Optimizing the interactive teaching method based on artificial intelligence algorithms for the integration of Olympic spirit into the Civic and Political Education in colleges and universities
Online veröffentlicht: 24. März 2025
Eingereicht: 25. Okt. 2024
Akzeptiert: 09. Feb. 2025
DOI: https://doi.org/10.2478/amns-2025-0752
Schlüsselwörter
© 2025 Suilong Xiao et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Civic and political education in colleges and universities is an important way to cultivate students’ core values and moral qualities, as well as a necessary part of cultivating high-quality and innovative talents. With the continuous development and progress of the society, Civic and political education in colleges and universities in the new era is facing new opportunities and challenges. As the cradle of cultivating outstanding socialist builders and successors, ideological education in colleges and universities plays a crucial role in students’ ideological leadership, moral molding, value cultivation and comprehensive quality improvement [1-4]. The Olympic spirit refers to the spirit and values of the Olympic movement such as unity, friendship, respect and justice. The Olympic spirit not only symbolizes the spirit of athletes and sports fans, but also what all people should pursue. The integration of the Olympic spirit into the ideological education of colleges and universities is of great significance in improving the comprehensive quality of students [5-8].
Olympic sports occupy an important position in the history of human social civilization, which originated from the practice of human production and life, as the activities of human beings to overcome nature, transcend themselves and pursue the limits of physical fitness, which implies the goal of encouraging human beings to maintain robust body shape and healthy body as well as to strive for strength and unremitting aggressiveness through sports, and it can help students to enhance their physical fitness and form a strong will [9-12]. Realizing the deep integration of sports and education, the educational value of role models can be brought into full play. Therefore, colleges and universities can incorporate Olympic content in carrying out Civic and political education in order to realize the comprehensive and harmonious development of students [13-15]. The integration of the Olympic spirit into the Civic and Political Education is not only to cultivate the comprehensive ability of the students, but also has important significance for the students to establish a correct outlook on life and develop good values [16-18].
This paper discusses the recognition of ideological and political education in colleges and universities that fully integrates the value implications of the Olympic spirit. Taking the teaching of the course “Olympic Spirit-Ideological and Political Education” as an example, a three-part practical teaching model based on machine learning is proposed to further optimize the interactive experience of the whole teaching by introducing an algorithm of online educational prediction model. A modified loss function is used in the first part of the model to simulate the prediction task. The CA method in SENet was used in the second part to enhance the ability of the LightGBM model to predict student performance. Finally, the LGBCAN model integrates the three-part practical instruction. The model is applied to practice teaching, and the application of the model is analyzed from three perspectives: performance in the Civics course, learning attitude and satisfaction, and interactive behavior.
The Olympic Spirit is one of the most valuable intangible assets left to the world by the Olympic Movement (also known as the Olympic Games). The Olympic spirit is the spirit of mutual understanding, friendship, solidarity, and fair competition. The Olympic Games have now become a symbol of peace and friendship. One of the important reasons why the Olympic Spirit shines through the ages is that it has been gradually formed throughout its development, with Olympism at its core. One of the important reasons why the Olympic spirit has shone through the ages is that, in the course of its development, it has gradually formed a system of thought and culture with Olympism at its core, combining the all-round development of human beings with a balanced combination of physical fitness, spirituality and morality, and elevating it to a positive life philosophy. Therefore, the Olympic spirit is of great importance to the ideological and political education of college students. Colleges and universities, as the cradle of cultivating socialist builders and successors with all-round development of morality, intelligence, physicality and aesthetics, “what kind of people to cultivate, how to cultivate people” is a fundamental problem that must be solved, and the report of the 18th National Congress puts forward that “we should take the cultivation of moral integrity as the fundamental task of education”. “Establishing moral character and educating people” is a strong and powerful answer to this question concerning the future destiny of the Party and the country, and points out the direction for strengthening and improving the work of ideological and political education of college students. However, in the period of social transition, at a time of diversified values, when various ideologies and cultures are agitating each other, the ideological and moral education of college students is facing the challenge of insisting on using the socialist core value system to lead the social trend of thought, but also respecting differences, tolerating diversity, and fully exploring and utilizing the essence of different cultures. Therefore, to provide a good ideological and political education for college students, the value of the Olympic spirit is self-evident.
The quadrennial International Olympic Games are not just a platform for athletes to compete, but also a platform for the Olympic spirit to be showcased. The cultural and spiritual connotations given by the Olympic spirit are not only reflected on the athletic field, but also in our daily life. For example, the Olympic spirit advocates the spirit of challenging oneself, the courage to overcome difficulties, the will to pursue excellence, the idea of equality and win-win situation, honesty and trustworthiness, etc., all of which are necessary for contemporary college students. The core of ideological and political education in colleges and universities is similar to the ideas advocated by the Olympic Spirit and can be promoted together, which is also generally recognized by college students.
The results of the survey are shown in Table 1, and it can be found that college students generally have a high degree of recognition of the Olympic culture and spiritual connotations, especially the holding of the 29th Olympic Games in Beijing in 2008, which is a good popularization of the knowledge and education of the Olympic spirit to the nationals, especially to the young students, and 76.67% of the college students said that the Olympic spirit has a great deal of when it comes to the improvement of their ideological and political literacy help, and only 8.33% of the investigators said it did not help. The essence of Olympic spirit is the spirit of mutual understanding, friendship, solidarity, and fair competition, which usually includes the principles of participation, competition, justice, friendship, and struggle. These spirits are precisely what contemporary college students are lacking and should have. Therefore, strengthening the education of Olympic spirit in colleges and universities will have a positive influence and good educational effect on the ideological and political quality of contemporary college students, and together provide another effective way for the ideological and political education of college students.
The relationship and recognition of the Olympic spirit and the education
| Big relationship | Connect with | Not close | No relation | Total | |
|---|---|---|---|---|---|
| Number | 318 | 420 | 119 | 43 | 900 |
| Percentage | 35.33% | 46.67% | 13.22% | 4.78% | 100% |
| Very helpful | Be helpful | General action | Unaided | Total | |
| Number | 213 | 477 | 135 | 75 | 900 |
| Percentage | 23.67% | 53.00% | 15.00% | 8.33% | 100% |
This paper takes the teaching of “Olympic Spirit - Ideological and Political Education” course as an example, adds more practical links, and combines the practical links with the course content, really utilizes the advantages of applying computers in on-line teaching, and adds the hands-on practical links to complete the closed-loop of teaching practice. Increase the student operation interaction buried point in the weak interaction mode of the traditional catechism form, the system is difficult to obtain the student learning reality. In this paper, we take advantage of the use of electronic devices as terminals in online education to increase more teaching interactions, such as adding clicking operations, adding exercises to ask questions, or using the camera to identify the target of the students, so as to increase the acquisition of data on the state of the students, so as to analyze the effectiveness of student learning in various aspects and the reasons for failure. The long and difficult video will be disassembled into a combination of graphic, video, and voice, with the interactive operation of students in the teaching system to explain gradually, so that students do not miss the knowledge points as much as possible. And in the subsequent practice process, it can also quickly review the knowledge points and complete the closed loop of practice teaching. Further optimize the whole teaching experience by introducing algorithms: predicting students’ mastery, learning status, students’ participation, frequency and depth of interaction, etc., to ensure the teaching effect. Unilateral acceptance of knowledge without communication and feedback will again affect the sense of social presence.
On this basis, this paper will break up the lectures in the traditional catechism system into teaching, practicing and evaluation respectively, so as to build a more flexible three-segment interactive Civics teaching mode. The interactive flow chart of the teaching link for the three-segment interactive Civics teaching mode is shown in Figure 1.
The teaching link interaction process
The three-stage online practical teaching strategy, the strategy needs to accurately capture the student’s learning status in order to turn the system to recommend the subsequent suitable courses and realize the online and intelligent practical teaching. In order to allow students to better use the system for rapid learning, this paper develops a labeled distribution-based predictive model for online education (LGBCAN), the realization of this structure will be divided into two, divided into two steps of boosting tree and convolutional neural network. For the step of boosting tree, the LightGBM model is chosen to be used, and for the step of convolutional neural network, the label approximation step is added to convert the values of the prediction results from the proposed method into prediction categories by thresholding.
In this paper, a modified loss function is used in LightGBM. In the mathematical task of simulating predictions of serial relationships in function time, the loss variable function time is a variable function time relationship that is widely used later to respond to the large degree of difference in the interaction between the simulated and real prediction results, and is able to evaluate the degree of model excellence.The loss function of LightGBM is usually given by Eq:
The concept of class weights is introduced into the loss function of the LightGBM model, so that the weight of the majority sample class in the loss function is lower than that of the minority sample class. At the same time, we get sparse nodes by introducing
In this paper, the CA method in SENet is used to enhance the training results of LightGBM. The better model results in the prediction results will be adaptively given higher weights to improve the model’s prediction of student performance, while the results that are not related to the outcome will be given lower weights.The Attention part firstly maps all the information in the feature matrix
The online education model in this paper based on the approximate distribution of labels first uses regression analysis to compute the predicted output
Labeling Distribution Approximation Methods:
where
For a mature and reliable model, it is not enough to rely on accuracy as a criterion for model evaluation. The existence of data imbalance and other factors can lead to a higher probability that a class with less data is misclassified by the model as a class with higher data when the model relies on the accuracy rate as a criterion. Since this experiment is a multi-categorization task, this paper adopts the ACC and F1_score metrics. The formulas for the metrics are shown below:
In the previous section, the students’ online learning behavior dataset was applied to the machine learning model and the comparison of the model performance was conducted, and the results are shown in Table 2. Therefore, the 720 data points of learning behaviors obtained in the Civics classroom were used as inputs to the machine learning model to predict learning performance. It was finally concluded that the accuracy of the model reached 0.945, and the recall and F1 values were 0.711 and 0.852, respectively, and the model performance metrics were obtained with good results. Therefore, it is feasible to use the random forest model to analyze the classroom learning behavior data of secondary school students and predict whether students can pass or not.
Model performance indicator
| Accuracy | 0.945 |
| Recall | 0.711 |
| F1-score | 0.852 |
In order to be able to have a detailed and comprehensive understanding of the students’ deep interaction using the three-stage interactive in the teaching of Civics and Politics incorporating the Olympic spirit, the second-year undergraduates of two classes of Educational Technology in the class of 2023 at H Normal University were selected to constitute the experimental group and the control group respectively in this study. The experimental data collection of this study is mainly carried out in the following aspects, the first is to analyze the changes of learning results through student performance, the second is the feedback of learning attitude and satisfaction, and the third is the analysis of interactive behavior, which are three aspects to evaluate this study is the effectiveness of interactive teaching mode. This course is based on students’ design works as the final grade, so we evaluate the change of students’ grades through the analysis of works, analyze the learning experience through the questionnaire of the application of the Olympic spirit of thinking and politics teaching in the three-stage interaction, the feedback questionnaire of the learning process after the class, and the learning attitude and satisfaction of students, and combine with classroom observation, video analysis, and teacher-student interview to understand the interactive behaviors and interactive effects, and to understand the interactive effects through the learning participation, interaction frequency, and interaction depth to analyze the interactive behavior. In addition, this study conducts classroom observation without interfering with teachers and students, observes the implementation of each stage of the course in real time, as well as the learning status and learning progress of students, and this study refers to the research on the application of the teaching model by a number of experts in the field, evaluating the three-stage interactive Civic and Political Science teaching model from three aspects.
Since the model constructed in this study mainly wants to cultivate students’ ability of active meaning construction, active reflection, and thinking expansion, this part mainly assesses the cultivation of students’ higher-order thinking ability, the depth of the level of thinking expansion after learning, and whether it achieves effective learning, so before the experiment, by communicating with the subject teachers, the pre and post-test papers for evaluating the training of students’ thinking ability were jointly developed. The changes in students’ performance before and after participating in this teaching activity can directly reflect the effectiveness of the three-stage interactive thinking teaching model of this study. By comparing the changes in students’ grades before and after the experimental group (applying the model) and the control group (previous teaching model), the effectiveness of the model in actual teaching can be evaluated. Before the implementation of SPSS22.0 on the two groups of achievement test, the results are shown in Table 3, sig value of 0.127, (much greater than 0.05) this data shows that before the experiment, the two groups of students initial ability level is comparable, there is no significant difference in performance, can be ruled out due to the starting level of the students are different resulting in the results of the error, to ensure that the experimental scientificity and effectiveness.
Test group and control group
| N | Mean | Standard deviation | Minimum value | Maximum value | Mean standard error | Sig. | |
|---|---|---|---|---|---|---|---|
| Experimental group | 50 | 65.87 | 3.745 | 60 | 75 | 0.552 | 0.127 |
| Control group | 50 | 66.79 | 3.842 | 60 | 75 | 0.549 |
After that, the experimental group was studied, and after a five-week experiment, the paired-sample t-test was conducted for the two classes, and the experimental and control groups were analyzed in comparison with the pre- and post-tests, and the results of the analysis were shown in Table 4 respectively. As can be seen from the analysis of the paired samples t-test, the Sig value of T is 0.001, and the difference between the pre- and post-tests of the students’ performance in the experimental group (the interactive teaching mode constructed in this study) and the control group (the previous teaching mode) is significant, and the performance is improved in all of them. It shows that both kinds of teaching are effective.
The experimental group and the control group were measured
| Experimental group | N | Mean | Standard deviation | Minimum value | Maximum value | Mean standard error | Sig. |
|---|---|---|---|---|---|---|---|
| Pretest | 50 | 65.87 | 4.028 | 60 | 75 | 0.552 | 0.001 |
| Posttest | 50 | 84.39 | 7.759 | 60 | 75 | 1.124 | |
| Control group | N | Mean | Standard deviation | Minimum value | Maximum value | Mean standard error | Sig. |
| Pretest | 50 | 66.79 | 3.452 | 60 | 75 | 0.549 | 0.001 |
| Posttest | 50 | 78.95 | 5.249 | 60 | 75 | 0.725 |
The results of the independent samples test posttest for the two groups are shown in Table 5. The posttest Sig. (two-sided) are both much less than 0.05, indicating that the difference between the two groups is significant, and the experimental group’s performance is significantly better than that of the control group. In summary, the teaching model proposed in this study can improve teaching effectiveness and student performance in civics.
Comparison analysis of the results of the experimental group
| N | Mean | Standard deviation | Minimum value | Maximum value | Mean standard error | Sig. | |
|---|---|---|---|---|---|---|---|
| Experimental group | 50 | 84.39 | 7.759 | 60 | 75 | 1.124 | 0.001 |
| Control group | 50 | 78.95 | 5.249 | 60 | 75 | 0.725 |
In order to investigate the application of the model, the end of the course through the questionnaire star push link and QR code, online collection of data, from the learning process, the application of the model and influencing factors, learning attitude and satisfaction of the three dimensions of the experimental group of 50 students questionnaire survey, the questionnaire was tested for reliability and validity of the questionnaire, and its alpha coefficient of 0.842>0.8, the questionnaire reliability is good. A total of 50 questionnaires were sent out and 50 were recovered.
The questionnaire was measured by Likert 5-level scale, and the questions were all attitudinal tendencies, which were statistically analyzed by SPSS 22.0, and the score levels were sequentially reduced from the highest 5 to 1. The higher the score of the questionnaire, the higher the satisfaction, and the better the effect. The statistical data are shown in Table 6. Considering all the factors, the average score of each item is above 3.98, which can be seen that the vast majority of students are satisfied with the overall teaching quality of the application of the model, which can be seen to help improve learning initiative and motivation.
Satisfaction feedback
| Topic | Very agree | Consent | Comparative consent | Different meaning | Very different | Mean |
|---|---|---|---|---|---|---|
| This pattern is more interesting and attractive | 20 |
17 |
10 |
3 |
0 |
4.08 |
| Can help me find new problems | 20 |
18 |
10 |
2 |
0 |
4.12 |
| Change the way you think about it | 19 |
13 |
16 |
2 |
0 |
3.98 |
| Like this learning style | 20 |
16 |
11 |
3 |
0 |
4.06 |
| Accept this kind of school approach | 20 |
15 |
11 |
3 |
0 |
3.98 |
| I would recommend this to other students | 21 |
15 |
12 |
2 |
0 |
4.1 |
Regarding the enhancement of students’ abilities by applying the interactive teaching model proposed in this study, the findings are shown in Table 7. Nearly 80% of the students believe that the model has a uniformly positive and positive effect on the enhancement of knowledge acquisition, analyzing and problem solving, increased interest in learning, interactive communication, independent inquiry, and dialectical thinking skills, but it is worth noting that the students generally believe that they have had their doubts answered, have learned more, have facilitated their thinking about the relevant issues, and have stimulated the motivation to participate in the classroom under the model.
Improve the ability of interactive teaching mode
| Topic | Very agree | Consent | Comparative consent | Different meaning | Very different | Mean |
|---|---|---|---|---|---|---|
| Knowledge acquisition and mastery | 22 |
20 |
6 |
1 |
1 |
4.22 |
| Analyze the problem and improve the problem | 23 |
19 |
6 |
2 |
0 |
4.68 |
| Improve your interest in learning | 20 |
21 |
8 |
1 |
0 |
4.2 |
| Improved cooperation and communication skills | 23 |
20 |
5 |
2 |
0 |
4.32 |
| Ability to learn autonomously | 22 |
21 |
4 |
3 |
0 |
4.24 |
| The dialectical thinking ability improves | 23 |
15 |
11 |
1 |
0 |
4.2 |
With the continuous and deeper integration of information technology and the classroom, there are 18 codes that can reflect the content of students’ behavior in the Civics classroom that incorporates the Olympic spirit as well as the content that can reflect the content of information technology and teacher-student interactions, of which 1-8 is the teacher’s language, which includes both indirect and direct influences, and the indirect influences include: accepting the feelings, praising or encouraging, accepting or using the students’ assertions, asking open questions, and asking closed questions, which are represented by codes 1-5, respectively, and direct influence includes: lecturing, giving guidance or instructions, criticizing, or asserting authoritativeness, which are represented by codes 6-8, respectively, and 9-12 are student language, which are, in order, students’ passive speaking (e.g., answering teacher questions), students’ active dialogue, active questioning, and group discussion.13-15 are silence, which are, respectively, silence or confusion , thinking about problems, and doing exercises.16-18 are technology, in order of teacher manipulation of technology, student manipulation of technology, and technology acting on students.
Two coders performed coding operations in 3-second increments on the 10 selected Civics teaching factual videos, and both coded data were analyzed for reliability, and the reliability coefficient was 0.820, which was considered valid. The clip presentation of a lesson example is shown in Table 8.
Case fragment rendering
| Numbering | Time stop | Interaction content | Interaction type | Interactive behavior |
|---|---|---|---|---|
| 1 | 00:00-00:12 | The bell rang and the teacher called to class | Teacher-student interaction | Organizational management |
| 2 | 00:12-02:47 | The teacher reviews the old knowledge | Teacher and student interaction - teacher control technology | guiding |
| 3 | 02:47-04:06 | Summarize the knowledge points in the last class | Teacher-student interaction | Guidance summary |
| 4 | 04:06-04:58 | Ask questions and be new | Teacher-student interaction | question |
| 5 | 04:58-09:56 | Team communication, try to solve problems | Student interaction student control technology | Interactive interaction |
| 6 | 09:56-12:37 | Panel display | student control technology | Request and response |
| 7 | 12:37-13:12 | Student evaluation | Student interaction | Evaluation and feedback |
After coding the lesson examples, each lesson example can generate a coding table and a migration matrix. The migration matrix is shown in Figure 2. A machine learning model is used to analyze the classroom interaction behaviors that affect students’ academic performance. The red diagonal line refers to the steady state grid, which means that the behaviors that fall on this red line are relatively stable and occurring over a long period of time, including behaviors such as 7 Giving directions or instructions (20), 9 Students talking passively (answering teacher’s questions) (26), 10 Students initiating conversations (133), 12 Discussing in small groups (48), and 18 Technology acting on students (21), and marking the part of the columns 1-3, 1-3 behaviors Positive grid, 7-8 columns 8-9 rows area is defective grid, the rate of positive grid is 3.91%, the rate of defective grid is 1.95%, the proportion of falling in the positive grid is significantly higher than the proportion of falling in the defective grid, which can be inferred that the teacher-student emotional climate in the class is more harmonious, in addition, we can get the proportion of the interactive behaviors of the classroom through the migration matrix. In the following, we analyze interactive behaviors based on student participation, frequency of interaction, and depth of interaction.
Flanders migration matrix
By coding the 10 teaching videos, the migration matrix analysis of the 10 Civics classroom videos incorporating the Olympic spirit can be obtained as a statistical table of the average rate of video classroom teaching interaction behaviors. The results are shown in Figure 3. Variables 1~13: Teacher language rate, student language rate, silence rate, silence or confusion rate, rate of students thinking about questions in silence, rate of doing exercises in silence, teacher questioning rate, rate of asking open-ended questions, rate of asking closed-ended questions, rate of technology use, teacher manipulation of technology, rate of technology acting on students, and rate of group discussion.
The average ratio of interactive behavior in video classroom teaching
Firstly, the proportion of students’ language is 50.2% higher than the proportion of teachers’ language is 34.2%, which can be inferred that the students take the main position in these classrooms, and the proportion of silence is 4%, and among them the proportion of students thinking about the problem is 1.32%, the proportion of students doing exercises is 2.32%, and the proportion of really ineffective verbal behaviors is 0.41%, and we can see that the ineffective verbal behaviors are fewer in the classroom in the proportion of silence. In this silent ratio, we can see that the ineffective language behavior in the classroom is decreasing, and the overall efficiency of the classroom is still relatively high. Secondly, the ratio of the use of technology is 12.1%, in which the ratio of the teacher’s manipulation of the technology is 5.14%, the ratio of the technology’s effect on the students is 3.13%, and the ratio of the overall students’ participation in the classroom behavior reaches 66.27%, which can be seen that students’ participation in the classroom of Civic Politics Teaching based on the three-paragraph interactive teaching is high.
The interaction frequency of teacher-student interaction behavior, student-student interaction behavior, and teacher-student technology use can be similarly obtained through the migration matrix, and the statistics of classroom interaction behavior are shown in Table 9. Classroom interactive behaviors account for 78.73% of the complete classroom, and interactive behaviors constitute the main classroom behaviors. The highest percentage of interactive behaviors in the Civics classroom under the three-stage interactive Civics teaching mode is student-student interaction, accounting for 40.7%, followed by teacher-student interaction, accounting for 25.86%.
The average ratio of classroom interaction behavior is statistically
| Interactive behavior type | Behavior coding | Behavioral average ratio | Total |
|---|---|---|---|
| Teacher-student interaction | Accept affection(1) | 1.54% | 25.86% |
| Praise(2) | 2.72% | ||
| To accept or use the student’s claim(3) | 6.12% | ||
| Open question(4) | 2.44% | ||
| Issue closure(5) | 0.53% | ||
| Students are passive(9) | 12.51% | ||
| Student interaction | Do exercises(15) | 2.53% | 40.7% |
| Student active dialogue(10) | 27.22% | ||
| Active question(11) | 1.35% | ||
| Group discussion(12) | 9.6% | ||
| Technical application | Teacher control technology(16) | 5.14% | 12.17% |
| Student manipulation(17) | 3.16% | ||
| Technical student(18) | 3.87% |
The depth of interaction is shown in Figure 4, A~H: asking open questions (behavior coded 4), asking closed questions (behavior coded 5), students’ passive talking (behavior coded 9), students’ active dialogue (behavior coded 10), active questioning (behavior coded 11), group discussion (behavior coded 12), teachers’ manipulation of technology (behavior coded 16), and students’ manipulation of technology (behavior coded 17). From the comparison of the average ratio of behaviors coded 4 and 5, it can be seen that the ratio of teachers asking open questions 2.52% is much higher than the ratio of asking closed questions 0.50%, which indicates that during the process of teacher-student interactions, the teachers focus on the cultivation of students’ analytical and problem-solving abilities, rather than simple intellectual memorization. As can be seen from the comparison of the average rate of coding 9 and 11 behaviors, the ratio of students’ active questioning 1.34% is lower than the ratio of students’ passive speaking 12.42%, indicating that students’ problem consciousness and questioning ability have not been fully stimulated, and the goal of students taking charge of the classroom on their own initiative has not been well achieved, and it needs to be continued to be explored and improved at a later stage. As can be seen from codes 10 and 12, the proportion of students taking the initiative in conversation reaches 27.2%, and the proportion of discussion with peers reaches 9.3%, indicating that students’ awareness of active interaction is still relatively strong.
The average rate of interaction between classes
From codes 16 and 17 human-computer interaction combined with actual classroom observation, it can be seen that teachers use information technology in the classroom to support teaching and learning activities in a large number of ways, especially with the help of some persuasive charts, so that students can clarify their own knowledge blind zones through independent analysis, and even summarize the conclusions and take the initiative to question, which on the one hand, fully explains that teachers pay attention to the cultivation of higher-order thinking skills of students based on analysis and evaluation.
In order to realize online and intelligent Civics teaching and optimize the interactive experience. This paper proposes an online education prediction model based on label distribution, and introduces an improved three-stage teaching mode based on this model. The teaching mode is applied to the practical teaching of Civics, and the results show that the experimental group’s performance is significantly better than that of the control group, therefore, the teaching mode in this paper can improve students’ performance in Civics and improve the teaching effect. In terms of students’ attitude and satisfaction, the average scores of all dimensions are above 3.98. It can be seen that most students are more satisfied with the three-stage teaching mode, which can improve the initiative and enthusiasm of high-achieving students. Through the analysis of students’ interactive behavior, it can be seen that students’ participation in the Civics classroom using this mode is high, and the frequency of interaction is improved, with a greater depth of interaction.