CN114021984A - Invigilation data processing method - Google Patents
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Abstract
The embodiment of the invention relates to an invigilation data processing method, which comprises the following steps: in the examination process, identifying identification information of a current test question which is being answered by each examinee to generate first test question identification data, arranging writing tracks of the current test question to generate first test question track data, and forming first invigilation data records by the first test question identification data and the first test question track data to be stored in a first invigilation record queue; acquiring a first test question data group sequence; the examination questions of the first invigilation record queue are scored to generate a first scoring data group sequence; analyzing the examination progress of each examinee in real time according to the first grading data group sequence; analyzing the total progress of all examinees in real time; real-time knowledge category to be enhanced of each examinee according to the first scoring data group sequence; and analyzing the general knowledge category to be strengthened reflected by the examination in real time. By the method and the system, the real-time answering state of the examinee can be tracked and analyzed in the examination process.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an invigilation data processing method.
Background
With the application and development of network technology in the teaching field, the application technology for processing the online examination of multiple persons and quickly giving the evaluation result after the examination is finished is mature. However, the conventional multi-person online examination processing scheme also has some disadvantages: in order to facilitate tracking of real-time answer states of examinees, on-line examination conventionally only provides objective question types (such as choice questions, non-questions and the like) which answer by clicking a mouse, and does not provide subjective question types (such as discussion questions and the like) which answer by manually handwriting input; if the examination questions with the subjective question types are provided, the examination papers of the examinees can only be manually collected and sorted after the examination, and the answering states of the examination questions with the subjective question types of the examinees cannot be tracked in real time in the examination process.
An electronic pen (digital pen) is a common personal handwriting input device. The electronic pen can write and draw on any handwriting medium (such as an electronic screen, a dot code paper, a common paper and the like), and collects the writing position and the writing track of the electronic pen in real time during the writing process of a user. The electronic pen can keep the good writing habit of the user and can transmit the acquired track data to the upper equipment connected with the electronic pen in real time.
In view of the above-mentioned shortcomings of the conventional multi-user online examination processing scheme, the problem to be solved by the invention is how to improve the conventional scheme by utilizing a mature electronic pen technology, so that the answering state of the subjective question type test questions of the examinees can be tracked and analyzed in real time in the examination process.
Disclosure of Invention
The invention aims to provide an invigilating data processing method, electronic equipment and a computer readable storage medium aiming at the defects of the prior art, wherein an electronic pen is used as a question answering tool for examinees, real-time question answering information of each examinee is collected by the aid of the question answering tool, and the examination progress of each examinee and even the total progress of all examinees are analyzed in real time according to the collected information; and analyzing the knowledge scope to be strengthened of each examinee and even the general knowledge scope to be strengthened of the examination in real time. By the method and the system, the real-time answering state of the examinee can be tracked and analyzed in the examination process.
In order to achieve the above object, a first aspect of the embodiments of the present invention provides an invigilation data processing method, including:
in the examination process, the invigilation system identifies identification information of current test questions being answered by each examinee through an image identification function and a writing track acquisition function of an electronic pen to generate corresponding first test question identification data, arranges writing tracks of the questions answered by each examinee under the current test questions to generate corresponding first test question track data, and forms first invigilation data records by the first test question identification data and the first test question track data to store the first invigilation data records in a first invigilation record queue corresponding to each examinee; the invigilation system is connected with a plurality of electronic pens;
acquiring comprehensive examination question information of examination questions of the examination and generating a first examination question data group sequence;
carrying out examination question grading processing on the first invigilation record queue according to the first examination question data group sequence to generate a first grading data group sequence;
analyzing the examination progress of each examinee in real time according to the first grading data group sequence to generate corresponding first examination progress data; analyzing the total progress of all examinees in real time according to all the first examination progress data;
analyzing the knowledge domain to be enhanced of each examinee in real time according to the first scoring data group sequence to generate a first knowledge domain data sequence; and analyzing the general knowledge category to be strengthened reflected by the examination in real time according to all the first knowledge category data sequences.
Preferably, the first test question data group sequence comprises a plurality of first test question data groups; the first test question data group comprises second test question identification data, first test question type data, first test question knowledge category data, first test question answer data and first test question score data; the first test question type data comprises objective question types and subjective question types;
the first scoring data set sequence comprises a plurality of first scoring data sets; the first grading data group comprises third test question identification data, second test question knowledge category data, second test question score data and first test question score data.
Preferably, the scoring the test questions of the first invigilation record queue according to the first test question data group sequence to generate a first scoring data group sequence specifically includes:
polling each first invigilation data record of the first invigilation record queue, and recording the first invigilation data record which is polled currently as a current invigilation data record; recording the first test question data in the first test question data group sequence, wherein the second test question identification data is matched with the first test question identification data recorded by the current invigilation data, as current test question data; distributing a corresponding first grading data set for the current invigilation data record to be recorded as a current grading data set;
carrying out graphic/character information conversion processing on the first test question track data recorded by the current invigilation data to generate corresponding first data to be compared;
when the first test question type data of the current test question data is an objective question type, judging whether the first test question answer data of the current test question data is matched with the first to-be-compared data; if the test question data are matched with the test question data, setting the first test question score data of the current score data set according to the first test question score data of the current test question data; if not, setting the first test question scoring data of the current scoring data group as 0;
when the first test question type data of the current test question data is a subjective question type, calling a preset subjective question scoring interface, and carrying out subjective question scoring processing on the first to-be-compared data according to the first test question answer data of the current test question data to generate corresponding first score data; setting the first test question scoring data of the current scoring data set according to the first scoring data;
setting the third test question identification data of the current grading data set according to the first test question identification data recorded by the current invigilation data or the second test question identification data of the current test question data; setting the second test question knowledge domain data of the current grading data set according to the first test question knowledge domain data of the current test question data; setting the second test question score data of the current score data group according to the first test question score data of the current test question data;
and the first scoring data set sequence is formed by all the first scoring data sets which are allocated to all the first invigilation data records.
Preferably, the analyzing the examination progress of each examinee in real time according to the first scoring data group sequence to generate corresponding first examination progress data specifically includes:
summing all the second test question score data of the first scoring data group sequence to generate first answered total score data; and generating corresponding first examination progress data according to the ratio of the first total score data to a preset total score of the examination paper.
Preferably, the analyzing the total progress of all the examinees in real time according to all the first examination progress data specifically includes:
the identity information of each examinee and the corresponding first examination progress data form corresponding first examinee real-time information records, and all the first examinee real-time information records form a first total real-time list;
performing sum calculation on all the first examination progress data, and dividing the result of the sum calculation by the total number of the examination population to obtain first total progress data;
calculating the remaining time of the examination according to the current system time, the initial time of the examination and the total duration of the examination to generate first remaining time;
and according to the first total real-time list, the first total progress data and the first remaining time, performing data filling on a preset examinee total progress display template to generate and display a corresponding first display interface.
Preferably, the analyzing the knowledge domain to be enhanced of each examinee in real time according to the first scoring data group sequence to generate a first knowledge domain data sequence specifically includes:
extracting the second test question knowledge category data of the first test question scoring data set with the first test question scoring data of 0 in the first scoring data set sequence to form a first data sequence; dividing the same second test question knowledge domain data in the first data sequence into a group, and counting the total number of the second test question knowledge domain data of each group to generate a corresponding first group total number; and sequencing the second test question knowledge domain data corresponding to the first group of total numbers in a descending order to generate the first knowledge domain data sequence.
Preferably, the analyzing, in real time, the general knowledge category to be enhanced reflected in the examination according to all the first knowledge category data sequences specifically includes:
the identity information of each examinee and the corresponding first knowledge category data sequence form a corresponding second examinee real-time information record, and all the second examinee real-time information records form a second overall real-time list;
performing sequence combination on all the first knowledge domain data sequences to generate a second data sequence; dividing the same second test question knowledge domain data in the second data sequence into one group, and counting the total number of the second test question knowledge domain data of each group to generate a corresponding second group total number; sequencing the second test question knowledge domain data corresponding to the second group of total data in a descending order to generate a first total knowledge domain data sequence;
and according to the second total real-time list and the first total knowledge domain data sequence, performing data filling on a preset total to-be-enhanced knowledge domain display template to generate and display a corresponding second display interface.
A second aspect of an embodiment of the present invention provides an electronic device, including: a memory, a processor, and a transceiver;
the processor is configured to be coupled to the memory, read and execute instructions in the memory, so as to implement the method steps of the first aspect;
the transceiver is coupled to the processor, and the processor controls the transceiver to transmit and receive messages.
A third aspect of embodiments of the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a computer, cause the computer to perform the method of the first aspect.
The embodiment of the invention provides an invigilation data processing method, electronic equipment and a computer readable storage medium, wherein an electronic pen is used as an answering tool of an examiner, real-time answering information of each examiner is collected by the answering tool, and the examination progress of each examinee and even the total progress of all examinees are analyzed in real time according to the collected information; and analyzing the knowledge scope to be strengthened of each examinee and even the general knowledge scope to be strengthened of the examination in real time. By the method and the system, the real-time answering state of the examinee can be tracked and analyzed in the examination process.
Drawings
FIG. 1 is a schematic diagram of an invigilation data processing method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an electronic device according to a second embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic diagram of an invigilation data processing method according to an embodiment of the present invention, as shown in fig. 1, the method mainly includes the following steps:
step 1, in the examination process, an invigilation system identifies identification information of current test questions being answered by each examinee through an image identification function and a writing track acquisition function of an electronic pen to generate corresponding first test question identification data, arranges writing tracks of the questions answered by each examinee under the current test questions to generate corresponding first test question track data, and forms first invigilation data records by the first test question identification data and the first test question track data to store in a first invigilation record queue corresponding to each examinee;
wherein, invigilating the system and being connected with a plurality of electronic pens.
Before the examination, each examinee is assigned with an electronic pen and an examination paper in the examination, and the identity information of each examinee is bound with the assigned electronic pen; in the examination process, each examinee uses the electronic pen to answer each examination question by handwriting on an examination paper; when answering each test question handwriting, an examinee firstly clicks a test question identification symbol at the position of an identification area of a current test question on an examination paper by using an electronic pen, and an invigilation system identifies the information of the test question identification symbol in the identification area through the image identification function of the electronic pen in the clicking process to obtain first test question identification data; after the click operation of the test question identification symbol is completed at the position of the current test question identification area, an examinee can write an answer in the answer area of the current test question on an examination paper by using an electronic pen, the invigilation system carries out single track information acquisition on all writing tracks in the current answer area through the image recognition function and the writing track acquisition function of the electronic pen in the process of writing the answer, and carries out track combination processing on all acquired single tracks, so that first test question track data are obtained. Each first invigilation data record corresponds to one examination question, and the first invigilation record queue obtained in real time can reflect the number of the answered questions of the current examinee at the current moment, and the identification and answering content of the answered questions of each examination question.
Step 2, acquiring comprehensive examination question information of examination questions of the examination and generating a first examination question data set sequence;
wherein the first test question data group sequence comprises a plurality of first test question data groups; the first test question data group comprises second test question identification data, first test question type data, first test question knowledge category data, first test question answer data and first test question score data; the first test question type data includes an objective question type and a subjective question type.
Here, the first examination question data group sequence is a comprehensive information sequence corresponding to all questions of the examination paper of the current time; each first test question data set corresponds to a specific test question on the examination paper of the test; the second test question identification data is identification information of the current test question; the first test question type data is question type information of the current test question, and specifically comprises an objective question type and a subjective question type; the first test question knowledge domain data is knowledge domain classification information of the current test question; the first test question data is the specific question information of the current test question; the first test question answer data is the reference answer information of the current test question; the first test question score data is full score information of the current test question.
Step 3, carrying out test question grading processing on the first invigilation record queue according to the first test question data group sequence to generate a first grading data group sequence;
wherein the first scoring data set sequence comprises a plurality of first scoring data sets; the first grading data group comprises third test question identification data, second test question knowledge category data, second test question score data and first test question score data;
here, the first scoring data set sequence is the real-time scoring data sequence of the first invigilation record queue; each first scoring data set corresponds to a first invigilation data record and a first test question data set, namely the three data sets correspond to the same test question; the third test question identification data is identification information of the current test question, is consistent with the first test question identification data of the first invigilation data record corresponding to the current grading data group, and is also consistent with the second test question identification data of the first test question data group corresponding to the current grading data group; the second test question knowledge domain data is knowledge domain classification information of the current test question and is consistent with the first test question identification data of the first test question data group corresponding to the current grading data group; the second test question score data is full score information of the current test question and is consistent with the first test question score data of the first test question data group corresponding to the current score data group;
here, in the embodiment of the present invention, each first test question trajectory data in the first invigilation record queue is subjected to image-text conversion to generate recognizable image-text information, a corresponding relation of test questions in the first invigilation record queue is performed according to a first test question data group sequence, score evaluation is performed on each converted image-text information by using first test question answer data in the first test question data group sequence as a scoring basis to obtain corresponding score information, and then associated information such as test question identification, test question knowledge category, test question score and the like are extracted from the first test question data group sequence or the first invigilation record queue to form a first scoring data group, so as to obtain a first scoring data group sequence;
the method specifically comprises the following steps: step 31, polling each first invigilation data record of the first invigilation record queue, and recording the currently polled first invigilation data record as a current invigilation data record; recording the first test question data in the first test question data group sequence, wherein the second test question identification data is matched with the first test question identification data recorded by the current invigilation data, as the current test question data; distributing a corresponding first grading data group for the current invigilation data record and recording the first grading data group as a current grading data group;
step 32, carrying out graph/character information conversion processing on the first test question track data recorded by the current invigilation data to generate corresponding first data to be compared;
here, when the first test question type data corresponding to the first test question trajectory data is a subjective question type, the content of the first test question trajectory data may involve operations such as drawing, formulas and the like, and in order to ensure that answer information is not missed, the first test question trajectory data is subjected to graph/image information conversion at this time to generate first data to be compared; when the first test question type data corresponding to the first test question track data is an objective question type, the content of the first test question track data is generally character information or character string information, and at the moment, the first test question track data is subjected to character information conversion to generate first data to be compared;
step 33, when the first test question type data of the current test question data is an objective question type, judging whether the first test question answer data of the current test question data is matched with the first to-be-compared data; if the test question data are matched with the current test question data, setting first test question score data of a current score data set according to the first test question score data of the current test question data; if not, setting the first test question scoring data of the current scoring data set as 0;
here, as described above, when the first test question type data of the current test question data is the objective question type, the first to-be-compared data is conventionally the text information, so that the first test question answer data and the first to-be-compared data can be directly used for character comparison to verify whether the two are matched; it should be noted that, when comparing characters, if the characters are letters, the sizes of the letters are not distinguished;
step 34, when the first test question type data of the current test question data is the subjective question type, calling a preset subjective question scoring interface, and performing subjective question scoring processing on the first to-be-compared data according to the first test question answer data of the current test question data to generate corresponding first score data; setting first test question scoring data of the current scoring data set according to the first scoring data;
here, as described above, the first to-be-compared data is conventionally the graphic/image information when the first test question type data of the current test question data is the subjective question type; the preset subjective question scoring interface can be an artificial scoring interface or an artificial intelligence model interface based on an artificial intelligence image semantic recognition model; the corresponding subjective question scoring interface is also provided with a system parameter which needs to be preset, namely an interface use mode;
further, a preset subjective question scoring interface is called, subjective question scoring processing is performed on the first to-be-compared data according to first test question answer data of the current test question data, and corresponding first score data are generated, wherein the method specifically comprises the following steps:
step A1, recognizing the interface use mode;
step A2, when the interface using mode is manual mode, setting the subjective question scoring interface as manual scoring interface; sending first test question answer data and first to-be-compared data to a scoring teacher through a manual scoring interface, and receiving scoring information returned by the scoring teacher as first scoring data through the manual scoring interface;
step A3, when the interface using mode is a dynamic mode, identifying whether the answer data of the first test question is single image data; if the answer data of the first test question is single image data, setting a subjective question scoring interface as an artificial intelligence model interface; comparing the image matching degree of the first test question answer data with the first data to be compared through an artificial intelligence model interface to generate a first matching degree; if the first matching degree is higher than the designated threshold value, setting the corresponding first score data as full score, namely the corresponding first test question score data; if the first matching degree is not higher than the designated threshold value, modifying the subjective question scoring interface into a manual scoring interface, sending first test question answer data and first to-be-compared data to a scoring teacher through the manual scoring interface, and receiving scoring information returned by the scoring teacher through the manual scoring interface to serve as first scoring data; if the first test question answer data is not single image data, the subjective question scoring interface is modified into a manual scoring interface, the first test question answer data and the first to-be-compared data are sent to a scoring teacher through the manual scoring interface, and scoring information returned by the scoring teacher is received through the manual scoring interface and serves as first scoring data;
here, when the interface usage mode is the dynamic mode, if the answer data of the first test question is single image data, it indicates that the current test question is a subjective question type similar to geometric drawing, in this case, the artificial intelligent model interface is preferentially used for scoring, so that the scoring efficiency can be greatly improved; to ensure the accuracy of the model comparison, the specified threshold for defining the degree of match is generally set to a percentage value of over 90%; if the answer data of the first test question is lower than the threshold value, the answer data of the first test question is obviously different from the data to be compared, and in order to ensure the grading accuracy, the grading needs to be carried out again through a manual grading interface; in addition, if the answer data of the first test question is single image data, the answer content of the current test question may include complex contents such as images, characters, formulas and the like, and in order to ensure the scoring accuracy, scoring can be performed only through a manual scoring interface;
step 35, setting third test question identification data of the current grading data set according to the first test question identification data recorded by the current invigilation data or the second test question identification data of the current test question data; setting second test question knowledge domain data of the current grading data set according to first test question knowledge domain data of the current test question data; setting second test question score data of the current score data group according to the first test question score data of the current test question data;
a first scoring data set sequence is formed by all first scoring data sets assigned to all first invigilation data records, step 36.
Step 4, analyzing the examination progress of each examinee in real time according to the first grading data group sequence to generate corresponding first examination progress data; analyzing the total progress of all examinees in real time according to all first examination progress data;
the method specifically comprises the following steps: step 41, analyzing the examination progress of each examinee in real time according to the first grading data group sequence to generate corresponding first examination progress data;
the method specifically comprises the following steps: summing all second test question score data of the first score data group sequence to generate first answered total score data; generating corresponding first examination progress data according to the ratio of the first total score data answered to the preset total score of the examination paper;
for example, the examination questions of the examination have 3 times, each time has 10 points, and the total number of the examination papers is 30; the first scoring data set sequence includes 2 first scoring data sets (first scoring data set 1, first scoring data set 2); wherein, the second test question score data of the first grading data group 1 is 10, and the second test question score data of the first grading data group 2 is 10; then the first total point data is 10+ 10-20, and the first test progress data is 2/3;
step 42, analyzing the total progress of all examinees in real time according to all first examination progress data;
the method specifically comprises the following steps: step 421, forming corresponding first examinee real-time information records by the identity information of each examinee and corresponding first examination progress data, and forming a first total real-time list by all the first examinee real-time information records;
step 422, performing sum calculation on all the first examination progress data, and dividing the result of the sum calculation by the total number of the examination persons to obtain first total progress data;
here, the first total progress data is actually an average value of real-time progress of all examinees;
step 423, calculating the remaining time of the examination according to the current system time, the initial time of the examination and the total duration of the examination to generate first remaining time;
and 424, according to the first total real-time list, the first total progress data and the first remaining time, performing data filling on a preset total examinee progress display template to generate and display a corresponding first display interface.
Here, by displaying the first total real-time list, the first total progress data and the first remaining time on the same screen, the invigilator can inquire the real-time examination progress of each examinee, and can also visually know the real-time total average progress of the examination.
Step 5, analyzing the knowledge domain to be enhanced of each examinee in real time according to the first scoring data group sequence to generate a first knowledge domain data sequence; analyzing the general knowledge category to be strengthened reflected by the examination in real time according to all the first knowledge category data sequences;
the method specifically comprises the following steps: step 51, analyzing the knowledge domain to be enhanced of each examinee in real time according to the first scoring data group sequence to generate a first knowledge domain data sequence;
the method specifically comprises the following steps: extracting second test question knowledge domain data of a first score data group with first test question score data of 0 in the first score data group sequence to form a first data sequence; dividing the same second test question knowledge domain data in the first data sequence into a group, and counting the total number of the second test question knowledge domain data of each group to generate a corresponding first group total number; sequencing the second test question knowledge domain data corresponding to the first group of total numbers in a descending order to generate a first knowledge domain data sequence;
for example, the test questions of the mathematical examination include 4 test questions, which are divided into test questions 1, 2, 3, and 4, and the second test question knowledge domain data corresponding to the test questions 1, 2, 3, and 4 are respectively the second test question knowledge domain data 1 "a binary linear equation domain", the second test question knowledge domain data 2 "a trigonometric function domain", the second test question knowledge domain data 3 "a trigonometric function domain", and the second test question knowledge domain data 4 "an arrangement and combination domain"; the first test question scoring data corresponding to the test questions 1, 2, 3 and 4 in the first scoring data group sequence are all 0, 0 and 10; then, the first data sequence should be ("one-dimensional equation category", "trigonometric function category"); the first data sequence is divided into 2 groups: the 1 st group is a 'binary linear equation category' group, the corresponding first group total number is 1, the 2 nd group is a 'trigonometric function category' group, and the corresponding first group total number is 2; the finally obtained first knowledge category data sequence is in a ' trigonometric function category ' or a ' linear equation of two elements ' category ';
the first knowledge domain data sequence can reflect the knowledge domain of the wrong question of the examinee, and can reflect the priority relationship of each wrong knowledge domain through the sequencing relationship of the sequence, and the higher the sequencing is, the more the importance of the examinee or the proctor is;
step 52, analyzing the general knowledge category to be strengthened reflected by the examination in real time according to all the first knowledge category data sequences;
the method specifically comprises the following steps: step 521, forming corresponding second examinee real-time information records by the identity information of each examinee and the corresponding first knowledge category data sequence, and forming a second overall real-time list by all the second examinee real-time information records;
step 522, combining all the first knowledge domain data sequences to generate a second data sequence; dividing the same second test question knowledge domain data in the second data sequence into one group, and counting the total number of the second test question knowledge domain data of each group to generate a corresponding second group total number; sequencing the second test question knowledge domain data corresponding to the second group of total data in a descending order to generate a first general knowledge domain data sequence;
similar to step 51, the statistical analysis is simply performed on the wrong-question knowledge range of the whole examinees, and the finally obtained first overall knowledge range data sequence can reflect the main wrong-question knowledge range of the examinees, and the closer the ranking is, the more the importance of the whole examinees or the proctor is;
step 523, according to the second total real-time list and the first total knowledge domain data sequence, data filling is performed on the preset total to-be-enhanced knowledge domain display template to generate and display a corresponding second display interface.
Here, by displaying the second total real-time list and the first total knowledge domain data sequence on the same screen, the invigilator can visually understand the knowledge domain to be enhanced for each examinee, and can visually understand the comprehensive missing knowledge domain of all examinees.
It should be noted that the embodiment of the present invention further supports synchronous tracking and display of the real-time answer trajectory of each examinee according to the first invigilation record queue, and specifically includes:
step B1, distributing an examination paper display page for each examinee, and initializing each examination paper display page according to the first examination question data set sequence and a preset examination paper display template; an answer content display area is preset for each test question on the test paper display page;
step B2, extracting first test question track data of each first invigilation data record in sequence according to a first-in first-out principle from a first invigilation record queue corresponding to the examinee regularly according to a preset time interval to form a first track sequence; image data conversion processing is carried out on each first test question track data of the first track sequence, and corresponding first test question images are generated;
step B3, setting each first test question image to an answer content display area of the corresponding test question on an examination paper display page corresponding to the examinee;
and step B4, acquiring examinee identity information input by the invigilator, and displaying an examination scroll display page corresponding to the examinee identity information.
Fig. 2 is a schematic structural diagram of an electronic device according to a second embodiment of the present invention. The electronic device may be the terminal device or the server, or may be a terminal device or a server connected to the terminal device or the server and implementing the method according to the embodiment of the present invention. As shown in fig. 2, the electronic device may include: a processor 301 (e.g., a CPU), a memory 302, a transceiver 303; the transceiver 303 is coupled to the processor 301, and the processor 301 controls the transceiving operation of the transceiver 303. Various instructions may be stored in memory 302 for performing various processing functions and implementing the processing steps described in the foregoing method embodiments. Preferably, the electronic device according to an embodiment of the present invention further includes: a power supply 304, a system bus 305, and a communication port 306. The system bus 305 is used to implement communication connections between the elements. The communication port 306 is used for connection communication between the electronic device and other peripherals.
The system bus 305 mentioned in fig. 2 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus. The communication interface is used for realizing communication between the database access device and other equipment (such as a client, a read-write library and a read-only library). The Memory may include a Random Access Memory (RAM) and may also include a Non-Volatile Memory (Non-Volatile Memory), such as at least one disk Memory.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), a Graphics Processing Unit (GPU), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
It should be noted that the embodiment of the present invention also provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to execute the method and the processing procedure provided in the above-mentioned embodiment.
The embodiment of the present invention further provides a chip for executing the instructions, where the chip is configured to execute the processing steps described in the foregoing method embodiment.
The embodiment of the invention provides an invigilation data processing method, electronic equipment and a computer readable storage medium, wherein an electronic pen is used as an answering tool of an examiner, real-time answering information of each examiner is collected by the answering tool, and the examination progress of each examinee and even the total progress of all examinees are analyzed in real time according to the collected information; and analyzing the knowledge scope to be strengthened of each examinee and even the general knowledge scope to be strengthened of the examination in real time. By the method and the system, the real-time answering state of the examinee can be tracked and analyzed in the examination process.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. An invigilation data processing method, comprising:
in the examination process, the invigilation system identifies identification information of current test questions being answered by each examinee through an image identification function and a writing track acquisition function of an electronic pen to generate corresponding first test question identification data, arranges writing tracks of the questions answered by each examinee under the current test questions to generate corresponding first test question track data, and forms first invigilation data records by the first test question identification data and the first test question track data to store the first invigilation data records in a first invigilation record queue corresponding to each examinee; the invigilation system is connected with a plurality of electronic pens;
acquiring comprehensive examination question information of examination questions of the examination and generating a first examination question data group sequence;
carrying out examination question grading processing on the first invigilation record queue according to the first examination question data group sequence to generate a first grading data group sequence;
analyzing the examination progress of each examinee in real time according to the first grading data group sequence to generate corresponding first examination progress data; analyzing the total progress of all examinees in real time according to all the first examination progress data;
analyzing the knowledge domain to be enhanced of each examinee in real time according to the first scoring data group sequence to generate a first knowledge domain data sequence; and analyzing the general knowledge category to be strengthened reflected by the examination in real time according to all the first knowledge category data sequences.
2. The examination data processing method according to claim 1,
the first test question data group sequence comprises a plurality of first test question data groups; the first test question data group comprises second test question identification data, first test question type data, first test question knowledge category data, first test question answer data and first test question score data; the first test question type data comprises objective question types and subjective question types;
the first scoring data set sequence comprises a plurality of first scoring data sets; the first grading data group comprises third test question identification data, second test question knowledge category data, second test question score data and first test question score data.
3. The invigilation data processing method of claim 2, wherein said scoring the first invigilation record queue according to the first test question data group sequence to generate a first scoring data group sequence, specifically comprising:
polling each first invigilation data record of the first invigilation record queue, and recording the first invigilation data record which is polled currently as a current invigilation data record; recording the first test question data in the first test question data group sequence, wherein the second test question identification data is matched with the first test question identification data recorded by the current invigilation data, as current test question data; distributing a corresponding first grading data set for the current invigilation data record to be recorded as a current grading data set;
carrying out graphic/character information conversion processing on the first test question track data recorded by the current invigilation data to generate corresponding first data to be compared;
when the first test question type data of the current test question data is an objective question type, judging whether the first test question answer data of the current test question data is matched with the first to-be-compared data; if the test question data are matched with the test question data, setting the first test question score data of the current score data set according to the first test question score data of the current test question data; if not, setting the first test question scoring data of the current scoring data group as 0;
when the first test question type data of the current test question data is a subjective question type, calling a preset subjective question scoring interface, and carrying out subjective question scoring processing on the first to-be-compared data according to the first test question answer data of the current test question data to generate corresponding first score data; setting the first test question scoring data of the current scoring data set according to the first scoring data;
setting the third test question identification data of the current grading data set according to the first test question identification data recorded by the current invigilation data or the second test question identification data of the current test question data; setting the second test question knowledge domain data of the current grading data set according to the first test question knowledge domain data of the current test question data; setting the second test question score data of the current score data group according to the first test question score data of the current test question data;
and the first scoring data set sequence is formed by all the first scoring data sets which are allocated to all the first invigilation data records.
4. The invigilation data processing method of claim 2, wherein the real-time analysis of the examination progress of each examinee according to the first scoring data group sequence to generate corresponding first examination progress data specifically comprises:
summing all the second test question score data of the first scoring data group sequence to generate first answered total score data; and generating corresponding first examination progress data according to the ratio of the first total score data to a preset total score of the examination paper.
5. The invigilation data processing method of claim 2, wherein the real-time analysis of the total progress of all the examinees according to all the first examination progress data specifically comprises:
the identity information of each examinee and the corresponding first examination progress data form corresponding first examinee real-time information records, and all the first examinee real-time information records form a first total real-time list;
performing sum calculation on all the first examination progress data, and dividing the result of the sum calculation by the total number of the examination population to obtain first total progress data;
calculating the remaining time of the examination according to the current system time, the initial time of the examination and the total duration of the examination to generate first remaining time;
and according to the first total real-time list, the first total progress data and the first remaining time, performing data filling on a preset examinee total progress display template to generate and display a corresponding first display interface.
6. The invigilation data processing method of claim 2, wherein said analyzing the knowledge domain to be enhanced of each examinee in real time according to the first scoring data set sequence to generate a first knowledge domain data sequence, specifically comprising:
extracting the second test question knowledge category data of the first test question scoring data set with the first test question scoring data of 0 in the first scoring data set sequence to form a first data sequence; dividing the same second test question knowledge domain data in the first data sequence into a group, and counting the total number of the second test question knowledge domain data of each group to generate a corresponding first group total number; and sequencing the second test question knowledge domain data corresponding to the first group of total numbers in a descending order to generate the first knowledge domain data sequence.
7. The invigilation data processing method according to claim 2, wherein said analyzing the general knowledge domain to be enhanced reflected in the examination in real time according to all the first knowledge domain data sequences specifically comprises:
the identity information of each examinee and the corresponding first knowledge category data sequence form a corresponding second examinee real-time information record, and all the second examinee real-time information records form a second overall real-time list;
performing sequence combination on all the first knowledge domain data sequences to generate a second data sequence; dividing the same second test question knowledge domain data in the second data sequence into one group, and counting the total number of the second test question knowledge domain data of each group to generate a corresponding second group total number; sequencing the second test question knowledge domain data corresponding to the second group of total data in a descending order to generate a first total knowledge domain data sequence;
and according to the second total real-time list and the first total knowledge domain data sequence, performing data filling on a preset total to-be-enhanced knowledge domain display template to generate and display a corresponding second display interface.
8. An electronic device, comprising: a memory, a processor, and a transceiver;
the processor is used for being coupled with the memory, reading and executing the instructions in the memory to realize the method steps of any one of claims 1 to 7;
the transceiver is coupled to the processor, and the processor controls the transceiver to transmit and receive messages.
9. A computer-readable storage medium having stored thereon computer instructions which, when executed by a computer, cause the computer to perform the method of any of claims 1-7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114580375A (en) * | 2022-05-09 | 2022-06-03 | 南京赛宁信息技术有限公司 | Distributed online match subjective question marking and scoring method and system |
| CN116778770A (en) * | 2023-08-21 | 2023-09-19 | 莱芜职业技术学院 | Interactive system for intelligent teaching |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114580375A (en) * | 2022-05-09 | 2022-06-03 | 南京赛宁信息技术有限公司 | Distributed online match subjective question marking and scoring method and system |
| CN114580375B (en) * | 2022-05-09 | 2022-08-12 | 南京赛宁信息技术有限公司 | Distributed online match subjective question marking and scoring method and system |
| CN116778770A (en) * | 2023-08-21 | 2023-09-19 | 莱芜职业技术学院 | Interactive system for intelligent teaching |
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