Experimental process and experimental data management system, method, equipment and medium

Abstract

The invention provides an experimental process and experimental data management system, method, equipment and medium, an experimental process information management module of the system is used for generating an experimental record for each experimenter, and the content of the experimental record comprises experimental result inspection information and experimental process inspection information; the experimental data acquisition module is used for filling experimental data in an experimental process by an experimenter and performing data rationality evaluation so as to feed back experimental result inspection information; the experiment report information acquisition module is used for respectively filling content evaluation by experimenters and experiment teachers; and the score summarization module is used for processing and scoring the data acquired in the experiment process to realize score summarization. According to the invention, the experimental process management can be enhanced, the proportion of the experimental process in examination can be enhanced, the experimental feedback information and feedback speed can be enhanced, the experimental completion effect can be improved, the CT-type experimental data management can realize omnibearing observation of experimental objects, the problems of low efficiency and low response of data auditing of experimental teachers are solved, and the teaching quality is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of experimental management, and particularly relates to a system, method, device and medium for experimental process and experimental data management. Background Art

[0002] In traditional circuit experiment teaching, the experimental data processing process generally includes students collecting and recording experimental data in class and simply processing the experimental data after class, such as: listing, calculating, drawing fitting curves, verifying theories, etc. Usually, multiple experimental steps are set within the experimental class hours, and each experimental step corresponds to a circuit structure. Since the circuit needs to be disassembled after each experimental step is completed, the next step can only be carried out after the teacher's acceptance and review. Therefore, after each experimental step is completed in the experimental class, students record the collected experimental result data on the experimental record paper and hand it over to the experimental teacher for review. After passing, the next experimental step is carried out. However, in practice, students are used to submitting all the experimental steps for review at one time after all the steps are completed.

[0003] The main role played by the experimental teacher in the experimental data processing process is to review the data after the students have completed the collection of experimental data. And the teacher needs sufficient experimental experience to review the experimental data and have an overall understanding of the experimental results. However, since the time when students submit the experimental data for acceptance often concentrates before class, the experimental teacher needs to have a high review response ability. In fact, it is very difficult to ensure both of these two points.

[0004] In traditional circuit experiment teaching, the experimental teaching class hours are limited. From the perspective of the curriculum, the experiment needs to cover many knowledge points of the discipline. From the perspective of experimental implementation, the premise for completing the collection of experimental data is to complete the circuit construction and debugging. The time left for experimental data collection is limited, the amount of data collected is limited and isolated, and the collected data cannot comprehensively outline the attributes of the experimental object.

[0005] In summary, the traditional circuit experiment assessment system emphasizes results over processes, and there are defects in the experimental data processing method in traditional circuit experiment teaching, such as limited experimental time, isolated experimental data, and difficulty for experimental teachers to review experimental data.

[0006] In related technologies, some experimental data management solutions are developed by real-time collection through third-party hardware, mainly to complete the judgment of the authenticity and correctness of experimental data, but cannot achieve experimental process management, collection and division of students' experimental data, acquisition of comprehensive parameters, judgment of experimental data and correction of experimental processes, big data technology of experimental data, etc.

[0007] Therefore, it is necessary to provide a new method to solve the above technical problems. Summary of the Invention

[0008] To achieve the above objects and other advantages of the present invention, the first object of the present invention is to provide an experimental process and experimental data management system, including an experimental process information management module, an experimental data acquisition module, an experimental report information acquisition module, and a score summary module; wherein,

[0009] The experimental process information management module is used to generate an experimental record for each experimental personnel, and the content of the experimental record includes experimental result inspection information and experimental process inspection information;

[0010] The experimental data acquisition module is used for experimental personnel to fill in experimental data during the experimental process and conduct data rationality evaluation to feedback experimental result inspection information;

[0011] The experimental report information acquisition module is used for experimental personnel and experimental teachers to fill in content evaluations respectively;

[0012] The score summary module is used to process and score the data collected during the experimental process to achieve score summary.

[0013] Further, the experimental process inspection information is obtained by performing AI analysis on the device working status interface diagram uploaded by the experimental personnel to extract the experimental process information data therein, or obtained by the experimental teacher's on-site inspection and filling.

[0014] Further, the experimental report information acquisition module is configured to use a table in the background and a questionnaire in the foreground to collect data; wherein, the questionnaire involves objective content evaluation, which is filled in by experimental personnel and experimental teachers respectively and synthesized as the objective scoring part of the experimental report, and the subjective content evaluation is filled in by the experimental teacher.

[0015] Further, the data types filled in by students in the experimental data acquisition module include numerical type, text information type, and waveform; wherein, the text information type is configured with multiple preset options; the waveform is configured as a text format describing the digital signal timing diagram and the waveform description length is agreed; the numerical type is configured as integer type and floating-point type, the integer type uses equal value judgment, and the floating-point type adopts interval judgment. If there is a monotonic change rule or formula relationship rule between the data, then rule judgment is performed.

[0016] Further, the experimental data acquisition module realizes data verification through functions or scripts.

[0017] Further, the experimental data acquisition module calls scripts to analyze the rationality of filled data, the rationality of function calculation results, and the position of the measurement data of experimental personnel in the big data sample of the experimental personnel group, and displays it in the acceptance conclusion field.

[0018] Further, the position of the measurement data of the experimenter in the big data sample of the experimenter group is characterized by the semi-percentile and semi-range ratio of the current sample in the current data item; wherein,

[0019] The semi-percentile is the ratio of the number of internal and external samples in the interval from the current sample to the mean value, and the formula is:

[0020] m / (m + n)×100%

[0021] wherein, m is the number of samples between the mean value and the current sample, and m + n is the total number of samples;

[0022] The semi-range ratio is the ratio of the internal and external distances in the interval from the current sample to the mean value, and the formula is:

[0023] Δy / (Δy + Δx)×100%

[0024] wherein, Δy is the numerical difference between the mean value and the current sample, Δy + Δx is the difference between the mean value and the farthest sample, and the farthest sample is the sample that is farther from the mean value among the maximum value and the minimum value.

[0025] Further, it further includes an auxiliary module, and the auxiliary module is used to provide judgment rules, and store the evaluation weight parameters of different experimental process data collected during the score summary, and the data rationality judgment basis of the experimental data acquisition module for querying the rationality judgment of experimental data.

[0026] Further, the experimental data acquisition module is further configured with a task field, and the task field is used to implement the segmentation of experimental tasks to allocate different task experiments and all measurement requirements under the task experiment to the experimenter.

[0027] Further, the auxiliary module is also configured with a task field, and the task field of the auxiliary module is used to implement task differential review.

[0028] Further, the experimental process information management module, the experimental data acquisition module, the experimental report information acquisition module, the score summary module, and the auxiliary module are configured as a general collaborative form.

[0029] Further, the score summary module processes and scores the data collected during the experimental process through a script.

[0030] Further, the score summary module calculates the total score by adding the weighted integral of the objective item unit, the weighted integral of the subjective evaluation unit, the weighted integral calculated by compiling built-in functions for the design class acquisition index parameters, and the weighted integral converted by the acceptance time.

[0031] The second object of the present invention is to provide an experimental process and experimental data management method, which is applied to the above system and includes the following steps:

[0032] Receive the experimental process information submitted by the experimenter and generate an experimental record for the experimenter; wherein, the content of the experimental record includes experimental result inspection information and experimental process inspection information;

[0033] Receive the experimental data filled in by the experimenter and conduct a rationality evaluation of the data to feedback the experimental result inspection information;

[0034] Receive the content evaluations filled in by the experimenter and the experimental teacher respectively;

[0035] Process and score the data collected during the experiment to achieve result summary.

[0036] Furthermore, it also includes the step of obtaining experimental process inspection information:

[0037] Receive the device working status interface diagram uploaded by the experimenter;

[0038] Conduct AI analysis on the device working status interface diagram to extract the experimental process information data therein;

[0039] Or, receive the information filled in by the teacher during the inspection tour as the experimental process inspection information obtained.

[0040] Furthermore, the step of receiving the content evaluations filled in by the experimenter and the experimental teacher respectively includes:

[0041] Collect the objective content evaluations filled in by the experimenter and the experimental teacher respectively by means of a questionnaire;

[0042] Integrate the objective content evaluations of the experimenter and the experimental teacher as the objective scoring part of the experimental report;

[0043] Receive the subjective content evaluation filled in by the experimental teacher.

[0044] Furthermore, the step of receiving the experimental data filled in by the experimenter and conducting a rationality evaluation of the data includes:

[0045] Receive the numerical type, text information type, and waveform filled in by the experimenter; wherein, the text information type is configured with multiple preset options, the waveform is configured as a text format describing the digital signal timing diagram, and the waveform description length is agreed upon, and the numerical type is configured as an integer type and a floating-point type;

[0046] Conduct an equal value judgment on the integer type;

[0047] Conduct an interval judgment on the floating-point type;

[0048] For the data with a monotonic change law or a formula relationship law, conduct a law judgment;

[0049] Display the judgment result in the acceptance conclusion field.

[0050] Furthermore, the data rationality evaluation step further includes:

[0051] Analyze the position of the measurement data of the experimenter in the big data sample of the experimenter group.

[0052] Furthermore, the step of analyzing the position of the measurement data of the experimenter in the big data sample of the experimenter group includes:

[0053] Calculate the semi-percentile and semi-range ratio characterization of the current sample in the current data item; where

[0054] The semi-percentile is the ratio of the number of internal and external samples in the interval from the current sample to the mean value, and the formula is:

[0055] m / (m + n)×100%

[0056] where m is the number of samples between the mean value and the current sample, and m + n is the total number of samples;

[0057] The semi-range ratio is the ratio of the internal and external distances in the interval from the current sample to the mean value, and the formula is:

[0058] Δy / (Δy + Δx)×100%

[0059] where Δy is the numerical difference between the mean value and the current sample, Δy + Δx is the difference between the mean value and the farthest sample, and the farthest sample is the sample that is farther from the mean value among the maximum value and the minimum value.

[0060] Furthermore, the step of receiving the experimental data filled in by the experimenter and performing data rationality evaluation further includes:

[0061] Establish an association relationship between the experimental data filled in by the experimenter and the task field;

[0062] Match the corresponding data rationality judgment basis through the task field to achieve task-differentiated review.

[0063] Furthermore, the step of processing and scoring the data collected during the experiment process to achieve score summary includes:

[0064] Calculate the total score by adding the weighted integral of the objective item unit, the weighted integral of the subjective evaluation unit, the weighted integral calculated by compiling the built-in function for the design type collection index parameters, and the weighted integral converted by the acceptance time.

[0065] The third object of the present invention is to provide a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the steps of the above method are implemented.

[0066] The fourth object of the present invention is to provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0067] Compared with the prior art, the beneficial effects of the embodiments of the present invention are as follows:

[0068] The present invention provides an experimental process and experimental data management system, method, device and medium, which can enhance the management of the experimental process, strengthen the proportion of the experimental process in the assessment, enhance the experimental feedback information and feedback speed, improve the experimental completion effect, and the CT-style experimental data management can realize the all-round observation of the experimental object, solve the problems of low efficiency and low response of the experimental teacher's data review, and improve the teaching quality.

[0069] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly and implement it in accordance with the content of the specification, the following takes the preferred embodiments of the present invention and combines the accompanying drawings to describe in detail as follows. The specific implementation manners of the present invention are given in detail by the following embodiments and their accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The accompanying drawings described herein are used to provide a further understanding of the present invention, form a part of this application, and the illustrative embodiments and descriptions of the present invention are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0071] Figure 1 is a schematic diagram of the experimental process and experimental data management system;

[0072] Figure 2 is a schematic diagram of the mobile phone operation interface;

[0073] Figure 3 is a schematic diagram of the table data structure;

[0074] Figure 4 is a partial schematic diagram of the experimental personnel data filling interface;

[0075] Figure 5 is the interface of the real-time statistical chart of the experimental class;

[0076] Figure 6 is the experimental data graph of all students;

[0077] Figure 7 is for f(VCO in ) all sample data statistical analysis sample diagram;

[0078] Figure 8 is the schematic diagram of the collected data distribution of the center frequency of f(VCO in ).

[0079] Figure 9 is the schematic diagram of the parameter measurement task assignment for showing the overall picture of the phase-locked loop;

[0080] Figure 10 is the schematic diagram of the experimental data samples;

[0081] Figure 11 is the flow chart of the experimental process and experimental data management method;

[0082] Figure 12 is the flow chart of obtaining the inspection information of the experimental process;

[0083] Figure 13 is the flow chart of filling in the content evaluation;

[0084] Figure 14 is the flow chart of filling in the experimental data and evaluating its rationality;

[0085] Figure 15 is the flow chart of the task differentiation review;

[0086] Figure 16 is the schematic diagram of the computer device;

[0087] Figure 17 is the schematic diagram of the computer-readable storage medium. Specific embodiments

[0088] Next, in combination with the accompanying drawings and specific embodiments, the present invention will be further described. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. It should be noted that, on the premise of no conflict, any combination of the following-described embodiments or technical features can form a new embodiment.

[0089] All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts belong to the scope of protection of the present invention.

[0090] In this application, the accompanying drawing numbers are only used to distinguish each step in the solution and are not used to limit the execution order of each step. The specific execution order shall be subject to the description in the specification.

[0091] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0092] Example 1

[0093] An experimental process and experimental data management system 1, as Figure 1 shown, includes an experimental process information management module 100, an experimental data acquisition module 110, an experimental report information acquisition module 120, and a score summary module 130; among them,

[0094] The experimental process information management module is used to generate an experimental record for each experimental personnel, and the content of the experimental record includes experimental result inspection information and experimental process inspection information; among them, the experimental result inspection information is obtained through data verification of the experimental data acquisition module, and there are 2 ways to collect the experimental process inspection information.

[0095] In some embodiments, the experimental process inspection information is obtained by performing AI analysis on the device working status interface diagram uploaded by the experimental personnel to extract the experimental process information data therein, or obtained by the experimental teacher observing and filling in through patrol.

[0096] Specifically, the experimental personnel submit the device working status interface diagram taken by the mobile phone. After uploading, the AI extracts the device usage standardization parameters, registers and displays them to feedback to the students, rather than taking the device to automatically extract the device screenshot. The purpose is to make the students actively take pictures and upload them, strengthening the awareness of operating the standardization parameters. For the information that cannot be analyzed by the current AI technology, the teacher manually registers it through inspections.

[0097] As Figure 4 shown, every time an experimental personnel completes a data measurement, one data is registered online, and the experimental data platform automatically gives a judgment on whether the data is within a reasonable range. The experimental teacher monitors the uploaded data in the background and makes a timely response to improve the quality of the experimental process.

[0098] As Figure 2 、 Figure 3 shown, when the experiment is carried out and the results are submitted, the experimental teacher collects the experimental process information of the experimental personnel through patrol, including whether the use of various instruments is standardized, and safety issues, etc. The information input methods for the experimental teacher to operate the mobile phone include: single selection, multiple selection, rating stars, etc., without keyboard input, and the collection is convenient and efficient.

[0099] The experimental data acquisition module is used for the experimental personnel to fill in the experimental data during the experimental process and conduct a data rationality evaluation to feedback the experimental result inspection information;

[0100] Furthermore, the experimental data acquisition module realizes data verification through functions or scripts, mainly used for rapid feedback of experimental results and improving the quality of experimental completion.

[0101] The experimental report information acquisition module is used for the experimental personnel and the experimental teacher to fill in the content evaluation respectively;

[0102] The score summary module is used to process and score the data collected during the experiment, and achieve score summary.

[0103] Furthermore, the score summary module realizes the processing and scoring of the data collected during the experiment through a script.

[0104] Furthermore, the score summary module calculates the total score by adding the weighted integral of the objective item unit, the weighted integral of the subjective evaluation unit, the weighted integral calculated by compiling built-in functions for the design class acquisition index parameters, and the weighted integral converted by the acceptance time. The specific formula is as follows:

[0105]

[0106] Among them, S is the total score, S s is the weighted integral of the objective item unit, S e is the weighted integral of the subjective evaluation unit, S d is the weighted integral calculated by compiling built-in functions for the design class acquisition index parameters, S t is the weighted integral converted by the acceptance time.

[0107] It should be noted that the scripts for all data processing in this embodiment adopt general codes, that is, for different experimental projects, one script is used for auditing or calculation, which has extremely high maintenance efficiency.

[0108] The experimental process and experimental data management system provided in this embodiment replaces and covers the assessment and methods of traditional circuit experiments, and improves the quality of experimental teaching.

[0109] Since the data filled in by the experimental personnel has various styles, the rationality (correctness) of the data needs to be determined after judgment, and different styles of data have different judgment rules. In some embodiments, as Figure 1 shown, it further includes an auxiliary module 140. The auxiliary module is used to provide judgment rules, and store the evaluation weight parameters of different experimental process data collected during the score summary process, and the basis for judging the rationality of the data of the experimental data acquisition module for querying the rationality of the experimental data.

[0110] This experimental process and experimental data management system can create an independent experimental server platform or can be created in a general collaborative form. Preferably, the experimental process information management module, the experimental data acquisition module, the experimental report information acquisition module, the score summary module, and the auxiliary module are configured as a general collaborative form, such as using the open-source super table SeaTable.

[0111] In some embodiments, the experimental report information collection module is configured to collect data in the background using a table and in the foreground using a questionnaire; among them, the questionnaire involves the evaluation of objective contents such as document format. The experimenters and experiment teachers each fill it out and synthesize it as the objective scoring part of the experimental report, and the experiment teachers fill out the subjective content evaluation. For example, the experiment teachers fill in the table according to the subjective content evaluation such as the depth of discussion in the report.

[0112] Preferably, the experimental report information collection module sets a format standard questionnaire inspection. When submitting the experimental report, the experimenters fill out the questionnaire on following the report format standard during the writing process of the experimental report, so as to strengthen the report format standard. The experiment teachers give format scores and subjective scores for discussion-related contents according to the report content of the experimenters.

[0113] In some embodiments, the data types filled in by students in the experimental data collection module include numerical type, text information type, waveform, etc.; among them, the text information type is configured to preset multiple options, which can reduce the judgment difficulty; the waveform is configured to describe the text format of the digital signal timing diagram, and the waveform description length, etc. are agreed to effectively fix the answers. For example, the waveform is submitted in the WaveDrom text format; the numerical type is configured as integer type and floating-point type. The integer type uses equal value judgment, and the floating-point type uses interval judgment. If there is a monotonic change rule or formula relationship rule between the data, then rule judgment is performed. Among them, the equal value judgment type and interval judgment type answers are stored in the auxiliary table for querying during the verification and judgment of experimental data.

[0114] Furthermore, the experimental data collection module calls scripts to analyze and fill in the rationality of the data, the rationality of the function calculation results, and the position of the measurement data of the experimenters in the large data sample of the experimenter group, and displays it in the acceptance conclusion field.

[0115] As Figure 5 shown, the teacher designs an instant statistical chart for the experimental data on the platform. When a certain amount of experimental data accumulates, the statistical chart becomes effective and the students can observe some simple statistical information and analyze the position of their self-tested data in the distribution of the whole measurement sample.

[0116] Furthermore, as Figure 10 shown, the position of the measurement data of the experimenters in the large data sample of the experimenter group is characterized by the semi-percentile and semi-range ratio of the current sample in the current data item; among them,

[0117] the semi-percentile is the ratio of the number of internal and external samples from the current sample to the mean value interval, and the formula is:

[0118] m / (m + n)×100%

[0119] Among them, m is the number of samples between the mean and the current sample, and m+n is the total number of samples;

[0120] The half range ratio is the ratio of the inner and outer distances of the current sample to the mean interval, and the formula is:

[0121] Δy / (Δy+Δx)×100%

[0122] Among them, Δy is the difference between the mean and the current sample value, Δy+Δx is the difference between the mean and the farthest sample, and the farthest sample is the sample that is farther from the mean between the maximum value and the minimum value.

[0123] like Figure 6 As shown in the figure, after all students' experimental data are collected, teachers can set all data (including multiple years) to be shared. Figure 7 f(VCO in ) Sample graph of statistical analysis of all sample data, Figure 8 (b) is the f(VCO in ) Schematic diagram of the distribution of center frequency acquisition data, Figure 8 (a) is the current year f(VCO in ) Schematic diagram of data collection distribution at the center frequency. Figure 7 , Figure 8 It is found that there are two obvious peaks in the distribution of the measurement results of the two-year data. The research shows that the reason is that the devices of different manufacturers are purchased each year. After consulting the information, it is found that the data manuals of TI and Fairchild show that the qualitative characteristics are consistent but the quantitative characteristics are different. The fitting functions are different, and it is difficult to find data manuals when purchasing chips. In practice, the division of labor is used to measure the influence curves of component parameters, and the shared data is retrieved for characteristic analysis. The fitted f0(R1) curve is integrated into the design and implementation of the duty cycle meter, which makes the parameter selection in the design process more targeted, the correction of component parameters is more efficient, and the understanding of the device is deeper.

[0124] In order to achieve the effect of analyzing the whole picture of the experimental object, the experiment adopts a CT (tomography)-like method to segment the experimental tasks to obtain more experimental "slice" data. Furthermore, the experimental data acquisition module is also configured with a task field, which is used to achieve experimental task segmentation to assign different task experiments and all measurement requirements under the task experiment to the experimenter.

[0125] Traditional experiments are limited in class time, and the experimental measurements are few and isolated, so only a part of the experiment can be seen, and the whole picture of the experimental object cannot be understood. This embodiment can separate the comprehensive characteristics of the experimental object into multiple tasks for all students to measure separately, and each task can be completed by multiple people at the same time, which also obtains a larger sample space.

[0126] like Figure 9As shown, taking the phase-locked loop application design experiment as an example, the traditional experimental planning steps include: voltage-controlled oscillation response f(VCO in ) measurement, basic phase-locked loop design and test, frequency doubling circuit design and test, duty cycle meter design and experiment, these are the experimental steps that all experimenters must participate in and complete. In order to achieve parameter measurement that shows the overall picture of the phase-locked loop, the component parameter response f0 (R1) measurement, component parameter response f0 (R2) measurement, and component parameter response f0 (C1) measurement are assigned and completed.

[0127] Since the experimenters face the same experimental tasks with different parameters for the same experimental object, their experimental measurement results vary greatly. If a unified data rationality range is used for review, errors will occur. Therefore, it is necessary to conduct differentiated review of tasks for different students. The task field is the keyword for differentiated review of tasks. Furthermore, the auxiliary module is also configured with a task field, and the task field of the auxiliary module is used to implement differentiated review of tasks.

[0128] In the common-phase amplifier circuit experiment implementation example, Table 1 is created: Common-phase amplifier circuit test experiment process management table. In addition to the attribute fields such as student ID and class, process management also includes fields such as "pre-study submission", "pre-study", "experimental record standardization", "power supply current safety setting", "wiring: line color", "wiring: length", "amplitude-frequency completion", "input resistance completion", "output resistance completion", "acceptance time", and "acceptance completion".

[0129] Among them, "Preview submission": the collection method is for students to upload the preview credentials, and the data format is a picture;

[0130] "Preview": teachers conduct process evaluation based on the preview credentials submitted by students; the data format is multiple-choice option type;

[0131] "Standardization of experimental records": Considering the isolation of data filled in the form, the tabular records in the traditional manual experimental records can show the experimenter's understanding of the logic between the data. Therefore, the evaluation options are set, the data style is a single-choice option, and the collection method is for the teacher to review the recorded data;

[0132] "Power supply current safety setting": During the circuit experiment, the current voltage stabilizer can limit the output current of the voltage source, which can be used to protect the experimental circuit. The normal operating current of the op amp circuit does not exceed 20mA. The experimental specification stipulates that in general verification experiments, the output current of the voltage source shall not exceed 50mA. The collection method is submitted by the student selfie instrument interface and analyzed by AI; the data format is text information;

[0133] "Wiring: Wire Color" and "Wiring: Length": The quality of wiring has a very significant impact on the efficiency and effectiveness of experiments. Standardizing wiring specifications is conducive to cultivating good experimental habits. The data format is a single-choice option, and the collection method is for teachers to inspect and record data;

[0134] "Bandwidth Completion", "Input Resistance Completion", "Output Resistance Completion": The verification results of experimental recorded data are provided by script calculation from the experimental data collection form, and the data format is text;

[0135] "Acceptance Time": Reference information for the completion progress, which is the execution time of the data acceptance script for the experimental data collection form, and can also be set manually;

[0136] "Acceptance Completed": In traditional experiments, teachers sign and approve after reviewing the data. Now, in addition to paper records, there are also pad handwritten records and document recording methods for experimental data. The signature approval method is not fully applicable. Here, a field information for acceptance completion is added. Students can confirm that the experimental results are recognized when they see the word "completed" in their entries.

[0137] Table 2: Experimental Data Collection Form for In-phase Amplifier Circuit Testing. Mainly for students to fill in and verify experimental data. In addition to fields such as student ID and class, there are several other types:

[0138] Data input fields: Such as input signal Vpp, output signal Vpp at 1k, -3dB, -10dB, -20dB frequencies (for the above gain bandwidth measurement), input voltage-dividing resistor, signal source output, in-phase terminal voltage (for the above input resistance measurement), open-circuit voltage, loaded voltage (for the above output resistance measurement). All these types of fields are registered by students during the experiment.

[0139] Function fields: For example, after filling in the bandwidth measurement data, the bandwidth-gain product is calculated and output in the specified field. After filling in the relevant parameters for input resistance measurement, the input resistance value is calculated and displayed in the specified field.

[0140] Acceptance button and acceptance conclusion field: After clicking the acceptance button, a script is called to analyze the rationality of the filled data (such as whether the output voltage Vpp is reasonable), the rationality of the function calculation results (such as whether the bandwidth-gain product is reasonable), and the position of the measured data of this experimenter in the large data sample submitted by the experimenter group (such as the sample serial number of the calculated bandwidth-gain product in the whole sample, the distance ratio of the average value of the data with the largest relative deviation, etc.), and display it in the acceptance conclusion field. The basis for the script to judge the data rationality, that is, the reasonable data range, is stored in another table "Data Range Table".

[0141] "Task": The experiment adopts a method similar to CT (tomography) for experimental task segmentation to obtain more experimental "slice" data and achieve the effect of comprehensive analysis of the experimental object. Therefore, the experimenters need to face experiments with the same task but different parameters. For example, in the measurement of gain bandwidth, parameters with amplification factors of 2 times, 3 times, 5 times, and 10 times are assigned to different students. The experimental measurement results vary greatly, and it will be incorrect to review with a unified data rationality range. Therefore, it is necessary to conduct task differentiation review for different students. The "Task" field is the keyword used for task differentiation review. Similarly, for the measurement of input resistance, slice measurements are also carried out with input signal frequencies of 1k, 5k, 10k, and 50k. Through such slice measurements, after aggregating and analyzing the large amounts of measurement data with different gains, the theory of consistent gain-bandwidth product can be more effectively verified. And the slice measurements of input resistance at different frequencies can verify the concept that the input resistance that is not taken seriously is the AC equivalent resistance.

[0142] Table 3: Data range table, with fields including "Field", "Lower Limit", "Upper Limit", "Task", etc.;

[0143] "Field": Such as Vpp output at the center frequency;

[0144] "Lower Limit": Such as 200mVrms;

[0145] "Upper Limit": Such as 400mVrms;

[0146] "Task": Such as in-phase gain bandwidth of 10kΩ (10kΩ is the slice parameter).

[0147] In the embodiment of the digital circuit basic experiment, the digital circuit basic experiment adopts the black box experiment mode. Taking the combinational logic circuit as an example, the rules of the black box experiment mode are as follows: Many three-input logic circuits are created in advance, and the logic expressions of each circuit are different. They are made into FPGA bitstream files and stored on the server. The experimenter logs in to the server to obtain a randomly assigned bitstream file, configures the FPGA experimental board, judges the truth table and logic expression of the circuit through testing, and submits the judgment result and fills in the form.

[0148] Since the bitstream files are randomly assigned and there are more than a hundred bitstream files for one experiment, it is difficult to manage them in the way of a field answer table. Therefore, one bitstream answer is one record. The specific different fields and answers are stored in a field in dictionary form. In addition, the data of randomly assigned files are imported from the black box server as the task list.

[0149] Compared with the measurement of analog circuit data, the types of experimental data measured and recorded in digital circuits are more complex, and there are more flexible review methods during data review.

[0150] Taking waveform verification as an example, general waveforms cannot be verified. By describing the waveforms with letter symbols (such as the WaveDrom mode) and stipulating the starting rules and sequence lengths of the waveform character sequences, it can be conveniently completed through equivalent judgment.

[0151] For the verification of the simplest logical expressions, there are various ways to write the simplest logical expressions of some logic circuits. After stipulating that the product terms are arranged in the order of the sizes of the included minterms, there are still some circuits with two different simplest logical expressions. In addition, there are also some data with multiple answers. For this type, different answers in the answers are separated by specific symbols, such as the semicolon ";". That is, add the ";" sign before and after each answer. When judging, add the ";" before and after the string input by the experimenter and use the "is contained in" function to judge whether it is within the answer string to ensure correct judgment.

[0152] The present invention provides an experimental process and experimental data management system, which can realize the verification of students' independent experimental data, adopt various methods to analyze the rationality of data during the verification process, and improve the quality of experiment completion; it can reduce the difficulty of experimental teachers in verifying experimental data, improve the verification efficiency, and avoid the hidden danger of data verification errors brought by the explosive verification requirements; it can change the characteristics of traditional experimental data being thin and isolated, realize multi-angle and multi-parameter observation of experimental objects, and obtain CT-style experimental data groups; it can change the experimental assessment mode that emphasizes results over processes and strengthen the assessment of the experimental process.

[0153] Embodiment 2

[0154] An experimental process and experimental data management method is applied to the above experimental process and experimental data management system. For the detailed description of the experimental process and experimental data management system, reference can be made to the corresponding description in the above embodiments of the experimental process and experimental data management system, which will not be elaborated here. As Figure 11 shown, the method includes the following steps:

[0155] S200. Receive the experimental process information submitted by the experimenter and generate an experimental record for the experimenter; wherein, the content of the experimental record includes experimental result inspection information and experimental process inspection information;

[0156] The experimental result inspection information is obtained through data calculation of the experimental data acquisition module, and there are 2 ways to collect the experimental process inspection information.

[0157] Furthermore, as Figure 12 shown, it further includes the step of obtaining the experimental process inspection information:

[0158] S201. Receive the device working status interface diagram uploaded by the experimenter;

[0159] S202. Perform AI analysis on the interface diagram of the device working state to extract the experimental process information data therein;

[0160] Or, receive the information filled in by the teacher during the inspection as the information for obtaining the experimental process inspection.

[0161] Specifically, the experimental personnel submit the interface diagram of the device working state taken by the mobile phone. After uploading, AI is used to extract the device usage standardization parameters, register them, and display and feedback them to the students. Instead of the device automatically extracting the device screenshots, the purpose is to enable the students to actively take pictures and upload them, strengthening the awareness of operating the standardization parameters. For the information that cannot be analyzed by the current AI technology, the teacher manually registers it through inspections.

[0162] As Figure 4 shown, every time the experimental personnel complete a data measurement, they register one data online, and the experimental data platform automatically gives a judgment on whether the data is within the reasonable range. The experimental teacher monitors the uploaded data in the background and makes timely responses to improve the quality of the experimental process.

[0163] As Figure 2 、 Figure 3 shown, when the experiment is in progress and the results are submitted, the experimental teacher collects the experimental process information of the experimental personnel through inspections, including whether various instruments are used standardly and safety issues, etc. The information input methods for the experimental teacher's mobile phone operation include: single-choice, multiple-choice, star rating, etc., without keyboard input, and the collection is convenient and efficient.

[0164] S210. Receive the experimental data filled in by the experimental personnel and conduct a data rationality evaluation to feedback the experimental result inspection information;

[0165] Since the data filled in by the experimental personnel has various styles, the rationality (correctness) of the data needs to be determined after judgment, and different styles of data have different judgment rules. In some embodiments, by setting up an auxiliary module to provide judgment rules, as well as storing the evaluation weight parameters of different experimental process data collected during the process of summarizing the scores and the data rationality judgment basis of the experimental data acquisition module, it is used for querying the data rationality judgment of the experimental data.

[0166] In some embodiments, as Figure 14 shown, the step of receiving the experimental data filled in by the experimental personnel and conducting a data rationality evaluation includes:

[0167] S211. Receive the numerical values, text information, and waveforms filled in by the experimenter. Among them, the text information is configured with multiple preset options to reduce the difficulty of judgment. The waveform is configured as a text format describing the digital signal timing diagram, and the waveform description length and other effective fixed answers are agreed upon. For example, the waveform is submitted in the WaveDrom text format. The numerical values are configured as integers and floating-point numbers.

[0168] S212. Perform an equal-value judgment on the integer type.

[0169] S213. Perform an interval judgment on the floating-point type. Among them, the equal-value judgment type and interval judgment type answers are stored in the auxiliary table for querying during the verification and judgment of experimental data.

[0170] S214. For the data with a monotonic change law or formula relationship law, perform a law judgment.

[0171] S215. Display the judgment result in the acceptance conclusion field.

[0172] Further, the data rationality evaluation step further includes:

[0173] Analyze the position of the measurement data of the experimenter in the large data sample of the experimenter group.

[0174] As Figure 5 shown, the teacher designs an instant statistical chart for the experimental data on the platform. When a certain amount of experimental data accumulates, the statistical chart becomes effective and students can observe some simple statistical information to analyze the position of their self-test data in the distribution of the whole measurement sample.

[0175] Further, as Figure 10 shown, the step of analyzing the position of the measurement data of the experimenter in the large data sample of the experimenter group includes:

[0176] Calculate the semi-percentile and semi-range ratio of the current sample in the current data item for characterization. Among them,

[0177] The semi-percentile is the ratio of the number of internal and external samples in the interval from the current sample to the mean value. The formula is:

[0178] m / (m + n)×100%

[0179] where m is the number of samples between the mean value and the current sample, and m + n is the total number of samples;

[0180] The semi-range ratio is the ratio of the internal and external distances in the interval from the current sample to the mean value. The formula is:

[0181] Δy / (Δy + Δx)×100%

[0182] Among them, Δy is the difference between the mean value and the current sample value, and Δy + Δx is the difference between the mean value and the farthest sample. The farthest sample is the sample that is farther from the mean value among the maximum value and the minimum value.

[0183] As Figure 6 shown, after the experimental data of all students is collected, the teacher can set all the data (which may include data of multiple years) to be shared. For example, Figure 7 is the statistical analysis sample diagram of all sample data of f(VCO in ), Figure 8 (b) is the schematic diagram of the distribution of the collected data of the center frequency of f(VCO in ) in the past two years, Figure 8 (a) is the schematic diagram of the distribution of the collected data of the center frequency of f(VCO in ) this year. From Figure 7 and Figure 8 , it is found that there are obviously two peak regions in the distribution of the measurement results of the two-year data. The reason for the research is that the devices from different manufacturers are purchased every year. After consulting the data, it is found that the data manual graphs of TI and Fairchild show qualitative consistency but quantitative differences, and there are differences in the fitting functions. And it is difficult to find the data manual for the purchased chips. In practice, the component parameters are measured separately by different people, and the shared data is retrieved for characteristic analysis. The f0(R1) curve obtained by fitting is integrated into the design and implementation of the duty cycle measuring instrument, which makes the parameter selection in the design process more targeted, improves the efficiency of correcting component parameters, and deepens the understanding of the device.

[0184] In order to achieve the effect of analyzing the whole picture of the experimental object, the experiment adopts a method similar to CT (tomography) to divide the experimental tasks to obtain more experimental "slice" data. Further, as Figure 15 shown, the step of receiving the experimental data filled in by the experimental personnel and evaluating the data rationality further includes:

[0185] S216. Establish an association relationship between the experimental data filled in by the experimental personnel and the task fields; that is, the task fields are used to implement the division of experimental tasks to allocate different task experiments and all measurement requirements under the task experiment to the experimental personnel.

[0186] S217. Match the corresponding data rationality judgment basis through the task fields to achieve differential review of tasks.

[0187] Due to limited class hours in traditional experiments, the experimental measurements are few and isolated, only showing a partial view and unable to understand the whole picture of the experimental object. This embodiment can realize that the all-round characteristics of the experimental object are split into multiple tasks and measured separately by all students, and each task is completed by multiple people at the same time, thus obtaining a relatively large sample space.

[0188] As Figure 9As shown, taking the phase-locked loop application design experiment as an example, the traditional experimental planning steps include: voltage-controlled oscillation response f(VCO in ) measurement, basic phase-locked loop design and test, frequency doubling circuit design and test, duty cycle meter design and experiment, these are the experimental steps that all experimenters must participate in and complete. In order to achieve parameter measurement that shows the overall picture of the phase-locked loop, the component parameter response f0 (R1) measurement, component parameter response f0 (R2) measurement, and component parameter response f0 (C1) measurement are assigned and completed.

[0189] Since the experimenters face the same experimental tasks with different parameters for the same experimental object, their experimental measurement results vary greatly. If a unified data rationality range is used for review, errors will occur. Therefore, it is necessary to conduct differentiated review of tasks for different students. The task field is the keyword for differentiated review of tasks. Furthermore, the auxiliary module is also configured with a task field, and the task field of the auxiliary module is used to implement differentiated review of tasks.

[0190] S220, receiving content evaluations filled out by experimenters and experiment teachers;

[0191] In some embodiments, Figure 13 As shown, the steps of receiving the content evaluation filled in by the experimenter and the experiment teacher include:

[0192] S221, collect objective content evaluations filled out by experimenters and experiment teachers through questionnaires;

[0193] S222. The objective content evaluation of the experimenters and the experiment teachers is combined as the objective scoring part of the experiment report;

[0194] Specifically, the experimental report information collection form is configured to use a form in the background and a questionnaire in the front end to collect data; the questionnaire involves objective content evaluation such as document format, which is filled out by the experimenters and experimental teachers respectively and combined as the objective scoring part of the experimental report.

[0195] S223. Receive the subjective content evaluation filled in by the experimental teacher. For example, the experimental teacher fills in the form based on the subjective content evaluation such as the depth of discussion in the report.

[0196] Preferably, the experimental report information collection module sets a format normative questionnaire check. When submitting the experimental report, the experimenter fills in the questionnaire on the report format normativeness during the experimental report writing process, thereby strengthening the report format normativeness. The experimental teacher gives the format score and the subjective score of the discussion content according to the content of the experimenter's report.

[0197] S230, process and score the data collected during the experiment to summarize the results.

[0198] Further, the step of processing and scoring the data collected during the experiment to achieve result summary includes:

[0199] The total score is calculated by adding the weighted integral of the objective item unit, the weighted integral of the subjective evaluation unit, the weighted integral calculated by programming built-in functions for the design class collection index parameters, and the weighted integral converted by the acceptance time. The specific formula is as follows:

[0200]

[0201]

[0202] Among them, S is the total score, S s is the weighted integral of the objective item unit, S e is the weighted integral of the subjective evaluation unit, S d is the weighted integral calculated by programming built-in functions for the design class collection index parameters, S t is the weighted integral converted by the acceptance time.

[0203] The present invention provides an experimental process and experimental data management method, which can realize the independent verification of students' experimental data, adopt various methods for data rationality analysis during the verification process, and improve the quality of experiment completion; it can reduce the difficulty of experimental teachers in verifying experimental data, improve the verification efficiency, and avoid the potential risk of data verification errors caused by explosive verification requirements; it can change the characteristics of traditional experimental data being thin and isolated, realize multi-angle and multi-parameter observation of experimental objects, and obtain a CT-style experimental data group; it can change the experimental assessment mode that emphasizes results over processes and strengthen the assessment of the experimental process.

[0204] Example 3

[0205] A computer device 300, as Figure 16 shown, includes a memory 310, a processor 320, and a computer program 330 stored on the memory and executable on the processor. When the processor executes the computer program, it implements the steps of an experimental process and experimental data management method. For a detailed description of the method, reference can be made to the corresponding description in the above method embodiments, and details will not be repeated here.

[0206] Example 4

[0207] A computer-readable storage medium, as Figure 17 shown, stores a computer program thereon. When the computer program is executed by a processor, it implements the steps of an experimental process and experimental data management method. For a detailed description of the method, reference can be made to the corresponding description in the above method embodiments, and details will not be repeated here.

[0208] The number of devices and the processing scale described here are used to simplify the description of the present invention. Applications, modifications, and variations of the present invention will be apparent to those skilled in the art.

[0209] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily achieved. Therefore, without departing from the general concept defined by the claims and the equivalent scope, the present invention is not limited to specific details and the illustrations shown and described here.

[0210] The devices, computer devices, non-volatile computer storage media, and methods provided in the embodiments of this specification are corresponding. Therefore, the devices, computer devices, and non-volatile computer storage media also have beneficial technical effects similar to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the corresponding devices, computer devices, and non-volatile computer storage media will not be elaborated here.

[0211] Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program code, the method steps can be logically programmed to enable the controller to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. to achieve the same functions. Therefore, such a controller can be regarded as a hardware component, and the devices included therein for implementing various functions can also be regarded as the structures within the hardware component. Or even, the devices for implementing various functions can be regarded as either software units for implementing the method or structures within the hardware component.

[0212] The systems, devices, or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. For the convenience of description, when describing the above devices, they are described separately as various units according to their functions. Of course, when implementing one or more embodiments of this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0213] Those skilled in the art should understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the embodiments of this specification can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0214] This specification is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the specification. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to produce a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0215] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0216] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0217] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or also includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, commodity or device including the said element.

[0218] This specification can be described in the general context of computer-executable instructions executed by a computer, such as program units. Generally, program units include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The specification can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program units can be located in local and remote computer storage media including storage devices.

[0219] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and reference can be made to the relevant parts of the method embodiments for the related content.

[0220] The above description is only for the embodiments of this specification and is not intended to limit one or more embodiments of this specification. For those skilled in the art, various changes and modifications can be made to one or more embodiments of this specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of one or more embodiments of this specification.

Claims

1. An experimental process and experimental data management system, characterized in that: It includes an experimental process information management module, an experimental data acquisition module, an experimental report information acquisition module, and a score summary module. Among them, the experimental process information management module is used to generate an experimental record for each experimental personnel, and the content of the experimental record includes experimental result inspection information and experimental process inspection information; the experimental data acquisition module is used for experimental personnel to fill in experimental data during the experimental process and conduct data rationality evaluation to feedback experimental result inspection information; the experimental report information acquisition module is used for experimental personnel and experimental teachers to fill in content evaluations respectively; the score summary module is used to process and score the data collected during the experimental process to achieve score summary.

2. The experimental process and experimental data management system according to claim 1, characterized in that: The experimental process inspection information is obtained by performing AI analysis on the device working state interface diagram uploaded by the experimental personnel to extract the experimental process information data therein, or obtained by the experimental teacher filling in through on-site inspection.

3. An experimental process and experimental data management system according to claim 1, characterized in that: The experimental report information acquisition module is configured to use a form in the background and a questionnaire in the foreground to collect data. Among them, the questionnaire involves objective content evaluation, which is filled in by experimental personnel and experimental teachers respectively and synthesized as the objective scoring part of the experimental report, and the subjective content evaluation is filled in by the experimental teacher.

4. The experimental process and experimental data management system according to claim 3, characterized in that: The data types filled in by students in the experimental data acquisition module include numerical type, text information type, and waveform. Among them, the text information type is configured with multiple preset options; the waveform is configured as a text format describing the digital signal timing diagram, and the waveform description length is agreed upon; the numerical type is configured as integer type and floating-point type. The integer type uses equal value judgment, and the floating-point type uses interval judgment. If there is a monotonic change rule or formula relationship rule between data, rule judgment is performed.

5. An experimental process and experimental data management system according to claim 4, characterized in that: The experimental data acquisition module realizes data verification through functions or scripts.

6. The experimental process and experimental data management system according to claim 5, characterized in that: The experimental data acquisition module calls scripts to analyze and fill in the rationality of data, the rationality of function calculation results, and the position of the measurement data of experimental personnel in the big data sample of the experimental personnel group, and displays it in the acceptance conclusion field.

7. The experimental process and experimental data management system according to claim 6, characterized in that: The position of the measurement data of the experimental personnel in the big data sample of the experimental personnel group is characterized by the semi-percentile and semi-range ratio of the current sample in the current data item. Among them, the semi-percentile is the ratio of the number of internal and external samples in the interval from the current sample to the mean value, and the formula is: m / (m + n)×100% where m is the number of samples between the mean value and the current sample, and m + n is the total number of samples; the semi-range ratio is the ratio of the internal and external distances in the interval from the current sample to the mean value, and the formula is: Δy / (Δy + Δx)×100% where Δy is the numerical difference between the mean value and the current sample, and Δy + Δx is the difference between the mean value and the farthest sample. The farthest sample is the sample that is farther from the mean value among the maximum value and the minimum value.

8. The experimental process and experimental data management system according to claim 5, characterized in that: It also includes an auxiliary module, which is used to provide judgment rules, and store the evaluation weight parameters of different experimental process data collected during the score summary process, and the data rationality judgment basis of the experimental data acquisition module for querying the rationality of experimental data.

9. The experimental process and experimental data management system according to claim 8, wherein: The experimental data acquisition module is also configured with a task field, which is used to implement the segmentation of experimental tasks so as to allocate different task experiments and all measurement requirements under the task experiment to the experimenters.

10. An experimental process and experimental data management system according to claim 9, characterized in that: The auxiliary module is also configured with a task field, and the task field of the auxiliary module is used to implement task-differentiated review.

11. The experimental process and experimental data management system according to claim 9, characterized in that: The experimental process information management module, the experimental data acquisition module, the experimental report information acquisition module, the score summary module, and the auxiliary module are configured as a general collaborative form.

12. The experimental process and experimental data management system according to claim 8, characterized in that: The score summary module processes and grades the data collected during the experiment through a script.

13. An experimental process and experimental data management system according to claim 12, characterized in that: The score summary module calculates the total score by adding the weighted integral of the objective item unit, the weighted integral of the subjective evaluation unit, the weighted integral calculated by compiling built-in functions for the design-type acquisition index parameters, and the weighted integral converted by the acceptance time.

14. An experimental process and experimental data management method, applied to the system according to any one of claims 1 to 13, characterized in that, It includes the following steps: Receive the experimental process information submitted by the experimenter and generate an experimental record for the experimenter; wherein, the content of the experimental record includes experimental result inspection information and experimental process inspection information. Receive the experimental data filled in by the experimenter and conduct a data rationality evaluation to feedback the experimental result inspection information. Receive the content evaluations filled in by the experimenter and the experimental teacher respectively. Process and grade the data collected during the experiment to achieve score summary.

15. A method for managing an experimental process and experimental data according to claim 14, characterized in that, It also includes the step of obtaining experimental process inspection information: Receive the device working status interface diagram uploaded by the experimenter. Conduct AI analysis on the device working status interface diagram to extract the experimental process information data therein. Or, receive the information filled in by the teacher during the inspection tour as the experimental process inspection information obtained.

16. The experimental process and experimental data management method according to claim 14, characterized in that: The step of receiving the content evaluations filled in by the experimenter and the experimental teacher respectively includes: Collect the objective content evaluations filled in by the experimenter and the experimental teacher respectively by means of a questionnaire. Integrate the objective content evaluations of the experimenter and the experimental teacher as the objective scoring part of the experimental report. Receive the subjective content evaluation filled in by the experimental teacher.

17. A method for experimental process and experimental data management according to claim 14, characterized in that: The step of receiving the experimental data filled in by the experimenter and conducting a data rationality evaluation includes: Receive the numerical type, text information type, and waveform filled in by the experimenter; wherein, the text information type is configured with a preset number of options, the waveform is configured as a text format describing the digital signal timing diagram, and the waveform description length is agreed, and the numerical type is configured as an integer type and a floating-point type. Conduct an equal value judgment on the integer type. Conduct an interval judgment on the floating-point type. For the data with a monotonic change law or a formula relationship law, conduct a law judgment. Display the judgment result in the acceptance conclusion field.

18. The experimental process and experimental data management method according to claim 17, characterized in that: The data rationality evaluation step further includes: Analyze the position of the measurement data of the experimenter in the large data sample of the experimenter group.

19. A method for experimental process and experimental data management according to claim 18, characterized in that: The step of analyzing the position of the measurement data of the experimenter in the large data sample of the experimenter group includes: Calculate the semi-percentile and semi-range ratio characterization of the current sample in the current data item; wherein, The semi-percentile is the ratio of the number of internal and external samples in the interval from the current sample to the mean value, and the formula is: m / (m + n)×100% where m is the number of samples between the mean value and the current sample, and m + n is the total number of samples; The semi-range ratio is the ratio of the inner and outer distances from the current sample to the mean interval, and the formula is: Δy / (Δy + Δx)×100% where Δy is the difference between the mean and the current sample value, and Δy + Δx is the difference between the mean and the farthest sample. The farthest sample is the sample among the maximum and minimum values that is farther from the mean.

20. The experimental process and experimental data management method according to claim 17, wherein: The step of receiving the experimental data filled in by the experimenter and evaluating the data rationality further includes: Establishing an association relationship between the experimental data filled in by the experimenter and the task fields; Matching the corresponding data rationality judgment basis through the task fields to achieve differential review of tasks.

21. A method for experimental process and experimental data management according to claim 14, characterized in that: The step of processing and scoring the data collected during the experiment to achieve score summary includes: Calculating the total score by adding the weighted integral of the objective item unit, the weighted integral of the subjective evaluation unit, the weighted integral calculated by compiling built-in functions for the design type acquisition index parameters, and the weighted integral converted from the acceptance time.

22. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 14 to 21 are implemented.

23. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 14 to 21 are implemented.

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