CN112184503A - Children multinomial ability scoring method and system for preschool education quality evaluation - Google Patents
Children multinomial ability scoring method and system for preschool education quality evaluation Download PDFInfo
- Publication number
- CN112184503A CN112184503A CN202010993460.4A CN202010993460A CN112184503A CN 112184503 A CN112184503 A CN 112184503A CN 202010993460 A CN202010993460 A CN 202010993460A CN 112184503 A CN112184503 A CN 112184503A
- Authority
- CN
- China
- Prior art keywords
- scoring
- module
- children
- test
- test question
- 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.)
- Pending
Links
Images
Classifications
-
- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
Abstract
The invention discloses a method and a system for scoring multiple abilities of children for preschool education quality evaluation, wherein the method comprises the following steps: directionally dividing test question sets according to five fields of preschool education and constructing a knowledge base; utilizing AR or VR technology to scene each test question in the test question set; directionally acquiring related index data of a tested child in the process of answering a current test question; quantitatively storing the index data according to types to serve as original data; extracting characteristic data in the original data by using an AI technology; calling investigation knowledge points matched with the characteristic data in the knowledge base, and determining a score calculation method according to the investigation knowledge points; obtaining the scoring value of each investigation knowledge point related to the current test question by using a score calculation method; and quantitatively calculating and outputting a final scoring value, and qualitatively outputting an evaluation result and a guidance opinion according to the final scoring value. The invention can carry out objective, automatic and intelligent evaluation on the preschool education quality.
Description
Technical Field
The invention relates to the technical field of preschool education, in particular to a method and a system for scoring multiple abilities of children for evaluating preschool education quality.
Background
In the evaluation of education quality, the assessment and monitoring of the language ability development results of preschool children are the most important contents and are also an important factor influencing the education quality. In China, 3-6 years old children's study and development guidelines divide kindergarten education into five major fields of health, language, society, science and art according to the scope of infant study and activities, and language is only next to the important position of health and is the field of key cultivation and development. Due to the interpenetration of the five major fields, language ability has influence on the development of cognitive ability, sociality and emotion of infants.
The evaluation of the preschool education quality is an effective way for improving the preschool education quality, but the standard and the system for objectively evaluating the preschool education quality are not established in China. The existing preschool education evaluation has the defects of long evaluation period, single evaluation index and the like, and has limitation and influence on the long-term development of infants and informatization of preschool education in many aspects. In addition, the existing evaluation mode mainly depends on preschool education specialists teachers, and has the limitation of strong individual subjective consciousness. Because the tasks of preschool education teachers and resources in China are heavy, one teacher faces dozens of preschool children on average, the traditional method is to use an expression form evaluation method, the teacher needs to develop one by one, the teacher or voice standardization degree, the expression mode, the operation process and the scoring standard are different, more manual judgments are introduced along with the increase of the number, more measurement errors are brought, and the reliability of the measurement result is influenced. Even if the AHP hierarchical analysis method which is the currently accepted education comprehensive ability evaluation method is used in the current preschool education field, the defects of the expert consultation method for weight setting, subjective weight optimization and the like still exist. For the method of evaluating the preschool education quality by relying on the traditional statistical analysis, professional evaluation scene setting is needed, the test time is long, and higher attention of children is needed, for example, a multispectral evaluation method needs dozens of minutes for testing one language item, and if the test is to be implemented in each field of a multivariate intelligent evaluation method, longer time is needed. The problem of information asymmetry is ubiquitous in preschool education markets, and due to the existence of the problem of information asymmetry, a lot of problems are derived from the preschool education markets, the problems comprise that the preschool education markets with poor quality are flooded, the prices of high-end preschool schools are high, the markets are in low-level balance, the preschool school publicity is substantial, and a long-term mechanism for solving the problem of information asymmetry is to try to improve the education quality of preschool education institutions and monitor and evaluate the quality of the preschool education institutions. The construction of a scientific and perfect preschool education quality evaluation system plays an important role in improving the preschool education quality.
Therefore, it is an urgent need to solve the problem of providing a scoring method and system that can objectively, automatically and intelligently score the preschool education quality.
Disclosure of Invention
In view of the above, the invention provides a method and a system for scoring the multi-item abilities of children for pre-school education quality evaluation, which utilize immersion type VR/AR technology, sound collection and intelligent analysis, bone behavior video capture and pictures and other means, and comprehensively utilize a pre-school education testing method to achieve maximum scoring of the pre-school education quality of children. The method can effectively reduce the influence of artificial subjective scoring, and can automatically and intelligently perform objective evaluation on preschool children education.
In order to achieve the purpose, the invention adopts the following technical scheme:
a child multi-competence scoring method for preschool education quality assessment, comprising:
s1, directionally dividing test question sets according to five fields of preschool education, and constructing a knowledge base corresponding to the test question sets;
s2, utilizing AR or VR technology to scene each test question in the test question set;
s3, directionally collecting related index data of the tested children in the process of answering the current test questions;
s4, quantitatively storing the index data according to types to serve as original data;
s5, extracting feature data in the original data by using an AI technology;
s6, retrieving investigation knowledge points matched with the feature data in the knowledge base, and determining a score calculation method according to the investigation knowledge points;
s7, obtaining the scoring value of each investigation knowledge point related to the current test question by using the score calculation method;
and S8, quantitatively calculating and outputting a final scoring value, and qualitatively outputting an evaluation result and a guidance opinion according to the final scoring value.
Preferably, in the above method for scoring the multiple abilities of children for the assessment of preschool education quality, the size and duration of the test questions in each of the test question sets in S1 may be dynamically adjusted as necessary.
Preferably, in the above method for scoring the multiple abilities of children for the assessment of preschool education quality, the knowledge base in S1 includes a question type base and a corpus; the question type library is matched with the test question set and used for providing reference for the test question set; the corpus at least stores the noun types and the noun number which should be mastered by the preschool children.
Preferably, in the above method for scoring the multiple abilities of a child for the assessment of preschool education quality, the relevant index data in S3 includes various video real-time recordings of the child when answering questions during the test, the skeleton movement track of the child, the drawing action of the child in the plane drawing scene, the sound and the voice print.
Preferably, in the above method for scoring the multiple abilities of children for the assessment of preschool education quality, the index data is quantitatively stored in terms of images, texts and voices in S4.
Preferably, in the above method for scoring the multiple abilities of children for the pre-education quality evaluation, in S5, the voice in the original data is transcribed into the text information by using the AI technique, and the sentence structure in the text information is analyzed by using the mandarin vocabulary and the grammar analysis according to the transcribed text information; feature data is extracted in the sentence structure.
Preferably, in the above method for scoring the multiple abilities of children for the assessment of the preschool education quality, the feature data includes nouns, verbs, a speech rate and a intonation of the answer, fluency of the answer, and richness of the sentence.
Preferably, in the above method for scoring the multiple abilities of children for the assessment of preschool education quality, S7 includes the steps of:
s701, making a total test target;
s702, dividing the total test target into five fields according to five fields of preschool education;
s703, dividing each field into a plurality of capacity items;
s704, dividing each capacity item into a plurality of sub capacity items;
s705, dividing each sub-capability item into a plurality of scoring items;
s706, scoring relevant scoring items related to the current test questions, and sequentially calculating scores and combined scores of each level by using an analytic hierarchy process according to the scoring values of the scoring items; the combined score is the final score.
According to the technical scheme, compared with the prior art, the invention has the following beneficial effects:
1. the invention directionally divides the test question set according to five fields of preschool education and establishes a scientific evaluation system by a five-layer analysis method. And meanwhile, a plurality of scoring details are set, so that the evaluation reliability can be effectively improved. The consistency, stability and reliability of the test result of the same child after repeated evaluation are ensured.
2. The invention realizes the scene of the test questions by the AR or VR technology, truly simulates the test process, enables the test children to have immersive feeling, and avoids the problems that the attention of the children in the age group is not concentrated and the test process is easily disturbed.
3. The invention combines a plurality of societies and technical disciplines such as phonetics, linguistics, preschool education, knowledge maps, machine learning and the like, leads all disciplines to be fully fused and run through, adopts a plurality of recognition technologies to record and collect different characteristic expressions of the tested children in the aspects of phonetics, drawings, skeletons and the like in real time, forms an effective education evaluation system and realizes the individual development of the children in the kindergarten.
4. According to the invention, the acquired index data is quantitatively stored, the test result stored in the current period can be adjusted and compared with the current test result, and the capability growth condition of the child can be more accurately evaluated.
The invention also provides a children multinomial ability scoring system for preschool education quality evaluation, which comprises the following components:
the question bank module is used for directionally dividing test question sets according to five fields of preschool education and constructing a knowledge base corresponding to the test question sets;
a scenarization module to scenarize each test question in the set of test questions using AR or VR technology;
the index data acquisition module is used for directionally acquiring related index data of the tested children in the process of answering the current test questions;
the storage module is used for quantitatively storing the index data according to types to serve as original data;
the characteristic extraction module is used for extracting characteristic data in the original data by utilizing an AI technology;
the investigation knowledge point determining and calculating module is used for calling the investigation knowledge points matched with the characteristic data in the knowledge base and determining a score calculating method according to the investigation knowledge points;
the scoring module is used for obtaining a scoring value of each investigation knowledge point related to the current test question by using the score calculation method; and
and the result output module is used for quantitatively calculating and outputting a final score value and qualitatively outputting an evaluation result and a guidance suggestion according to the final score value.
Preferably, in the above system for scoring the multiple abilities of children for the assessment of preschool education quality, the scoring module includes:
the overall target formulation module is used for formulating a test overall target;
a domain dividing module for dividing the total test target into five domains according to five domains of preschool education;
a capability partitioning module for partitioning each of the domains into a plurality of capability items;
a sub-capability partitioning module for partitioning each capability item into a plurality of sub-capability items;
a scoring item partitioning module to partition each sub-capability item into a plurality of scoring items; and
and the final scoring value calculating module is used for scoring the related scoring items related to the current test question and sequentially calculating the scores and the combined scores of the grades by using an analytic hierarchy process according to the scoring values of the scoring items.
According to the technical scheme, compared with the prior art, the immersive VR/AR technology and the related index data of the directional acquisition test process are used for storing and intelligently analyzing, the scoring items related to five fields of preschool education are respectively scored hierarchically, and the combination value and the guidance suggestion of each scoring item are output quantitatively and qualitatively. The preschool education testing method is comprehensively utilized, and the evaluation of preschool children education quality is maximized. The method can effectively reduce the influence of artificial subjective scoring, and can automatically and intelligently perform objective evaluation on preschool children education.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a method for scoring a child's multiple competencies for preschool education quality assessment according to the present invention;
FIG. 2 is a flow chart of S7 provided by the present invention;
FIG. 3 is a block diagram illustrating a multi-item ability scoring system for pre-school education quality assessment according to the present invention;
fig. 4 is a block diagram of a scoring module according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the embodiment of the invention discloses a method for scoring multiple abilities of children for pre-school education quality evaluation, which is characterized by comprising the following steps:
s1, directionally dividing test question sets according to the five fields of preschool education, and constructing a knowledge base corresponding to the test question sets;
s2, making each test question in the test question set into a scene by utilizing an AR or VR technology;
s3, directionally collecting related index data of the tested children in the process of answering the current test questions;
s4, quantitatively storing the index data according to types to serve as original data;
s5, extracting feature data in the original data by using an AI technology;
s6, taking investigation knowledge points matched with the characteristic data in the knowledge base, and determining a score calculation method according to the investigation knowledge points;
s7, obtaining the scoring value and the final scoring value of each investigation knowledge point related to the current test question by using a score calculation method;
and S8, quantitatively calculating and outputting a final scoring value, and qualitatively outputting an evaluation result and a guidance suggestion according to the final scoring value.
The preschool education testing method based on the immersion VR/AR technology has the advantages that relevant index data in the testing process are directionally collected by using the immersion VR/AR technology for storage and intelligent analysis, each examined knowledge point is scored, the combined score of each examined knowledge point is calculated, and the preschool education testing method is comprehensively used for achieving maximum scoring of preschool education quality of children. The method can effectively reduce the influence of artificial subjective scoring, and can automatically and intelligently perform objective evaluation on preschool children education.
Specifically, each test question set in S1 is presented in an animation manner, and each test question set tests the two-way to-be-tested in an interactive manner. Wherein, the size and the duration of the test questions in each test question set can be dynamically adjusted according to the needs.
In one embodiment, the knowledge base in S1 includes a question type base and a corpus; the question type library is matched with the test question set and used for providing reference for the test question set; the corpus stores at least the noun types and the number that the preschool children should master.
And each test question in the S2 is designed with a specific test scene, so that the test process is truly simulated, the tested children can feel immersive, the phenomenon that the attention of the children in the age group is not concentrated and the situation that the children are easily disturbed in the test process is avoided.
In other embodiments, the relevant index data in S3 includes various video real-time recordings of the child as it answers questions during the test, the child 'S skeletal movement trajectory, the child' S drawing action in a planimetric scene, sounds, and voiceprints. The invention combines a plurality of societies and technical disciplines such as phonetics, linguistics, preschool education, knowledge maps, machine learning and the like, leads all disciplines to be fully fused and run through, adopts a plurality of recognition technologies to record and collect different characteristic expressions of the tested children in the aspects of phonetics, drawings, skeletons and the like in real time, forms an effective education evaluation system and realizes the individual development of the children in the kindergarten.
More advantageously, in S4, the index data is stored quantitatively in terms of image, text, and speech. According to the invention, the acquired index data is quantitatively stored, the test result stored in the current period can be adjusted and compared with the current test result, and the capability growth condition of the child can be more accurately evaluated.
In one embodiment, when a language test is performed on a child, voice in original data needs to be collected, the voice in the original data is transcribed into character information by using an AI technology, and sentence structures in the character information are analyzed by using mandarin vocabularies and grammar analysis according to the transcribed character information; extracting feature data from the sentence structure; the feature data includes nouns, verbs, pace and intonation of answers, fluency of answers, and richness of sentences.
As shown in fig. 2, S7 includes the steps of:
s701, making a total test target;
s702, dividing a total test target into five fields according to five fields of preschool education;
s703, dividing each field into a plurality of capacity items;
s704, dividing each capacity item into a plurality of sub capacity items;
s705, dividing each sub-capability item into a plurality of scoring items;
s706, scoring related scoring items related to the current test questions, and reversely calculating scores of all levels and combined scores thereof by using an analytic hierarchy process according to the scoring values of all the scoring items; the combined score is the final score.
The invention directionally divides the test question set according to five fields of preschool education and establishes a scientific evaluation system by a five-layer analysis method. A plurality of scoring details are set at the same time, the number of the scoring details is up to 500, and the evaluation reliability can be effectively improved. The consistency, stability and reliability of the test result of the same child after repeated evaluation are ensured.
As shown in fig. 3, the embodiment of the present invention further discloses a system for scoring the multiple abilities of children for pre-school education quality evaluation, comprising:
the question bank module 1 is used for directionally dividing test question sets according to five fields of preschool education and constructing a knowledge base corresponding to the test question sets;
the scene module 2 is used for making each test question in the test question set into a scene by utilizing AR or VR technology;
the index data acquisition module 3 is used for directionally acquiring related index data of the tested children in the process of answering the current test questions;
the storage module 4 is used for quantitatively storing the index data according to types to serve as original data;
the characteristic extraction module 5 is used for extracting characteristic data in the original data by utilizing an AI technology;
the investigation knowledge point determining and calculating module 6 is used for calling the investigation knowledge points matched with the characteristic data in the knowledge base and determining a score calculating method according to the investigation knowledge points;
the scoring module 7 is used for obtaining a scoring value of each investigation knowledge point related to the current test question by using a score calculation method; and
and the result output module 8 is used for quantitatively calculating and outputting a final scoring value, and qualitatively outputting an evaluation result and a guidance suggestion according to the final scoring value.
In one embodiment, as shown in fig. 4, scoring module 7 includes:
a total target formulation module 701, wherein the total target formulation module 701 is used for formulating a test total target;
a domain dividing module 702, wherein the domain dividing module 702 is used for dividing the total test target into five domains according to five domains of preschool education;
the capability dividing module 703 is used for dividing each domain into a plurality of capability items;
a sub-capability dividing module 704, wherein the sub-capability dividing module 704 is used for dividing each capability item into a plurality of sub-capability items;
a scoring item dividing module 705, wherein the scoring item dividing module 705 is used for dividing each sub-capability item into a plurality of scoring items; and
and the final scoring value calculating module 706 is used for scoring the related scoring items related to the current test question, and sequentially calculating the scores of all the levels and the combined scores thereof by using an analytic hierarchy process according to the scoring values of all the scoring items.
The invention utilizes the immersion VR/AR technology and directionally collects the relevant index data of the test process for storage and intelligent analysis, scores the scoring items related to the five fields of preschool education in a hierarchical manner, and quantitatively and qualitatively outputs the combination value and guidance suggestion of each scoring item. The preschool education testing method is comprehensively utilized, and the evaluation of preschool children education quality is maximized. The method can effectively reduce the influence of artificial subjective scoring, and can automatically and intelligently perform objective evaluation on preschool children education.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A children multinomial ability scoring method for preschool education quality evaluation is characterized by comprising the following steps:
s1, directionally dividing test question sets according to five fields of preschool education, and constructing a knowledge base corresponding to the test question sets;
s2, utilizing AR or VR technology to scene each test question in the test question set;
s3, directionally collecting related index data of the tested children in the process of answering the current test questions;
s4, quantitatively storing the index data according to types to serve as original data;
s5, extracting feature data in the original data by using an AI technology;
s6, retrieving investigation knowledge points matched with the feature data in the knowledge base, and determining a score calculation method according to the investigation knowledge points;
s7, obtaining the score value and the final score value of each investigation knowledge point related to the current test question by using the score calculation method;
and S8, quantitatively calculating and outputting the final scoring value, and qualitatively outputting the evaluation result and the guidance opinion according to the final scoring value.
2. The method for scoring the multiple abilities of children according to claim 1, wherein the size and duration of the test questions in each of the test question sets in S1 are dynamically adjusted as necessary.
3. The method for scoring the multiple abilities of children in preschool education quality according to claim 1, wherein the knowledge base in S1 includes question type base and corpus; the question type library is matched with the test question set and used for providing reference for the test question set; the corpus at least stores the noun types and the noun number which should be mastered by the preschool children.
4. The method as claimed in claim 1, wherein the related index data in S3 includes video recordings of children answering questions during the test, skeleton movement tracks of children, drawing actions of children in a plane drawing scene, voice and voice print.
5. The children multinomial ability scoring method for preschool education quality assessment according to claim 1 wherein the index data is quantitatively stored in terms of images, texts and voices in S4.
6. The method as claimed in claim 5, wherein the step of S5 comprises transcribing the speech in the raw data into text information by AI technique, and analyzing the sentence structure in the text information by mandarin vocabulary and grammar analysis according to the transcribed text information; feature data is extracted in the sentence structure.
7. The method of claim 6, wherein the feature data includes nouns, verbs, speech rate and intonation of answers, fluency of answers, and richness of sentences.
8. The method for scoring the multiple abilities of children in order to evaluate the quality of preschool education as claimed in claim 1, wherein S7 comprises the steps of:
s701, making a total test target;
s702, dividing the total test target into five fields according to five fields of preschool education;
s703, dividing each field into a plurality of capacity items;
s704, dividing each capacity item into a plurality of sub capacity items;
s705, dividing each sub-capability item into a plurality of scoring items;
s706, scoring relevant scoring items related to the current test questions, and sequentially calculating scores and combined scores of each level by using an analytic hierarchy process according to the scoring values of the scoring items; the combined score is the final score.
9. A system for scoring a child's multiple abilities for assessing preschool educational quality, comprising:
the question bank module (1) is used for directionally dividing test question sets according to five fields of preschool education and constructing a knowledge bank corresponding to the test question sets;
a scenarization module (2), the scenarization module (2) for scenarizing each test question in the set of test questions using AR or VR technology;
the index data acquisition module (3) is used for directionally acquiring related index data of the tested children in the process of answering the current test questions;
the storage module (4) is used for quantitatively storing the index data according to types to serve as original data;
a feature extraction module (5), wherein the feature extraction module (5) is used for extracting feature data in the original data by using an AI technology;
the investigation knowledge point determining and calculating module (6) is used for calling investigation knowledge points matched with the characteristic data in the knowledge base and determining a score calculating method according to the investigation knowledge points;
the scoring module (7) is used for obtaining a scoring value of each investigation knowledge point related to the current test question by using the score calculation method; and
a result output module (8), wherein the result output module (8) is used for quantitatively calculating and outputting a final score value, and qualitatively outputting an evaluation result and a guidance opinion according to the final score value.
10. A system for scoring the multiple abilities of children for pre-school education quality assessment according to claim 9, characterized in that the scoring module (7) comprises:
a total goal formulation module (701), the total goal formulation module (701) for formulating a test total goal;
a domain division module (702), the domain division module (702) for dividing the total test goal into five domains according to five domains of preschool education;
a capability partitioning module (703), the capability partitioning module (703) for partitioning each of the domains into a plurality of capability items;
a sub-capability division module (704), the sub-capability division module (704) for dividing each capability item into a plurality of sub-capability items;
a scoring item partitioning module (705), the scoring item partitioning module (705) for partitioning each sub-capability item into a plurality of scoring items; and
and the final scoring value calculating module (706) is used for scoring the related scoring items related to the current test questions, and sequentially calculating the scores of all the levels and the combined scores thereof by using a hierarchical analysis method according to the scoring values of all the scoring items.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010993460.4A CN112184503A (en) | 2020-09-21 | 2020-09-21 | Children multinomial ability scoring method and system for preschool education quality evaluation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010993460.4A CN112184503A (en) | 2020-09-21 | 2020-09-21 | Children multinomial ability scoring method and system for preschool education quality evaluation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112184503A true CN112184503A (en) | 2021-01-05 |
Family
ID=73955601
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010993460.4A Pending CN112184503A (en) | 2020-09-21 | 2020-09-21 | Children multinomial ability scoring method and system for preschool education quality evaluation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112184503A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115456826A (en) * | 2022-09-13 | 2022-12-09 | 杭州中暖科技有限公司 | Method and system for evaluating family education mode merit index |
| CN116403604A (en) * | 2023-06-07 | 2023-07-07 | 北京奇趣万物科技有限公司 | Child reading ability evaluation method and system |
| CN117496787A (en) * | 2024-01-03 | 2024-02-02 | 小白智能科技（长春）股份有限公司 | Six-ability assessment and training system for children |
-
2020
- 2020-09-21 CN CN202010993460.4A patent/CN112184503A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115456826A (en) * | 2022-09-13 | 2022-12-09 | 杭州中暖科技有限公司 | Method and system for evaluating family education mode merit index |
| CN116403604A (en) * | 2023-06-07 | 2023-07-07 | 北京奇趣万物科技有限公司 | Child reading ability evaluation method and system |
| CN116403604B (en) * | 2023-06-07 | 2023-11-03 | 北京奇趣万物科技有限公司 | Child reading ability evaluation method and system |
| CN117496787A (en) * | 2024-01-03 | 2024-02-02 | 小白智能科技（长春）股份有限公司 | Six-ability assessment and training system for children |
| CN117496787B (en) * | 2024-01-03 | 2024-03-19 | 小白智能科技（长春）股份有限公司 | Six-ability assessment and training system for children |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Enayat et al. | Vocabulary size and depth as predictors of second language speaking ability | |
| Hulstijn | Measuring second language proficiency | |
| CN112184503A (en) | Children multinomial ability scoring method and system for preschool education quality evaluation | |
| Bolaños et al. | FLORA: Fluent oral reading assessment of children's speech | |
| Pallotti | Doing interlanguage analysis in school contexts | |
| Gómez et al. | Predicting proficiency in signed language interpreting: A preliminary study | |
| van Kleeck et al. | The effects of race and maternal education level on children’s retells of the Renfrew Bus Story—North American Edition | |
| Heilmann et al. | Assessing functional language in school-aged children using language sample analysis | |
| Delais-Roussarie et al. | Learner corpora and prosody: From the COREIL corpus to principles on data collection and corpus design | |
| Leńko-Szymańska | Defining and assessing lexical proficiency | |
| Al-Jaro et al. | Content analysis of the pedagogical content knowledge in the curriculum of Yemeni EFL teacher education programme | |
| Robinson et al. | Predicting difficulties in learning phonetic transcription: Phonemic awareness screening for beginning speech-language pathology students | |
| Yang et al. | Implementation and evaluation of computer‐aided Mandarin phonemes training system for hearing‐impaired students | |
| Mesut | Opinions of instructors about reading skills of Syrian students learning Turkish | |
| Kashiwagi et al. | EFL Learners' Grammatical Awareness through Accumulating Formulaic Sequences of Morphological Structure (-ing). | |
| Curtin et al. | The Pimsleur Battery as a predictor of student performance | |
| Muñoz et al. | English at the End of Primary School: Explanatory Factors | |
| Czap | Online subjective assessment of the speech of deaf and hard of hearing children | |
| Moon et al. | Can secondary teaching graduates support literacy in the classroom?: Evidence from undergraduate assignments | |
| Valentika | Students’ Error Spoken Language Production Through Monitor Theory | |
| Nurcahyani et al. | Teaching Strategy of Intensive English Course at Language Center of IAIN Samarinda | |
| KR102260115B1 (en) | Language learning method that provides learning materials to improve pronunciation | |
| KR102658252B1 (en) | Video education content providing method and apparatus based on artificial intelligence natural language processing using characters | |
| Shizuka et al. | VELC Test for testing competency: Verification of reliability and validity | |
| Rousoulioti et al. | Modern Greek language e-diagnostic tests |
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 | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210824 Address after: 650000 5th floor, 1866 Guannan Avenue, Guandu District, Kunming, Yunnan Applicant after: Shuwanzi Technology (Yunnan) Co.,Ltd. Address before: 1138-29, 11 / F, 18 Zhongguancun Street, Haidian District, Beijing Applicant before: Shuwanzi (Beijing) Technology Co.,Ltd. Applicant before: Shuwanzi Technology (Yunnan) Co.,Ltd. |