Teaching quality evaluation method and device, storage medium and electronic equipment

Abstract

The invention discloses a teaching quality evaluation method and device, a storage medium and electronic equipment, and relates to the technical field of education, knowledge points with high student participation degree are screened out by using a preset knowledge point screening algorithm, the knowledge points really concerned and participated by students in a classroom can be found out, and the teaching quality evaluation efficiency is improved. And the attraction of teaching contents and the acceptance degree of students are reflected. Evaluation is performed according to the proportion of the teaching feedback knowledge point cluster in the teaching plan text, and the actual teaching effect is compared with the teaching plan, so that the achievement condition of the teaching target can be objectively measured, and the accuracy of teaching quality evaluation is improved.

Description

Technical Field

[0001] The present application relates to the field of educational technology, and in particular to a teaching quality assessment method, device, storage medium and electronic device. Background Art

[0002] With the continuous advancement of educational technology, the demand for an objective and accurate teaching quality evaluation method in the education field is increasing. Using technical means to quantify the interaction and behavior of teachers and students in the classroom can more scientifically evaluate the teaching quality and provide strong data support and accurate basis for teaching improvement.

[0003] In the relevant technologies of teaching quality assessment, subjective observation and questionnaire surveys are usually used. For example, teaching quality is measured based on students' evaluation questionnaires on teachers' teaching. However, these methods are easily influenced by students' subjective factors, and the evaluation results are one-sided and cannot fully reflect the actual teaching situation, resulting in low accuracy of teaching quality assessment. Summary of the invention

[0004] The present application provides a teaching quality evaluation method, device, storage medium and electronic device. The main purpose is to solve the problem of low accuracy of teaching quality evaluation.

[0005] According to a first aspect of the present application, a teaching quality assessment method is provided, which includes: Obtain a real-life video of a history class in which a teacher teaches students, and extract classroom text of an interactive video that triggers classroom interactive behavior in the real-life video of the history class; Using a preset knowledge point screening algorithm, screen out knowledge points in the classroom text whose student participation is greater than a preset participation threshold, to obtain a teaching feedback knowledge point cluster; The lesson plan text corresponding to the history classroom recording video is obtained, and the teaching quality of the history classroom recording video is evaluated according to the proportion of the knowledge points of the teaching feedback knowledge point cluster in the teaching text.

[0006] Optionally, the method of using a preset knowledge point screening algorithm to screen out knowledge points whose student participation is greater than a preset participation threshold from all knowledge points in the classroom text to obtain a teaching feedback knowledge point cluster includes: Extracting all the knowledge points in the classroom text; Count the number of students’ answers in the interactive video, the accuracy of students’ answers, and the duration of the conversation in which students answer correctly for each of all the knowledge points; Calculate the student participation of each knowledge point according to the number of students' answers, the accuracy of the students' answers and the duration of the conversation; The knowledge points whose student participation degree is greater than the preset participation degree threshold among all the knowledge points are combined into the teaching feedback knowledge point cluster.

[0007] Optionally, the calculating the student participation degree of each knowledge point according to the number of students' quick answers, the accuracy of the students' answers and the duration of the conversation includes: Student engagement The calculation formula is:

[0008] in, , , are the number of times the student answered the question, the accuracy of the student's answer and the duration of the conversation in which the student answered the question correctly, , , are the first weights corresponding to the number of times the student answers the questions, the accuracy rate of the student's answers and the duration of the conversation in which the student answers the questions correctly.

[0009] Optionally, the performing teaching quality evaluation on the history classroom recorded video according to the proportion of the knowledge points of the teaching feedback knowledge point cluster in the teaching text includes: Calculate the proportion of all the knowledge points in the teaching plan text; According to the proportion ratio and the average participation rate of students in all knowledge points, the teaching quality score of the history classroom recording video is calculated, so as to evaluate the teaching quality of the history classroom recording video based on the teaching quality score.

[0010] Optionally, the calculating of the teaching quality score of the history classroom video recording according to the proportion ratio and the average participation degree of the students in all the knowledge points includes: Teaching quality rating The calculation formula is:

[0011] in, , are the proportion ratio and the average participation of students in all knowledge points, For all the knowledge points mentioned, For the lesson plan text, , The second weights respectively correspond to the proportion ratio and the average participation degree of the students in all the knowledge points.

[0012] Optionally, obtaining a real video of a history class in which a teacher teaches students includes: Using the video acquisition module and the audio acquisition module in the classroom to record the process of the teacher teaching the students, to obtain the real-life video of the history class; Alternatively, the smart blackboard in the classroom and a student interaction module that interacts with the smart blackboard are used to record the process of the teacher teaching the students to obtain a real-life video of the history class.

[0013] According to a second aspect of the present application, a teaching quality assessment device is provided, comprising: An acquisition unit, used for acquiring a real-time video of a history class in which a teacher teaches students; An extraction unit, used to extract the classroom text of the interactive video that triggers the classroom interactive behavior in the real-recorded video of the history classroom; A screening unit, configured to screen out knowledge points whose student participation is greater than a preset participation threshold from all knowledge points in the classroom text using a preset knowledge point screening algorithm, to obtain a teaching feedback knowledge point cluster; An evaluation unit is used to obtain the lesson plan text corresponding to the history classroom recording video, and evaluate the teaching quality of the history classroom recording video according to the proportion of the knowledge points of the teaching feedback knowledge point cluster in the teaching text.

[0014] Optionally, the screening unit includes: An extraction module, used to extract all the knowledge points in the classroom text; A statistics module is used to count the number of students' answers to each knowledge point in the interactive video, the accuracy of students' answers, and the duration of conversations in which students answer correctly; A first calculation module is used to calculate the student participation degree of each knowledge point according to the number of students' answers, the accuracy of the students' answers and the duration of the conversation; The combination module is used to combine the knowledge points whose student participation degree is greater than the preset participation degree threshold among all the knowledge points into the teaching feedback knowledge point cluster.

[0015] Optionally, the first calculation module is further used for: Student engagement The calculation formula is:

[0016] in, , , are the number of times the student answered the question, the accuracy of the student's answer and the duration of the conversation in which the student answered the question correctly, , , are the first weights corresponding to the number of times the student answers the questions, the accuracy rate of the student's answers and the duration of the conversation in which the student answers the questions correctly.

[0017] Optionally, the evaluation unit includes: A second calculation module is used to calculate the proportion of all the knowledge points in the teaching plan text; The second calculation module is also used to calculate the teaching quality score of the history classroom recording video based on the proportion ratio and the average student participation of all knowledge points, so as to evaluate the teaching quality of the history classroom recording video based on the teaching quality score.

[0018] Optionally, the second calculation module is further used for: Teaching quality rating The calculation formula is:

[0019] in, , are the proportion ratio and the average participation of students in all knowledge points, For all the knowledge points mentioned, For the lesson plan text, , The second weights respectively correspond to the proportion ratio and the average participation degree of the students in all the knowledge points.

[0020] Optionally, the acquisition unit is further used for: Using the video acquisition module and the audio acquisition module in the classroom to record the process of the teacher teaching the students, to obtain the real-life video of the history class; Alternatively, the smart blackboard in the classroom and a student interaction module that interacts with the smart blackboard are used to record the process of the teacher teaching the students to obtain a real-life video of the history class.

[0021] According to a third aspect of the present application, an electronic device is provided, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0022] According to a fourth aspect of the present application, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0023] According to a fifth aspect of the present application, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the method according to the first aspect is implemented.

[0024] The teaching quality evaluation method, device, storage medium and electronic device provided in this application can find out the knowledge points that students really pay attention to and participate in in class by using a preset knowledge point screening algorithm to screen out knowledge points with high student participation, thereby reflecting the attractiveness of the teaching content and the acceptance of students. According to the proportion of the teaching feedback knowledge point cluster in the lesson plan text, the actual teaching effect is compared with the teaching plan, which can objectively measure the achievement of teaching objectives, thereby improving the accuracy of teaching quality evaluation. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present application. Figure 1 A flow chart of a teaching quality assessment method provided in an embodiment of the present application; Figure 2 A schematic diagram of a knowledge graph of a teaching feedback knowledge point cluster provided in an embodiment of the present application; Figure 3 A flow chart of a method for generating a teaching feedback knowledge point cluster provided in an embodiment of the present application; Figure 4 A schematic diagram of the layout of a recording and broadcasting device provided in an embodiment of the present application; Figure 5 A schematic diagram of the structure of a teaching quality assessment device provided in an embodiment of the present application; Figure 6 A schematic diagram of the structure of another teaching quality assessment device provided in an embodiment of the present application; Figure 7 A schematic block diagram of an example electronic device provided for an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following is a description of exemplary embodiments of the present application in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0027] The following describes the teaching quality assessment method, device, storage medium and electronic device of the embodiments of the present application with reference to the accompanying drawings.

[0028] Figure 1 A flow chart of a teaching quality assessment method provided in an embodiment of the present application.

[0029] like Figure 1 As shown, the method is applied in a server, and the method comprises the following steps: Step 101, obtain a real-time video of a history class in which a teacher teaches students, and extract the classroom text of the interactive video that triggers classroom interactive behavior in the real-time video of the history class.

[0030] The history classroom recording video refers to the video recording of the entire classroom teaching process, including the complete teaching process such as teacher teaching, student response, blackboard writing, multimedia use, etc. Classroom interactive behavior refers to the communication and interaction activities between teachers and students, or between students in the classroom, such as teachers asking questions and students answering, group discussions between students, role-playing interactions in the classroom, etc. Interactive video refers to the video clips edited from the classroom recording that contain complete interactive behaviors, including but not limited to the interaction start / end timestamps of the video clips, the triggering factors of the interaction (such as teacher questions) and results (such as student answers). Classroom text refers to structured text data extracted from interactive videos, including but not limited to speech transcription text (teacher explanation, student speech), blackboard content recognition text, and text extracted from screen sharing content.

[0031] To obtain the real-time video of the teacher's teaching to students in history class, you can equip the classroom with recording and broadcasting equipment, such as an integrated recording and broadcasting machine, multiple cameras, etc., and start the equipment to record during the teaching process. The recorded video is stored in the school's server or storage device and can be obtained by accessing the server, copying the storage medium, etc. If the teacher uses the live broadcast method to teach students on the Internet, you can also obtain the real-time video of the teacher's teaching to students in history class by obtaining the live broadcast recording video of the teacher's teaching to students.

[0032] Extracting classroom text from interactive videos that trigger classroom interactive behaviors in real-life historical classroom videos can be done by slicing the real-life historical classroom videos and dividing them into multiple small segments. Then, extract key frames from each segment, perform feature extraction on the extracted key frames, and identify whether there is classroom interactive behavior in them. This can be achieved through image recognition technology, such as detecting students' hand-raising actions and teachers' questioning actions. Once classroom interactive behaviors are identified, the corresponding video segments are located, and these segments are interactive videos. Converting the conversation content in the interactive video into text can be achieved through a speech recognition algorithm, extracting the audio part of the video and converting it into text. Extracting text information from the video, such as writing on the blackboard and text on the PPT, can be done through optical character recognition technology. Optical character recognition technology can recognize text from images and convert it into editable text format to obtain classroom text. The extracted classroom text is sorted out to remove redundant information, correct recognition errors, etc., to ensure the accuracy and completeness of the classroom text.

[0033] By analyzing students' answers to questions in interactive texts, teachers can more accurately understand students' mastery of each knowledge point, discover students' confusion and difficulties in the learning process, and provide targeted guidance and reinforcement.

[0034] Step 102, using a preset knowledge point screening algorithm, screen out knowledge points whose student participation is greater than a preset participation threshold from all knowledge points in the classroom text, and obtain a teaching feedback knowledge point cluster.

[0035] The preset knowledge point screening algorithm refers to an intelligent screening model built based on natural language processing and statistical methods. The preset knowledge point screening algorithm identifies the knowledge points in the classroom text through semantic analysis, calculates the student participation corresponding to each knowledge point, and dynamically screens the knowledge points with higher participation according to the preset participation threshold. All knowledge points in the classroom text refer to the teaching content involved in the classroom text, usually the specific concepts, theories, formulas or methods explained by the teacher in class. Knowledge points are the core component of teaching and the basic unit of student learning. Student participation is a quantitative indicator used to measure the degree of active participation and investment of students in the classroom learning process. Student participation comprehensively considers various behavioral performances of students in the classroom, such as the number of students' quick answers, the accuracy of students' answers, and the duration of conversations when students answer correctly. Among them, the number of students' quick answers refers to the number of times students actively answer through the classroom response system during the knowledge point explanation period, the accuracy of students' answers refers to the proportion of correct answers to questions about the knowledge point (number of correct answers / total number of questions), and the duration of conversations when students answer correctly refers to the duration of extended discussions with teachers after students answer correctly.

[0036] The preset participation threshold is a pre-set critical value of student participation, which is used to distinguish the importance and influence of knowledge points at the student participation level. The setting of the preset participation threshold is usually based on a large number of empirical studies and the empirical judgment of educational experts, aiming to ensure that the selected knowledge points have sufficient representativeness and teaching value, and can truly reflect the quality of classroom teaching. Through further analysis of the selected knowledge points, the correlation between different knowledge points is found. The correlation relationship includes logical sequence, mutual complementation in content, and conceptual hierarchy. According to the correlation relationship between the knowledge points obtained by analysis, the selected knowledge points are organized and integrated to form an organically connected knowledge system, that is, a teaching feedback knowledge point cluster. Data structures or knowledge graph technology can be used to represent and store the relationship between different knowledge points.

[0037] In order to better understand the knowledge graph of teaching feedback knowledge point clusters, Figure 2 As shown, Figure 2 A schematic diagram of a knowledge graph of a teaching feedback knowledge point cluster provided in an embodiment of the present application, wherein A is a main node, which can be classified by chapter, b1 and b2 are slave nodes, which can be classified by section, and c1, c2, and c3 are slave nodes of b1 and b2, which can be classified by unit results.

[0038] The teaching feedback knowledge point clusters clearly show which knowledge points students have shown high participation and interest in, and also imply which knowledge points may need further teaching. Teachers can use the teaching feedback knowledge point clusters to deeply analyze students' learning advantages and characteristics in high-participation knowledge points and apply their successful experience to the teaching of other knowledge points; for knowledge points with low participation, teachers can adjust teaching methods in a targeted manner, such as using more vivid and interesting cases, increasing interactive links, optimizing explanation methods, etc., so as to improve the overall teaching quality and promote students' all-round development.

[0039] Step 103, obtaining the lesson plan text corresponding to the history classroom recording video, and performing a teaching quality evaluation on the history classroom recording video according to the proportion of the knowledge points of the teaching feedback knowledge point cluster in the teaching text.

[0040] Lesson plan text refers to the standardized teaching plan document prepared by teachers before class, which contains structured content such as teaching objectives, course chapter division, knowledge point list, teaching key points and difficulties, classroom activity design, etc. It is usually stored in electronic documents or education platform-specific formats.

[0041] The proportion refers to the ratio between the number of knowledge points in the teaching feedback knowledge point cluster and the total number of knowledge points in the lesson plan text, which is used to measure the coverage of the teaching feedback knowledge points in the overall teaching plan. For ease of understanding, an example is provided. If there are 10 knowledge points planned in the lesson plan text, 8 of which belong to the teaching feedback knowledge point cluster, the proportion is 80%.

[0042] Corresponding evaluation standards are formulated for teaching quality evaluation, and the teaching quality levels or scoring ranges corresponding to different proportions are clarified. For example, when the knowledge point coverage reaches more than 80%, it indicates that the teaching quality is high and the teaching content in the lesson plan text can be completed well; when the coverage is less than 50%, it means that there is a large deviation in the implementation of the lesson plan text during the teaching process, and the teaching quality needs to be improved. By quantitatively analyzing the proportion of teaching feedback knowledge points in the lesson plan text, the influence of subjective factors in the teaching quality evaluation in related technologies is reduced, making the evaluation results more objective and fair, and being able to more truly reflect the teaching level and teaching effect of teachers.

[0043] The teaching quality evaluation method provided in this application can find out the knowledge points that students really pay attention to and participate in in class by using a preset knowledge point screening algorithm to screen out the knowledge points with high student participation, thereby reflecting the attractiveness of the teaching content and the acceptance of students. The evaluation is conducted based on the proportion of the teaching feedback knowledge point cluster in the teaching plan text, and the actual teaching effect is compared with the teaching plan, which can objectively measure the achievement of the teaching objectives, thereby improving the accuracy of the teaching quality evaluation.

[0044] As a refinement of step 102, when performing the method of using the preset knowledge point screening algorithm to screen out the knowledge points whose student participation is greater than the preset participation threshold from all the knowledge points in the classroom text to obtain the teaching feedback knowledge point cluster, it can be implemented in the following ways but not limited to, such as Figure 3 As shown, Figure 3 A flow chart of a method for generating a teaching feedback knowledge point cluster provided in an embodiment of the present application includes: Step 201, extracting all the knowledge points in the classroom text.

[0045] By analyzing the classroom text, remove the noise information in the classroom text, such as irrelevant punctuation, special characters, repeated content, and conversations irrelevant to teaching (such as the chat content of teachers or students). For example, remove the extra spaces, garbled characters, and some modal particles in the text to make the text more concise and standardized, which is convenient for subsequent analysis. Use the word segmentation tool to split the continuous text sequence into independent words or phrases. Mark the part of speech for each word segmentation result, such as noun, verb, adjective, adverb, etc. Through part of speech tagging, you can preliminarily determine which words are teaching knowledge points. Generally speaking, nouns are often related to knowledge points such as concepts and names of things. For example, in mathematics classroom texts, nouns such as triangles and equations are usually important teaching knowledge points; verbs involve operations, methods, etc., such as calculations and proofs. Identify specific named entities in the text. In teaching scenarios, they mainly include subject terms, names of people, places, names of organizations, etc. They can be accurately extracted through named entity recognition. Analyze the semantic relationship between each word in a sentence and determine the semantic role of each word in the sentence. Use existing subject knowledge graphs and domain dictionaries to assist in knowledge point extraction. The knowledge graph contains the relationship and attribute information between various knowledge points in the subject. By matching the words in the classroom text with the knowledge graph, it is possible to determine which are the existing teaching knowledge points and obtain their related attributes and relationship information.

[0046] Through text analysis, we can ensure that all teaching knowledge points are identified and extracted to avoid missing important teaching content.

[0047] Step 202, counting the number of students' quick answers, the accuracy of students' answers, and the duration of conversations in which students answer correctly for each of all the knowledge points in the interactive video.

[0048] Perform preliminary processing on the interactive video, including video format unification and noise removal, to improve the accuracy of subsequent analysis. Use computer vision technology and speech recognition technology to identify student responses and answering questions in the video, and mark the time when the behavior occurs, student identity and other information. Associate the marked behavior with the knowledge points in the classroom text to determine the knowledge point corresponding to each behavior. According to the marked information, for each knowledge point, count the number of times each student answers, and then sum up to get the number of answers for that knowledge point. For each knowledge point, count the number of correct answers and the total number of answers for each student, calculate the accuracy of each student's answers, and then average to get the average accuracy of the answers for that knowledge point. For each knowledge point, filter out the correct answers of students, calculate the duration of communication with teachers or classmates each time the answer is correct, and sum up to get the total correct dialogue duration for that knowledge point.

[0049] By analyzing these data, teachers can understand students' participation and mastery of different knowledge points, and thus adjust teaching strategies, optimize teaching content, and improve teaching quality in a targeted manner.

[0050] Step 203, calculating the student participation degree of each knowledge point according to the number of students' quick responses, the accuracy of the students' answers and the duration of the conversation.

[0051] The formula for student participation is: Student participation = (number of student responses × response weight + student answer accuracy × accuracy weight + conversation duration × duration weight). According to the pre-set weights, for example, the weight of the number of student responses is 0.4, the weight of the answer accuracy is 0.3, and the weight of the conversation duration is 0.3. The number of student responses, answer accuracy, and conversation duration are multiplied by the corresponding weights, and then added together to obtain the student participation value for each knowledge point.

[0052] To facilitate understanding, an example is provided. Suppose a student answers a certain knowledge point 5 times, the answer accuracy is 80%, the conversation duration is 3 minutes, and the corresponding weights are 0.4, 0.3, and 0.3, respectively. Then the student participation = (5×0.4+ 0.8×0.3 + 3×0.3) = 2 + 0.24 + 0.9 = 3.14.

[0053] By comprehensively analyzing students' participation in each knowledge point, teachers can clearly understand which knowledge points are more difficult for students and which knowledge points students have mastered better. Based on these data, teachers can adjust teaching content and methods more targetedly and improve teaching efficiency.

[0054] Step 204: Combining the knowledge points whose student participation degree is greater than the preset participation degree threshold among all the knowledge points into the teaching feedback knowledge point cluster.

[0055] To facilitate understanding, an example is provided. In the classroom text of a certain mathematics class, after calculation, the student participation in the Pythagorean theorem is 0.65, the student participation in the triangle similarity theorem is 0.7, and the student participation in the properties of congruent triangles is 0.58. Then the Pythagorean theorem and the triangle similarity theorem will be included in the teaching feedback knowledge point cluster, while the properties of congruent triangles will be excluded.

[0056] By combining student engagement data, the system helps teachers identify which knowledge points students have mastered well and avoid over-explaining these knowledge points, thus saving teaching time and energy. Teachers can invest more time and resources in knowledge points where students have low engagement, thereby optimizing teaching results.

[0057] As a refinement of step 203, when calculating the student participation of each knowledge point according to the number of students' quick answers, the accuracy of the students' answers and the duration of the conversation, the following methods may be used but are not limited to: Student engagement The calculation formula is:

[0058] in, , , are the number of times the student answered the question, the accuracy of the student's answer and the duration of the conversation in which the student answered the question correctly, , , are the first weights corresponding to the number of times the student answers the questions, the accuracy rate of the student's answers and the duration of the conversation in which the student answers the questions correctly.

[0059] By calculating the student participation method, it can more objectively and comprehensively reflect the student's learning status and participation level in the classroom. Compared with the subjective observation and questionnaire survey in related technologies, it avoids the interference of human factors, making the evaluation results more scientific and reliable. At the same time, student participation can help teachers accurately understand the students' mastery of different knowledge points, so as to adjust the teaching strategy in a targeted manner and improve the teaching quality. In addition, this method can also stimulate students' enthusiasm, prompting them to participate more actively in classroom interaction and improve learning effects.

[0060] As a refinement of step 103, when performing the teaching quality evaluation of the history classroom recording video based on the proportion of knowledge points in the teaching feedback knowledge point cluster in the teaching text, it can be implemented in but not limited to the following ways, including: calculating the proportion ratio of all knowledge points in the lesson plan text; calculating the teaching quality score of the history classroom recording video based on the proportion ratio and the average participation rate of students in all knowledge points, so as to evaluate the teaching quality of the history classroom recording video based on the teaching quality score.

[0061] The average participation rate is the average of the student participation rates of all knowledge points, reflecting the overall participation of students in each knowledge point in class. The teaching quality score is a quantitative indicator calculated based on the proportion and average participation rate, which is used to comprehensively evaluate the teaching quality.

[0062] For ease of understanding, an example is provided to count the number of knowledge points in the teaching feedback knowledge point cluster based on the history classroom video recording, assuming that there are 15. Obtain the lesson plan text corresponding to the history classroom video recording, and count the number of all knowledge points in the lesson plan text, assuming that there are 20. The proportion ratio is 15 / 20=0.75. Assume that the participation of the 15 knowledge points in the teaching feedback knowledge point cluster is 80%, 85%, 75%, 90%, 70%, 88%, 72%, 83%, 77%, 86%, 74%, 89%, 71%, 82%, and 76% respectively. Add up all the participation values ​​to get 1230%, and then divide it by 15 to get an average participation of 82%. Assume that the second weight corresponding to the proportion ratio is 0.6, and the second weight corresponding to the average participation is 0.4. Teaching quality score = 0.75×0.6+82%×0.4=0.45+0.328=0.778, that is, 77.8 points.

[0063] The teaching quality is pre-divided into at least two teaching quality levels, and each teaching quality level has a corresponding teaching quality score numerical range. For ease of understanding, an example is provided, assuming that there are three teaching quality levels, namely, need to be improved, qualified and excellent, where the numerical range corresponding to need to be improved is 0-60, the numerical range corresponding to qualified is 60-80, and the numerical range corresponding to excellent is 80-100.

[0064] As a refinement of the above embodiment, when calculating the teaching quality score of the history classroom video according to the proportion ratio and the average participation of the students in all the knowledge points, the following methods may be used but are not limited to: Teaching quality rating The calculation formula is:

[0065] in, , are the proportion ratio and the average participation of students in all knowledge points, For all the knowledge points mentioned, For the lesson plan text, , The second weights respectively correspond to the proportion ratio and the average participation degree of the students in all the knowledge points.

[0066] In the teaching process, the completeness of teaching content and the students' learning participation are both crucial. The proportion ratio ensures that teachers fully cover the knowledge points in the lesson plan, while the average participation rate focuses on whether students are truly involved in learning these knowledge points. By setting weights for these two indicators separately, their contributions to the teaching quality score can be flexibly adjusted according to teaching objectives and actual conditions, so that the evaluation results are more in line with the actual needs of teaching.

[0067] As a refinement of step 101, when executing the acquisition of the real-time video of the history class in which the teacher teaches the students, it can be implemented by but not limited to the following methods, including: using the video acquisition module and the audio acquisition module in the classroom to record the process of the teacher teaching the students to obtain the real-time video of the history class; or, using the smart blackboard in the classroom and the student interaction module that interacts with the smart blackboard to record the process of the teacher teaching the students to obtain the real-time video of the history class.

[0068] The video acquisition module refers to the camera and other equipment installed in the classroom, which is used to record the teacher's teaching process to obtain video materials of the classroom. The audio acquisition module refers to the microphone and other equipment in the classroom, which is used to collect the sound of the teacher's teaching process, including the teacher's explanation, the student's answer, etc., and cooperates with the video acquisition module to form an audible classroom record. The smart blackboard is an intelligent teaching device that integrates traditional blackboard functions with modern information technology. It has functions such as touch interaction, multimedia display, and classroom recording, which can realize the digitization and intelligence of the teaching process. The student interaction module is a device or software connected to the smart blackboard, which enables students to interact with the smart blackboard in a specific way, such as submitting answers, participating in classroom discussions, etc., to enhance the interactivity of the classroom and the participation of students.

[0069] In order to better understand the classroom recording video of teachers teaching students in the classroom equipped with recording and broadcasting equipment, Figure 4 As shown, Figure 4 A layout diagram of a recording and broadcasting device provided in an embodiment of the present application, the sound collection device is the audio collection module in the present application, the student-side interactive device is the student interaction module in the present application, the teaching content of the teacher's lectures to the students is collected through the smart blackboard, the conversation audio of the teacher's lectures to the students is collected through the sound collection device, and the classroom interactive behavior is collected through the student-side interactive device.

[0070] Recorded history classroom videos can be saved and shared as valuable teaching resources. Teachers can use them for subsequent teaching reflection, teaching research or training of new teachers. Students can also watch the videos after class to review and consolidate what they have learned, while providing reference and reference for teaching in other classes or schools.

[0071] In summary, the embodiments of the present application can achieve the following effects: This application uses a preset knowledge point screening algorithm to screen out knowledge points with high student participation, and can find out the knowledge points that students really pay attention to and participate in in class, which reflects the attractiveness of the teaching content and the degree of acceptance of students. According to the proportion of teaching feedback knowledge point clusters in the lesson plan text, the actual teaching effect is compared with the teaching plan, which can objectively measure the achievement of teaching objectives, thereby improving the accuracy of teaching quality evaluation.

[0072] Corresponding to the above teaching quality evaluation method, the present invention also provides a teaching quality evaluation device. Since the device embodiment of the present invention corresponds to the above method embodiment, details not disclosed in the device embodiment can be referred to the above method embodiment, and will not be repeated in the present invention.

[0073] Figure 5 A schematic diagram of the structure of a teaching quality evaluation device provided in an embodiment of the present application, the device can be applied to a server, such as Figure 5 As shown, including: An acquisition unit 31 is used to acquire a video of a history class in which a teacher teaches students; An extraction unit 32 is used to extract the classroom text of the interactive video that triggers the classroom interactive behavior in the real-recorded video of the history classroom; A screening unit 33 is used to screen out knowledge points whose student participation is greater than a preset participation threshold from all knowledge points in the classroom text using a preset knowledge point screening algorithm to obtain a teaching feedback knowledge point cluster; The evaluation unit 34 is used to obtain the teaching plan text corresponding to the history classroom recording video, and evaluate the teaching quality of the history classroom recording video according to the proportion of the knowledge points of the teaching feedback knowledge point cluster in the teaching text.

[0074] The teaching quality evaluation device provided by the present application can find out the knowledge points that students really pay attention to and participate in in class by using a preset knowledge point screening algorithm to screen out the knowledge points with high student participation, thereby reflecting the attractiveness of the teaching content and the acceptance of students. By evaluating the proportion of the teaching feedback knowledge point cluster in the teaching plan text and comparing the actual teaching effect with the teaching plan, it is possible to objectively measure the achievement of the teaching objectives, thereby improving the accuracy of the teaching quality evaluation.

[0075] Furthermore, in a possible implementation of the embodiment of the present application, as Figure 6 As shown, the screening unit 33 includes: An extraction module 331 is used to extract all the knowledge points in the classroom text; A statistics module 332 is used to count the number of students' answers in the interactive video, the accuracy of students' answers, and the duration of conversations in which students answer correctly for each of all the knowledge points; A first calculation module 333 is used to calculate the student participation degree of each knowledge point according to the number of students' answers, the accuracy of the students' answers and the duration of the conversation; The combining module 334 is used to combine the knowledge points whose student participation degree is greater than the preset participation degree threshold among all the knowledge points into the teaching feedback knowledge point cluster.

[0076] Furthermore, in a possible implementation of the embodiment of the present application, as Figure 6 As shown, the first calculation module 333 is also used for: Student engagement The calculation formula is:

[0077] in, , , are the number of times the student answered the question, the accuracy of the student's answer and the duration of the conversation in which the student answered the question correctly, , , are the first weights corresponding to the number of times the student answers the questions, the accuracy rate of the student's answers and the duration of the conversation in which the student answers the questions correctly.

[0078] Furthermore, in a possible implementation of the embodiment of the present application, as Figure 6 As shown, the evaluation unit 34 includes: The second calculation module 341 is used to calculate the proportion of all the knowledge points in the teaching plan text; The second calculation module 341 is also used to calculate the teaching quality score of the history classroom recording video according to the proportion ratio and the average participation rate of students in all knowledge points, so as to evaluate the teaching quality of the history classroom recording video based on the teaching quality score.

[0079] Furthermore, in a possible implementation of the embodiment of the present application, as Figure 6 As shown, the second calculation module 341 is also used for: Teaching quality rating The calculation formula is:

[0080] in, , are the proportion ratio and the average participation of students in all knowledge points, For all the knowledge points mentioned, For the lesson plan text, , The second weights respectively correspond to the proportion ratio and the average participation degree of the students in all the knowledge points.

[0081] Furthermore, in a possible implementation of the embodiment of the present application, as Figure 6 As shown, the acquisition unit 31 is also used for: Using the video acquisition module and the audio acquisition module in the classroom to record the process of the teacher teaching the students, to obtain the real-life video of the history class; Alternatively, the smart blackboard in the classroom and a student interaction module that interacts with the smart blackboard are used to record the process of the teacher teaching the students to obtain a real-life video of the history class.

[0082] It should be noted that the above explanation of the method embodiment is also applicable to the device of the embodiment of the present application, the principle is the same, and it is no longer limited in the embodiment of the present application.

[0083] According to an embodiment of the present application, the present application also provides an electronic device, a readable storage medium and a computer program product.

[0084] Figure 7 A schematic block diagram of an example electronic device 400 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0085] like Figure 7As shown, the electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 402 or a computer program loaded from a storage unit 408 to a RAM (Random Access Memory) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An I / O (Input / Output) interface 405 is also connected to the bus 404.

[0086] Multiple components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the electronic device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0087] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as a teaching quality assessment method. For example, in some embodiments, the teaching quality assessment method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the aforementioned teaching quality assessment method in any other appropriate manner (eg, by means of firmware).

[0088] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a dedicated or general-purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0089] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0090] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage device, magnetic storage device, or any suitable combination of the foregoing.

[0091] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0092] The systems and techniques described herein may be implemented in a computing system that includes a backend component (e.g., as a data server), or a computing system that includes a middleware component (e.g., an application server), or a computing system that includes a frontend component (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0093] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0094] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0095] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution disclosed in this application can be achieved, and this document is not limited here.

[0096] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A teaching quality evaluation method, characterized in that: include: Obtain a real-life video of a history class in which a teacher teaches students, and extract classroom text of an interactive video that triggers classroom interactive behavior in the real-life video of the history class; Using a preset knowledge point screening algorithm, screen out knowledge points in the classroom text whose student participation is greater than a preset participation threshold, to obtain a teaching feedback knowledge point cluster; The lesson plan text corresponding to the history classroom recording video is obtained, and the teaching quality of the history classroom recording video is evaluated according to the proportion of the knowledge points of the teaching feedback knowledge point cluster in the teaching text.

2. The teaching quality evaluation method according to claim 1, characterized in that: The method of using a preset knowledge point screening algorithm to screen out knowledge points with a student participation greater than a preset participation threshold from all knowledge points in the classroom text to obtain a teaching feedback knowledge point cluster includes: Extracting all the knowledge points in the classroom text; Count the number of students’ answers in the interactive video, the accuracy of students’ answers, and the duration of the conversation in which students answer correctly for each of all the knowledge points; Calculate the student participation of each knowledge point according to the number of students' answers, the accuracy of the students' answers and the duration of the conversation; The knowledge points whose student participation degree is greater than the preset participation degree threshold among all the knowledge points are combined into the teaching feedback knowledge point cluster.

3. The teaching quality evaluation method according to claim 2, characterized in that: Calculating the student participation of each knowledge point according to the number of students' answers, the accuracy of the students' answers and the duration of the conversation includes: Student engagement The calculation formula is: in, , , are the number of times the student answered the question, the accuracy of the student's answer and the duration of the conversation in which the student answered the question correctly, , , are the first weights corresponding to the number of times the student answers the questions, the accuracy rate of the student's answers and the duration of the conversation in which the student answers the questions correctly.

4. The teaching quality evaluation method according to claim 2, characterized in that: The teaching quality evaluation of the history classroom video recording according to the proportion of the knowledge points of the teaching feedback knowledge point cluster in the teaching text includes: Calculate the proportion of all the knowledge points in the teaching plan text; According to the proportion ratio and the average student participation of all knowledge points, the teaching quality score of the history classroom recording video is calculated, so as to evaluate the teaching quality of the history classroom recording video based on the teaching quality score.

5. The teaching quality evaluation method according to claim 4, characterized in that: The calculating of the teaching quality score of the history classroom video according to the proportion ratio and the average participation degree of the students in all the knowledge points includes: Teaching quality rating The calculation formula is: in, , are the proportion ratio and the average participation of students in all knowledge points, For all the knowledge points mentioned, For the teaching plan text, , The second weights respectively correspond to the proportion ratio and the average participation degree of the students in all the knowledge points.

6. The teaching quality evaluation method according to claim 1, characterized in that: The acquisition of the real-time video of the history class taught by the teacher to the students includes: Using the video acquisition module and the audio acquisition module in the classroom to record the process of the teacher teaching the students, to obtain the real-life video of the history class; Alternatively, the smart blackboard in the classroom and a student interaction module that interacts with the smart blackboard are used to record the process of the teacher teaching the students to obtain a real-life video of the history class.

7. A teaching quality evaluation device, characterized in that: include: An extraction unit is used to obtain a real-time video of a history class in which a teacher teaches students, and to extract classroom text of an interactive video that triggers classroom interactive behavior in the real-time video of the history class; A screening unit, configured to screen out knowledge points whose student participation is greater than a preset participation threshold from all knowledge points in the classroom text using a preset knowledge point screening algorithm, to obtain a teaching feedback knowledge point cluster; The evaluation unit is used to obtain the lesson plan text corresponding to the history classroom recording video, and evaluate the teaching quality of the history classroom recording video according to the proportion of the knowledge points of the teaching feedback knowledge point cluster in the teaching text.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the teaching quality assessment method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to enable the computer to execute the teaching quality assessment method according to any one of claims 1-6.

10. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the teaching quality assessment method according to any one of claims 1 to 6.

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