CN-121982947-A - Interactive teaching method and system based on teaching video

CN121982947ACN 121982947 ACN121982947 ACN 121982947ACN-121982947-A

Abstract

The invention discloses an interactive teaching method and system based on teaching videos, and relates to the technical field of information, comprising the following steps of 1, collecting surface behavior data and corresponding knowledge assessment data in the process of watching the teaching videos by students at least 3 times recently; the method comprises the steps of (1) analyzing collected behavior data and knowledge assessment data through a machine learning algorithm to obtain a concentration state distribution diagram of students in each video class, and judging knowledge absorption capacity of the students by combining the corresponding knowledge assessment data, wherein (3) carrying out targeted optimization processing on teaching video content in a video library according to the knowledge absorption capacity of the students, inserting an interaction task set adapting to the students into corresponding time nodes in the teaching video, and (4) pushing the optimized teaching video to a student terminal, receiving task completion data of the students in real time, and continuing to optimize interaction tasks according to the task completion data to complete teaching of the video.

Inventors

LIN HUI
FANG HAO
ZHENG XIAOJIN
LIANG YAN
LI ZHENNAN
CAI WENJIE

Assignees

杭州博览新智教育科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260114

Claims (10)

1. An interactive teaching method based on teaching videos is characterized by comprising the following steps: Step 1, collecting surface behavior data and corresponding knowledge assessment data in the process of watching teaching videos by students for a plurality of times; Step 2, analyzing the collected behavior data and knowledge assessment data through a machine algorithm to obtain a concentration state distribution diagram of the students in each video class, and judging the knowledge absorbing capacity of the students by combining the corresponding knowledge assessment data; Step 3, optimizing the teaching video content in the video library according to the knowledge absorbing capacity of the student, and inserting an interaction task set adapting to the student into a corresponding time node in the teaching video; And 4, pushing the teaching video which is subjected to optimization processing to a student terminal, teaching the student in a dialogue or interactive mode, and repeating the steps 1-3 by combining the completion data of the interactive task, so as to continuously optimize the teaching video content.
2. The interactive teaching method based on teaching videos according to claim 1, wherein in the step 1, the surface behavior data comprises a fast forward ratio, a line-of-sight concentration ratio and an interactive participation ratio, and the knowledge assessment data comprises an assessment accuracy.
3. The interactive teaching video-based teaching method according to claim 2, wherein step 2 comprises the steps of: Defining computable quantization indexes by collected surface behavior data, integrating each quantized quantization index into a concentration state feature vector, and carrying out standardization processing on the concentration state feature vector by adopting a Min-Max normalization algorithm; Firstly screening samples with clear high concentration and clear low concentration based on a preset quantization index threshold combination, inputting the rest samples into a random forest model, obtaining the probability of each sample being the high concentration by using a random forest algorithm, and if the output probability value is larger than a set threshold X, obtaining the sample to be the high concentration, otherwise obtaining the sample to be the low concentration; Associating the video time period determined to be low concentration with knowledge evaluation data of the corresponding knowledge points, and correcting the concentration state determination result according to the evaluation result; based on the corrected concentration state judgment result, the concentration state of the student in each period of the teaching video, the corresponding knowledge point difficulty coefficient and the mastering condition are output, and the strength of the knowledge absorbing capacity of the student is obtained.
4. The interactive teaching video-based teaching method according to claim 3, wherein, The method comprises the steps of locating the video time period with low concentration in a preliminary concentration state judgment result, extracting a teaching knowledge point corresponding to the time period, and inquiring the difficulty coefficient of the knowledge point and the evaluation accuracy of students on the knowledge point.
5. The interactive teaching method based on teaching video according to claim 3, wherein the step of correcting the focus state judgment result according to the evaluation result comprises the steps of maintaining low focus judgment and marking as effective low focus if the evaluation accuracy is greater than or equal to a threshold value M, maintaining low focus judgment and marking as ineffective low focus if the evaluation accuracy is less than a threshold value N, and further judging whether fast forward is only performed on basic knowledge in the data of fast forward ratio if the evaluation accuracy is N-M, and correcting low focus as medium focus if the evaluation accuracy is greater than or equal to a threshold value M.
6. The interactive teaching method based on teaching video according to claim 3, wherein the concentration state distribution is presented in a time axis form, and comprises concentration states, corresponding knowledge point difficulty coefficients and grasping conditions of each period, if the student shows that learning is not concentrated and the evaluation result is grasped, the student belongs to a student with strong knowledge absorbing ability, and if the student shows that learning is concentrated and the evaluation result is not grasped, the student belongs to a student with weak knowledge absorbing ability.
7. The interactive teaching method based on teaching video according to claim 1, wherein in step 3, the step of optimizing the teaching video content in the video library is: content analysis is carried out on the teaching video, the difficulty coefficients of all knowledge points in the teaching video are identified, and interactive marks are inserted into the teaching video: if the student belongs to a student with strong knowledge absorbing capability, the interactive task of the knowledge point with large difficulty coefficient is set at the end of the knowledge point, the interactive task of the knowledge point with small difficulty coefficient is set in the interval of the knowledge point, and if the student belongs to a student with weak knowledge absorbing capability, the interactive task of the knowledge point with large difficulty coefficient is set in the interval of the knowledge point, and the interactive task of the knowledge point with small difficulty coefficient is set at the end of the knowledge point.
8. The interactive teaching method based on teaching videos according to claim 1, wherein the interactive task set comprises a depth expansion type interactive task aiming at knowledge points corresponding to a low concentration period and a precision enhancement type interactive task aiming at knowledge points to be consolidated, which are associated with the low concentration period, wherein the depth expansion type interactive task comprises knowledge point migration application problems and cross-section association analysis problems, and the precision enhancement type interactive task comprises confusable point resolution problems and step resolution real operation problems.
9. The interactive teaching method based on teaching video according to claim 1, wherein during the teaching process, the system collects surface behavior data of the students in real time, and if the students have fast-forward video, have line of sight deviating from a screen and skip interactive tasks, the system judges whether to push the online interactive tasks according to video content.
10. An interactive teaching system based on teaching video, comprising: The system comprises a data acquisition module, a video playing terminal, a data acquisition module, a multi-terminal data fusion support module and a data processing module, wherein the data acquisition module is used for acquiring surface behavior data and corresponding knowledge evaluation data in the process of watching teaching videos by students, the data acquisition module is in butt joint with the video playing terminal to capture a playing operation log, associates synchronous answer results and wrong question information of an evaluation system and supports multi-terminal data fusion; The learning characteristic analysis module is used for analyzing the collected behavior data and knowledge assessment data through a machine learning algorithm to obtain a concentration state distribution diagram of each student in a video class, and judging the knowledge absorption capacity of the student by combining the corresponding knowledge assessment data; The teaching video optimizing module is used for optimizing the teaching video content in the video library according to the knowledge absorbing capacity of the students, and inserting an interaction task set adapting to the students into corresponding time nodes in the teaching video; And the teaching and feedback module is used for pushing the optimized teaching video to the student terminal, teaching the students in a dialogue or interactive mode, and continuously optimizing the teaching video content by combining the completion data of the interactive task.

Description

Interactive teaching method and system based on teaching video Technical Field The invention relates to the technical field of information, in particular to an interactive teaching method and system based on a teaching video. Background Along with the rapid development of information technology, the teaching video becomes a core carrier for knowledge transfer, provides precious learning resources for a large number of students, and is also extremely necessary to provide an effective teaching method in order to facilitate the students to obtain corresponding knowledge from the teaching video and improve the learning effect of the students. However, the teaching method in the prior art has single interaction form and lacks pertinence, and cannot adapt to the knowledge base and learning rhythm of different users, namely, a part of students can obtain good results in the detection along with the hall although displaying an inattentive state when watching teaching videos by virtue of strong knowledge learning ability or basic storage, and if the same interaction mechanism and interaction task are adopted for all students with different levels, the part of students can be tired of the interaction task, so that not only is the teaching effect influenced, but also the learning experience of the students is reduced. Disclosure of Invention The invention provides an interactive teaching method based on a teaching video, which aims at teaching students which show a state of inattention but can obtain good learning results when watching the teaching video partially. The invention provides a teaching video-based interactive teaching method, which comprises the following steps: Step 1, collecting surface behavior data and corresponding knowledge assessment data in the process of watching teaching videos by students for a plurality of times; Step 2, analyzing the collected behavior data and knowledge assessment data through a machine algorithm to obtain a concentration state distribution diagram of the students in each video class, and judging the knowledge absorbing capacity of the students by combining the corresponding knowledge assessment data; Step 3, optimizing the teaching video content in the video library according to the knowledge absorbing capacity of the student, and inserting an interaction task set adapting to the student into a corresponding time node in the teaching video; And 4, pushing the teaching video which is subjected to optimization processing to a student terminal, teaching the student in a dialogue or interactive mode, and repeating the steps 1-3 by combining the completion data of the interactive task, so as to continuously optimize the teaching video content. In the preferred scheme of the invention, in the step 1, the surface behavior data comprise a fast forward ratio, a sight line concentration ratio and an interaction participation ratio, and the knowledge evaluation data comprise an evaluation accuracy. As a preferred embodiment of the present invention, step 2 includes the steps of: Defining computable quantization indexes by collected surface behavior data, integrating each quantized quantization index into a concentration state feature vector, and carrying out standardization processing on the concentration state feature vector by adopting a Min-Max normalization algorithm; Firstly screening samples with clear high concentration and clear low concentration based on a preset quantization index threshold combination, inputting the rest samples into a random forest model, obtaining the probability of each sample being the high concentration by using a random forest algorithm, and if the output probability value is larger than a set threshold X, obtaining the sample to be the high concentration, otherwise obtaining the sample to be the low concentration; Associating the video time period determined to be low concentration with knowledge evaluation data of the corresponding knowledge points, and correcting the concentration state determination result according to the evaluation result; based on the corrected concentration state judgment result, the concentration state of the student in each period of the teaching video, the corresponding knowledge point difficulty coefficient and the mastering condition are output, and the strength of the knowledge absorbing capacity of the student is obtained. The method comprises the following steps of locating the video time period with low concentration in a preliminary concentration state judgment result, extracting a teaching knowledge point corresponding to the time period, and inquiring a difficulty coefficient of the knowledge point and an evaluation accuracy of students on the knowledge point. The method comprises the steps of maintaining low concentration judgment and marking as effective low concentration if the evaluation accuracy is greater than or equal to a threshold M, maintaining low concentration judgment and marking as ineffective low con