CN112269857A - Automatic correction method and device for multi-subject family operation - Google Patents
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Abstract
The disclosure relates to an automatic approval method and device for multi-subject family operation. Wherein, the method comprises the following steps: acquiring teaching information of each subject, and searching a post-lesson exercise corresponding to the current teaching progress in the teaching content information; generating family jobs with a plurality of subjects according to the after-class exercise sequencing and the job time distributed for each subject; the homework comprises a homework exercise and a first exercise answer; receiving collected homework to be corrected, which comprises second exercise answers, matching exercises in the homework to be corrected with the homework exercises one by one to obtain first exercise answers of the matched homework exercises, matching key information of the second exercise answers of the homework to be corrected with the first exercise answers, and obtaining homework correcting results according to matching results of all the exercises in the homework to be corrected. The homework correction system can automatically finish homework correction and reduce homework correction cost.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to an automatic correction method and apparatus for multi-subject home jobs, an electronic device, and a computer-readable storage medium.
Background
Homework is to achieve the purpose of consolidating the teaching result, and the homework which is finished at home and is arranged for students by teaching or corresponding programs is an extension of a classroom and has the effects of consolidating and promoting the understanding of the teaching content.
However, when a teacher corrects homework, the teacher takes a lot of time and effort to correct homework due to the large number of homework questions, the large number of students, and frequent arrangement, so how to correct homework in batches is a problem to be solved.
Therefore, it is desirable to provide one or more solutions that at least address the above-mentioned problems.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
An object of the present disclosure is to provide a method, an apparatus, an electronic device, and a computer-readable storage medium for automatic correction of multi-subject homework, thereby overcoming, at least to some extent, one or more of the problems due to the limitations and disadvantages of the related art.
According to one aspect of the present disclosure, there is provided a method for automatic approval of multi-subject home jobs, comprising:
an information acquisition step, wherein teaching information of each subject is received through a data receiving interface of the electronic equipment, and the teaching information comprises current teaching progress information, teaching content information and teaching key information;
a problem searching step, namely searching a post-lesson problem corresponding to the current teaching progress in the teaching content information;
the exercise sorting step, sorting the after-class exercises of each subject according to the teaching key information;
a time distribution step, which is to distribute operation time for each subject respectively, wherein the total operation time of each subject is not more than the preset operation time;
a homework generation step, which generates homework with a plurality of subjects according to the after-class exercise sequencing and the homework time distributed for each subject; the family operation comprises an operation exercise and a first exercise answer;
and a job correction step, namely receiving the collected home jobs to be corrected containing second exercise answers, matching the exercises in the home jobs to be corrected with the job exercises one by one to obtain first exercise answers of the matched job exercises, matching the second exercise answers of the home jobs to be corrected with the first exercise answers in a key information manner, and obtaining job correction results according to the matching results of all the exercises in the home jobs to be corrected.
In an exemplary embodiment of the present disclosure, the method further comprises:
the key information is marked exercise review points, and after key information matching is carried out on the second exercise answer of the to-be-approved family operation and the first exercise answer, the exercise review point matching value of the second exercise answer of the to-be-approved family operation and the first exercise answer is determined;
obtaining a score corresponding to the matching value of the investigation point according to a preset matching value and score mapping table;
and scoring the exercise according to the obtained score, wherein the score is the operation correction result.
In an exemplary embodiment of the present disclosure, the method further comprises:
and acquiring the completion time of the home homework to be corrected, and comprehensively scoring the home homework to be corrected according to the scores of all the exercises in the home homework to be corrected and the completion time of the home homework to be corrected.
In an exemplary embodiment of the present disclosure, the information acquiring step includes:
acquiring the current teaching progress of each subject; the current teaching progress is the teaching content from the teaching starting knowledge point to the teaching ending knowledge point of each subject on the day;
acquiring teaching key information in the current progress of each subject; the teaching key information comprises teaching contents in the current teaching progress of each subject and the knowledge point importance levels of the teaching contents.
In an exemplary embodiment of the present disclosure, the problem finding step includes:
searching a post-session exercise corresponding to the current teaching progress in each subject exercise library;
the exercise ordering step comprises the following steps:
and sequencing the after-class exercises of each subject according to the teaching contents and the knowledge point importance levels in the current teaching progress of each subject.
In an exemplary embodiment of the present disclosure, the method further comprises:
respectively presetting subject importance levels for each subject;
and respectively allocating operation time and operation sequence for each subject according to the subject importance level of each subject.
In an exemplary embodiment of the present disclosure, the job generating step includes:
according to the operation time and the operation sequence distributed for each subject, distributing a first preset number of post-class exercises according to the post-class exercise sequencing in the total operation time of each subject;
pre-evaluating the remaining time length of each subject after completing the first preset number of post-session exercises;
and according to the operation sequence distributed to each subject, distributing a second preset number of post-session exercises according to the post-session exercise sequencing in the residual time length.
In an exemplary embodiment of the present disclosure, the method further comprises:
after distributing a first preset number of post-class exercises according to the post-class exercise sequencing, sending the first preset number of post-class exercises to each student;
receiving homework completion information fed back by each student;
and counting student information of uncompleted first preset number of post-class exercises after the preset operation reserved time is reached, and generating corresponding overtime information.
In an exemplary embodiment of the present disclosure, the method further comprises:
after receiving homework completion information fed back by each student, analyzing the homework completion information, and counting homework response results of each subject;
and scoring the homework of each student according to the answer result of each subject homework and the overtime information of each subject homework.
In an exemplary embodiment of the present disclosure, the time allocation step includes:
and within the preset operation time, allocating the operation time for each subject in a continuous or discrete mode.
In an exemplary embodiment of the disclosure, the teaching information further includes teaching duration of each subject of the current day and/or the current school date and ranking information of historical achievement of each subject of each student.
In one aspect of the present disclosure, there is provided an automatic correction apparatus for multi-subject home work, comprising:
the information acquisition module is used for receiving teaching information of each subject through a data receiving interface of the electronic equipment, wherein the teaching information comprises current teaching progress information, teaching content information and teaching key information;
the exercise searching module is used for searching the after-class exercise corresponding to the current teaching progress in the teaching content information;
the exercise ordering module is used for ordering the after-class exercises of each subject according to the teaching key information;
the time distribution module is used for distributing operation time for each subject respectively, wherein the total operation time of each subject is not more than the preset operation time;
the homework generation module is used for generating homework with a plurality of subjects according to the after-class exercise sequencing and the homework time distributed for each subject; the family operation comprises an operation exercise and a first exercise answer;
and the operation correcting module is used for receiving the collected home operation to be corrected, which comprises second exercise answers, matching the exercise in the home operation to be corrected with the operation exercise one by one to obtain a first exercise answer of the matched operation exercise, matching the second exercise answer of the home operation to be corrected with the first exercise answer for key information, and obtaining an operation correcting result according to the matching results of all the exercises in the home operation to be corrected.
In one aspect of the present disclosure, there is provided an electronic device including:
a processor; and
a memory having computer readable instructions stored thereon which, when executed by the processor, implement a method according to any of the above.
In an aspect of the disclosure, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, realizes the method according to any one of the above.
In the automatic correction method for multi-subject family homework in the exemplary embodiment of the disclosure, teaching information of each subject is obtained, and a post-session exercise corresponding to the current teaching progress is searched in the teaching content information; generating family jobs with a plurality of subjects according to the after-class exercise sequencing and the job time distributed for each subject; the homework comprises a homework exercise and a first exercise answer; receiving collected homework to be corrected, which comprises second exercise answers, matching exercises in the homework to be corrected with the homework exercises one by one to obtain first exercise answers of the matched homework exercises, matching key information of the second exercise answers of the homework to be corrected with the first exercise answers, and obtaining homework correcting results according to matching results of all the exercises in the homework to be corrected. The homework correction system can automatically finish homework correction and reduce homework correction cost.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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The above and other features and advantages of the present disclosure will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
FIG. 1 illustrates a flow chart of a method for automatic wholesale of multi-subject homework according to an exemplary embodiment of the present disclosure;
FIG. 2 is a schematic diagram illustrating an application scenario of an automatic wholesale method for multi-subject homework according to an exemplary embodiment of the present disclosure;
FIG. 3 is a schematic diagram illustrating an application scenario of an automatic wholesale method for multi-subject homework according to an exemplary embodiment of the present disclosure;
FIG. 4 is a schematic diagram illustrating an automated wholesale method interactive application scenario for a multi-subject family job according to an illustrative embodiment of the present disclosure;
FIG. 5 shows a schematic block diagram of an apparatus for automatic batching of multi-subject home jobs according to an exemplary embodiment of the present disclosure;
FIG. 6 schematically illustrates a block diagram of an electronic device according to an exemplary embodiment of the present disclosure; and
fig. 7 schematically illustrates a schematic diagram of a computer-readable storage medium according to an exemplary embodiment of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals denote the same or similar parts in the drawings, and thus, a repetitive description thereof will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the embodiments of the disclosure can be practiced without one or more of the specific details, or with other methods, components, materials, devices, steps, and so forth. In other instances, well-known structures, methods, devices, implementations, materials, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in the form of software, or in one or more software-hardened modules, or in different networks and/or processor devices and/or microcontroller devices.
In the present exemplary embodiment, first, an automatic approval method for multi-subject family jobs is provided, which can be applied to electronic devices such as computers; referring to fig. 1, the automatic approval method of a multi-subject family job may include the steps of:
an information obtaining step S110, of receiving teaching information of each subject through a data receiving interface of the electronic device, where the teaching information includes current teaching progress information, teaching content information, and teaching focus information;
a problem searching step S120, searching the teaching content information for a post-lesson problem corresponding to the current teaching progress;
a step S130 of problem sorting, which is to sort the after-class problems of each subject according to the teaching key information;
a time allocation step S140, which allocates operation time for each subject, wherein the total operation time of each subject is not more than the preset operation time;
a job generation step S150, which generates a family job with a plurality of subjects according to the after-class exercise sequence and the job time distributed for each subject; the family operation comprises an operation exercise and a first exercise answer;
and a job correction step S160, receiving the collected homework to be corrected containing second exercise answers, matching the exercise questions in the homework to be corrected with the job exercise questions one by one to obtain first exercise question answers of the matched job exercise questions, matching the second exercise question answers of the homework to be corrected with the first exercise question answers for key information, and obtaining job correction results according to the matching results of all the exercise questions in the homework to be corrected.
According to the automatic approval method for the multi-subject family operation in the exemplary embodiment of the disclosure, teaching information of each subject is obtained, wherein the teaching information comprises a current teaching progress, teaching content information and teaching key information; searching a post-lesson exercise corresponding to the current teaching progress in the teaching content information; generating family jobs with a plurality of subjects according to the after-class exercise sequencing and the job time distributed for each subject; the homework comprises a homework exercise and a first exercise answer; receiving collected homework to be corrected, which comprises second exercise answers, matching exercises in the homework to be corrected with the homework exercises one by one to obtain first exercise answers of the matched homework exercises, matching key information of the second exercise answers of the homework to be corrected with the first exercise answers, and obtaining homework correcting results according to matching results of all the exercises in the homework to be corrected. The homework correction system can automatically finish homework correction and reduce homework correction cost.
Next, a further description will be made of an automatic correction method of a multi-subject family job in the present exemplary embodiment.
In the information obtaining step S110, teaching information of each subject may be obtained, where the teaching information includes a current teaching progress, teaching content information, and teaching focus information.
In the embodiment of the present example, the key information is a marked exercise review point, and after the second exercise answer of the to-be-approved home job is matched with the first exercise answer by key information, the exercise review point matching value of the second exercise answer of the to-be-approved home job and the first exercise answer is determined;
obtaining a score corresponding to the matching value of the investigation point according to a preset matching value and score mapping table;
in the embodiment of the present example, the problem review point may be a preset key word with key answers, and when the key word with key answers is included, the answer is correct and the highest matching value is given; and when a plurality of preset key words with key answers are provided, determining a matching value according to the number of the matched key words with key answers. Or the synonym of the preset key keyword of the answer also belongs to correct answer, and the value obtained by subtracting a certain ratio from the highest matching value (such as two tenths) is given. And scoring the exercise according to the obtained score, wherein the obtained score is the operation correction result.
In an embodiment of the present example, the method further comprises:
and acquiring the completion time of the home homework to be corrected, and comprehensively scoring the home homework to be corrected according to the scores of all the exercises in the home homework to be corrected and the completion time of the home homework to be corrected.
In the embodiment of the example, according to the acquisition and analysis of some specific teaching information, the importance levels of homework of students can be ordered, and the students can be ordered when controlling the homework time of the students. The teaching information comprises the current teaching progress, teaching content information and teaching key information, and the current day teaching content and teaching key information of each subject can be analyzed and generated according to the information.
In the embodiment of the present example, the teaching information further includes teaching duration of each subject of the current day and/or the current school date and ranking information of historical performance of each subject of each student. Furthermore, in order to rank the subjects in the response sequence of the homework of the student, the importance of each subject needs to be known, so that the importance level of each subject needs to be comprehensively analyzed and judged by acquiring the teaching duration of each subject of the student on the same day and/or in the current school. Furthermore, the historical score ranking information of the students can be acquired, the mastering condition of each subject of each student can be analyzed, the distribution and the sequencing of each subject of homework can be guided, and the homework is generated more flexibly and humanizedly.
In an embodiment of the present example, the information acquiring step includes: acquiring the current teaching progress of each subject; the current teaching progress is the teaching content from the teaching starting knowledge point to the teaching ending knowledge point of each subject on the day; acquiring teaching key information in the current progress of each subject; the teaching key information comprises teaching contents in the current teaching progress of each subject and the knowledge point importance levels of the teaching contents. The essence of teaching progress and teaching content of each subject is composed of knowledge points, and after-class exercises are corresponding to the knowledge points, so that the distribution and importance of the knowledge points of each subject can be comprehensively grasped, and the generation of homework sequencing of each subject can be better realized.
In the problem search step S120, a post-session problem corresponding to the current teaching progress may be searched in the teaching content information.
In the embodiment of the present example, each knowledge point in the obtained teaching content information is analyzed according to the obtained teaching content information, the knowledge point is associated with a post-lesson exercise, the post-lesson exercise is counted, and a post-lesson exercise corresponding table entry corresponding to the knowledge point is generated.
In the embodiment of the present example, the problem finding step includes: and searching a post-session exercise corresponding to the current teaching progress in each subject exercise library. Searching corresponding exercises in the exercise library of each subject is also an important way for acquiring the exercises.
In the exercise sorting step S130, the after-class exercises of the subjects may be sorted according to the teaching focus information.
In the embodiment of the present example, the after-class exercises are ranked according to the importance of each content in the acquired teaching content information, and an exercise ranking ranked according to the importance level of the teaching content information can be generated for each exercise of the subject for further selection of each subject exercise.
In the embodiment of the present example, the problem ranking step includes: and sequencing the after-class exercises of each subject according to the teaching contents and the knowledge point importance levels in the current teaching progress of each subject. And sorting the post-lesson exercises in the post-lesson exercise corresponding table items according to the acquired post-lesson exercise corresponding table items corresponding to the knowledge points and the importance levels of the knowledge points in the teaching content information, and generating post-lesson exercise corresponding table items consistent with the importance level sorting of the knowledge points.
In the time allocating step S140, an operation time may be allocated to each subject, wherein the total operation time of each subject is not greater than the preset operation time.
In the embodiment of the present example, in order to advocate the students, particularly the primary and secondary school students, to reduce the burden, it is necessary to control the total amount of homework, the most direct way being to control the total length of time for completing homework. According to different time periods for finishing the homework of the students in different grades, the homework duration is preset for the students, and the total duration of the homework time distributed by each subject is not more than the preset homework duration.
In the embodiment of the present example, the time allocation step includes: and within the preset operation time, allocating the operation time for each subject in a continuous or discrete mode. When the subjects are few or the preset operation time is short, the operation time can be allocated for the subjects in a continuous mode, and when the subjects are many or the preset operation time is long, the completion time of the number of the subjects in each category is not easy to be effectively evaluated, so that the operation time can be allocated for the subjects in a discrete mode, and the problems which can be completed by sorting the subjects according to the importance levels to the maximum extent can be guaranteed.
In an embodiment of the present example, the method further comprises: respectively presetting subject importance levels for each subject; and respectively allocating operation time and operation sequence for each subject according to the subject importance level of each subject. And sequencing the subjects according to the importance levels of the subjects, and arranging the completion sequence of the home operation of the subjects in a discrete or continuous mode. Fig. 2 is a schematic diagram showing the homework subject sequence and the corresponding time length of a student determined according to the total time of each subject in the current school date and the time of the day.
In the job generation step S150, a homework having a plurality of subjects may be generated according to the post-lesson exercises ranking, the work time allocated for each subject.
In the embodiment of the example, after-class exercises are sorted according to the importance levels of the knowledge points and the sorting sequence of each subject, corresponding exercises are sequentially distributed to each subject in the work time distributed to each subject, and a family work with a plurality of subjects is generated. Fig. 3 is a schematic diagram of a homework with a plurality of subjects generated according to the above conditions.
In the embodiment of the present example, the job generating step includes: according to the operation time and the operation sequence distributed for each subject, distributing a first preset number of post-class exercises according to the post-class exercise sequencing in the total operation time of each subject; pre-evaluating the remaining time length of each subject after completing the first preset number of post-session exercises; and according to the operation sequence distributed to each subject, distributing a second preset number of post-session exercises according to the post-session exercise sequencing in the residual time length. If the operation time allocated to each subject is discretely allocated, a preset number of post-session exercises can be allocated to each subject for one time in each discrete time, so that the control on the operation time is improved, and all subjects can finish the exercises corresponding to the knowledge points with higher priority levels.
In an embodiment of the present example, the method further comprises: after distributing a first preset number of post-class exercises according to the post-class exercise sequencing, sending the first preset number of post-class exercises to each student; receiving homework completion information fed back by each student; and counting student information of uncompleted first preset number of post-class exercises after the preset operation reserved time is reached, and generating corresponding overtime information. And counting the conditions of finishing a preset number of after-class exercises of each student within the assigned homework time of each subject, wherein the statistics can be used as the basis for homework scoring.
In an embodiment of the present example, the method further comprises: after receiving homework completion information fed back by each student, analyzing the homework completion information, and counting homework response results of each subject; and scoring the homework of each student according to the answer result of each subject homework and the overtime information of each subject homework. The homework of each student can be scored by combining the accuracy information and the overtime information of the homework answering result, and the homework can be used as a part of the investigation of the mastering degree of the teaching contents of the day by each student.
In the operation correction step S160, collected homework to be corrected including second exercise answers can be received, the exercises in the homework to be corrected are matched with the operation exercises one by one, a first exercise answer of the matched homework exercise is obtained, the second exercise answer of the homework to be corrected is matched with the first exercise answer in key information, and an operation correction result is obtained according to matching results of all the exercises in the homework to be corrected.
The first exercise answer is a preset exercise answer, and the second exercise answer is an exercise answer responded by the student. The key information is marked exercise review points, and after key information matching is carried out on the second exercise answer of the to-be-approved family operation and the first exercise answer, the exercise review point matching value of the second exercise answer of the to-be-approved family operation and the first exercise answer is determined; obtaining a score corresponding to the matching value of the investigation point according to a preset matching value and score mapping table; and scoring the exercise according to the obtained score, wherein the score is the operation correction result. In addition, the completion time of the family jobs to be corrected can be obtained, and the family jobs to be corrected are comprehensively scored according to the scores of all the exercises in the family jobs to be corrected and the completion time of the family jobs to be corrected.
In the embodiment of the example, teaching information of each subject is acquired, and a post-session problem corresponding to the current teaching progress is searched in the teaching content information; generating family jobs with a plurality of subjects according to the after-class exercise sequencing and the job time distributed for each subject; the homework comprises a homework exercise and a first exercise answer; receiving collected homework to be corrected, which comprises second exercise answers, matching exercises in the homework to be corrected with the homework exercises one by one to obtain first exercise answers of the matched homework exercises, matching key information of the second exercise answers of the homework to be corrected with the first exercise answers, and obtaining homework correcting results according to matching results of all the exercises in the homework to be corrected. The homework correction system can automatically finish homework correction and reduce homework correction cost.
In this exemplary embodiment, the method may be applied to a PC, or a portable handheld device, and may also implement data interaction between the two devices. Fig. 4 is a schematic diagram of a data interaction scenario in which the method is applied to a PC and a portable handheld device.
It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
In addition, in the present exemplary embodiment, an automatic correction apparatus for multi-subject home jobs is also provided. Referring to fig. 5, the apparatus 500 for automatically modifying a multi-subject homework may include: an information acquisition module 510, a problem search module 520, a problem sorting module 530, a time distribution module 540, a job generation module 550, and a job modification module 560. Wherein:
the information acquisition module 510 is configured to receive teaching information of each subject through a data receiving interface of the electronic device, where the teaching information includes current teaching progress information, teaching content information, and teaching focus information;
the problem searching module 520 is used for searching the teaching content information for the after-class problem corresponding to the current teaching progress;
the exercise sorting module 530 is used for sorting the after-class exercises of each subject according to the teaching key information;
the time distribution module 540 is configured to distribute operation time for each subject, where the total operation time of each subject is not longer than a preset operation time;
a job generation module 550, configured to generate a homework with multiple subjects according to the post-lesson exercise ranking and the job time allocated to each subject; the family operation comprises an operation exercise and a first exercise answer;
and the job correcting module 560 is used for receiving the collected home jobs to be corrected, which contain second exercise answers, matching the exercises in the home jobs to be corrected with the job exercises one by one to obtain first exercise answers of the matched job exercises, matching the second exercise answers of the home jobs to be corrected with the first exercise answers in a key information manner, and obtaining job correcting results according to the matching results of all the exercises in the home jobs to be corrected.
The specific details of the automatic correction device module for each multi-subject family job have been described in detail in the corresponding audio paragraph identification method, and therefore are not described herein again.
It should be noted that although several modules or units of the automatic modification apparatus 500 for multi-subject home jobs are mentioned in the above detailed description, such division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 600 according to such an embodiment of the invention is described below with reference to fig. 6. The electronic device 600 shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 6, the electronic device 600 is embodied in the form of a general purpose computing device. The components of the electronic device 600 may include, but are not limited to: the at least one processing unit 610, the at least one memory unit 620, a bus 630 connecting different system components (including the memory unit 620 and the processing unit 610), and a display unit 640.
Wherein the storage unit stores program code that is executable by the processing unit 610 such that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention as described in the above section "exemplary method" of the present specification. For example, the processing unit 610 may perform steps S110 to S150 as shown in fig. 1.
The storage unit 620 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)6201 and/or a cache memory unit 6202, and may further include a read-only memory unit (ROM) 6203.
The memory unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 600 may also communicate with one or more external devices 670 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 600, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 600 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 650. Also, the electronic device 600 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 660. As shown, the network adapter 660 communicates with the other modules of the electronic device 600 over the bus 630. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above-mentioned "exemplary methods" section of the present description, when said program product is run on the terminal device.
Referring to fig. 7, a program product 700 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is to be limited only by the terms of the appended claims.
Claims (14)
1. An automatic batching method for multi-subject home operations, characterized in that it is applied to electronic devices, and in that it comprises the following steps:
an information acquisition step, wherein teaching information of each subject is received through a data receiving interface of the electronic equipment;
a problem searching step, namely searching a post-lesson problem corresponding to the current teaching progress in the teaching content information;
the exercise sorting step, sorting the after-class exercises of each subject according to the teaching key information;
a time distribution step, which is to distribute operation time for each subject respectively, wherein the total operation time of each subject is not more than the preset operation time;
a homework generation step, which generates homework with a plurality of subjects according to the after-class exercise sequencing and the homework time distributed for each subject; the family operation comprises an operation exercise and a first exercise answer;
and a job correction step, namely receiving the collected home jobs to be corrected containing second exercise answers, matching the exercises in the home jobs to be corrected with the job exercises one by one to obtain first exercise answers of the matched job exercises, matching the second exercise answers of the home jobs to be corrected with the first exercise answers in a key information manner, and obtaining job correction results according to the matching results of all the exercises in the home jobs to be corrected.
2. The method of claim 1, wherein the method further comprises:
the key information is marked exercise review points, and after key information matching is carried out on the second exercise answer of the to-be-approved family operation and the first exercise answer, the exercise review point matching value of the second exercise answer of the to-be-approved family operation and the first exercise answer is determined;
obtaining a score corresponding to the matching value of the investigation point according to a preset matching value and score mapping table;
and scoring the exercise according to the obtained score, wherein the score is the operation correction result.
3. The method of claim 2, wherein the method further comprises:
and acquiring the completion time of the home homework to be corrected, and comprehensively scoring the home homework to be corrected according to the scores of all the exercises in the home homework to be corrected and the completion time of the home homework to be corrected.
4. The method of claim 1, wherein the information obtaining step comprises:
acquiring the current teaching progress of each subject; the current teaching progress is the teaching content from the teaching starting knowledge point to the teaching ending knowledge point of each subject on the day;
acquiring teaching key information in the current progress of each subject; the teaching key information comprises teaching contents in the current teaching progress of each subject and the knowledge point importance levels of the teaching contents.
5. The method of claim 4, wherein the problem finding step comprises:
searching a post-session exercise corresponding to the current teaching progress in each subject exercise library;
the exercise ordering step comprises the following steps:
and sequencing the after-class exercises of each subject according to the teaching contents and the knowledge point importance levels in the current teaching progress of each subject.
6. The method of claim 1, wherein the method further comprises:
respectively presetting subject importance levels for each subject;
and respectively allocating operation time and operation sequence for each subject according to the subject importance level of each subject.
7. The method of claim 6, wherein the job generation step comprises:
according to the operation time and the operation sequence distributed for each subject, distributing a first preset number of post-class exercises according to the post-class exercise sequencing in the total operation time of each subject;
pre-evaluating the remaining time length of each subject after completing the first preset number of post-session exercises;
and according to the operation sequence distributed to each subject, distributing a second preset number of post-session exercises according to the post-session exercise sequencing in the residual time length.
8. The method of claim 7, wherein the method further comprises:
after distributing a first preset number of post-class exercises according to the post-class exercise sequencing, sending the first preset number of post-class exercises to each student;
receiving homework completion information fed back by each student;
and counting student information of uncompleted first preset number of post-class exercises after the preset operation reserved time is reached, and generating corresponding overtime information.
9. The method of claim 8, wherein the method further comprises:
after receiving homework completion information fed back by each student, analyzing the homework completion information, and counting homework response results of each subject;
and scoring the homework of each student according to the answer result of each subject homework and the overtime information of each subject homework.
10. The method of claim 1, wherein the time allocating step comprises:
and within the preset operation time, allocating the operation time for each subject in a continuous or discrete mode.
11. The method of claim 1, wherein the teaching information further comprises teaching duration of each subject of the current day and/or the current school, and ranking information of historical performance of each subject of each student.
12. An apparatus for automatic approval of multi-subject homework, the apparatus comprising:
the information acquisition module is used for receiving teaching information of each subject through a data receiving interface of the electronic equipment, wherein the teaching information comprises current teaching progress information, teaching content information and teaching key information;
the exercise searching module is used for searching the after-class exercise corresponding to the current teaching progress in the teaching content information;
the exercise ordering module is used for ordering the after-class exercises of each subject according to the teaching key information;
the time distribution module is used for distributing operation time for each subject respectively, wherein the total operation time of each subject is not more than the preset operation time;
the homework generation module is used for generating homework with a plurality of subjects according to the after-class exercise sequencing and the homework time distributed for each subject; the family operation comprises an operation exercise and a first exercise answer;
and the operation correcting module is used for receiving the collected home operation to be corrected, which comprises second exercise answers, matching the exercise in the home operation to be corrected with the operation exercise one by one to obtain a first exercise answer of the matched operation exercise, matching the second exercise answer of the home operation to be corrected with the first exercise answer for key information, and obtaining an operation correcting result according to the matching results of all the exercises in the home operation to be corrected.
13. An electronic device, comprising
A processor; and
a memory having computer readable instructions stored thereon which, when executed by the processor, implement the method of any of claims 1 to 13.
14. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 13.
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| CN202011136693.9A CN112269857A (en) | 2020-10-22 | 2020-10-22 | Automatic correction method and device for multi-subject family operation |
| PCT/CN2020/138492 WO2022082988A1 (en) | 2020-10-22 | 2020-12-23 | Automatic correction method and device for multi-subject homework |
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| CN202011136693.9A CN112269857A (en) | 2020-10-22 | 2020-10-22 | Automatic correction method and device for multi-subject family operation |
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| WO (1) | WO2022082988A1 (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113051300A (en) * | 2021-03-05 | 2021-06-29 | 深圳市鹰硕技术有限公司 | Online learning method and device based on learning partner matching |
| CN113140210A (en) * | 2021-04-30 | 2021-07-20 | 武汉悦学帮网络技术有限公司 | Audio correction method and device, electronic equipment and storage medium |
| CN113407674A (en) * | 2021-06-24 | 2021-09-17 | 作业帮教育科技（北京）有限公司 | Question answer selection method and device and electronic equipment |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116798046B (en) * | 2023-04-19 | 2024-05-17 | 江西风向标智能科技有限公司 | Automatic modification method, device, medium and program product for junior middle school mathematical formulas |
| CN118552972A (en) * | 2024-06-13 | 2024-08-27 | 暗物质(北京)智能科技有限公司 | Teaching and assisting operation modifying method and system based on machine vision |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030059761A1 (en) * | 2001-09-21 | 2003-03-27 | Pamela Patterson | On-line homework solution system |
| CN103236196A (en) * | 2013-04-08 | 2013-08-07 | 明博教育科技有限公司 | Electronic assignment system and method allowing for automatic distributing, receiving, marking and counting |
| WO2016029627A1 (en) * | 2014-08-29 | 2016-03-03 | 风腾科技（北京）有限公司 | Course teaching system and operation method for course teaching system |
| CN105809354A (en) * | 2016-03-14 | 2016-07-27 | 成都爱易佰网络科技有限公司 | System and method based on personalized work assignment and monitoring |
| CN106057003A (en) * | 2016-06-25 | 2016-10-26 | 广州伟度计算机科技有限公司 | Homework implementation system and implementation method for teaching process |
| CN109242736A (en) * | 2018-09-27 | 2019-01-18 | 广东小天才科技有限公司 | Method and system for assisting teacher to know learning condition of student |
| CN109637238A (en) * | 2018-11-05 | 2019-04-16 | 广东共升教育科技有限公司 | A kind of generation method of exercise, device, equipment and storage medium |
| CN109903617A (en) * | 2017-12-11 | 2019-06-18 | 北京三好互动教育科技有限公司 | Individualized exercise method and system |
| CN110969412A (en) * | 2019-11-25 | 2020-04-07 | 大连理工大学 | Electronic experiment report generation, intelligent reading, storage and downloading system |
| CN111192490A (en) * | 2019-12-31 | 2020-05-22 | 浙江天鹏教育科技有限公司 | Intelligent education student end homework system and operation method thereof |
| CN211237318U (en) * | 2019-10-24 | 2020-08-11 | 孙明亮 | Class operation overall planning feedback alternating current equipment |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105678663A (en) * | 2016-01-12 | 2016-06-15 | 四川文轩教育科技有限公司 | Question bank management system based on tree-structure knowledge tree model |
| CN105654403A (en) * | 2016-01-12 | 2016-06-08 | 四川文轩教育科技有限公司 | Student homework result data-based knowledge tree problem analysis method |
-
2020
- 2020-10-22 CN CN202011136693.9A patent/CN112269857A/en active Pending
- 2020-12-23 WO PCT/CN2020/138492 patent/WO2022082988A1/en active Application Filing
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030059761A1 (en) * | 2001-09-21 | 2003-03-27 | Pamela Patterson | On-line homework solution system |
| CN103236196A (en) * | 2013-04-08 | 2013-08-07 | 明博教育科技有限公司 | Electronic assignment system and method allowing for automatic distributing, receiving, marking and counting |
| WO2016029627A1 (en) * | 2014-08-29 | 2016-03-03 | 风腾科技（北京）有限公司 | Course teaching system and operation method for course teaching system |
| CN105809354A (en) * | 2016-03-14 | 2016-07-27 | 成都爱易佰网络科技有限公司 | System and method based on personalized work assignment and monitoring |
| CN106057003A (en) * | 2016-06-25 | 2016-10-26 | 广州伟度计算机科技有限公司 | Homework implementation system and implementation method for teaching process |
| CN109903617A (en) * | 2017-12-11 | 2019-06-18 | 北京三好互动教育科技有限公司 | Individualized exercise method and system |
| CN109242736A (en) * | 2018-09-27 | 2019-01-18 | 广东小天才科技有限公司 | Method and system for assisting teacher to know learning condition of student |
| CN109637238A (en) * | 2018-11-05 | 2019-04-16 | 广东共升教育科技有限公司 | A kind of generation method of exercise, device, equipment and storage medium |
| CN211237318U (en) * | 2019-10-24 | 2020-08-11 | 孙明亮 | Class operation overall planning feedback alternating current equipment |
| CN110969412A (en) * | 2019-11-25 | 2020-04-07 | 大连理工大学 | Electronic experiment report generation, intelligent reading, storage and downloading system |
| CN111192490A (en) * | 2019-12-31 | 2020-05-22 | 浙江天鹏教育科技有限公司 | Intelligent education student end homework system and operation method thereof |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113051300A (en) * | 2021-03-05 | 2021-06-29 | 深圳市鹰硕技术有限公司 | Online learning method and device based on learning partner matching |
| CN113140210A (en) * | 2021-04-30 | 2021-07-20 | 武汉悦学帮网络技术有限公司 | Audio correction method and device, electronic equipment and storage medium |
| CN113140210B (en) * | 2021-04-30 | 2024-06-07 | 武汉悦学帮网络技术有限公司 | Audio correction method, device, electronic equipment and storage medium |
| CN113407674A (en) * | 2021-06-24 | 2021-09-17 | 作业帮教育科技（北京）有限公司 | Question answer selection method and device and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2022082988A1 (en) | 2022-04-28 |
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