Inc. | System and method for real-time observation assessment |
| CN101000600A (en) * | 2006-12-30 | 2007-07-18 | 南京凌越教育科技服务有限公司 | Study management system and method |
| CN101958062A (en) * | 2009-07-17 | 2011-01-26 | 成都中医药大学 | System for traditional Chinese medicine and western medicine clinical diagnosis training |
| CN102201177A (en) * | 2011-06-23 | 2011-09-28 | 北京新东方教育科技（集团）有限公司 | Self-adapting evaluation method and system |
| CN103531046A (en) * | 2013-10-29 | 2014-01-22 | 广东小天才科技有限公司 | Learning monitoring method and device based on usage data of learning product |
| CN104240544A (en) * | 2014-09-25 | 2014-12-24 | 肖显全 | System combining intelligent knowledge diagnosing and teacher online tutoring |
| CN104268812A (en) * | 2014-09-25 | 2015-01-07 | 肖显全 | Mobile terminal comprehensive learning system based on massive learning resources |
| CN104966427A (en) * | 2015-05-27 | 2015-10-07 | 北京创数教育科技发展有限公司 | Self-adaptation teaching interaction system and method |
| CN104978630A (en) * | 2015-06-19 | 2015-10-14 | 百度在线网络技术（北京）有限公司 | Intelligent test method and apparatus |
| CN108665394B (en) * | 2018-05-07 | 2021-11-30 | 北京文华在线教育科技股份有限公司 | Self-adaptive learning method and system |
| CN108629717A (en) * | 2018-07-02 | 2018-10-09 | 芜湖通全电子电器科技创业有限公司 | A kind of enterprise technology training system and method based on computer networking technology |
-
2018
- 2018-10-25 CN CN201811247516.0A patent/CN109255998B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN109255998A (en) | 2019-01-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109255998B (en) | Student score diagnosis and promotion system | |
| McCroskey et al. | Toward a general model of instructional communication | |
| Rock et al. | Assessment issues in the testing of children at school entry | |
| Saraç et al. | On-line and off-line assessment of metacognition | |
| Seemiller et al. | How generation Z college students prefer to learn: a comparison of US and Brazil students | |
| Bloom | Toward a theory of testing which includes measurement-evaluation-assessment | |
| Zamzam et al. | Error analysis of newman to solve the geometry problem in terms of cognitive style | |
| CN110232343B (en) | Child personalized behavior statistical analysis system and method based on latent variable model | |
| CN110472808A (en) | Deagnostic test method and device | |
| Muslihin et al. | Analysis of the Reliability and Validity of the Self-Determination Questionnaire Using Rasch Model. | |
| Hardegree | Standards-based assessment and high stakes testing: Accuracy of standards-based grading | |
| Ingram et al. | Observing Effective Mathematics Teaching: A Review of the Literature. | |
| Simonson | Attitude measurement: Why and how | |
| Valle et al. | Multiple goals and homework involvement in elementary school students | |
| Tileston | What every teacher should know about student assessment | |
| Reyes | Social research: A deductive approach | |
| Lucksnat et al. | Comparing the teaching quality of alternatively certified teachers and traditionally certified teachers: Findings from a large-scale study | |
| Arieli-Attali et al. | Beyond correctness: development and validation of concept-based categorical scoring rubrics for diagnostic purposes | |
| Krishna | Examination system | |
| Ioannou | The dynamic model of educational effectiveness tested by investigating the impact of classroom level factors on slow learners' outcomes in language: an effectiveness study on a specific student population | |
| Tacke et al. | Behavioral changes in teachers as a function of student feedback: A case for the achievement motivation theory? | |
| Valen-Dacanay et al. | Exploring The Learning Analytics Of Skill-Based Course Using Machine Learning Classification Models | |
| Gaines et al. | School accountability reports: Lessons learned in SREB states. | |
| Whitebread et al. | Patterns of children's emotional responses to mathematical problem-solving | |
| De Pace | Concept Maps for Middle School Computer Science Assessment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |