CN103971555A - Multi-level automated assessing and training integrated service method and system - Google Patents
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Abstract
The invention provides a multi-level automated assessing and training integrated service method and system. The method comprise the first step of establishing a question bank, the second step of extracting test questions in line with test paper composition setting parameters from the question bank according to a preset test paper composition strategy to form appointed test papers, the third step of pushing the appointed test papers to question answering clients and calculating the grades of final papers when the final papers, fed back by the question answering clients, filled in test question answering information are received to figure out the grades of the test papers, the fourth step of establishing a capability assessing model, the fifth step of calculating assessing index scores of all terms of capacity, and the sixth step of pushing obtained learning resources to learning clients. By the utilization of the method and system, the learning and training mode is automated in the whole process, and a learning effect and learning efficiency are improved. In addition, as human intervention is not required in the assessing process, the credibility of assessing results is improved, and the assessing results can more objectively, truly and comprehensively reflect the capacity of assessed persons. Besides, the learning effect and learning efficiency are further improved.
Description
Technical field
The invention belongs to Computer Applied Technology field, be specifically related to a kind of multi-level robotization assessment training integrated method of servicing and system.
Background technology
Along with the development of computer technology, the application of computer-aided instruction in education sector is more and more far-reaching.In modern teaching system, extensively adopt the mode of carrying out capability evaluation and ability training by network.But current evaluating system needs human intervention in the time assessing, cause the with a low credibility of the assessment result that obtains, cannot be objective, the ability of reacting truly, all sidedly evaluated person.In addition, existing evaluating system and training system are separate, after assessing, need to manually obtain the education resource of training system storage, thereby extend obtaining the cycle of education resource, greatly reduced learning efficiency, can not obtain fast good results of learning.
Summary of the invention
The defect existing for prior art, the invention provides a kind of multi-level robotization assessment training integrated method of servicing and system, and whole-course automation study and training patterns, improve results of learning and learning efficiency; And because assessment time does not need human intervention, improved the confidence level of assessment result, make assessment result more objective,
Truly, react all sidedly evaluated person's ability; In addition, also improve results of learning and learning efficiency.
The technical solution used in the present invention is as follows:
The invention provides a kind of multi-level robotization assessment training integrated method of servicing, comprise the following steps:
S1, sets up exam pool, and described exam pool comprises exam pool concordance list and multiple tracks examination question, and described exam pool concordance list is made up of multiple list items, and described in each, list item is for storing the examination question ID of described exam pool examination question and the corresponding relation of examination question attribute; Wherein, described examination question attribute comprises: knowledge point and examination question score value that examination question type, item difficulty value, examination question are investigated;
S2 extracts the examination question that meets group volume setup parameter from described exam pool according to default tactic of generating test paper, form and specify paper;
S3, is pushed to answer client by described appointment paper; In the time receiving the filling in examination question and answer the final paper of information of described answer client feedback, calculate the achievement of described final paper, draw paper achievement;
S4, sets up capability assessment model, and described capability assessment model is for storing the corresponding relation of evaluation index and evaluation index attribute; Wherein, described evaluation index attribute comprises the score value of evaluation index, the weight of evaluation index, the knowledge point corresponding with evaluation index, the education resource corresponding with evaluation index;
S5, calculates the mark of each knowledge point of described final paper, and the corresponding relation by evaluation index described in described capability assessment model with corresponding knowledge point calculates the evaluation index mark of every ability;
S6, the evaluation index mark based on described every ability, obtains the education resource corresponding with the evaluation index mark of described every ability by described capability assessment model, then the described pushing learning resource obtaining is given to study client.
Preferably, in S1, described examination question type comprises the topic of filling a vacancy, multiple-choice question, true and false and simple answer.
Preferably, in S2, described default tactic of generating test paper is for taking out at random topic strategy; Described group of volume setup parameter comprises: the examination question quantity that needs setting in the Distribution of knowledge gists situation of the examination question type distribution scenario of the appointment paper of needs composition, the difficulty situation of described appointment paper, described appointment paper and described appointment paper.
Preferably, in S3, calculate the achievement of described final paper, show that paper achievement is specially:
The achievement of calculating described final paper according to the described examination question score value in described examination question attribute, draws paper achievement.
The present invention also provides a kind of multi-level robotization assessment training integrated service system, comprising:
Exam pool is set up module, and for setting up exam pool, described exam pool comprises exam pool concordance list and multiple tracks examination question, and described exam pool concordance list is made up of multiple list items, and described in each, list item is for storing the examination question ID of described exam pool examination question and the corresponding relation of examination question attribute; Wherein, described examination question attribute comprises: knowledge point and examination question score value that examination question type, item difficulty value, examination question are investigated;
Set up module, extract for the exam pool of setting up module foundation from described exam pool according to default tactic of generating test paper the examination question that meets group volume setup parameter, form appointment paper;
Paper achievement grading module, is pushed to answer client for the appointment paper that described establishment module is set up; In the time receiving the filling in examination question and answer the final paper of information of described answer client feedback, calculate the achievement of described final paper, draw paper achievement;
Capability assessment model, described capability assessment model is for storing the corresponding relation of evaluation index and evaluation index attribute; Wherein, described evaluation index attribute comprises the score value of evaluation index, the weight of evaluation index, the knowledge point corresponding with evaluation index, the education resource corresponding with evaluation index;
Evaluation index mark computing module, for calculating the mark of each knowledge point of described final paper, the corresponding relation by evaluation index described in described capability assessment model with corresponding knowledge point, calculates the evaluation index mark of every ability;
Pushing learning resource module, for the evaluation index mark based on described every ability, obtain the education resource corresponding with the evaluation index mark of described every ability by described capability assessment model, then the described pushing learning resource obtaining is given to study client.
Beneficial effect of the present invention is as follows:
The invention provides a kind of multi-level robotization assessment training integrated method of servicing and system, calculate every capacity index assessment result by test result, automatically push Learning Scheme to terminal user by assessment result.Terminal user learns by circuit training, Exam Evaluation, and resource supplying, such closed loop flow process, whole-course automation study, improves results of learning and learning efficiency; And because assessment time does not need human intervention, improved the confidence level of assessment result, make the ability that assessment result is more objective, react truly, all sidedly evaluated person; In addition, also improve results of learning and learning efficiency.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of multi-level robotization assessment training integrated method of servicing provided by the invention.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in detail:
As shown in Figure 1, the invention provides a kind of multi-level robotization assessment training integrated method of servicing, comprise the following steps:
S1, sets up exam pool, and described exam pool comprises exam pool concordance list and multiple tracks examination question, and described exam pool concordance list is made up of multiple list items, and described in each, list item is for storing the examination question ID of described exam pool examination question and the corresponding relation of examination question attribute; Wherein, described examination question attribute comprises: knowledge point and examination question score value that examination question type, item difficulty value, examination question are investigated; Concrete, examination question type include but not limited to fill a vacancy topic, multiple-choice question, true and false and simple answer.
S2 extracts the examination question that meets group volume setup parameter from described exam pool according to default tactic of generating test paper, form and specify paper;
In this step, default tactic of generating test paper can be for taking out topic strategy at random; Described group of volume setup parameter comprises: the examination question quantity that needs setting in the Distribution of knowledge gists situation of the examination question type distribution scenario of the appointment paper of needs composition, the difficulty situation of described appointment paper, described appointment paper and described appointment paper.
S3, is pushed to answer client by described appointment paper; In the time receiving the filling in examination question and answer the final paper of information of described answer client feedback, calculate the achievement of described final paper, draw paper achievement;
Wherein, account form is specially: calculate the achievement of described final paper according to the described examination question score value in described examination question attribute, draw paper achievement.
S4, sets up capability assessment model, and described capability assessment model is for storing the corresponding relation of evaluation index and evaluation index attribute; Wherein, described evaluation index attribute comprises the score value of evaluation index, the weight of evaluation index, the knowledge point corresponding with evaluation index, the education resource corresponding with evaluation index;
S5, calculates the mark of each knowledge point of described final paper, and the corresponding relation by evaluation index described in described capability assessment model with corresponding knowledge point calculates the evaluation index mark of every ability;
S6, the evaluation index mark based on described every ability, obtains the education resource corresponding with the evaluation index mark of described every ability by described capability assessment model, then the described pushing learning resource obtaining is given to study client.
The present invention also provides a kind of multi-level robotization assessment training integrated service system, comprising:
Exam pool is set up module, and for setting up exam pool, described exam pool comprises exam pool concordance list and multiple tracks examination question, and described exam pool concordance list is made up of multiple list items, and described in each, list item is for storing the examination question ID of described exam pool examination question and the corresponding relation of examination question attribute; Wherein, described examination question attribute comprises: knowledge point and examination question score value that examination question type, item difficulty value, examination question are investigated.
As shown in table 1, be the concrete form of the list item of an examination question:
Table 1
For one examination question, also comprise examination question option, as shown in table 2, be the concrete form of the examination question option of one examination question:
Table 2
| Parameter name | Data type | Explanation |
| QUES_ID | String | Examination question ID |
| ID | String | Option ID |
| QUES_ITEM_CONTENT | String | Option content |
| QUES_ITEM_SEQUENCE | Int | Option serial number |
| QUES_RESULT | String | Model answer |
| RESULT_ANALYSIS | String | The detailed resolving of model answer |
Set up module, extract for the exam pool of setting up module foundation from described exam pool according to default tactic of generating test paper the examination question that meets group volume setup parameter, form appointment paper; As shown in table 3, be the attribute information of a set up paper, and, as shown in table 4, for the large topic information of paper of a set up paper, as shown in table 5, be the little topic information of paper of a set up paper.
Table 3
| Parameter name | Data type | Explanation |
| ID | String | Paper ID |
| PAPER_NUM | String | Test sheet numbers |
| PAPER_TITLE | String | Paper title |
| CATEGORY_CODE | Int | Test paper classifying recursive query numbering |
| PAPER_MARK | Float | Total score |
| PAPER_TIME | int | Total test time |
| DIFFCULT_LEVEL | int | Complexity 1=is easy; 2=is medium; 3=is highly difficult |
| CREATOR_ID | String | The people that makes the test numbering |
| CREATOR_NAME | String | People's name makes the test |
| CREATE_TIME | String | Make the test the time |
| CREATE_TYPE | int | 1=random creating test papers; 2=manually organizes volume |
| PAPER_DESC | String | Paper is described |
| PREVIEW_CONTENT | String | Paper preview |
Table 4
Table 5
| Parameter name | Data type | Explanation |
| ID | String | Little topic ID |
| BIGQUES_ID | String | Test sheet numbers |
| QUES_ID | String | Paper title |
| QUES_CONTENT | String | Examination question title |
| QUES_MARK | Float | Examination question score value |
| ORDER_NUM | int | Sequence number |
Paper achievement grading module, is pushed to answer client for the appointment paper that described establishment module is set up; In the time receiving the filling in examination question and answer the final paper of information of described answer client feedback, calculate the achievement of described final paper, draw paper achievement;
Capability assessment model, described capability assessment model is for storing the corresponding relation of evaluation index and evaluation index attribute; Wherein, described evaluation index attribute comprises the score value of evaluation index, the weight of evaluation index, the knowledge point corresponding with evaluation index, the education resource corresponding with evaluation index.
As shown in table 6, for a kind of concrete evaluation index master meter, as shown in table 7, for a kind of concrete evaluation index attribute list, as shown in table 8, be a kind of concrete evaluation index pick list; As shown in table 9, be a kind of concrete assessment subject heading list; As shown in table 10, be the concrete assessment subject heading list of another kind.
Table 6
| Parameter name | Data type | Explanation |
| ID | String | Questionnaire masterplate ID |
| QUEST_TITLE | String | Questionnaire masterplate title |
| QUEST_TYPE | String | Questionnaire masterplate type |
| INPUT_TIME | String | The typing time |
| INPUT_USER_ID | String | Typing people ID |
| INPUT_USER_NAME | String | Typing people name |
| INPUT_ORG_ID | String | Typing organization id |
| INPUT_ORG_NAME | String | Typing organization name |
Table 7
| Parameter name | Data type | Explanation |
| ID | String | Index ID |
| QUEST_ID | String | Questionnaire masterplate ID |
| UP_KPI_ID | String | Higher level's index ID |
| KPI_NAME | String | Index name |
| KPI_NAME_REMARK | String | Index is explained in detail |
| WEIGHT_VALUE | float | Weighted value |
Table 8
| Parameter name | Data type | Explanation |
| ID | String | Index ID |
| QUEST_ID | String | Questionnaire masterplate ID |
| KPI_ID | String | Index ID |
| KPI_OPTION_NAME | String | Option names |
| KPI_OPTION_SCORE | String | Option score value |
Table 9
| Parameter name | Data type | Explanation |
| ID | String | Theme ID |
| SUBJECT_NAME | String | Subject name |
| BEGIN_DATE | String | The investigation start time |
| END_DATE | String | The investigation end time |
| WEIGHT_VALUE | String | Total weight |
| AUDIT_STATUS | float | Theme state: 1. 3 end are carried out in design 2. |
| INPUT_TIME | String | The typing time |
| INPUT_USER_ID | String | Typing people ID |
| INPUT_USER_NAME | String | Typing people name |
| INPUT_ORG_ID | String | Typing organization id |
| INPUT_ORG_NAME | String | Typing organization name |
Table 10
| Parameter name | Data type | Explanation |
| ID | String | ID |
| SURVEY_ID | String | Theme ID |
| QUEST_ID | String | Assessment masterplate questionnaire ID |
| IS_FK | String | Whether must reply feedback opinion |
Evaluation index mark computing module, for calculating the mark of each knowledge point of described final paper, the corresponding relation by evaluation index described in described capability assessment model with corresponding knowledge point, calculates the evaluation index mark of every ability.
Concrete, in the time that appointment paper is pushed to the process of answer client, need to set up survey crowd, as shown in table 11, be a kind of survey crowd table of concrete form; As shown in table 12, be a kind of survey result table of concrete form.
Table 11
| Parameter name | Data type | Explanation |
| ID | String | ID |
| QUEST_ID | String | Questionnaire ID |
| USER_ID | String | User ID |
| USER_NAME | String | Address name |
| DEPT_ID | String | The ID of department |
| DEPT_NAME | String | Department name |
| ORG_ID | String | Organization id |
| ORG_NAME | String | Organization name |
Table 12
| Parameter name | Data type | Explanation |
| ID | String | ID |
| SURVEY_ID | String | Theme ID |
| QUEST_ID | String | Questionnaire masterplate ID |
| KPIID | String | Index ID |
| KPI_OPTION_ID | String | Index option ID |
| KPI_OPTION_NAME | String | Index name |
| KPI_OPTION_SCORE | String | Index option mark |
| SCORE | String | Actual score |
| INPUT_TIME | String | The typing time |
| INPUT_USER_ID | String | Typing people ID |
| INPUT_USER_NAME | String | Typing people name |
Pushing learning resource module, for the evaluation index mark based on described every ability, obtain the education resource corresponding with the evaluation index mark of described every ability by described capability assessment model, then the described pushing learning resource obtaining is given to study client.As shown in table 13, be the concrete form of an education resource:
Table 13
In sum, multi-level robotization assessment training integrated method of servicing provided by the invention and system, calculate every capacity index assessment result by test result, automatically pushes Learning Scheme to terminal user by assessment result.Terminal user learns by circuit training, Exam Evaluation, and resource supplying, such closed loop flow process, whole-course automation study, improves results of learning and learning efficiency; And because assessment time does not need human intervention, improved the confidence level of assessment result, make the ability that assessment result is more objective, react truly, all sidedly evaluated person; In addition, also improve results of learning and learning efficiency.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should be looked protection scope of the present invention.
Claims (5)
1. a multi-level robotization assessment training integrated method of servicing, is characterized in that, comprises the following steps:
S1, sets up exam pool, and described exam pool comprises exam pool concordance list and multiple tracks examination question, and described exam pool concordance list is made up of multiple list items, and described in each, list item is for storing the examination question ID of described exam pool examination question and the corresponding relation of examination question attribute; Wherein, described examination question attribute comprises: knowledge point and examination question score value that examination question type, item difficulty value, examination question are investigated;
S2 extracts the examination question that meets group volume setup parameter from described exam pool according to default tactic of generating test paper, form and specify paper;
S3, is pushed to answer client by described appointment paper; In the time receiving the filling in examination question and answer the final paper of information of described answer client feedback, calculate the achievement of described final paper, draw paper achievement;
S4, sets up capability assessment model, and described capability assessment model is for storing the corresponding relation of evaluation index and evaluation index attribute; Wherein, described evaluation index attribute comprises the score value of evaluation index, the weight of evaluation index, the knowledge point corresponding with evaluation index, the education resource corresponding with evaluation index;
S5, calculates the mark of each knowledge point of described final paper, and the corresponding relation by evaluation index described in described capability assessment model with corresponding knowledge point calculates the evaluation index mark of every ability;
S6, the evaluation index mark based on described every ability, obtains the education resource corresponding with the evaluation index mark of described every ability by described capability assessment model, then the described pushing learning resource obtaining is given to study client.
2. multi-level robotization assessment training integrated method of servicing according to claim 1, is characterized in that, in S1, described examination question type comprises the topic of filling a vacancy, multiple-choice question, true and false and simple answer.
3. multi-level robotization assessment training integrated method of servicing according to claim 1, is characterized in that, in S2, described default tactic of generating test paper is for taking out at random topic strategy; Described group of volume setup parameter comprises: the examination question quantity that needs setting in the Distribution of knowledge gists situation of the examination question type distribution scenario of the appointment paper of needs composition, the difficulty situation of described appointment paper, described appointment paper and described appointment paper.
4. multi-level robotization assessment training integrated method of servicing according to claim 1, is characterized in that, in S3, calculates the achievement of described final paper, show that paper achievement is specially:
The achievement of calculating described final paper according to the described examination question score value in described examination question attribute, draws paper achievement.
5. a multi-level robotization assessment training integrated service system, is characterized in that, comprising:
Exam pool is set up module, and for setting up exam pool, described exam pool comprises exam pool concordance list and multiple tracks examination question, and described exam pool concordance list is made up of multiple list items, and described in each, list item is for storing the examination question ID of described exam pool examination question and the corresponding relation of examination question attribute; Wherein, described examination question attribute comprises: knowledge point and examination question score value that examination question type, item difficulty value, examination question are investigated;
Set up module, extract for the exam pool of setting up module foundation from described exam pool according to default tactic of generating test paper the examination question that meets group volume setup parameter, form appointment paper;
Paper achievement grading module, is pushed to answer client for the appointment paper that described establishment module is set up; In the time receiving the filling in examination question and answer the final paper of information of described answer client feedback, calculate the achievement of described final paper, draw paper achievement;
Capability assessment model, described capability assessment model is for storing the corresponding relation of evaluation index and evaluation index attribute; Wherein, described evaluation index attribute comprises the score value of evaluation index, the weight of evaluation index, the knowledge point corresponding with evaluation index, the education resource corresponding with evaluation index;
Evaluation index mark computing module, for calculating the mark of each knowledge point of described final paper, the corresponding relation by evaluation index described in described capability assessment model with corresponding knowledge point, calculates the evaluation index mark of every ability;
Pushing learning resource module, for the evaluation index mark based on described every ability, obtain the education resource corresponding with the evaluation index mark of described every ability by described capability assessment model, then the described pushing learning resource obtaining is given to study client.
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