CN111027941A - Teaching experiment platform based on STM32 singlechip - Google Patents
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Abstract
The invention belongs to the technical field of teaching experiment platforms, and discloses a teaching experiment platform based on an STM32 single chip microcomputer, which comprises: the device comprises a power supply module, a driver loading module, a parameter configuration module, a central control module, a video recording module, a storage module, a simulation test module, an examination module, a teaching analysis module, a knowledge map construction module and a display module. According to the invention, the teaching analysis module is used for carrying out statistical analysis on the teaching data of each dimension, so that the teaching quality can be improved in various aspects, and the teaching level can be effectively improved; meanwhile, knowledge points with the strongest correlation can be determined at any time in the learning process by the mode of obtaining the teaching knowledge map through the knowledge map building module, so that the effects of missing and filling in gaps and one-to-three actions in the learning process are realized, the probability of occurrence of learning blind areas is reduced, and the learning effectiveness is finally enhanced.
Description
Technical Field
The invention belongs to the technical field of teaching experiment platforms, and particularly relates to a teaching experiment platform based on an STM32 single chip microcomputer.
Background
The Single-Chip Microcomputer is an integrated circuit Chip, which is a small and perfect Microcomputer system formed by integrating the functions of a central processing unit CPU with data processing capacity, a random access memory RAM, a read-only memory ROM, various I/O ports, interrupt systems, timers/counters and the like (possibly comprising circuits such as a display driving circuit, a pulse width modulation circuit, an analog multiplexer, an A/D converter and the like) on a silicon Chip by adopting a super-large scale integrated circuit technology, and is widely applied to the field of industrial control. From the 80 s of the last century, the current high-speed single chip microcomputer of 300M is developed by 4-bit and 8-bit single chip microcomputers. However, the existing device applying the single chip microcomputer to teaching cannot accurately perform statistical analysis on the teaching, and the teaching level is influenced; meanwhile, no complete knowledge point induction method exists, so that the learning process is difficult to arrange.
In summary, the problems of the prior art are as follows: the existing teaching experiment platform based on the single chip microcomputer can not carry out accurate statistical analysis on teaching, and the teaching level is influenced; meanwhile, no complete knowledge point induction method exists, so that the learning process is difficult to arrange.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a teaching experiment platform based on an STM32 single chip microcomputer.
The invention is realized in this way, a teaching experiment platform based on STM32 singlechip includes:
the device comprises a power supply module, a driver loading module, a parameter configuration module, a central control module, a video recording module, a storage module, a simulation test module, an examination module, a teaching analysis module, a knowledge map construction module and a display module;
the power supply module is connected with the central control module and used for converting power supply voltage and providing electric power with required voltage for a teaching experiment platform based on an STM32 single chip microcomputer;
the driver loading module is connected with the central control module and used for loading a driver to the STM32 single chip microcomputer through a loading program;
the parameter configuration module is connected with the central control module and used for configuring the experimental parameters of the STM32 single chip microcomputer through the input device;
the central control module is connected with the power supply module, the driver loading module, the parameter configuration module, the video recording module, the storage module, the simulation test module, the examination module, the teaching analysis module, the knowledge map construction module and the display module and is used for controlling each module to normally work through the STM32 single chip microcomputer;
the video recording module is connected with the central control module and is used for carrying out video recording on the teaching process through the camera equipment and acquiring video information in real time during teaching;
the storage module is connected with the central control module and is used for dividing and storing the real-time collected teaching information in different time periods;
the simulation test module is connected with the central control module and used for monitoring the test scene through the set invigilation parameters and analyzing the test scene;
the assessment module is connected with the central control module and used for analyzing the acquired data information, analyzing and evaluating the teaching results and dividing assessment results according to evaluation grades;
the teaching analysis module is connected with the central control module and is used for comprehensively analyzing the teaching content according to the teaching video information and the teaching assessment information;
the knowledge map building module is connected with the central control module and used for building a teaching knowledge map through a map building program;
the display module is connected with the central control module and used for displaying the teaching video, the simulation test result and the assessment result through the display;
the teaching analysis module adopts the following analysis method:
(1) acquiring teaching data in a teaching process through camera equipment;
(2) performing statistical analysis on the teaching data according to each preset dimension, and performing facial expression recognition on the face image of the lecturer and the face image of the lecturer; storing facial expression data of the lecturer and facial expression data of the lecturer;
(3) obtaining analysis result data;
(4) and executing corresponding measures for improving teaching according to the analysis result data.
Further, the statistical analysis is performed on the teaching data according to each preset dimension to obtain analysis result data, and the statistical analysis includes:
carrying out statistical analysis on facial expression data of all the students in each teaching content;
correspondingly, the corresponding measure for improving teaching is executed according to the analysis result data, and the measure comprises the following steps:
if the facial expressions of the lecturers larger than the first preset percentage threshold are expressions which dislike the lecture, improving the corresponding teaching contents or replacing the lecturers;
if the facial expressions of the lecturers which are larger than the second preset percentage threshold value are all expressions which like to listen to the lesson, teaching in a corresponding teaching content mode is added or rewarding measures are taken for the lecturers;
if the facial expressions of a certain lessee or lecturer which are larger than a third preset percentage threshold value in a preset time period are all expressions which dislike listening or teaching, criticizing education is carried out on the lessee or lecturer;
if the facial expressions of a certain lessee or lecturer which are greater than the fourth preset percentage threshold value in the preset time period are all expressions which like listening or giving lessons, rewarding measures are carried out on the lessee or lecturer;
if the facial expressions of the lecturers larger than the fifth preset percentage threshold are all expressions of non-calm answer, adjusting the content of the examination or strengthening the teaching of the content of the examination;
and if the facial expressions of a certain lessee which are larger than the sixth preset percentage threshold value in the examination process are all the expressions which are not calm answer, strengthening the examination supervision on the lessee.
Further, the storage module is based on two aspects of node management and data management to reduce energy consumption;
the node management mainly selects part of nodes or disks in the storage system to provide data service for upper-layer application, and other nodes enter a low-energy consumption mode;
the data management technology mainly comprises three types of technologies, namely static data placement, dynamic data placement and cache prefetching, wherein the data management based on the static data placement does not change the storage structure of each node after storing data to each node in the system according to a fixed data placement strategy; the data management based on the dynamic data placement dynamically adjusts the data storage position according to the data access frequency, transfers the data with high access frequency and low frequency to different magnetic disks, and performs energy-saving processing on the magnetic disks storing the data with low frequency so as to reduce the system energy consumption; data management based on cache prefetching references a data caching mode in a memory, data in a disk are fetched to the memory or other low-energy-consumption auxiliary storage equipment, and the original disk enters a low-energy-consumption mode.
Further, when the assessment module analyzes and evaluates the teaching results, the following method is adopted:
collecting teacher teaching images at intervals, setting time labels for the collected teacher teaching images at each time, and storing the teacher teaching images and the time labels in an associated manner; collecting student classroom images at the same or different time intervals, processing the student classroom images to obtain the attendance state, the attendance state and the understanding degree of all students at each collection time point, judging the attendance state and/or the understanding degree of each student at each collection time point to reach the standard in classroom performance, and marking the collection time point as a video band label of the student if the attendance state and/or the understanding degree of each student at each collection time point do not reach the standard; acquiring classroom performance evaluation of students based on attendance states, listening states and understanding degrees of all collection time points of the students, and creating a student set by utilizing student information, course information, classroom performance evaluation and video band labels; converting video segment tags in a student set into time tags, extracting knowledge points in a teacher teaching image associated with the time tags, calculating the intensity of each knowledge point and sequencing all the knowledge points according to the intensity; and/or performing classroom teaching quality evaluation based on classroom performance evaluation in the student set.
The system further comprises a communication module, wherein a data end of the communication module is connected with a data end of the video recording module, when the classroom performance of the student at any classroom image acquisition time point does not meet the standard, the video recording module sends a first reminding signal to the communication module, and the communication module sends the first reminding signal to the monitoring terminal; when the student classroom performance of two or more than two continuous student classroom image acquisition time points of the same student does not reach the standard, the video recording module sends a second reminding signal to the communication module, and the communication module transmits the second reminding signal to the teacher intelligent terminal.
Further, the construction method of the knowledge graph construction module comprises the following steps:
1) acquiring a meta knowledge point representing a basic teaching knowledge point and a composite knowledge point consisting of at least two meta knowledge points through a map construction program, and constructing a knowledge point database consisting of the meta knowledge point and the composite knowledge point;
2) selecting teaching knowledge points according to teaching requirements, selecting first unary knowledge points from a knowledge point database according to the content represented by the teaching knowledge points, and combining the basic knowledge points which have a dependency relationship with the first unary knowledge points;
3) determining the proportion of each element single chip microcomputer knowledge point in the first element single chip microcomputer knowledge point and basic knowledge point combination in the teaching knowledge point, and determining the path length of each element knowledge point relative to the first element knowledge point according to the proportion;
4) and constructing a knowledge graph according to the dependency hierarchy of the meta knowledge points relative to the first meta knowledge point and the path length.
Further, the meta knowledge points stored in the knowledge point database comprise knowledge point IDs, knowledge point names, knowledge point paths, ranking information of the knowledge points in the same hierarchy, version numbers and knowledge point description information.
Further, the construction method comprises the following steps: adding a meta knowledge point; the specific adding process comprises the following steps:
acquiring meta-knowledge points to be added, and extracting knowledge point paths of the meta-knowledge points to be added and sequencing information of the knowledge points to be added in the same hierarchy;
acquiring a preposed meta knowledge point and/or a postposition knowledge point of which the meta knowledge point to be added has a dependency relationship in a knowledge point database according to a knowledge point path of the meta knowledge point to be added, and storing the meta knowledge point to be added behind the preposed meta knowledge point or in front of the postposition knowledge point according to the dependency relationship;
correcting the information of the element knowledge points to be added in the database according to the sequencing information of the knowledge points to be added in the same hierarchy to obtain a corrected organization relation;
and updating the hierarchy in the knowledge point database according to the corrected organization relation to finish the addition of the meta-knowledge points.
Further, the construction method comprises the following steps: deleting the meta knowledge points; the specific deletion process is as follows:
selecting meta-knowledge points to be deleted, and extracting knowledge point paths of the meta-knowledge points to be deleted and sequencing information of the knowledge points to be deleted in the same hierarchy;
determining a preposed meta knowledge point and/or a postpositional knowledge point which has a dependency relationship with the meta knowledge point to be deleted according to a knowledge point path of the meta knowledge point to be deleted;
deleting the dependency relationship between the meta-knowledge points to be deleted and the pre-meta-knowledge points and/or the post-meta-knowledge points, and deleting the sequencing information which is stored in the knowledge point database and corresponds to the meta-knowledge points to be deleted;
correcting the information of the meta knowledge points to be deleted in the database according to the sequencing information of the knowledge points to be deleted in the same hierarchy to obtain a corrected organization relation;
and updating the hierarchy in the knowledge point database according to the corrected organization relation to finish the deletion of the meta-knowledge points.
Further, the construction method comprises the following steps: moving the meta knowledge points; the specific moving process is as follows:
acquiring knowledge points of the element to be moved, and extracting knowledge point paths of the knowledge points of the element to be moved and target sequencing information of the knowledge points to be moved;
determining a preposed meta knowledge point and/or a postpositional knowledge point which has a dependency relationship with the meta knowledge point to be moved according to a knowledge point path of the meta knowledge point to be moved;
selecting a preposed element knowledge point and/or a postpositive element knowledge point of which the element knowledge point to be moved has a dependency relationship after being moved according to the target sorting information of the element knowledge point to be moved;
changing the knowledge point path of the knowledge point to be moved into a preposed element knowledge point and/or a postposition element knowledge point with a dependency relationship after the knowledge point is moved;
correcting the information of the knowledge points of the to-be-moved elements in the database according to the sequencing information of the knowledge points of the to-be-moved elements in the same hierarchy to obtain a corrected organization relation;
and updating the hierarchy in the knowledge point database according to the corrected organization relation to finish the movement of the meta-knowledge points.
The invention has the advantages and positive effects that: the teaching data in the teaching process is acquired through a teaching analysis module; performing statistical analysis on the teaching data according to each preset dimension to obtain analysis result data; executing corresponding measures for improving teaching according to the analysis result data; the teaching quality can be improved in various aspects and the teaching level can be effectively improved due to the statistical analysis of the teaching data of each dimension; meanwhile, the knowledge graph building module is used for determining the path length of each element knowledge point relative to the first element knowledge point in the basic knowledge point combination which has the dependency relationship with the first element knowledge point representing the current learning progress, drawing a net-shaped relationship graph containing the dependency relationship and path length values corresponding to the dependency relationship, and obtaining the knowledge graph, so that the element knowledge point with the strongest correlation with the first element knowledge point can be determined at any time in the learning process, the effects of missing and filling up and taking three steps are achieved in the learning process, the probability of blind area learning is reduced, and the effectiveness of learning is finally enhanced.
Drawings
FIG. 1 is a structural block diagram of a teaching experiment platform based on an STM32 single chip microcomputer provided by the embodiment of the invention.
In the figure: 1. a power supply module; 2. a driver loading module; 3. a parameter configuration module; 4. a central control module; 5. a video recording module; 6. a storage module; 7. a simulation test module; 8. a teaching analysis module; 9. a teaching analysis module; 10. a knowledge graph construction module; 11. and a display module.
Fig. 2 is a flowchart of an analysis method of a teaching analysis module according to an embodiment of the present invention.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following embodiments are illustrated and described in detail with reference to the accompanying drawings.
The structure of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the teaching experiment platform based on the STM32 single chip microcomputer provided by the embodiment of the present invention includes: the system comprises a power supply module 1, a driver loading module 2, a parameter configuration module 3, a central control module 4, a video recording module 5, a storage module 6, a simulation test module 7, a teaching analysis module 8, a teaching analysis module 9, a knowledge graph construction module 10 and a display module 11.
The power supply module 1 is connected with the central control module and used for converting power supply voltage and providing electric power with required voltage for a teaching experiment platform based on an STM32 single chip microcomputer;
the driver loading module 2 is connected with the central control module and is used for loading a driver to the STM32 single chip microcomputer through a loading program;
the parameter configuration module 3 is connected with the central control module and used for configuring the experimental parameters of the STM32 single chip microcomputer through the input device;
the central control module 4 is connected with the power supply module, the driver loading module, the parameter configuration module, the video recording module, the storage module, the simulation test module, the examination module, the teaching analysis module, the knowledge map construction module and the display module and is used for controlling each module to normally work through an STM32 single chip microcomputer;
the video recording module 5 is connected with the central control module and is used for carrying out video recording on the teaching process through the camera equipment and acquiring video information in teaching in real time;
the storage module 6 is connected with the central control module and is used for dividing and storing the real-time collected teaching information in different time periods;
the simulation test module 7 is connected with the central control module and is used for monitoring the test scene through the set invigilation parameters and analyzing the test scene;
the assessment module 8 is connected with the central control module and is used for analyzing the acquired data information, analyzing and evaluating the teaching results and dividing assessment results according to evaluation grades;
the teaching analysis module 9 is connected with the central control module and is used for comprehensively analyzing the teaching contents according to the teaching video information and the teaching assessment information;
the knowledge map building module 10 is connected with the central control module and used for building a teaching knowledge map through a map building program;
the display module 11 is connected with the central control module and used for displaying a teaching video, a simulation test result and an assessment result through a display;
as shown in fig. 2, the teaching analysis module 9 adopts the following analysis method:
s201: acquiring teaching data in a teaching process through camera equipment;
s202: performing statistical analysis on the teaching data according to each preset dimension, and performing facial expression recognition on the face image of the lecturer and the face image of the lecturer; storing facial expression data of the lecturer and facial expression data of the lecturer;
s203: obtaining analysis result data;
s204: and executing corresponding measures for improving teaching according to the analysis result data.
In the embodiment of the present invention, performing statistical analysis on the teaching data according to each preset dimension to obtain analysis result data, including:
carrying out statistical analysis on facial expression data of all the students in each teaching content;
correspondingly, the corresponding measure for improving teaching is executed according to the analysis result data, and the measure comprises the following steps:
if the facial expressions of the lecturers larger than the first preset percentage threshold are expressions which dislike the lecture, improving the corresponding teaching contents or replacing the lecturers;
if the facial expressions of the lecturers which are larger than the second preset percentage threshold value are all expressions which like to listen to the lesson, teaching in a corresponding teaching content mode is added or rewarding measures are taken for the lecturers;
if the facial expressions of a certain lessee or lecturer which are larger than a third preset percentage threshold value in a preset time period are all expressions which dislike listening or teaching, criticizing education is carried out on the lessee or lecturer;
if the facial expressions of a certain lessee or lecturer which are greater than the fourth preset percentage threshold value in the preset time period are all expressions which like listening or giving lessons, rewarding measures are carried out on the lessee or lecturer;
if the facial expressions of the lecturers larger than the fifth preset percentage threshold are all expressions of non-calm answer, adjusting the content of the examination or strengthening the teaching of the content of the examination;
and if the facial expressions of a certain lessee which are larger than the sixth preset percentage threshold value in the examination process are all the expressions which are not calm answer, strengthening the examination supervision on the lessee.
In the embodiment of the invention, the storage module 6 is based on two aspects of node management and data management to reduce energy consumption;
the node management mainly selects part of nodes or disks in the storage system to provide data service for upper-layer application, and other nodes enter a low-energy consumption mode;
the data management technology mainly comprises three types of technologies, namely static data placement, dynamic data placement and cache prefetching, wherein the data management based on the static data placement does not change the storage structure of each node after storing data to each node in the system according to a fixed data placement strategy; the data management based on the dynamic data placement dynamically adjusts the data storage position according to the data access frequency, transfers the data with high access frequency and low frequency to different magnetic disks, and performs energy-saving processing on the magnetic disks storing the data with low frequency so as to reduce the system energy consumption; data management based on cache prefetching references a data caching mode in a memory, data in a disk are fetched to the memory or other low-energy-consumption auxiliary storage equipment, and the original disk enters a low-energy-consumption mode.
Further, when the assessment module 8 analyzes and evaluates the teaching results, the following method is adopted:
collecting teacher teaching images at intervals, setting time labels for the collected teacher teaching images at each time, and storing the teacher teaching images and the time labels in an associated manner; collecting student classroom images at the same or different time intervals, processing the student classroom images to obtain the attendance state, the attendance state and the understanding degree of all students at each collection time point, judging the attendance state and/or the understanding degree of each student at each collection time point to reach the standard in classroom performance, and marking the collection time point as a video band label of the student if the attendance state and/or the understanding degree of each student at each collection time point do not reach the standard; acquiring classroom performance evaluation of students based on attendance states, listening states and understanding degrees of all collection time points of the students, and creating a student set by utilizing student information, course information, classroom performance evaluation and video band labels; converting video segment tags in a student set into time tags, extracting knowledge points in a teacher teaching image associated with the time tags, calculating the intensity of each knowledge point and sequencing all the knowledge points according to the intensity; and/or performing classroom teaching quality evaluation based on classroom performance evaluation in the student set.
The system further comprises a communication module, wherein a data end of the communication module is connected with a data end of the video recording module, when the classroom performance of the student at any classroom image acquisition time point does not meet the standard, the video recording module sends a first reminding signal to the communication module, and the communication module sends the first reminding signal to the monitoring terminal; when the student classroom performance of two or more than two continuous student classroom image acquisition time points of the same student does not reach the standard, the video recording module sends a second reminding signal to the communication module, and the communication module transmits the second reminding signal to the teacher intelligent terminal.
The construction method of the knowledge graph construction module in the embodiment of the invention comprises the following steps:
1) acquiring a meta knowledge point representing a basic teaching knowledge point and a composite knowledge point consisting of at least two meta knowledge points through a map construction program, and constructing a knowledge point database consisting of the meta knowledge point and the composite knowledge point;
2) selecting teaching knowledge points according to teaching requirements, selecting first unary knowledge points from a knowledge point database according to the content represented by the teaching knowledge points, and combining the basic knowledge points which have a dependency relationship with the first unary knowledge points;
3) determining the proportion of each element single chip microcomputer knowledge point in the first element single chip microcomputer knowledge point and basic knowledge point combination in the teaching knowledge point, and determining the path length of each element knowledge point relative to the first element knowledge point according to the proportion;
4) and constructing a knowledge graph according to the dependency hierarchy of the meta knowledge points relative to the first meta knowledge point and the path length.
The meta knowledge points stored in the knowledge point database in the embodiment of the invention comprise knowledge point IDs, knowledge point names, knowledge point paths, ordering information of the knowledge points in the same hierarchy, version numbers and knowledge point description information.
The construction method in the embodiment of the invention comprises the following steps: adding a meta knowledge point; the specific adding process comprises the following steps:
acquiring meta-knowledge points to be added, and extracting knowledge point paths of the meta-knowledge points to be added and sequencing information of the knowledge points to be added in the same hierarchy;
acquiring a preposed meta knowledge point and/or a postposition knowledge point of which the meta knowledge point to be added has a dependency relationship in a knowledge point database according to a knowledge point path of the meta knowledge point to be added, and storing the meta knowledge point to be added behind the preposed meta knowledge point or in front of the postposition knowledge point according to the dependency relationship;
correcting the information of the element knowledge points to be added in the database according to the sequencing information of the knowledge points to be added in the same hierarchy to obtain a corrected organization relation;
and updating the hierarchy in the knowledge point database according to the corrected organization relation to finish the addition of the meta-knowledge points.
The construction method in the embodiment of the invention comprises the following steps: deleting the meta knowledge points; the specific deletion process is as follows:
selecting meta-knowledge points to be deleted, and extracting knowledge point paths of the meta-knowledge points to be deleted and sequencing information of the knowledge points to be deleted in the same hierarchy;
determining a preposed meta knowledge point and/or a postpositional knowledge point which has a dependency relationship with the meta knowledge point to be deleted according to a knowledge point path of the meta knowledge point to be deleted;
deleting the dependency relationship between the meta-knowledge points to be deleted and the pre-meta-knowledge points and/or the post-meta-knowledge points, and deleting the sequencing information which is stored in the knowledge point database and corresponds to the meta-knowledge points to be deleted;
correcting the information of the meta knowledge points to be deleted in the database according to the sequencing information of the knowledge points to be deleted in the same hierarchy to obtain a corrected organization relation;
and updating the hierarchy in the knowledge point database according to the corrected organization relation to finish the deletion of the meta-knowledge points.
The construction method in the embodiment of the invention comprises the following steps: moving the meta knowledge points; the specific moving process is as follows:
acquiring knowledge points of the element to be moved, and extracting knowledge point paths of the knowledge points of the element to be moved and target sequencing information of the knowledge points to be moved;
determining a preposed meta knowledge point and/or a postpositional knowledge point which has a dependency relationship with the meta knowledge point to be moved according to a knowledge point path of the meta knowledge point to be moved;
selecting a preposed element knowledge point and/or a postpositive element knowledge point of which the element knowledge point to be moved has a dependency relationship after being moved according to the target sorting information of the element knowledge point to be moved;
changing the knowledge point path of the knowledge point to be moved into a preposed element knowledge point and/or a postposition element knowledge point with a dependency relationship after the knowledge point is moved;
correcting the information of the knowledge points of the to-be-moved elements in the database according to the sequencing information of the knowledge points of the to-be-moved elements in the same hierarchy to obtain a corrected organization relation;
and updating the hierarchy in the knowledge point database according to the corrected organization relation to finish the movement of the meta-knowledge points.
When the teaching experiment platform works, firstly, a teaching experiment platform based on an STM32 single chip microcomputer is supplied with power through a power supply module 1; loading a drive to the STM32 single chip microcomputer by using a loading program through a driver loading module 2; configuring experimental parameters of the STM32 single chip microcomputer by using a configuration program through a parameter configuration module 3; secondly, the central control module 4STM32 controls the power supply module 1, the driver loading module 2, the parameter configuration module 3, the video recording module 5, the storage module 6, the simulation test module 7, the teaching analysis module 8, the teaching analysis module 9, the knowledge map construction module 10 and the display module 11 by single chip microcomputer control; recording a teaching video through a video recording module 5; the teaching information is stored through a storage module 6; carrying out simulation test by a simulation test module 7; the teaching is examined through an examination module 8; the teaching is analyzed through a teaching analysis module 9; then, the knowledge graph is constructed by the knowledge graph construction module 10; and finally, displaying the teaching video, the simulation test result and the assessment result by using a display through the display module 11.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent changes and modifications made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (10)
1. The utility model provides a teaching experiment platform based on STM32 singlechip, a serial communication port, teaching experiment platform based on STM32 singlechip includes:
the device comprises a power supply module, a driver loading module, a parameter configuration module, a central control module, a video recording module, a storage module, a simulation test module, an examination module, a teaching analysis module, a knowledge map construction module and a display module;
the power supply module is connected with the central control module and used for converting power supply voltage and providing electric power with required voltage for a teaching experiment platform based on an STM32 single chip microcomputer;
the driver loading module is connected with the central control module and used for loading a driver to the STM32 single chip microcomputer through a loading program;
the parameter configuration module is connected with the central control module and used for configuring the experimental parameters of the STM32 single chip microcomputer through the input device;
the central control module is connected with the power supply module, the driver loading module, the parameter configuration module, the video recording module, the storage module, the simulation test module, the examination module, the teaching analysis module, the knowledge map construction module and the display module and is used for controlling each module to normally work through the STM32 single chip microcomputer;
the video recording module is connected with the central control module and is used for carrying out video recording on the teaching process through the camera equipment and acquiring video information in real time during teaching;
the storage module is connected with the central control module and is used for dividing and storing the real-time collected teaching information in different time periods;
the simulation test module is connected with the central control module and used for monitoring the test scene through the set invigilation parameters and analyzing the test scene;
the assessment module is connected with the central control module and used for analyzing the acquired data information, analyzing and evaluating the teaching results and dividing assessment results according to evaluation grades;
the teaching analysis module is connected with the central control module and is used for comprehensively analyzing the teaching content according to the teaching video information and the teaching assessment information;
the knowledge map building module is connected with the central control module and used for building a teaching knowledge map through a map building program;
the display module is connected with the central control module and used for displaying the teaching video, the simulation test result and the assessment result through the display;
the teaching analysis module adopts the following analysis method:
(1) acquiring teaching data in a teaching process through camera equipment;
(2) performing statistical analysis on the teaching data according to each preset dimension, and performing facial expression recognition on the face image of the lecturer and the face image of the lecturer; storing facial expression data of the lecturer and facial expression data of the lecturer;
(3) obtaining analysis result data;
(4) and executing corresponding measures for improving teaching according to the analysis result data.
2. An teaching experiment platform based on STM32 single-chip microcomputer as claimed in claim 1, wherein the statistical analysis of the teaching data according to each preset dimension to obtain analysis result data comprises:
carrying out statistical analysis on facial expression data of all the students in each teaching content;
correspondingly, the corresponding measure for improving teaching is executed according to the analysis result data, and the measure comprises the following steps:
if the facial expressions of the lecturers larger than the first preset percentage threshold are expressions which dislike the lecture, improving the corresponding teaching contents or replacing the lecturers;
if the facial expressions of the lecturers which are larger than the second preset percentage threshold value are all expressions which like to listen to the lesson, teaching in a corresponding teaching content mode is added or rewarding measures are taken for the lecturers;
if the facial expressions of a certain lessee or lecturer which are larger than a third preset percentage threshold value in a preset time period are all expressions which dislike listening or teaching, criticizing education is carried out on the lessee or lecturer;
if the facial expressions of a certain lessee or lecturer which are greater than the fourth preset percentage threshold value in the preset time period are all expressions which like listening or giving lessons, rewarding measures are carried out on the lessee or lecturer;
if the facial expressions of the lecturers larger than the fifth preset percentage threshold are all expressions of non-calm answer, adjusting the content of the examination or strengthening the teaching of the content of the examination;
and if the facial expressions of a certain lessee which are larger than the sixth preset percentage threshold value in the examination process are all the expressions which are not calm answer, strengthening the examination supervision on the lessee.
3. An STM32 singlechip-based teaching experiment platform as claimed in claim 1, wherein the storage module is based on both node management and data management to reduce energy consumption;
the node management mainly selects part of nodes or disks in the storage system to provide data service for upper-layer application, and other nodes enter a low-energy consumption mode;
the data management technology mainly comprises three types of technologies, namely static data placement, dynamic data placement and cache prefetching, wherein the data management based on the static data placement does not change the storage structure of each node after storing data to each node in the system according to a fixed data placement strategy; the data management based on the dynamic data placement dynamically adjusts the data storage position according to the data access frequency, transfers the data with high access frequency and low frequency to different magnetic disks, and performs energy-saving processing on the magnetic disks storing the data with low frequency so as to reduce the system energy consumption; data management based on cache prefetching references a data caching mode in a memory, data in a disk are fetched to the memory or other low-energy-consumption auxiliary storage equipment, and the original disk enters a low-energy-consumption mode.
4. The teaching experiment platform based on the STM32 single-chip microcomputer as claimed in claim 1, wherein the assessment module adopts the following method when analyzing and evaluating the teaching results:
collecting teacher teaching images at intervals, setting time labels for the collected teacher teaching images at each time, and storing the teacher teaching images and the time labels in an associated manner; collecting student classroom images at the same or different time intervals, processing the student classroom images to obtain the attendance state, the attendance state and the understanding degree of all students at each collection time point, judging the attendance state and/or the understanding degree of each student at each collection time point to reach the standard in classroom performance, and marking the collection time point as a video band label of the student if the attendance state and/or the understanding degree of each student at each collection time point do not reach the standard; acquiring classroom performance evaluation of students based on attendance states, listening states and understanding degrees of all collection time points of the students, and creating a student set by utilizing student information, course information, classroom performance evaluation and video band labels; converting video segment tags in a student set into time tags, extracting knowledge points in a teacher teaching image associated with the time tags, calculating the intensity of each knowledge point and sequencing all the knowledge points according to the intensity; and/or performing classroom teaching quality evaluation based on classroom performance evaluation in the student set.
5. A teaching experiment platform based on an STM32 singlechip as claimed in claim 1, further comprising a communication module, wherein the data terminal of the communication module is connected with the data terminal of the video recording module, when the classroom performance of a student at any classroom image acquisition time point does not reach standard, the video recording module sends a first reminding signal to the communication module, and the communication module transmits the first reminding signal to the monitoring terminal; when the student classroom performance of two or more than two continuous student classroom image acquisition time points of the same student does not reach the standard, the video recording module sends a second reminding signal to the communication module, and the communication module transmits the second reminding signal to the teacher intelligent terminal.
6. The teaching experiment platform based on the STM32 single-chip microcomputer as claimed in claim 1, wherein the construction method of the knowledge graph construction module is as follows:
1) acquiring a meta knowledge point representing a basic teaching knowledge point and a composite knowledge point consisting of at least two meta knowledge points through a map construction program, and constructing a knowledge point database consisting of the meta knowledge point and the composite knowledge point;
2) selecting teaching knowledge points according to teaching requirements, selecting first unary knowledge points from a knowledge point database according to the content represented by the teaching knowledge points, and combining the basic knowledge points which have a dependency relationship with the first unary knowledge points;
3) determining the proportion of each element single chip microcomputer knowledge point in the first element single chip microcomputer knowledge point and basic knowledge point combination in the teaching knowledge point, and determining the path length of each element knowledge point relative to the first element knowledge point according to the proportion;
4) and constructing a knowledge graph according to the dependency hierarchy of the meta knowledge points relative to the first meta knowledge point and the path length.
7. An instructional experimental platform based on an STM32 single chip microcomputer according to claim 6, wherein the meta knowledge points stored in the knowledge point database comprise knowledge point IDs, knowledge point names, knowledge point paths, ordering information of the knowledge points in the same hierarchy, version numbers and knowledge point description information.
8. An teaching experiment platform based on an STM32 single chip microcomputer as claimed in claim 6, wherein the construction method comprises: adding a meta knowledge point; the specific adding process comprises the following steps:
acquiring meta-knowledge points to be added, and extracting knowledge point paths of the meta-knowledge points to be added and sequencing information of the knowledge points to be added in the same hierarchy;
acquiring a preposed meta knowledge point and/or a postposition knowledge point of which the meta knowledge point to be added has a dependency relationship in a knowledge point database according to a knowledge point path of the meta knowledge point to be added, and storing the meta knowledge point to be added behind the preposed meta knowledge point or in front of the postposition knowledge point according to the dependency relationship;
correcting the information of the element knowledge points to be added in the database according to the sequencing information of the knowledge points to be added in the same hierarchy to obtain a corrected organization relation;
and updating the hierarchy in the knowledge point database according to the corrected organization relation to finish the addition of the meta-knowledge points.
9. An teaching experiment platform based on an STM32 single chip microcomputer as claimed in claim 6, wherein the construction method comprises: deleting the meta knowledge points; the specific deletion process is as follows:
selecting meta-knowledge points to be deleted, and extracting knowledge point paths of the meta-knowledge points to be deleted and sequencing information of the knowledge points to be deleted in the same hierarchy;
determining a preposed meta knowledge point and/or a postpositional knowledge point which has a dependency relationship with the meta knowledge point to be deleted according to a knowledge point path of the meta knowledge point to be deleted;
deleting the dependency relationship between the meta-knowledge points to be deleted and the pre-meta-knowledge points and/or the post-meta-knowledge points, and deleting the sequencing information which is stored in the knowledge point database and corresponds to the meta-knowledge points to be deleted;
correcting the information of the meta knowledge points to be deleted in the database according to the sequencing information of the knowledge points to be deleted in the same hierarchy to obtain a corrected organization relation;
and updating the hierarchy in the knowledge point database according to the corrected organization relation to finish the deletion of the meta-knowledge points.
10. An teaching experiment platform based on an STM32 single chip microcomputer as claimed in claim 6, wherein the construction method comprises: moving the meta knowledge points; the specific moving process is as follows:
acquiring knowledge points of the element to be moved, and extracting knowledge point paths of the knowledge points of the element to be moved and target sequencing information of the knowledge points to be moved;
determining a preposed meta knowledge point and/or a postpositional knowledge point which has a dependency relationship with the meta knowledge point to be moved according to a knowledge point path of the meta knowledge point to be moved;
selecting a preposed element knowledge point and/or a postpositive element knowledge point of which the element knowledge point to be moved has a dependency relationship after being moved according to the target sorting information of the element knowledge point to be moved;
changing the knowledge point path of the knowledge point to be moved into a preposed element knowledge point and/or a postposition element knowledge point with a dependency relationship after the knowledge point is moved;
correcting the information of the knowledge points of the to-be-moved elements in the database according to the sequencing information of the knowledge points of the to-be-moved elements in the same hierarchy to obtain a corrected organization relation;
and updating the hierarchy in the knowledge point database according to the corrected organization relation to finish the movement of the meta-knowledge points.
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