CN111968434A - Method and storage medium for on-line paperless language training and evaluation - Google Patents
Method and storage medium for on-line paperless language training and evaluation Download PDFInfo
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Abstract
The invention provides a method and a system for on-line paperless language training and evaluation, wherein the method comprises the following steps: s1: the first user terminal distributes test question information to the second user terminal; s2: the first user terminal receives an answer result of the second user terminal aiming at the test question information and inputs the answer result into a language calculation model; s3: and the language calculation model carries out semantic analysis and syntax analysis on the answer result, outputs score information and wrong question information corresponding to the answer result and sends the score information and the wrong question information to a second user terminal. According to the scheme, the user where the second user terminal is located answers by himself/herself by issuing the test question information, and the answer result is preliminarily scored by adopting the language calculation model, so that the time of teaching interaction is greatly saved, and the teaching quality and efficiency are improved.
Description
Technical Field
The invention relates to the field of communication, in particular to an online paperless language training and evaluating method, a storage medium and electronic equipment.
Background
With the development of computer technology and the internet, many schools or training institutions are put into the field of online teaching, and it is desired to provide more diversified teaching contents or more convenient teaching systems through the technology of computer multimedia. In the learning process, students often need to check the learning effect of the students through examination. However, the learning ability of students still depends on manual judgment at present, taking word dictation or article paragraph reciting as an example, a teacher needs to examine the learning degree of the students on knowledge points in a classroom in a dictation or question-asking manner, and in the process, the teacher's interpretation, the student's dictation, the student's rolling and the teacher's correction occupy a large amount of teaching time and affect the teaching efficiency. And for words which are wrongly listened by students or paragraphs which are not standard in reciting, the existing teaching mode does not have a good long-term feedback mechanism, so that the students forget the knowledge point again after a certain time, and the teaching quality further slides down.
Disclosure of Invention
Therefore, a technical scheme for online paperless language training and evaluation needs to be provided to solve the problems that the teaching interaction mode is complicated in steps and the teaching efficiency is affected.
To achieve the above object, a first aspect of the present application provides an online paperless language training and evaluating method, which includes the following steps:
s1: the first user terminal distributes test question information to the second user terminal;
s2: the first user terminal receives an answer result of the second user terminal aiming at the test question information and inputs the answer result into a language calculation model;
s3: and the language calculation model carries out semantic analysis and syntax analysis on the answer result, outputs score information and wrong question information corresponding to the answer result and sends the score information and the wrong question information to a second user terminal.
Further, step S3 further includes:
and identifying and recording the wrong question information, and displaying the standard answer information at the position of the wrong question information.
Further, step S1 is preceded by the following step S12:
and receiving a preset file uploaded by a first user terminal, and generating test question information matched with the preset file format.
Further, the method comprises:
receiving answer environment parameters set by a first user terminal, and sending the test question information and the answer environment parameters to a second user terminal; the answer environment parameters comprise the time for completing the test question;
and after detecting that the second user terminal starts answering the test question information, if the answering time reaches the time of finishing the test paper, stopping receiving the input information of the second user terminal, and uploading the answer result on the current second user terminal to the first user terminal.
Further, the answer result includes audio information, and the method includes:
inputting the audio information into an audio computational model;
and the audio calculation model outputs score information corresponding to the answer result of the current second user terminal aiming at the test question information according to the similarity between the audio information and the standard audio information, and issues the score information to the second user terminal.
Further, the audio information includes intonation information and tone information, the standard intonation information and standard tone information, and step S3 includes:
the audio calculation model records a part of the audio information, wherein the intonation information is dissimilar to the standard intonation information, and/or obtains a wrong question record corresponding to the current answer result according to the part of the audio information, wherein the tone information is dissimilar to the standard tone information;
and pushing test question information corresponding to the corresponding wrong question record to the second user terminal according to the rule of the memory curve and the preset time and date sequence.
Further, "pushing test question information corresponding to the corresponding wrong question record to the second user terminal according to a memory curve rule and a predetermined time date sequence" includes: and determining the weight information of each error according to the error rate and the timestamp information, and pushing test question information corresponding to the corresponding error record according to the weight information.
Furthermore, the answer environment parameters also comprise the limiting screen-switching times; the method comprises the following steps:
when detecting that the screen switching times of the second user terminal are larger than the preset screen switching times, stopping receiving input information of the second user terminal, and uploading an answer result on the current second user terminal to the first user terminal; the screen switching times refer to the times of switching from the application program running on the current screen to other application programs.
Further, step S3 includes:
acquiring test question types input by a first user terminal and the number of test questions of each type, and generating a plurality of test question information of different types; the question patterns of different types of test question information are not completely the same.
A second aspect of the present application provides an online paperless language training and evaluation system for performing the method according to the first aspect of the present application.
Different from the prior art, the invention provides an online paperless language training and evaluating method and system, wherein the method comprises the following steps: s1: the first user terminal distributes test question information to the second user terminal; s2: the first user terminal receives an answer result of the second user terminal aiming at the test question information and inputs the answer result into a language calculation model; s3: and the language calculation model carries out semantic analysis and syntax analysis on the answer result, outputs score information and wrong question information corresponding to the answer result and sends the score information and the wrong question information to a second user terminal. According to the scheme, the user at the second user terminal can answer the question by himself by issuing the test question information, and the answer result is preliminarily scored by adopting the language calculation model, so that the time of teaching interaction is greatly saved, and the teaching quality and the teaching efficiency are improved.
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Fig. 1 is a flowchart of an on-line paperless language training and evaluating method according to an embodiment of the present invention.
Detailed Description
To explain technical contents, structural features, and objects and effects of the technical solutions in detail, the following detailed description is given with reference to the accompanying drawings in conjunction with the embodiments.
Fig. 1 is a flowchart of a method for on-line paperless language training and evaluation according to an embodiment of the present invention. The method comprises the following steps:
s1: the first user terminal distributes the test question information to the second user terminal.
Preferably, the first user terminal is a teacher-controlled terminal, the second user terminal is a student-controlled terminal, the first user terminal and the second user terminal can be connected through wireless WIFI, a wired network, bluetooth and the like, and the first user terminal and the second user terminal can be mobile phones, tablets, personal computers and the like. After receiving the test question information, the second user terminal can answer the test question information on a corresponding application program, wherein the test question information can comprise text information and audio information so as to adapt to the requirements of different application scenes.
S2: and the first user terminal receives the answer result of the second user terminal aiming at the test question information and inputs the answer result into a language calculation model.
In this embodiment, the test question information is preferably composition information, and after the student answers the test question information by using the second user terminal, the student can upload the completed composition to the first user terminal, and the first user terminal can input the answer result into the language calculation model, so that the language calculation model can perform further calculation and scoring conveniently.
S3: and the language calculation model carries out semantic analysis and syntax analysis on the answer result, outputs score information and wrong question information corresponding to the answer result and sends the score information and the wrong question information to a second user terminal.
The language calculation model is a trained artificial intelligence model capable of automatically judging and analyzing test question information input by a user. Taking the language as english as an example, the semantic analysis of the answer result by the language calculation model includes: analyzing whether each word in the test question information is correctly spelled or not; the parsing includes: and analyzing whether the connection among the words in the test question information conforms to the English usage grammar rule. In addition, the language calculation model can also score the user according to the difficulty degree of the words contained in the test question information as an influence factor of the score information, wherein the more difficult the difficulty degree of the contained words is, the higher the score is.
According to the scheme, the user at the second user terminal can answer the question by himself by issuing the test question information, and the answer result is preliminarily scored by adopting the language calculation model, so that the time of teaching interaction is greatly saved, and the teaching quality and the teaching efficiency are improved.
In some embodiments, the answer result includes audio information, the method comprising: inputting the audio information into an audio computational model; and the audio calculation model outputs score information corresponding to the answer result of the current second user terminal aiming at the test question information according to the similarity between the audio information and the standard audio information, and issues the score information to the second user terminal. In this embodiment, the test question information includes paragraph information to be recited or vocabulary information to be recited, and the corresponding answer result receives audio information input by the user in addition to the result contained in the test question information itself. The audio information refers to the audio information which is input by the second user terminal after the second user terminal reads the test question information, and the audio information which is input into the audio calculation model.
The intelligent comparison and scoring of the received audio information and the standard audio information by the audio computing model can be realized by the following modes: the text information (e.g., vocabulary to be read, article) in the test question information is first aligned with the pronunciation audio of the second user, which is commonly referred to as "forced alignment". The audio calculation model can obtain the phoneme sequence corresponding to the current test question information text, and the phoneme (phone) is the minimum voice unit divided according to the natural attributes of the voice, is analyzed according to the pronunciation action in the syllables, and forms a phoneme by one action. The HMM models of the phones can then be concatenated to form a large HMM model, and based on this audio computation model and the speech feature sequence extracted from the user's audio information, the most likely phone state sequence can be computed, i.e., to which of the phones each frame of speech belongs and the pitch state of that phone. This allows correspondence between the audio frame and the phoneme state, from which the name "forced alignment" comes. After forced alignment, the speech frame interval range corresponding to each phoneme is known. If the pronunciation of the second user (such as a student) is accurate, the phonetic frame interval corresponding to each phoneme can be accurately positioned after forced alignment. If the second user pronunciation is wrong, e.g. a phoneme is misread, the aligned speech frame interval actually originates not this phoneme. In addition, a language identification mode can be directly adopted to identify and calculate the audio information of which the phoneme state sequence most conforms to the preset phoneme state sequence, and the score is carried out according to the matching degree.
The scoring of the audio computation model can be realized by a GOP (Goodness of probability) algorithm, which is essentially a conditional probability that measures the probability that a phoneme corresponds to a section of speech when the speech of a user is observed, wherein the higher the probability is, the more accurate the pronunciation is, the lower the probability is, the worse the pronunciation is, and the scoring metric is suitable in a physical sense. According to the GOP formula, the audio calculation model can score the pronunciation condition of each phoneme in the test question information, and meanwhile, the speech frame interval corresponding to the phoneme can be known according to the result of forced alignment, so that the position of pronunciation error can be obtained. More importantly, the audio calculation model can know what the real pronunciation of the user is according to the result of free recognition, and the information can also be returned to the user as a scoring result.
Further, the audio information includes intonation information and tone information, the standard intonation information and standard tone information, and step S3 includes: the audio calculation model records a part of the audio information, wherein the intonation information is dissimilar to the standard intonation information, and/or obtains a wrong question record corresponding to the current answer result according to the part of the audio information, wherein the tone information is dissimilar to the standard tone information; and pushing test question information corresponding to the corresponding wrong question record to the second user terminal according to the rule of the memory curve and the preset time and date sequence. The intelligent comparison method of the intonation information and the tone information has been discussed above, and is not expanded here, and the wrong record here refers to the vocabulary information with relatively large deviation of the intonation information or the tone information, or a sentence or a vocabulary in a paragraph of an article.
Preferably, the step of "pushing test question information corresponding to the corresponding wrong question record to the second user terminal according to the rule of the memory curve and the predetermined time and date sequence" includes: and determining the weight information of each error according to the error rate and the timestamp information, and pushing test question information corresponding to the corresponding error record according to the weight information.
The memory curve tells people that forgetting in learning is regular, and the forgetting process is fast and slow. Assuming that x hours have passed after the initial memory, the memory rate y approximately satisfies y 1-0.56x ^ 0.06. By observing the curve, it can be easily found that the learned knowledge is only 25% of the original knowledge left after one day if the learned knowledge is not closely reviewed. As time goes on, the forgetting speed is reduced, and the forgetting quantity is reduced. After some experiment, two groups of students study a lesson, the group A does not review after learning, the memory rate is 36% after one day, and only 13% remains after one week. The second group was reviewed according to the Ebinghaos memory law, with a memory rate of 98% after one day and 86% after one week, the memory rate of the second group being significantly higher than that of the first group.
Therefore, pushing new test point information to the second user terminal according to the memory curve rule and in a predetermined time interval sequence comprises: and pushing corresponding wrong question information aiming at each second user terminal, pushing new examination point information to the second user terminals when the time and date are in accordance with the change rule of the memory curve, and correspondingly setting the completion time during each pushing so that the second user terminals can finish answering within the preset completion time. Assuming that the rule of the memory curve is set to be 1 day later, 3 days later, 7 days later and 14 days later, the system will sequentially push the wrong-question information to the second user terminal after one day, three days later, one week later and two weeks later, and at the same time, the completion time is correspondingly set during each pushing, so that the second user terminal can finish answering within the preset completion time. The weight of the pushed wrong question information is determined according to the answering accuracy and the timestamp information in the user historical data, and the lower the accuracy is, the closer the wrong question is to the current time, the higher the pushed weight is.
For example, when a student answers to the test question information, if 20 questions are mistaken (where the wrong answer refers to that the pronunciation is not standard or wrong), the system will push the 20 questions to the student for practice after one day, if the student does the wrong 10 questions again in the present practice, then in the push wrong questions after three days, the student will push the 10 questions which were cumulatively mistakenly mistaken in the previous practice, and for the 10 questions which have been already paired in the previous practice, although the push will also be performed, the weight value of the push will be reduced, if the student does the wrong 10 questions again in the present practice (the error rate of the 10 questions is reduced, the weight of the push will be further reduced), then in the process of the next wrong questions (after one week), the system will only recommend the 5 questions which are paired in two exercises to the student, if the 5 questions are also paired, then the 5 questions will not be pushed during the next (two weeks later) pushing of wrong questions. Through the balance calculation of the error rate statistics and the number of the wrong questions to be pushed, the pushing of the wrong questions can be more targeted, so that students can master corresponding knowledge points more easily, and the teaching quality is improved.
In certain embodiments, the method further comprises: and receiving a page number range uploaded by the first user terminal, extracting a plurality of examination point vocabularies from a vocabulary library according to the page number range, and generating the test question information. The examination point vocabulary can be Chinese, English or other languages, preferably, in the embodiment, the examination point vocabulary is English. The examination point vocabularies can be obtained from a vocabulary library, the vocabulary library can be divided into different difficulty levels according to the requirements of different application scenes, and the examination point vocabularies can be divided into four-level vocabularies, six-level vocabularies, Abbe vocabularies and the like by taking English as an example. In a practical application scenario, the teacher can select a vocabulary library page number range through the first user terminal to generate test question information. For example, a teacher may select a page number range of a unit in the four-level vocabulary library, and the system may extract all examination point vocabularies within the selected page number range, generate corresponding vocabularies to be read aloud or writing questions to be written with the screened vocabularies as topics, and obtain test question information.
In certain embodiments, the method further comprises: receiving a preset file uploaded by a first user terminal, and generating test question information matched with the preset file format; the test question information comprises composition question types, number and/or vocabulary number and types to be read. Therefore, the teacher only needs to select the page number range of the vocabulary library and upload the preset file, and the system can automatically generate test paper matched with the format of the preset file (namely the generated question type arrangement and the number of the question types are matched with the question type arrangement and the number of the question types contained in the preset file), so that the operation steps of the teacher are greatly simplified, and the test question generation efficiency is improved. Of course, in other embodiments, the teacher may also directly input the generated question types and the number corresponding to each question type through the first user terminal controlled by the teacher to generate the test paper to be pushed, so as to meet the requirements of different application scenarios.
In certain embodiments, step S1 further includes: receiving answer environment parameters set by a first user terminal, and sending the test question information and the answer environment parameters to a second user terminal; the answer environment parameters comprise the time for completing the test question. The second user terminal is terminal equipment operated by students, and the first user terminal controlled by the teacher can synchronously set the answering time of the current test paper when the test paper to be pushed is sent to the second user terminal, so that the second user terminal can answer the test paper of the test paper completed by the teacher after receiving the test paper to be pushed, and the effective propulsion of the examination or the follow-up small test is ensured.
In certain embodiments, the method comprises: and after detecting that the second user terminal starts answering the test question information, if the answering time reaches the time of finishing the test paper, stopping receiving the input information of the second user terminal, and uploading the answer result on the current second user terminal to the first user terminal. Like this, when reaching the examination time, the system can realize the automatic rolling function, has both promoted efficiency and has guaranteed the fairness of examination again.
In some embodiments, the answer environment parameters further include limiting the number of screen cuts; the method comprises the following steps: when detecting that the screen switching times of the second user terminal are larger than the preset screen switching times, stopping receiving input information of the second user terminal, and uploading an answer result on the current second user terminal to the first user terminal; the screen switching times refer to the times of switching from the application program running on the current screen to other application programs. Preferably, the limited screen-cutting times are two times.
In short, after the test question information is sent to the second user terminal, the students can answer the corresponding application program or applet on the second user terminal, and in order to prevent cheating among the students, the answering interface needs to be kept running at the front end of the second user terminal all the time, so that the answer is realized by setting the limited screen switching times, that is, when the screen switching times of the second user terminal are detected to be larger than the preset screen switching times, the receiving of the input information of the second user terminal is stopped, and the answer result on the current second user terminal is uploaded to the first user terminal. Thus, the fairness of the examination test can be effectively ensured.
In certain embodiments, step S3 includes: acquiring test question types input by a first user terminal and the number of test questions of each type, and generating a plurality of test question information of different types; the question patterns of different types of test question information are not completely the same. In short, the question types (such as words, example sentences, articles and composition questions to be written) and the number of the generated test question information can be different, so that a plurality of sets of different test question information are pushed to different second user terminals, and the possibility of cheating among students is further avoided. Preferably, a random number algorithm can be adopted to push test question information to be pushed, namely, the generated sets of test question information are completely random when being pushed to a plurality of second user terminals, and each student does not know the test paper question type distributed by the student, so that the possibility of mutual cheating among the students is further avoided.
In certain embodiments, step S3 further includes: and identifying and recording the wrong question information, and displaying the standard answer information at the position of the wrong question information. The step of identifying and recording the wrong question information comprises the following steps: the words with misspelling are marked in a highlight form, and the lines of the sentences with errors in grammar are described. The system can also display standard answer information at the position of wrong question information so that students can correct the wrong question information by themselves after receiving the score information, and teaching efficiency is improved.
The second aspect of the present application also provides a storage medium having a computer program stored therein, the computer program being configured to perform the method of the first aspect of the present application. The storage medium is an electronic component with a data storage function, and includes but is not limited to: RAM, ROM, magnetic disk, magnetic tape, optical disk, flash memory, U disk, removable hard disk, memory card, memory stick, etc.
In a third aspect of the present application, there is provided an online paperless language training and evaluation system comprising a storage medium according to the second aspect of the present application. The system can be an electronic device with a data processing function, such as an intelligent mobile device like a mobile phone, a tablet computer and a personal digital assistant, and can also be an electronic device like a personal computer and a scanner.
It should be noted that, although the above embodiments have been described herein, the invention is not limited thereto. Therefore, based on the innovative concepts of the present invention, the technical solutions of the present invention can be directly or indirectly applied to other related technical fields by making changes and modifications to the embodiments described herein, or by using equivalent structures or equivalent processes performed in the content of the present specification and the attached drawings, which are included in the scope of the present invention.
Claims (10)
1. An on-line paperless language training and evaluating method, characterized by comprising the steps of:
s1: the first user terminal distributes test question information to the second user terminal;
s2: the first user terminal receives an answer result of the second user terminal aiming at the test question information and inputs the answer result into a language calculation model;
s3: and the language calculation model carries out semantic analysis and syntax analysis on the answer result, outputs score information and wrong question information corresponding to the answer result and sends the score information and the wrong question information to a second user terminal.
2. The method for paperless language training and evaluation according to claim 1, wherein step S3 further comprises:
and identifying and recording the wrong question information, and displaying the standard answer information at the position of the wrong question information.
3. The method for paperless language training and evaluation according to claim 1, wherein step S1 is preceded by the step S12 of:
and receiving a preset file uploaded by a first user terminal, and generating test question information matched with the preset file format.
4. The method for paperless language training and evaluation according to claim 1, wherein said method comprises:
receiving answer environment parameters set by a first user terminal, and sending the test question information and the answer environment parameters to a second user terminal; the answer environment parameters comprise the time for completing the test question;
and after detecting that the second user terminal starts answering the test question information, if the answering time reaches the time of finishing the test paper, stopping receiving the input information of the second user terminal, and uploading the answer result on the current second user terminal to the first user terminal.
5. The method for paperless language training and evaluation according to claim 4, wherein said answer results comprise audio information, said method comprising:
inputting the audio information into an audio computational model;
and the audio calculation model outputs score information corresponding to the answer result of the current second user terminal aiming at the test question information according to the similarity between the audio information and the standard audio information, and issues the score information to the second user terminal.
6. The method for paperless language training and evaluation according to claim 5, wherein said audio information comprises intonation information and tonal information, said standard intonation information and standard tonal information, and step S3 comprises:
the audio calculation model records a part of the audio information, wherein the intonation information is dissimilar to the standard intonation information, and/or obtains a wrong question record corresponding to the current answer result according to the part of the audio information, wherein the tone information is dissimilar to the standard tone information;
and pushing test question information corresponding to the corresponding wrong question record to the second user terminal according to the rule of the memory curve and the preset time and date sequence.
7. The method for on-line paperless language training and evaluation as claimed in claim 6, wherein "pushing test question information corresponding to the corresponding wrong question record to the second user terminal according to a rule of a memory curve and a predetermined time and date sequence" comprises: and determining the weight information of each error according to the error rate and the timestamp information, and pushing test question information corresponding to the corresponding error record according to the weight information.
8. The method for on-line paperless language training and evaluation according to claim 4, wherein said answer environment parameters further comprise limiting screen-cut times; the method comprises the following steps:
when detecting that the screen switching times of the second user terminal are larger than the preset screen switching times, stopping receiving input information of the second user terminal, and uploading an answer result on the current second user terminal to the first user terminal; the screen switching times refer to the times of switching from the application program running on the current screen to other application programs.
9. The method for paperless language training and evaluation according to claim 1, wherein step S3 comprises:
acquiring test question types input by a first user terminal and the number of test questions of each type, and generating a plurality of test question information of different types; the question patterns of different types of test question information are not completely the same.
10. An on-line paperless language training and evaluation system for performing the method of any of claims 1 to 9.
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| CN118506624A (en) * | 2024-07-16 | 2024-08-16 | 浙江强脑科技有限公司 | Memory training method based on color interaction, user terminal and storage medium |
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