CN113487928A - Accurate teaching evaluation and diagnosis method and system - Google Patents
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Abstract
The invention discloses a method and a system for accurate teaching evaluation and diagnosis, wherein the method comprises the following steps: s1, constructing a digital common question bank, resetting matched operation and recording digital resources; s2, constructing a digital individual question bank, enabling a teacher to independently research and develop exercises, and recording and maintaining the individual question bank of the teacher; s3, intelligently reviewing, and digitally collecting the review operation result; s323, setting a time range, and generating a student subject academic portrait and a teacher subject teaching portrait according to the reading results corresponding to a group of students in the time range; the system comprises: the system comprises a common question bank, a personal question bank, an independent question setting module, a group paper module and an intelligent evaluation module, wherein the intelligent evaluation module comprises a digital acquisition unit and a process evaluation data generation and application unit.
Description
Technical Field
The invention relates to the technical field of computer teaching, in particular to a method and a system for accurate teaching evaluation and diagnosis.
Background
The consistency of teaching, learning and evaluation is the basic logic of course design and teaching implementation, the key of the consistency of teaching, learning and evaluation is teaching evaluation, and the rationality of course design and the effectiveness of teaching implementation are detected through evaluation.
Taking the mathematics subject of primary school as an example, the functions of the system are explained in advance: the matching homework (book) is written and published by the organization of the education leader, and is matched with the homework book of the teaching materials, and the book is written by the students based on the course standard issued by the education department and the teaching process of the teaching materials and combined with the practical teaching. The matching exercise book aims at detecting the level of students meeting the requirements of classroom teaching targets, and is an important diagnostic evaluation tool for teaching of mathematical disciplines. Generally, the work of the matching workbook is completed in class, the teacher adopts a mode of batch making or centralized correction after class, wrong comment is made in a full class or individual feedback mode, then students make secondary correction, and finally the teacher makes secondary correction.
However, teachers often only have temporary impression evaluation on the working conditions of students, and are difficult to have accurate data evaluation, and on the other hand, the traditional reviewing method has the problems that reviewing efficiency is low, and materials after reviewing are lack of statistics and analysis, and the like, so that the students are difficult to accurately depict 'growth portraits' in the whole process of mathematics subject learning.
The 'learning material' + 'practice' + 'creation' is a learning material characteristic of the 'internet +' era under the background of big data, how to reset a work question bank, how to research and develop high-quality teaching exercises, how to construct a more effective digital question bank, how to more accurately push corresponding teaching exercises, and is a necessary link for academic evaluation. The development of artificial intelligence assisted education and teaching work gradually trends towards normalization and refinement, and the artificial intelligence technology based on education helps teachers to read and edit homework, collect information, classify data and present results by utilizing information technologies such as image recognition and natural language processing, and is also a necessary link for assisting education and teaching.
Disclosure of Invention
In order to solve the defects of the prior art and realize the precision of teacher evaluation and the purpose of describing the growth portrait of the whole process of student learning, the invention adopts the following technical scheme:
an accurate teaching evaluation and diagnosis method comprises the following steps:
s1, constructing a digital common question bank, recombining matching operation and recording digital resources;
s2, constructing a digital personalized problem library, enabling a teacher to independently research and develop problems, inputting and maintaining the personalized problem library of the teacher, and enabling the teacher to independently research and develop the problems on the basis of fully understanding course standards and deeply studying teaching materials, wherein the problems are indispensable in the evaluation and development of subject academic industries, and the problems can be reversely verified through the personalized problems researched and developed by the teacher and the teaching evaluation results;
s3, intelligently reviewing, digitally collecting the result of the reviewing operation on the premise of not changing the traditional teacher paper-pen reviewing, and reducing the workload of the teacher for combing the reviewing result, comprising the following steps:
s311, a teacher selects the page numbers of the read students and the paper workbooks thereof;
s312, identifying the reading and writing symbols in the segmentation handwriting identification area of the exercise in the page number corresponding to the paper exercise book through the handwriting identification board;
s313, according to the reading result, assigning or not assigning points to students and exercises according to the minimum assignable unit;
generating and applying process evaluation data, and performing linkage precision analysis, wherein the method comprises the following steps:
s321, gathering homework reading and amending results of a group of students, analyzing the correctness and error rate of homework, and locking high-frequency wrong questions to enable teachers to think about deficiencies in teaching according to the analysis results;
s322, according to the wrong question situation, pushing the course and the exercise of the related knowledge points to the student, such as: micro-lesson resources and secondary supplementary tasks (exercises);
s323, setting a time range, and generating a student subject industry portrait and a teacher subject teaching portrait according to the reading results corresponding to a group of students in the time range.
While avoiding the loss of the process evaluation data, the process evaluation data is utilized, and the dimension of a time axis and a knowledge axis can reflect the wrong problem conditions of different types of exercises of students in different periods and reflect the correct problem conditions of the students, so that the mastering conditions of the students in different periods and the advantages and disadvantages of the students (including the advantages and disadvantages of the exercise types and the learning receptivity, for example, one type of knowledge can be fast mastered in a short period) for different subjects and different knowledge points can be judged, and a academic portrait of the students taking the subjects as a unit is formed; the teacher can also form a teaching portrait of the teacher with the subject as a unit through the advantages and disadvantages mastered by the knowledge points of different subjects of the student.
And further, based on the high-frequency wrong questions, inputting and maintaining the individual question bank, performing different levels of question reorganization on the questions under the unit visual angle, and pushing the adaptive questions in due time according to different learning requirements of students. Matching with the time dimension and the dimension of the knowledge category, and pushing exercises of inferior knowledge points of students at proper time on time nodes of different learning stages, learning heat and forgetting degrees; on the basis of learning figures of students, teachers deeply, meticulously and accurately analyze specific mastering conditions of the students by means of accurate and effective data collected by an accurate academic evaluation system, and design an optimized and specific layered or individualized tutoring scheme aiming at the aspects of the cognition level, the academic foundation, personal talent and the like of the students so as to meet different requirements of the students at different levels, accurately push personalized homework and realize optimal development of each student on the basis of the existing academic achievement. Meanwhile, teachers and students revise relevant exercise data, and professional development of teachers is driven according to accurate teaching design of learning conditions.
Further, in S3, the exercise book is initialized, and the exercise book and the corresponding attributes thereof are recorded, where the attributes include the exercise book, subject, year of use, period of study, page number, question number, and assigned value, and the handwriting recognition area is divided according to the layout of the exercise book on each page of the paper exercise book, and the handwriting recognition area is divided according to the minimum assignable unit, and the assigned value and the divided handwriting recognition area are recorded.
Further, the academic portrait in S323 clusters the goodness rate of the student homework, reveals the truth of the class and the individual student showing the distribution of the learning effect, and constructs the academic portrait according to the student attributes, the learning process and the learning result. For example: according to the individual characteristics of the age, the grade, the sex, the hobbies, the partial family and the like of the students, combining the individual performance, the development perspective and the like of the students as the attributes of the students, and according to the learning process with the time dimension and the knowledge category dimension and the excellent rate clustering of the student homework as the learning result, the academic painting of a single student or a group of students (one class or one grade) is constructed; the teacher can accurately master the learning state and thinking level of each grade, class and student according to the academic portrait, dynamic assessment and adjustment are carried out, personalized learning experience is shown in a personalized learning mode, the academic achievement of each student is optimized, and accordingly professional development of the teacher is driven.
Further, clustering the goodness rate of student homework by adopting K-Means, setting A, B, C, D, E types, setting iteration times and clustering kernels, performing clustering iteration by using a K-Means algorithm, dividing the early warning degree according to the proportion of different goodness rates in a clustering iteration result, and pushing knowledge points to classmates without mastered knowledge points.
In S1, each page of the matching exercise book is divided into digital common exercise libraries for the exercise book to maintain its original appearance, and the small exercises are recombined to generate a new exercise book or exercise set for later exercise delivery.
The method according to claim 1, wherein in step S2, the individual question banks are shared with the common question bank, and the common question bank is expanded and updated and optimized by sharing the individual question bank, so that a unified exercise book is generated later or a student teacher calls the exercise book to perform a test and push students.
Furthermore, the teacher sets subject, grade, period, knowledge points and ratio thereof, question types and ratio thereof, and ratio in the common question bank, selects questions from the common question bank and the individual question bank, generates test paper, and arranges the test paper according to the minimum assigned value of the questions, and after the teacher checks and adjusts the test paper, the test paper is arranged according to the minimum assigned value of the test paper, so as to form a segmentation handwriting recognition area.
Further, the paper exercise book in S3 is preset with RFID tags with student information, and the handwriting recognition board recognizes (or manually selects in the software interface) the student information through the RFID tags and corresponds to the exercise.
An accurate teaching evaluation and diagnosis system comprising: the system comprises a common question bank and an individual question bank, and further comprises an independent question setting module, a group paper module and an intelligent evaluation module as shown in figure 3, wherein the intelligent evaluation module comprises a digital acquisition unit and a process evaluation data generation and application unit;
the shared question bank is used for resetting matching operation and inputting digital resources;
the individual question bank is used for the teacher to independently research and develop exercises, and the individual question bank of the teacher is input and maintained;
the independent question setting module is used for setting questions independently and inputting individual question banks or sharing the individual question banks to a shared question bank;
the examination paper combining module selects questions from the common question bank and/or the individual question bank according to the attributes set by the teacher to generate examination papers;
the digital acquisition unit is used for the teacher to identify the reading symbols in the segmentation handwriting identification area of the exercise in the page numbers corresponding to the paper exercise book through the handwriting identification board, and to assign or not assign the students and the exercise book according to the reading results and the minimum assignable unit
The process evaluation data generation and application unit collects homework reading results of a group of students, analyzes the correctness and error rate of homework, locks high-frequency wrong questions, pushes related knowledge points to the students according to wrong question conditions, sets a time range, and generates student subject industry pictures and teacher subject teaching pictures according to reading results corresponding to a group of students in the time range.
The invention has the advantages and beneficial effects that:
the invention carries out sharing through the exercises independently researched and developed by the teacher; on the premise of not changing the traditional teacher's paper-pen reading, the digital collection of the results of the reading operation is realized, and the workload of the teacher for combing the reading results is reduced; the method has the advantages that the process evaluation data are utilized while the process evaluation data are prevented from being lost, the wrong problem conditions of different types of exercises of students in different periods can be reflected in the dimensions of a time axis and a knowledge axis, the correct problem conditions of the students can be reflected, the mastering conditions of the students in different periods and the advantages and disadvantages of the students for different subjects and different knowledge points can be judged, and the academic portrait of the students taking the subjects as a unit is formed; the teacher can also form a teaching portrait of the teacher with the subject as a unit through the advantages and disadvantages mastered by the knowledge points of different subjects of the student.
Drawings
FIG. 1 is a diagram of the system of the present invention and its data integration platform.
FIG. 2 is a flow chart of intelligent review in the present invention.
Fig. 3 is a system block diagram of the present invention.
FIG. 4 is a flow chart of analysis and early warning by clustering in the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.
The intelligent academic evaluation based on big data is a data integration platform constructed by means of informatization means of artificial intelligence and academic evaluation, as shown in figure 1, by means of multi-support of traditional paper media and intelligent review combined technology, intelligent learning platform, artificial intelligence monitoring and the like, diagnosis, evaluation, prediction, early warning and decision making of evaluation data are fully exerted, improvement of teaching implementation is driven through accurate academic evaluation, and teaching quality is improved.
According to the system, the whole operation process is supported by information technology software and hardware, the effective longitudinal digital question bank in the whole teaching process is collected and accumulated, and the visual evaluation is accurately analyzed and improved. Form individual problem based on independently proposition, the operation of resetting supporting forms common problem storehouse, criticizes with the help of intelligence and read linkage depth analysis and is based on multidimensional analysis drive teaching, through improving, based on process data, accurate propelling movement operation, the accurate form of propelling movement. The method has the advantages that the digital intelligence academic evaluation, diagnosis, evaluation, prediction, early warning, decision making and display data of the growing image and the horizontal development data of the whole field of subject learning are generated, teachers are promoted to form intelligent data acquisition capacity, data analysis capacity, diagnosis capacity, feedback capacity and improved effect evaluation capacity through intelligent digital evaluation, the teaching, learning and evaluation consistency is realized, the 'digital portrait' of the student academic growth is formed, and the student growth is efficiently assisted. The teaching result of the teacher is formed into a digital portrait, and the professional development of the teacher is driven efficiently.
Firstly, accurately researching and developing exercises and constructing a digital question bank
1. Reorganizing the matching operation to form a digital common question bank
Taking the mathematics subject of primary school as an example, the functions of the system are explained in advance: the matching homework (book) is written and published by the organization of the education leader, and is matched with the homework book of the teaching material, and the book is written by the students based on the standard issued by the education department and the teaching process of the teaching material and combined with the practical teaching. The matching exercise book aims at detecting the level of students meeting the requirements of classroom teaching targets, and is an important diagnostic evaluation tool for teaching of mathematical disciplines.
Generally, the work of the matching workbook is completed in class, the teacher adopts a mode of batch making or centralized correction after class, wrong comment is made in a full class or individual feedback mode, then students make secondary correction, and finally the teacher makes secondary correction. The teacher often has only temporary impression evaluation to the homework condition of the student, and is difficult to have accurate data evaluation, and is difficult to help the student accurately describe the 'growth portrait' of the whole process of mathematics subject learning.
In order to make the procedural evaluation data chain clearly visible and to make the data-driven improved teaching, the matching exercise book is reset in the digital evaluation system, namely, the resources of the matching exercise book are input into the system by means of a digital means, and each exercise book is divided in the input process, so that the exercise book can keep the original appearance, and each question can be recombined to form a digital common question bank. When a teacher uses a shared question bank with matching operation as a core resource, two levels can be generally adopted: firstly, the student Chinese book is initialized to use, namely, a teacher arranges students to complete a lesson and a practice of 'mathematics exercise book', and the system randomly records the answering condition of each question of each student by adopting an artificial intelligence mode for reading. Secondly, the method is used precisely, namely high-frequency wrong problems are locked in combination with the accuracy of each problem in matching operation, problem reorganization of different levels is carried out on related problems under the unit visual angle, and adaptive problems are pushed according to different learning requirements of students.
2. Forming digital individual question bank based on independent proposition
The independent research and development problem of the teacher is indispensable in the development of the evaluation of the academic discipline, and two core problems of 'what to evaluate' and 'how to evaluate' need to be considered. The ' what ' is evaluated ' points to an evaluation target, the target of a clear system can ensure effective learning situation evaluation, and the effective learning situation evaluation can ensure accurate teaching promotion. In general, teachers are required to do this on the basis of a full understanding of the course standards and deep study of the textbook. The bidirectional list is the 'navigation' for research and development of the exercises, so that the exercise design is accurate and effective.
The exercises independently developed by the teacher are set as a personal digital library of the teacher in a digital chemistry evaluation system, the teacher logs in the system according to the own account number, can input the corresponding exercises at any time, can modify and perfect the warehoused exercises at any time, can form a paper according to knowledge points or capability points during use, is a supplement to a matching operation shared library, and can also be realized.
Secondly, by means of intelligent reading and amending, linkage precision analysis and improvement are realized, as shown in figure 2
1. Digital collection is realized by means of intelligent reading (the detailed technical means of intelligent reading is not mentioned here, for example, the answer content of students is identified, the answer is matched with the correct answer, whether the answer is correct or not is judged, the right and wrong of each question in the reading is recorded, the correct scores are accumulated, and the scores are pushed to parents/teachers … of students)
On the basis of a platform for constructing an accurate chemical industry evaluation system, artificial intelligence equipment and technology are utilized to read and edit traditional student workbooks and collect data. Through development work intelligence reading, on the premise of not changing traditional teacher's paper pen reading, realize the digital collection to reading the homework result.
The intelligent review overall framework takes a homework book (a test question bank) as a core and carries out data acquisition, data processing and intelligent review analysis on homework (test paper). Development work intelligence is reviewed and can be reduced the work load that the teacher combed the result of reviewing to a great extent, the short board of knowledge in student's learning process and the method defect in the teacher teaching process can in time discover and feed back to student and mr, can greatly improve student's learning efficiency and improve teacher's teaching action.
2. Generating evaluation data and analyzing linkage precision
In a traditional evaluation management system, due to lack of accumulation of procedural data, the generation situation of students is not accurately grasped, and the phenomenon of 'speaking repeatedly and wrong repeatedly' is often caused. The same question types appear repeatedly, but about 30% -20% of students always make mistakes each time, and the phenomenon can be caused by that the procedural evaluation data is lost and the teaching feedback of teachers is not accurate. This phenomenon will be altered based on the evaluation system of the digital chemical industry.
In a digital evaluation system, data of each question of each homework of a student are collected by means of intelligent reading and sorting the data of two dimensions of a time axis and a knowledge axis. When performing evaluation analysis on the collected data, we can proceed from the following four dimensions: descriptive analysis by which we see or know what; diagnostic analysis, deep digging the possible reasons behind the data; evaluative analysis, problems that students may encounter in learning; retrospective analysis, the revelation that can be obtained by data analysis. On the basis of the application of the matching operation common library, teachers independently develop exercises in grade groups and diagnose the understanding and application level of students on knowledge.
Through a four-dimensional analysis method, a teacher can fully understand data and fully play the roles of prediction, diagnosis, early warning and decision making of the data. By means of accurate and effective data provided by the accurate chemical industry evaluation system and multi-dimensional analysis data, a teacher is driven to evaluate classroom teaching behaviors, and classroom teaching behaviors in the next stage and individual tutoring scheme adjustment are improved.
3. Application of evaluation data to drive precision teaching
The digital evaluation system is advanced in a certain area, each topic in the system has the accuracy of class, grade and whole area, and also has the annual accuracy and the accumulated accuracy, so that the accurate implementation of teaching under the drive of big data can be realized.
Thirdly, accurate academic evaluation, visual learning image and follow-up
According to the principle of teaching according to the factors, through the presentation and analysis of the student homework results, the teacher can judge the effectiveness of the learning process and the learning results of the students according to the results, so that the teaching contents, the teaching method and the learning method can be reasonably adjusted in the next round of teaching, the teaching relationship is improved, and the three-in-one teaching and evaluation is realized.
1. Perfecting learning portrait and realizing visual evaluation
And (5) citing the group classification of K-Means according to the mark of the operation condition, and gradually updating the clustering center by an iteration method to realize the optimal clustering result. And the clustering of the student homework accuracy by the evidence reveals the truth of the class and the individual students in the distribution of the learning effect. The portrait model is built according to the data collected and processed by the accurate chemical industry evaluation system and the result after accurate teaching according to the learning situation and the learning attribute, the learning process and the learning result data of the students, and an accurate personalized learning path planning frame is designed based on the portrait model to realize visual evaluation. The characterization of the student learning portrait mainly comprises four levels of individual characteristics, individual performance, academic achievement and individual development vision, and the academic evaluation is visualized, as shown in fig. 4.
Based on the visual academic evaluation of big data, the subsequent teaching can be designed and improved by each teacher on the basis of accurately analyzing the academic level of each student; on the other hand, on the basis of accurately analyzing the comparison data of each lessee teacher, school managers can generate longitudinal evaluation data of all students in the whole process of all grade learning conditions and push accurate visual evaluation forms to students (parents), so that instant feedback and interaction of evaluation information are realized, and the students can find own 'recent development areas' according to own learning figures by seeing difficulties and errors encountered in learning.
2. Accurate push operation based on individual data
On the basis of learning figures of students, teachers deeply, meticulously and accurately analyze specific mastering conditions of the students by means of accurate and effective data collected by an accurate academic evaluation system, and design an optimized and specific layered or individualized tutoring scheme aiming at the aspects of the cognition level, the academic foundation, personal talent and the like of the students so as to meet different requirements of the students at different levels, accurately push personalized homework and realize optimal development of each student on the basis of the existing academic achievement. Meanwhile, teachers and students revise relevant exercise data, and professional development of teachers is driven according to accurate teaching design of learning conditions.
In summary, the accurate academic evaluation implementation based on the digital intelligent evaluation system needs to go through the links of digital exercise library construction, accurate data analysis and improvement, visual academic evaluation and the like, needs to go through the whole processes of data collection, data analysis, data decision, regulation and correction, and realizes the intelligent correction function by means of artificial intelligent equipment (such as intelligent recognition and the like) on the basis of not changing paper media application (such as paper workbooks for student answering or study notes), and then performs descriptive, diagnostic, predictive and decision analysis by combining with the visual evaluation data generated by the system, so that the data-driven teaching improvement is realized, the accurate teaching is realized, and each student has a unique learning figure. The teacher can accurately grasp the learning state and thinking level of each student according to the learning figures, dynamic assessment and adjustment are carried out, personalized learning experience is revealed in a personalized learning mode, the academic achievement of each student is optimized, and accordingly professional development of the teacher is driven.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An accurate teaching evaluation and diagnosis method is characterized by comprising the following steps:
s1, constructing a digital common question bank, recombining matching operation and recording digital resources;
s2, constructing a digital individual question bank, enabling a teacher to independently research and develop exercises, and recording and maintaining the individual question bank of the teacher;
s3, intelligent review, digital collection of the results of the review operation, including the following steps:
s311, a teacher selects the page numbers of the read students and the paper workbooks thereof;
s312, identifying the reading and writing symbols in the segmentation handwriting identification area of the exercise in the page number corresponding to the paper exercise book through the handwriting identification board;
s313, according to the reading result, assigning or not assigning points to students and exercises according to the minimum assignable unit;
generating and using process evaluation data, comprising the steps of:
s321, gathering homework reading and amending results of a group of students, analyzing the correctness and error rate of homework, and locking high-frequency wrong questions;
s322, pushing related knowledge points to students according to the wrong question condition;
s323, setting a time range, and generating a student subject industry portrait and a teacher subject teaching portrait according to the reading results corresponding to a group of students in the time range.
2. The method for accurate teaching evaluation and diagnosis according to claim 1, wherein the input and maintenance of the individual question bank is performed based on the high-frequency wrong questions, the questions are regrouped at different levels under the unit view angle, and the adaptive questions are pushed in due time according to different learning requirements of students.
3. The method of claim 1, wherein in step S3, the exercise book is initialized, the exercise questions and the corresponding attributes thereof are recorded, the attributes include exercise book, subject, year of use, period of study, page number, question number, assigned value, the handwriting recognition area is divided according to the layout of the exercise questions in the paper exercise book, wherein the handwriting recognition area is divided according to the smallest assignable unit, and the assigned value and the divided handwriting recognition area are recorded.
4. The method of claim 1, wherein the academic portrait of S323 clusters the goodness rate of student' S homework, and constructs the academic portrait according to student attributes, learning process and learning result.
5. The method of claim 1, wherein K-Means is used to cluster the goodness rate of student work, A, B, C, D, E categories are set, iteration times and clustering kernels are set, K-Means algorithm is used to perform clustering iteration, the degree of early warning is divided according to the proportion of different goodness rates in clustering iteration results, and knowledge points are pushed to classmates without knowledge points.
6. The method of claim 1, wherein in step S1, each page of the workbook is divided based on the problem to form a digital common problem bank.
7. The method of claim 1, wherein in step S2, the individual question banks are shared with the common question bank.
8. The method as claimed in claim 2, wherein the teacher sets subject, grade, period, knowledge points and their ratios, question types and their ratios, and ratios in the common question bank, selects questions from the common question bank and the individual question bank, generates test paper, and arranges the test paper according to the minimum assigned value of the questions, and after the teacher checks and adjusts the test paper, the test paper is arranged according to the minimum assigned value of the test paper, and the split handwriting recognition area is formed.
9. The method for accurately teaching, evaluating and diagnosing as claimed in claim 1, wherein the paper exercise book in S3 is preset with RFID tag with student information, and the handwriting recognition board selects and recognizes the student information in the software interface through the RFID tag or manually, and corresponds to the exercise.
10. An accurate teaching evaluation and diagnosis system comprising: the system comprises a shared question bank and an individual question bank, and is characterized by further comprising an independent question setting module, a group paper module and an intelligent evaluation module, wherein the intelligent evaluation module comprises a digital acquisition unit and a process evaluation data generation and application unit;
the shared question bank is used for resetting matching operation and inputting digital resources;
the individual question bank is used for the teacher to independently research and develop exercises, and the individual question bank of the teacher is input and maintained;
the independent question setting module is used for setting questions independently and inputting individual question banks or sharing the individual question banks to a shared question bank;
the examination paper combining module selects questions from the common question bank and/or the individual question bank according to the attributes set by the teacher to generate examination papers;
the digital acquisition unit is used for the teacher to identify the reading symbols in the segmentation handwriting identification area of the exercise in the page numbers corresponding to the paper exercise book through the handwriting identification board, and to assign or not assign the students and the exercise book according to the reading results and the minimum assignable unit
The process evaluation data generation and application unit collects homework reading results of a group of students, analyzes the correctness and error rate of homework, locks high-frequency wrong questions, pushes related knowledge points to the students according to wrong question conditions, sets a time range, and generates student subject industry pictures and teacher subject teaching pictures according to reading results corresponding to a group of students in the time range.
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