A Strategic Study of Internet Technology in Promoting the Integration of Physical Education and Ideological and Political Education

Traditional regression analyses are usually used to study the effect of a single variable (or the interaction of two variables) on an outcome after the exclusion of a control variable set by other factors, and it is usually assumed that “if X → Y, then ~X → ~Y”. However, the occurrence of a particular outcome is often the result of the joint action of multiple factors, and the study of the “net effect” of a single factor often fails to meet the need to explore the influencing factors. The QCA methodology uses set theory and Boolean arithmetic to bridge the gap between qualitative and quantitative methods. Set theory refers to treating the research object as a grouping of different combinations of conditional variables, replacing independent variables with conditional groupings, and replacing net effect with grouping ideas to investigate multiple concurrent causal problems. The main algebraic expressions in Boolean algebra are as follows: [1] means that the variable is “large, present, and high”, [0] means that the variable is “small, absent, and low”, and blank means that the presence (1) or absence (0) of the variable does not affect the result. The main operators used in Boolean algebra include [*]: for logical “and”, [+]: for logical “or”, and [~]: for logical “not”. The link between the condition and the result is represented by [→], which expresses a causal connection. In addition, QCA considers that the variables and the levels of the variables contained in the groupings leading to “Y” and “~Y” may not be the same (causal asymmetry), and QCA is able to capture relationships between variables, such as substitutability, vacancies, etc., as well as distinguishing between core and edge conditions.

According to the different ways of assigning values, QCA is divided into clear set qualitative comparative analysis (csQCA), fuzzy set qualitative comparative analysis (fsQCA), and multi-valued set qualitative comparative analysis (mvQCA). Since fsQCA uses continuous values to retain more detailed information about the data, this paper adopts fsQCA to analyse the influencing factors of the integration of sports and ideological and political education, and the software adopts fsqca3.0 for the analysis. It is mainly divided into the following steps: 1)

Assignment and calibration of variables. The raw data for each variable and outcome were calibrated to the corresponding fuzzy set values based on maximizing differences between groups in univariate analysis, combined with consideration of practical implications.

In this study, online and offline questionnaires were distributed to physical education teachers (associate professors and above) and sport-related administrators in 30 colleges and universities in a certain city, and 117 valid questionnaires were finally collected. In order to improve the validity of the study, based on the basic principle of the “triangulation method”, the data were further screened and cleaned, and 30 highly representative cases were finally selected for QCA analysis.

With the help of fs QCA software on the policy orientation value leading Y1, developing sports ideological resources Y2, developing professional training programmes Y3, multiple subjects collaborative education Y4, improving the mechanism to focus on implementation Y5 Resulting variables grouped to carry out the analysis of the necessary conditions, the results of the necessary conditions detection are shown in Figure 2. The reference value of Consistency is 0.9, if the Consistency of a variable is > 0.9, it indicates that the variable is a necessary condition to directly explain the results. The results show that “mining the elements of the sports programme’s ideology and politics X4” is a necessary condition for the group “developing sports ideology and politics resources Y2”, with a consistency of 0.94.

Figure 2.

Necessary condition detection results

In this study, the intermediate solution (standard analysis) was chosen to discuss the conditional group states, and the PRI consistency threshold was set at 0.75, which was analysed as follows. 1)

Analysis of group states led by policy orientated values

The grouping results of policy oriented value leadership are shown in Table 1, with “●” representing the presence of core conditions, “○” representing the presence of marginal conditions, “⊗” represents the absence of core conditions, and “△” represents the absence of marginal conditions. The core condition plays a key role in the variation of results and appears in both intermediate and simple solutions. However, the edge condition has only limited effect on the variation of results. Same below.

There are five sufficient solutions greater than the PRI threshold of 0.75, covering 93.4% of the policy-oriented value leading case samples, of which solution 3 covers 90.8% of this set of samples. The analysis shows that the national strategic policy documents X1 and the practice of socialist core values X3 are important influencing factors for the integration of curriculum ideology into physical education teaching, but the consolidation of the roots of ideals, beliefs and purposes X2 has not yet become the preferred condition in policy-oriented value leadership.

Firstly, the weights of the indicators at all levels for the integration of sports and civic education are calculated by the hierarchical analysis method and entropy weight method respectively, and both methods have unavoidable disadvantages. The hierarchical analysis method is susceptible to the influence of subjective judgment, entropy weight method requires a large amount of data for calculation and verification, so this paper is based on the game theory idea of using MATLAB software to couple the weights determined by hierarchical analysis method and entropy weight method, and calculates the combination of weights, so that the weight value given by each evaluation index is more scientific and reasonable.

The game theory comprehensive weight method combines the characteristics of multiple evaluation index weights to find the optimal solution between multiple evaluation index weights, and the results obtained can minimise the deviation between the weights of each evaluation index, which is representative. 1)

Establish the weight vector set and get the linear combination

Establish the set of weight vectors W_i = {w₁;w₂}, where w₁ represents the set of weight vectors and w₂ represents the set of weight vectors. Let β = {β₁;β₂} be the linear combination coefficient to obtain any linear combination of vectors as shown in equation (1) below: (1)W=β1w1T+β2w2T$$W = {\beta _1}w_1^T + {\beta _2}w_2^T$$

Style: (5)β1′=β1β1+β2;β2′=β2β1+β2$$\beta _1^\prime = \frac{{{\beta _1}}}{{{\beta _1} + {\beta _2}}};\beta _2^\prime = \frac{{{\beta _2}}}{{{\beta _1} + {\beta _2}}}$$

Using the game theory combination assignment method from the above formula (1) ~ (5) with the help of MATLAB software to calculate the AHP coefficient and EW coefficient can determine the evaluation system of sports and ideological and political education integration of the combination of indicators weights, sports and ideological and political education integration indicator weights results as shown in Table 6. Teaching practice C is at the core of the first-level indicators, with a weight of 0.4708, which is the focus of the evaluation of the integration of sports and ideological and political education that should be specifically implemented. At the same time, it can also directly reflect the specific and effective assessment of reflective practice D2 (0.1388), teaching expression C4 (0.1357), classroom atmosphere A1 (0.1224), information literacy C2 (0.1154), and nurturing methods C3 (0.1129), which is the main path to achieve the evaluation objective of teaching facilitation and curriculum nurturing measurability, and to promote the development of teachers’ professional ability, Focus on the overall development of students as the main path to achieve the evaluation purpose, while professional ethics C1 (0.1068) and teaching materials B1 (0.0868) are indispensable measures of it.

The so-called fuzzy comprehensive judgement refers to a comprehensive analysis and evaluation of target affairs in combination with the fuzzy transformation principle. There are two steps: first, focus on individual factors to implement the corresponding judgement. Second, focus on all relevant factors to implement the so-called comprehensive judgment. 1)

Establishment of evaluation index items

The factor set (U) is based on the factors that affect the object of the judgement (U_i): (6)U={U1,U2,...,Un}$$U = \{ {U_1},{U_2},...,{U_n}\}$$

Where R_i denotes the one-factor judgement set, which can be simply expressed as: (10)Ri={Ri1,Ri2,...Rim}$${R_i} = \{ {R_{i1}},\:{R_{i2}},...{R_{im}}\}$$ 5)

Fuzzy comprehensive judgement

The single-factor fuzzy judgement reflects only the influence of individual factors on the object of judgement, and if you want to judge an object accurately, you also need to consider the influence of each factor comprehensively according to the weight set, so as to make an accurate judgement. Therefore, when the weight set W and the single-factor judgement matrix R are known, a comprehensive judgement can be made by fuzzy transformation: (11)B=W⋅R$$B = W \cdot R$$

To wit: (12)B=(ω1,ω2,...,ωn)⋅[r11r12...r1mr21r22...r2m............rn1rn2...rnm]=b1,b2,...,bm$$B = ({\omega _1},{\omega _2},...,{\omega _{\text{n}}}) \cdot \left[ {\begin{array}{*{20}{c}} {{r_{11}}}&{{r_{12}}}&{...}&{{r_{1m}}} \\ {{r_{21}}}&{{r_{22}}}&{...}&{{r_{2m}}} \\ {...}&{...}&{...}&{...} \\ {{r_{n1}}}&{{r_{n2}}}&{...}&{{r_{nm}}} \end{array}} \right] = {b_1},{b_2},...,{b_m}$$

Where B is a fuzzy composite judgement set and b_j(j = 1, 2, …, m) is a fuzzy composite judgement indicator, where: (13)bj=Vi=1n(wi∧rij)$${b_j} = V_{i = 1}^n({w_i} \wedge {r_{ij}})$$ 6)

Assessment of judgement indicators

Take b_j and use it as a weight, then implement the so-called weighted average process with each alternative element v_j, then: (14)V=∑j=1mbjvj+∑j=1mbj$$V = \sum\limits_{j = 1}^m {{b_j}} {v_{{j^ + }}}\sum\limits_{j = 1}^m {{b_j}}$$

Then v is the result of fuzzy comprehensive judgement.

Using the fuzzy comprehensive evaluation model, the comprehensive score and the scores of indicators at all levels of integration of sports, ideological, and political education in the sample colleges were calculated. The evaluation scores of each three-level indicator are shown in Figure 4. After experiencing the Internet technology-based teaching practice of sports and ideological and political integration strategies, the evaluation scores of the three-level indicators of the integration of sports and ideological and political education in the sample colleges and universities are concentrated in the range of 0.7 to 0.9, of which 25% of the three-level indicators have scores of 0.85 or more, and the use of extracurricular sports and exercise methods d7 and the students’ initiative to engage in meaningful teaching and learning practice activities c15 have the highest scores, which are respectively 0.894 and 0.887.

Figure 4.

Evaluation scores of three indicators

The evaluation scores of each level 1 and level 2 indicators are shown in Figure 5. The overall physical education, ideological, and political education integration score of the university is 0.797, and the overall quality of the physical education, ideological, and political education integration of the sample university is good. Among the evaluation scores of the primary indicators, teaching resources B scored the highest and teaching practice C scored the second highest, with 0.813 and 0.807 scores, respectively. Among the evaluation scores of the second-level indicators, 50 per cent of the indicators scored above 0.8, with teaching expression C4 and teaching material B1 scoring the highest. This reflects that the advantages of the integration strategy of physical education and ideological and political education based on Internet technology lie in the rich expansion of teaching resources, the curricular integration of ideological and political elements, and the innovative expression of teaching methods. From the results of the students’ reflective development D, the students’ self-reflection habits and the improvement of the level of special skills have been significantly improved, especially in the mastery of sports theory, independent thinking, and the ability to analyse and solve problems, which is affirmed by the students, which fully demonstrates that the strategy of integrating sports and ideological-political education based on Internet technology plays an unparalleled role in improving the students’ physical fitness and sports skills, and promoting the integration of sports and ideological and political integration plays an irreplaceable and important role.

Figure 5.

The evaluation scores of primary and secondary indicators