CN114913039A - Course construction system and method based on investigation - Google Patents
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Abstract
The invention discloses a course construction system and a course construction method based on investigation, wherein the course construction system based on investigation comprises a practice expert experience extraction unit, a file knowledge extraction unit and a course structure modeling unit, the practice expert experience extraction unit is used for acquiring experience of practice experts, the file knowledge extraction unit is used for acquiring file information, and the course structure modeling unit is used for constructing courses. According to the invention, the experience of the expert is obtained by extracting the experience of the practical expert, the ASK database is formed by extracting the file content, and the course structure construction unit is utilized to plan the course which meets the actual requirement, so that the course can be accurately planned.
Description
Technical Field
The invention relates to the technical field of course construction, in particular to a course construction system and a course construction method based on investigation.
Background
Professional education refers to education for educators to obtain professional knowledge, skills and professional moral required for a certain professional or productive work, and includes elementary professional education, intermediate professional education and advanced professional education. Vocational education and general education are two different types of education, and have equal importance. Professional education is a type of education, not a level of education. Professional education includes professional school education and professional training. Vocational school education includes various vocational and technical schools, mechanic schools, vocational high schools (vocational schools), vocational colleges, vocational and educational centers, vocational universities, applied-type textbooks, vocational training institutions, and the like. Vocational school education is academic education and is divided into elementary, medium and high vocational school education. Professional training is non-academic education including various professional training such as pre-professional training for employees, re-employment training for employees who are off duty, and the like. Vocational education, an important form of education, has been developing more and more rapidly.
Course setting of vocational education needs to be butted with work tasks, the system structure of the courses needs to be matched with the work system structure, the courses are set according to the correlation of the work tasks, at present, the setting basis of professional education is disordered, and some of the professional education use vocational basis; some are set by taking a general technology as a setting basis, and some are set by taking an industry as a setting basis; some products are taken as setting basis; the situations that the professional positioning is not clear and the professional teaching target is not clear exist.
Disclosure of Invention
Technical problem to be solved
The invention can solve the problems that the existing course has poor construction accuracy, so that the deviation exists between the learning content and the actually used content in work, and the course is difficult to be constructed well.
(II) technical scheme
On one hand, the invention provides a course construction system based on research, which comprises a practice expert experience extraction unit, a file knowledge extraction unit and a course structure modeling unit, wherein:
the practice expert experience extraction unit is used for acquiring the experience of practice experts;
the file knowledge extraction unit is used for acquiring file information;
the course structure modeling unit is used for constructing courses.
As a preferred technical solution of the present invention, the practice expert experience extraction unit includes an interview task setting module, a responsibility task combing module, a weight proportioning module, a typical task screening module, a typical task refining module, an attitude-skill-knowledge (ASK) management module, and an ASK analysis module, wherein:
the interview task setting module is used for managing interview tasks, initiating expert interview tasks, selecting expert accounts of interviews according to the interview industry and posts, setting the importance, difficulty, frequency, standardization degree and experience requirement coefficient of the current tasks, and sending interview invitation information to experts in the form of in-station messages;
the responsibility task carding module is used for collecting the responsibility and task discrimination, correction and combination of the operator carding on all the expert lists;
the weight matching module is used for experts to perform functions and tasks including but not limited to scoring, weight configuration, voting, sorting and typicality screening;
the typical task screening module is used for the collector to check the total value of all experts including but not limited to scoring, weight configuration, voting, sequencing and typical screening, and finally screening out typical responsibility and a typical task;
the typical task refining module is used for editing and combing task work elements of typical tasks by collectors;
the ASK management module is used for enabling an expert to enumerate and fill corresponding A attitude, S skill and K knowledge for each typical work task according to work elements, enabling an acquirer to form an ASK database in the ASK classifying and sorting process, or directly adding, deleting and editing ASK content, and sorting and combining the attitude, the skill and the knowledge filled by the expert;
the ASK analysis module is used for summarizing the knowledge of the A attitude S skills and the K listed in each typical responsibility and work task, sorting and screening the A attitude, the S skills and the K knowledge and establishing a final ASK library.
As a preferred technical solution of the present invention, the file knowledge extraction unit includes an analysis task setting module, a structure configuration module, an ASK input module, and an ASK screening module, wherein:
the analysis task setting module is used for an analyst to set analysis tasks of various types, wherein the analysis tasks comprise but are not limited to analysis names, text names and analysis time;
the structure configuration module is used for establishing a clear structural framework for analysis objects, wherein the analysis objects comprise but are not limited to texts, teaching materials, skill certificates, national standards, industry standards, local standards, group standards and enterprise standards;
the ASK input module is used for inputting the A attitude, the S skill and the K knowledge obtained based on analysis of the analysis object and setting a corresponding degree value;
and the ASK screening module is used for confirming and removing the duplication of the obtained A attitude, S skill and K knowledge.
As a preferred technical solution of the present invention, the course structure modeling unit includes a learning objective management module, a task objective management module, a course setting module, and a course-objective association design module, wherein:
the learning target management module is used for leading in ASK data of various sources by a collector and an analyst;
the learning theme management module is used for collecting learning themes generated when a person checks the previous theme mapping on a learning target;
the task target topic module is used for carrying out detailed analysis on the typical task to form a corresponding relation between ASK in the typical work task and a learning target and a learning topic;
the task target management module is used for an acquirer to check the refined typical tasks and fill the learning target of each work task according to ASK content;
the course setting module is used for creating, deleting or editing a course and establishing course operation covering a theme combination, wherein the theme and course combination comprises but is not limited to one-to-one, one-to-many and many-to-one;
the course-target association design module is used for associating the learning target to the course and simultaneously forming an analysis chart and/or a table, and reflecting the association result condition including but not limited to numbers, numerical values, symbols and characters.
As a preferred technical solution of the present invention, the learning objective management module is further configured to check a previous task learning objective;
or directly adding, deleting and editing learning targets;
and setting targets of the docked result guide and professional certification requirements.
As a preferred technical solution of the present invention, the learning topic management module is further configured to directly add, delete, and edit the learning topic content.
In a second aspect, the present invention further provides a course construction method based on research, which specifically includes the following steps:
s1: extracting the experience of the practical experts;
s2: extracting file knowledge;
s3: and constructing courses.
As a preferred technical solution of the present invention, the S1 specifically includes the following steps:
the experts write out their own development stages and then write out which representative work tasks are respectively done in different stages, so that the capability of the experts is improved in quality and quantity;
all experts select representative tasks required by the occupation from all work task lists, and set weights for the representative work tasks;
performing task refinement on the typical tasks, performing weight matching, screening the typical tasks according to conditions including but not limited to scoring, weight configuration, voting, sorting and typical screening, and forming an original library, a typical task library and a typical task library;
the expert enumerates and fills corresponding A attitude, S skill and K knowledge for each typical work task according to the work elements;
and confirming and sorting ASK to form a temporary library, and forming an ASK database in the ASK classifying and sorting process.
As a preferred technical solution of the present invention, the S2 specifically includes the following steps:
the analysis task setting module is used for setting analysis tasks of various analysis tasks, including but not limited to analysis names, text names and analysis time, and analysis objects include but are not limited to texts, teaching materials, skill certificates, national standards, industry standards, local standards, group standards and enterprise standards;
establishing a clear structural framework according to an analysis object;
establishing a corresponding frame and inputting corresponding A attitude, S skill and K knowledge;
and (5) carrying out ASK confirmation and arrangement to form a new ASK database.
As a preferred technical solution of the present invention, the step S3 specifically includes the following steps:
during single post analysis, selecting corresponding responsibility and work task, calling out corresponding ASK, referring to work elements, selecting corresponding ASK to carry out learning objective compilation work, and then completing theme compilation and management work according to school objectives; when multi-channel ASK sources are combined and modeled, multi-channel ASK is imported to form a total library, after relevant editing processing is carried out, corresponding ASK is selected to carry out learning target compilation work, and finished learning targets can also be imported; meanwhile, the targets are hierarchically graded, and are associated with the results-oriented and professional certification targets in categories;
when the learning target is managed, adding, editing, correcting or deleting the learning target and the association relation;
when the task target is themed, adding, modifying or deleting the learning theme according to the type and the property of the learning target, and importing a corresponding course or theme;
when the subject is integrated, the subject is integrated into the course in one-to-one or many-to-one or one-to-many multi-mode, or when the course-target is designed in a correlated way, the learning target and the course are designed in a correlated way, the correlation corresponding relation can be inquired and displayed, the relation between the course or the subject and the knowledge point quantity and the corresponding relation between the result guidance and the professional authentication requirement target are displayed, and the relation can be exported.
(III) advantageous effects
1. The invention provides a research-based course construction system which implements an expert experience extraction unit to make experts write development stages of the experts, write representative work tasks at different stages to improve the quality and quantity of the abilities of the experts, select representative tasks required by the occupation from all work task lists, set weights for the representative duties and the work tasks, screen out typical tasks according to conditions including but not limited to scoring, weight configuration, voting, sorting and typical screening to form an original library, a typical duty library and typical tasks, make ASK confirmation and sorting according to the A attitude, S skill and K knowledge filled in each typical work task list by the experts according to work elements to form a temporary library, form an ASK database in the ASK classifying and sorting process, thereby realizing analysis of post capacity requirements and the like;
2. according to the investigation-based course construction system, the file knowledge extraction unit can comb any object to be analyzed, so that a sufficient knowledge source of A attitude S skills K is provided for relevant professional construction, course target design and the like, and a foundation is provided for various integration requirements (such as special creation integration and certificate integration) and docking requirements (such as inter-high-medium-height book connection, college entrance examination connection and special book connection) required by course development, so that analysis of various capacity requirements and the like is realized;
3. according to the investigation-based course construction system, the course structure modeling unit can fuse the skill K knowledge of the A attitude S from different sources, and a learning target is formed according to the combination relation of ASK points. The learning target can realize grading, can be associated with targets of achievement guidance and professional certification requirements, and is associated with knowledge of skill K of the A attitude S. The correlation between the correction and the review can be reviewed. Reasonable teaching subjects can be designed according to the learning objective. Meanwhile, the association between the learning target and the course is realized, the association condition between the knowledge of the skill K of the A attitude and the learning target and between the learning target and the course theme is consulted in time, and the course structure is constructed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a schematic block diagram of a research-based course construction system of the present invention;
FIG. 2 is a schematic block diagram of a research-based course construction system practicing expert experience extraction unit of the present invention;
FIG. 3 is a schematic block diagram of a document extraction unit of the research-based course construction system of the present invention;
FIG. 4 is a schematic block diagram of a course structure modeling unit of the investigation-based course construction system of the present invention;
FIG. 5 is a block diagram illustrating the process of the research-based course construction method of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without inventive efforts based on the embodiments of the present invention, are within the scope of protection of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined or explained in subsequent figures.
In the description of the present invention, it is to be understood that the terms "longitudinal", "upper", "lower", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In a first aspect, as shown in fig. 1 to 4, the present invention provides a research-based course construction system, which includes a practice expert experience extraction unit, a document knowledge extraction unit, and a course structure modeling unit, wherein:
the practice expert experience extraction unit is used for acquiring the experience of practice experts;
the file knowledge extraction unit is used for acquiring file information;
the course structure modeling unit is used for constructing courses.
As a preferred technical solution of the present invention, the practice expert experience extraction unit includes an interview task setting module, a responsibility task combing module, a weight matching module, a typical task screening module, a typical task refining module, an attitude-skill-knowledge (ASK) management module, and an ASK analysis module, wherein:
the interview task setting module is used for managing interview tasks, initiating expert interview tasks, selecting expert accounts of interviews according to the interview industry and posts, setting the importance, difficulty, frequency, standardization degree and experience requirement coefficient of the current tasks, and sending interview invitation information to experts in the form of in-station messages;
the responsibility task carding module is used for collecting the responsibility and task discrimination, correction and combination of the operator carding on all the expert lists;
the weight matching module is used for experts to perform functions and tasks including but not limited to scoring, weight configuration, voting, sorting and typicality screening;
the typical task screening module is used for the collector to check the total value of all experts including but not limited to scoring, weight configuration, voting, sequencing and typical screening, and finally screening out typical responsibility and a typical task;
the typical task refining module is used for editing and combing task work elements of typical tasks by collectors;
the ASK management module is used for enabling an expert to enumerate and fill corresponding A attitude, S skill and K knowledge for each typical work task according to work elements, enabling an acquirer to form an ASK database in the ASK classifying and sorting process, or directly adding, deleting and editing ASK content, and sorting and combining the attitude, the skill and the knowledge filled by the expert;
the ASK analysis module is used for summarizing the knowledge of the A attitude S skills and the K listed in each typical responsibility and work task, sorting and screening the A attitude, the S skills and the K knowledge and establishing a final ASK library.
As a preferred technical solution of the present invention, the file knowledge extraction unit includes an analysis task setting module, a structure configuration module, an ASK input module, and an ASK screening module, wherein:
the analysis task setting module is used for an analyst to set analysis tasks of various types, wherein the analysis tasks comprise but are not limited to analysis names, text names and analysis time;
the structure configuration module is used for establishing a clear structural framework for analysis objects, wherein the analysis objects comprise but are not limited to texts, teaching materials, skill certificates, national standards, industry standards, local standards, group standards and enterprise standards;
the ASK input module is used for inputting the A attitude, the S skill and the K knowledge which are obtained based on the analysis of the analysis object and setting a corresponding degree value;
and the ASK screening module is used for confirming and removing the duplication of the obtained A attitude, S skill and K knowledge.
As a preferred technical solution of the present invention, the course structure modeling unit includes a learning objective management module, a learning topic management module, a task objective theme module, a task objective management module, a course setting module, and a course-objective association design module, wherein:
the learning target management module is used for leading in ASK data of various sources by a collector and an analyst;
the learning theme management module is used for collecting learning themes generated when a person checks the previous theme mapping on a learning target;
the task target topic module is used for carrying out detailed analysis on the typical task to form a corresponding relation between ASK in the typical work task and a learning target and a learning topic;
the task target management module is used for an acquirer to check the refined typical tasks and filling the learning target of each work task according to ASK content;
the course setting module is used for creating, deleting or editing a course and establishing course operation covering a theme combination, wherein the theme and course combination comprises but is not limited to one-to-one, one-to-many and many-to-one;
the course-target association design module is used for associating the learning target to the course and simultaneously forming an analysis chart and/or a table, and reflecting the association result condition including but not limited to numbers, numerical values, symbols and characters.
As a preferred technical solution of the present invention, the learning objective management module is further configured to check a previous task learning objective;
or directly adding, deleting and editing learning targets;
and setting targets of the docked result guide and professional certification requirements.
As a preferred technical solution of the present invention, the learning topic management module is further configured to directly add, delete, and edit the learning topic content.
In a second aspect, the invention further provides a research-based course construction method, which specifically comprises the following steps:
s1: extracting the experience of practical experts;
s2: extracting file knowledge;
s3: and constructing courses.
As a preferred technical solution of the present invention, the S1 specifically includes the following steps:
the experts write out their own development stages and then write out which representative work tasks are respectively done in different stages, so that the capability of the experts is improved in quality and quantity;
all experts select representative tasks required by the occupation from all work task lists, and weight is set for the representative work tasks;
carrying out task refinement on the typical duties, carrying out weight matching, screening out the typical tasks according to the conditions including but not limited to scoring, weight configuration, voting, sequencing and typical screening, and forming an original library, a typical duty library and a typical task library;
the expert enumerates and fills the corresponding A attitude, S skill and K knowledge for each typical work task according to the work elements;
and confirming and sorting ASK to form a temporary library, and forming an ASK database in the ASK classifying and sorting process.
As a preferred technical solution of the present invention, the S2 specifically includes the following steps:
the analysis task setting module is used for setting analysis tasks of various analysis tasks, including but not limited to analysis names, text names and analysis time, and analysis objects include but are not limited to texts, teaching materials, skill certificates, national standards, industry standards, local standards, group standards and enterprise standards;
establishing a clear structural framework according to an analysis object;
establishing a corresponding frame to input corresponding A attitude, S skill and K knowledge;
and (4) carrying out ASK confirmation and arrangement to form a new ASK database.
As a preferred technical solution of the present invention, the step S3 specifically includes the following steps:
during single post analysis, selecting corresponding responsibility and work task, calling out corresponding ASK, referring to work elements, selecting corresponding ASK to carry out learning objective compilation work, and completing theme compilation and management work according to school objectives; when multi-channel ASK sources are combined for modeling, multi-channel ASK is imported to form a master library, after relevant editing processing is carried out, corresponding ASK is selected for learning target compilation work, and finished learning targets can also be imported; meanwhile, the targets are hierarchically graded, and are associated with the results-oriented and professional certification targets in categories;
when the learning target is managed, adding, editing, correcting or deleting the learning target and the association relation;
when the task target is themed, adding, modifying or deleting the learning theme according to the type and the property of the learning target, and importing a corresponding course or theme;
when the subject is integrated, the subject is integrated into the course in one-to-one or many-to-one or one-to-many multi-mode, or when the course-target is designed in a correlated way, the learning target and the course are designed in a correlated way, the correlation corresponding relation can be inquired and displayed, the relation between the course or the subject and the knowledge point quantity and the corresponding relation between the result guidance and the professional authentication requirement target are displayed, and the relation can be exported.
In summary, the experts write their own development stages, write which representative work tasks are respectively done in different stages to improve the quality and quality of the capacity of the experts, select representative tasks required by the job from all work task lists, set weights for the representative tasks and the work tasks, screen out typical tasks according to conditions including but not limited to scoring, weight configuration, voting, sorting and typical screening to form an original library, a typical task library and typical tasks, the experts fill corresponding a attitude, S skills and K knowledge for each typical work task list according to work elements, perform ASK confirmation and sorting to form a temporary library, and form an ASK database in the ASK classification and sorting process, thereby realizing analysis of post capacity requirements and the like;
any object needing analysis can be combed, a sufficient A-attitude S skill K knowledge source is provided for relevant professional construction, course target design and the like, and a foundation is provided for various integration requirements (such as special creation integration and certificate integration) and butt-joint requirements (such as inter-high and medium-height book connection, college entrance examination connection and special book connection) required by course development, so that analysis of various ability requirements and the like is realized;
the knowledge of the A-attitude S skills K from different sources can be fused, and a learning target is formed according to the combination relation of ASK points. The learning target can realize grading, can be associated with targets of achievement guidance and professional certification requirements, and is associated with knowledge of skill K of the A attitude S. The association between the correction and the review can be made. Reasonable teaching subjects can be designed according to the learning objective. Meanwhile, the association between the learning target and the course is realized, the association condition between the knowledge of the skill K of the A attitude and the learning target and between the learning target and the course theme is consulted in time, and the course structure is constructed.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The utility model provides a course construction system based on investigation which characterized in that: including practice expert's experience extraction element, file knowledge extraction element and course structure modeling unit, wherein:
the practice expert experience extraction unit is used for acquiring the experience of practice experts;
the file knowledge extraction unit is used for acquiring file information;
the course structure modeling unit is used for constructing courses.
2. The investigation-based course construction system of claim 1, wherein: the practice expert experience extraction unit comprises an interview task setting module, a responsibility task combing module, a weight proportioning module, a typical task screening module, a typical task refining module, an attitude-skill-knowledge (ASK) management module and an ASK analysis module, wherein:
the interview task setting module is used for managing interview tasks, initiating expert interview tasks, selecting expert accounts of interviews according to the interview industry and posts, setting the importance, difficulty, frequency, standardization degree and experience requirement coefficient of the current tasks, and sending interview invitation information to experts in the form of in-station messages;
the responsibility task carding module is used for collecting the responsibility and task discrimination, correction and combination of the operator carding on all the expert lists;
the weight matching module is used for experts to perform functions and tasks including but not limited to scoring, weight configuration, voting, sorting and typicality screening;
the typical task screening module is used for enabling a collector to check the summary values of all experts including but not limited to scoring, weight configuration, voting, sequencing and typical screening, and finally screening out typical responsibilities and typical tasks;
the typical task refining module is used for editing and combing task work elements of a typical task by an acquirer;
the ASK management module is used for enabling an expert to enumerate and fill corresponding A attitude, S skill and K knowledge for each typical work task according to work elements, enabling an acquirer to form an ASK database in the ASK classifying and sorting process, or directly adding, deleting and editing ASK content, and sorting and combining the attitude, the skill and the knowledge filled by the expert;
the ASK analysis module is used for summarizing the knowledge of the A attitude S skills and the K listed in each typical responsibility and work task, sorting and screening the A attitude, the S skills and the K knowledge and establishing a final ASK library.
3. The investigation-based course construction system and method of claim 2, wherein: the file knowledge extraction unit comprises an analysis task setting module, a structure configuration module, an ASK input module and an ASK screening module, wherein:
the analysis task setting module is used for an analyst to set analysis tasks of various types, wherein the analysis tasks comprise but are not limited to analysis names, text names and analysis time;
the structure configuration module is used for establishing a clear structural framework for analysis objects, wherein the analysis objects comprise but are not limited to texts, teaching materials, skill certificates, national standards, industry standards, local standards, group standards and enterprise standards;
the ASK input module is used for inputting the A attitude, the S skill and the K knowledge which are obtained based on the analysis of the analysis object and setting a corresponding degree value;
and the ASK screening module is used for confirming and removing the duplication of the obtained A attitude, S skill and K knowledge.
4. A research-based lesson construction system according to claim 3, wherein: the course structure modeling unit comprises a learning target management module, a learning theme management module, a task target theme module, a task target management module, a course setting module and a course-target associated design module, wherein:
the learning target management module is used for leading in ASK data of various sources by a collector and an analyst;
the learning theme management module is used for collecting learning themes generated when a person checks the previous theme mapping on a learning target;
the task target topic module is used for carrying out detailed analysis on the typical task to form a corresponding relation between ASK in the typical work task and a learning target and a learning topic;
the task target management module is used for an acquirer to check the refined typical tasks and fill the learning target of each work task according to ASK content;
the course setting module is used for creating, deleting or editing a course and establishing course operation covering a theme combination, wherein the theme and course combination comprises but is not limited to one-to-one, one-to-many and many-to-one;
the course-target association design module is used for associating the learning target to the course and simultaneously forming an analysis chart and/or a table, and reflecting the association result condition including but not limited to numbers, numerical values, symbols and characters.
5. The investigation-based course construction system of claim 4, wherein: the learning target management module is also used for checking the previous task learning target;
or directly add, delete and edit learning objectives;
and setting targets of the docked result guide and professional certification requirements.
6. The investigation-based course construction system of claim 4, wherein: the learning theme management module is also used for directly adding, deleting and editing learning theme contents.
7. A course construction method based on research is characterized in that: the method specifically comprises the following steps:
s1: extracting the experience of the practical experts;
s2: extracting file knowledge;
s3: and constructing courses.
8. The investigation-based course construction method of claim 7, wherein: the S1 specifically includes the following steps:
the experts write their own development stages and then write representative work tasks which are respectively done in different stages, so that the abilities of the experts are improved in quality and quantity;
all experts select representative tasks required by the occupation from all work task lists, and weight is set for the representative work tasks;
carrying out task refinement on the typical duties, carrying out weight matching, screening out the typical tasks according to the conditions including but not limited to scoring, weight configuration, voting, sequencing and typical screening, and forming an original library, a typical duty library and a typical task library;
the expert enumerates and fills corresponding A attitude, S skill and K knowledge for each typical work task according to the work elements;
and confirming and sorting ASK to form a temporary library, and forming an ASK database in the ASK classifying and sorting process.
9. A research-based course construction method as claimed in claim 8, wherein: in S2, the method specifically includes the following steps:
the analysis task setting module is used for setting various analysis tasks including but not limited to analysis names, text names and analysis time, and analysis objects include but not limited to texts, teaching materials, skill certificates, national standards, industry standards, local standards, group standards and enterprise standards;
establishing a clear structural framework according to an analysis object;
establishing a corresponding frame and inputting corresponding A attitude, S skill and K knowledge;
and (5) carrying out ASK confirmation and arrangement to form a new ASK database.
10. The investigation-based course construction method of claim 9, wherein: in step S3, the method specifically includes the following steps:
during single post analysis, selecting corresponding responsibility and work task, calling out corresponding ASK, referring to work elements, selecting corresponding ASK to carry out learning objective compilation work, and then completing theme compilation and management work according to school objectives; when multi-channel ASK sources are combined for modeling, multi-channel ASK is imported to form a master library, after relevant editing processing is carried out, corresponding ASK is selected for learning target compilation work, and finished learning targets can also be imported; meanwhile, the targets are hierarchically graded and associated with the achievement guidance and professional certification targets in categories;
when the learning target is managed, adding, editing, correcting or deleting the learning target and the association relation;
when the task target is themed, adding, modifying or deleting the learning theme according to the type and the property of the learning target, and importing a corresponding course or theme;
when the subject is integrated, the subject is integrated into the course in one-to-one or many-to-one or one-to-many multi-mode, or when the course-target is designed in a correlated way, the learning target and the course are designed in a correlated way, the correlation corresponding relation can be inquired and displayed, the relation between the course or the subject and the knowledge point quantity and the corresponding relation between the result guidance and the professional authentication requirement target are displayed, and the relation can be exported.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115759662A (en) * | 2022-11-24 | 2023-03-07 | 北京清华同衡规划设计研究院有限公司 | Method and system for managing settlement cultural heritage investigation project |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115759662A (en) * | 2022-11-24 | 2023-03-07 | 北京清华同衡规划设计研究院有限公司 | Method and system for managing settlement cultural heritage investigation project |
| CN115759662B (en) * | 2022-11-24 | 2024-02-09 | 北京清华同衡规划设计研究院有限公司 | Management method and system for gathering cultural heritage investigation project |
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