Innovative Development of English Teaching Management in Colleges and Universities Based on WSR Methodology

WSR is the abbreviation of “Wuli - Shili - Renli” methodology, which was proposed by Professor Gu Jifa and Dr. Zhu Zhichang, the famous Chinese experts in system science, at the University of HULL, UK, in 1994. It is both a methodology and a tool for solving complex problems. When observing and analyzing problems, especially when observing and analyzing systems with complex characteristics, WSR embodies its uniqueness and is a comprehensive unification of multiple methods with traditional Chinese philosophical thinking. Depending on the specific situation, WSR can rationalize and hierarchize the group of methods, which can simplify the complexity into simplicity [20]. It belongs to the Oriental system's thinking of comprehensive integration of qualitative and quantitative analysis.

The basic core of WSR methodological philosophy and concept, when dealing with complex problems, is to consider not only the physical aspects (the nature and characteristics of the objects themselves), but also the management or operation-related aspects (how to make better use of these things), and finally, the human-related aspects (especially the relationships between people). The human factor is indispensable for recognizing problems, handling problems, and implementing management and decision-making. The goal is to harmonize the facilities, operations, and people within the system. Although some of the existing systems theories and methodologies can analyze the physical structure-related aspects on the surface and the rest of the management-related aspects of the problem structure relatively clear in terms of practical feasibility, the effect is not satisfactory. This is mainly due to the neglect of the human factor or not clearly understanding the role of the human factor, resulting in inefficient efforts (doing twice the work for half the achievement). From the perspective of problem structure, the traditional system analysis method is suitable for solving structured problems, or problems that can be reduced to mechanical problems. However, in reality, there are many non-structured and poorly structured problems, such as social, economic, environmental, and management issues. Relying solely on the original “hard” method or “soft” method is not enough. The WSR methodology is based on the principles of synthesis, participation, operationalization, and iteration.

For Shili (managerial aspect), what are employed include various operations research, systems engineering, management science, cybernetics, and some mathematical methods. Especially in recent years, what are frequently used include soft computing methods such as evolutionary computing, fuzzy computing, and network computing, a variety of models and simulation techniques, as well as some qualitative methods and a combination of qualitative and quantitative methods, such as Telfer’s method and the hierarchical analysis method. The workflow of the WSR methodology in Figure 1 demonstrates that Renli can be further categorized into relationships, emotions, habits, knowledge, interests, conflicts, reconciliations, harmony, and management [21].

Figure 1.

Operation process of WSR approach

In English language teaching management, the subjects of the WSR system methodology are, i.e. School, teacher, and student are interconnected and coordinated with each other. This is conducive to the implementation and development of English language teaching management.

In terms of the main teaching management directions, there are Wuli namely physical level, which is influenced by the external environment and the material base; Shili, namely the managerial level, which involves the teacher's design of the curriculum and the selection of an appropriate teaching mode; and Renli, namely the humanistic level, which is the teaching goals that need to be achieved [22]. The smooth implementation of each direction ensures the stability of the next link. Therefore, for the construction of the entire English class evaluation system, Figure 2 shows the coordinated relationship between the three dimensions.

Figure 2.

Coordination between three dimensions

In the whole English teaching management evaluation system, the physical aspect represents an irresistible factor, and certain material conditions should be in place. In the process of teaching development, it is easy to overlook the development of the humanistic dimension. Thus, emphasis should be placed on the “human” factor. It is important to pay attention to the status of the subject and object of teaching as the receiver-giver.

Based on the research of the WSR system methodology, the subjects of teaching evaluation should be students, and the objects should be teachers. The subjects (students) provide feedback on the teaching management evaluation process through the WSR approach. After receiving this feedback, the objects (teachers) conduct teaching reflections which cover aspects such as whether the teaching management content is reasonable, whether the teaching management objectives are clear, and whether the teaching management design is scientific. The subjects (students) are influenced by these reflections again [23]. In this way, a closed loop structure is formed, capable of infinite looping. The evaluation process system for teaching management is shown in Figure 3.

Figure 3.

Teaching evaluation process system

Besides the theoretical basis of the WSR methodology, this paper also involves a case study, the operation of which was conducted in a well-known university in north China where the WSR - based English teaching management reform was implemented. The operation was carried out in two parallel classes of a certain major, with one class as the experimental group applying the WSR - based management model, and the other as the control group using the traditional management model.

In the experimental group, certain new teaching facilities were introduced, teaching materials were updated, curriculum planning was adjusted, and more attention was paid to teacher-student interaction and teacher professional development. In the control group, the original teaching management model remained unchanged. In addition, a questionnaire survey was conducted among the students concerned, and an interview was conducted with experts, including professional teachers and experts engaged in teaching management at this university.

We reviewed and categorized the relevant literature on teaching research in colleges and universities, referred to books on college English teaching, drew on the research theories of previous scholars, and combined these with the opinions of experts. We consolidated the content viewpoints that are suitable for this study into reference materials and established the indexes in a preliminary manner. The index system is shown in Table 1.

The authors used the hierarchical analysis method to test the consistency of the selected indicators, constructed the judgment matrix, and finally determined the specific weights of the selected indicators for evaluating the teaching effectiveness of English courses in colleges and universities. The weight values of the indicators in the evaluation system of English teaching management effectiveness in colleges and universities are shown in Table 2. From the table, through expert consultation interviews, it can be concluded that the weight of the physical dimension indicators of English teaching effect in colleges and universities is higher than that of the managerial dimension and humanistic dimension. The weight of the physical dimension indicators is 0.5231, and the managerial dimension and humanistic dimension indicators have weights of 0.3641 and 0.1128, respectively. Colleges and universities should strengthen the construction of the physical dimension aspects of the classroom, actively create an emotional environment and a competitive environment for English courses, popularize modern teaching equipment, and increase efforts to introduce high-quality and high-level English teaching experts with teaching experience. The curriculum's needs can be met, the teaching effectiveness of English courses in colleges and universities can be improved, and students' knowledge of the English language can be enhanced. The experts agreed that the weight of the English course design index in the Shili dimension (0.7000) is greater than that of the English teaching system (0.3000). English lecturers should design the key points of the course before class. During the class, they should do a good job of tailoring the teaching to the students’ comprehension ability, update teaching concepts, adhere to the “people-centered”, namely “student-centered” principle, and innovate the existing assessment methods. By doing so, they can improve the teaching effect in all aspects of the whole process. Besides, the teaching concept should be constantly updated. We should adhere to the “people-oriented” principle and innovate the existing assessment methods to improve the teaching effectiveness of English courses in an all-round way. In the humanistic dimension, experts believe that English teachers' teaching attitude and students' motivation to learn English are important indicators for evaluating the teaching effectiveness of English courses. In terms of teaching attitudes, experts believe that the teaching emotion is more important than teaching cognition and teaching behavior tendency. In terms of students' motivation to learn English, collective orientation and curiosity are considered the optimal indicators. We should actively cultivate college teachers’ professional emotions, correct their views on students, and enhance their emotional comprehension, expression, and control abilities to improve teachers’ teaching emotions and cognitions. At the same time, according to students' needs, we should create a campus cultural atmosphere, establish campus English clubs, and establish college English corners to stimulate students' interest in learning English.

The before-and-after comparison of students’ English learning motivation Q1 and Q2 survey data is shown in Figure 4. The figure shows the before-and-after comparison of the mean values of the survey data for two questions regarding students’ English learning motivation in the control class, namely, “Interested in the content of English lessons” and “Interested in the teaching method of English lessons”. As depicted in the figure, according to question 1 and question 2 of the questionnaire on learning motivation, a total of 33.1% of the students indicated that they “extremely like” English in the pre-practice period, and a total of 46.5% indicated that they “extremely like” English in the post-practice period, representing an increase of 13.4%, which is a relatively significant increase. The proportion of students choosing item “Like” only accounted for 37.7% before the experiment and increased to 44.2% after the experiment, which is an increase of 7.5%. This indicates that students in the control class showed a slight increase in their preference for English in the later stage of the English teaching practice (which was based on the WSR method in the experimental class).

Figure 4.

The comparison of students’ English learning dynamic Q1-Q2 survey data

The before-and-after comparisons of students’ English learning motivation in Q13 and Q15 are shown in Figure 5. The figure shows the comparison of the mean values of the survey data regarding two questions about students’ English learning motivation in the control class, namely, Q13 “Can actively study English courses” and Q15 “Can listen carefully to the teacher’s explanations of English knowledge in the classroom”. The data from questions 13 and 15 of the questionnaire on learning motivation indicate that the number of students in the control class who chose “Strongly agree” decreased after the teaching practice. Specifically, the proportion of students who thought that they could actively learn English decreased from 29.35% to 26.08% by “Strongly agree”. However, the number of students who chose “Agree” increased from 42.75% to 46.03%. From the above data, it can be observed that the number of students in the control class actively learning English increased slightly in the later stage of the English teaching practice (which was based on the WSR method in the experimental class). This indicates that the motivation of the students in the control class to actively learn English has shown a slight improvement.

Figure 5.

The comparison of students’ English learning dynamic Q13-Q15 survey data

The comparison of students’ English learning motivation Q14 survey data is shown in Figure 6. The figure shows the before-and-after comparison of the mean of the survey data for question 14 of the students’ English learning motivation in the control class, “Even if I study English for a long time, I will not get tired and sleepy”. As can be seen from the figure, regarding the data of the 14th question in the learning motivation questionnaire, “Even if I study English for a long time, I don’t get bored and sleepy”, the number of people who chose “Strongly disagree” increased by 1.25%, and the proportion of those who chose “Disagree” increased by 3.62%, which is not a big increase. Indeed, all of these increases were not significant. Meanwhile, the proportion of people who chose “Strongly agree”, “Agree” and “Neutral” slightly decreased. It can be said that for this survey, there was little change in the students of the control class before and after the practice of teaching English based on the WSR method, and the state of English learning of the students remained basically unchanged.

Figure 6.

The comparison of students’ English learning motivation Q14 survey data

The before-and-after comparisons of Q1 and Q2 survey data regarding students’ motivation to learn English are shown in Figure 7. The figure shows the comparison of the mean values of the survey data for two questions about the English learning motivation of the experimental class, namely, “Interested in the content of the English class” and “Interested in the teaching method of the English class”. As depicted in the figure, according to question 1 and question 2 of the questionnaire, it can be concluded that 41.36% of the students in the experimental class liked English very much in the first period of practice, while 91.5% of the students liked English very much in the second period of practice. This represents an increase of 50.14%, which is a very significant increase.

Figure 7.

The comparison of students’ English learning dynamic Q1-Q2 survey data

The before-and-after comparisons of students’ motivation to learn English in Q13 and Q15 are shown in Figure 8. The figure shows the comparison of the mean values of the survey data for two questions regarding the English learning motivation of students in the experimental class, namely, Q13 “Can actively study English courses” and Q15 “Can listen carefully to the teacher’s explanations of English knowledge in the classroom”.

Figure 8.

The comparison of students’ English learning dynamic Q13- Q15 survey data

The data from questions 13 and 15 of the questionnaire on learning motivation show that the proportion of students in the experimental class who chose “Strongly Agree” has increased significantly after the teaching practice. Specifically, the proportion of students who thought they could actively learn English increased from 32.71% to 67.25%, which is a substantial increase. At the same time, there were no cases of “Strongly disagree” for these two questions after the implementation of the teaching practice.

Figure 9 shows the comparison of Q14 survey data regarding students’ English learning motivation. The figure shows the comparison of the mean of the survey data for question 14 of the English learning motivation of the students in the experimental class, “Even if I study English for a long time, I will not get tired and sleepy”. As can be seen from the figure, the data for question 14 indicate that before the teaching practice, only 10.26% of the students chose the option “Strongly agree”, while 31.85% chose the option “Strongly agree” after the teaching practice. The proportion of students who chose “Agree” increased from 22.74% to 46.29%. For both options, the number of students in the later period is higher than that before the teaching practice. The proportion of students who chose “Strongly disagree” dropped from 5.36% to 0.

Figure 9.

The comparison of students’ English learning motivation Q14 survey data