


































Global Research in Higher Education 
ISSN 2576-196X (Print) ISSN 2576-1951 (Online) 

Vol. 4, No. 4, 2021 

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27 

 

Original Paper 

A Study of a Multiple Evaluation System of College English 

Online Teaching in China 

Fan Zhang
1,2*

 & Shuxiong Feng
2
 

1 
College of Foreign Languages, Central South University of Forestry & Technology, Changsha, Hunan, 

China 

2
 School of Education, University of Delaware, Newark, DE, USA 

*
 Fan Zhang, fzhang@udel.edu 

 

Received: September 2, 2021  Accepted: September 17, 2021  Online Published: December 6, 2021 

doi:10.22158/grhe.v4n4p27              URL: http://dx.doi.org/10.22158/grhe.v4n4p27 

 

Abstract 

The comprehensive and scientific evaluation of college English teaching in online mode is an important 

basis for further promoting and optimizing the pragmatic reform of college English teaching. Based on 

the operational principle, the principle of service to students, and the feasibility principle, this study 

aims to construct a multiple evaluation system of online college English teaching based on three 

aspects: online interaction, online autonomous learning, and English online practice. A questionnaire 

has been conducted among undergraduates, teachers, and experts. The Analytic Hierarchy Process 

(AHP) has been used to analyze the relative importance of the indicators at the first two levels in the 

multiple evaluation system. The results revealed that the weight coefficients of teacher-student 

interaction, learning resources, and English listening practice are higher, while those of learning 

freedom and oral English practice are lower. Therefore, the online college English teaching reform 

should take the following measures: equipment input of college English practice teaching should be 

reinforced, communication channels between teachers and students should be strengthened, and online 

teaching resources should be enriched. 

Keywords 

online teaching and learning, college English teaching, multiple evaluation system, analytic hierarchy 

process 

 

 

 

 



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1. Introduction 

The practice in College English education in China has been conducted based on nationally unified 

curriculum---the College English Curriculum Requirements (CECR) (Cai & Xin, 2009; Chen & 

Klenowski, 2009). China’s Ministry of Education (CMOE) has initiated College English curriculum 

reforms nation-wide with the attempt to promote the quality of College English education to better 

meet the needs of socioeconomic development in China (Cai & Xin, 2009; Chen & Klenowski, 2009; 

Zhang, 2004). The 2017 CECR advocated College English should vigorously promote the integration 

of the latest information technology and curriculum teaching, and continue to give play to the important 

role of modern educational technology, especially information technology in foreign language teaching 

(CMOE, 2017). The 2017 CECR called for a full use of information technology and actively create a 

diversified teaching and learning environment in colleges and universities (CMOE, 2017). Teachers are 

encouraged to build and use micro-courses and MOOCs, transform and expand teaching content by 

using high-quality online education resources, and implement mixed teaching modes such as flipped 

classroom based on classroom and online courses, so that students can develop towards active learning, 

independent learning and personalized learning (CMOE, 2017). The curriculum requirements 

emphasized that teaching assessment is a crucial link to achieve the goal of college English teaching 

(Xie et al., 2009; Yin, 2010). According to the Association for Educational Communications and 

Technology (AECT) (2004), the modern education technology is creating, using, and managing 

appropriate technological processes and resources to promote learning and improve the performance of 

the study and ethical practice. On the one hand, the new media, such as computers, multimedia, and 

internet applications in the actual teaching process, have been emphasized. On the other hand, the 

traditional teaching of knowledge structure’s linear defects is to be overcome to build up a diversified, 

multi-level, and nonlinear information structure. 

The modern educational technology with computer network has been gradually integrated into college 

English teaching in China, which has brought profound changes to the traditional English teaching 

model (Li, 2005; Wang, 2006). Since 2007, many forms of college English online teaching systems 

have emerged, such as the New Horizon College English online learning system and Bingo English 

functional Composition System (Zhang & Yin, 2010). The multimedia teaching system combined with 

digital technology enable students to communicate with each other and with teachers across time and 

space, and achieve the collaborative learning effects, to which the traditional teaching mode cannot be 

compared (Brett, 2000; Fang, 2011; Han et al., 2014; Li, 2005; Lukman & Krajnc, 2012). However, 

little research has been done to investigate the evaluation system of online college English teaching in 

China. This study aims to develop an effective network evaluation model of college English teaching in 

an online environment using the Analytic Hierarchy Process (AHP). 

 

 



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2. Literature Review 

For years, previous Chinese scholars have been working on the assessment of college English teaching 

in an online/virtual environment in China (Li, 2005; Peng, 2004; Tong & Shi, 2009; Wang, 2006; Yang, 

2012; Zhou & Qin, 2005). In terms of assessment methods, scholars have emphasized the importance 

of adopting formative assessment methods in college English teaching (Li, 2005; Yang, 2012; Zhou & 

Qin, 2005). Formative assessment methods include “self-correcting systems” that tap students’ 

potential and comprehensively examine students’ specific learning processes. Formative assessment 

gives full play to cultivating students’ independent and cooperative learning ability (Wang, 2006). 

However, based on the theory of connectionism, Tong and Shi (2009) examined the assessment system 

of college English teaching from the perspective of systematization, ecology, and language technology, 

and concluded that the assessment system must be based on formative assessment and supplemented by 

summative assessment. Peng (2004) proposed that the assessment system of college English teaching 

should neither be formative nor summative but should be a dynamic assessment system that can more 

effectively cultivate college students’ cognitive and understanding abilities. 

Prior researchers have also focused on the typical English composition scoring systems and scoring 

behaviors. In terms of the assessment model systems in different aspects of college English teaching, 

Wan (2005) explored the application of electronic software assessment systems in English writing tests 

for English majors in Anyang Institute of Technology. He explored the possibility of replacing manual 

assessment and found that electronic software assessment has higher reliability. Zhang and Yin (2010) 

did an overview of the relevant concepts of computer scoring for English composition, summarized the 

main research techniques of computer scoring for English composition, and introduced several typical 

computer scoring systems for English composition. Researchers have conducted a targeted discussion 

on the practical application of online assessment systems in college English teaching in China (Tan, 

2008; Zhou et al., 2009; Zheng, 2010; Zeng, 2010). For example, Tan (2008) reported a study using 

Rasch model to analyze English writing grading behavior of four raters. The results showed that the 

intra-rater reliability is difficult to achieve. It is necessary to establish clear grading standards and train 

the grading staff to ensure the correct understanding and application of grading standards (Tan, 2008). 

Zhou and colleagues (2009) found paperless examination can improve the efficiency of testing and 

evaluation; and a larger proportion of students (85%) and teachers (90%) have a positive attitude to it; 

on the other hand, they also found negative aspects of computer-based examinations, for example, 

deficit network technology and testing software will increase teachers’ workload infinitely; reading 

online will aggravate the degree of eye fatigue; 5% of students disapprove of paperless exams in 

writing courses; 70% of teachers worry that paperless exams are not easy to implement. Zeng (2010) 

found the main advantages of computerized examination are mainly reflected in these four aspects: 

innovative examination questions can be applied; adaptability testing can be implemented; 

multi-dimensional capability estimation is realized; immediate diagnostic information can be provided.  



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With the rapid development of computer technology, web-based test and evaluation of second language 

acquisition have a very broad development prospect. This issue has also gained popularity among 

scholars in other countries. For instance, Akinwamide et al. (2012) explored the online autonomous 

learning functions and strategies with a finding that teachers’ supervision predicted the performance of 

ESL students’ online autonomous learning. Teachers need to arrange and help students to complete 

different online learning tasks to achieve the self-construction of knowledge. In terms of a network 

language learning environment, Lukman and Krajnc (2012) discussed the commonalities and 

characteristics of non-traditional teaching methods in the virtual and real learning environments. The 

results showed the appropriateness of nontraditional learning methods in comparison with traditional 

ones, although collaborative learning in both environments causes several frustration based on conflicts 

(personal or disagreements during the learning phase), influencing the efficiency of the learning 

process. Dickenson and his colleagues (2010) found virtual action learning was corelated with social, 

cultural, technical and economic change in the society. Yang (2009) believed that new media (such as 

blogs, etc.) facilitated learning a second language. The results showed that 43 student teachers were 

able to critically reflect on their thoughts and they viewed technology a useful tool for reflecting and 

communicating with each other.  

To date, the Chinese scholars’ research on the evaluation of college English teaching in a virtual 

environment has been relatively broad, including assessment methods such as formative assessment, 

summative assessment, and dynamic assessment (Peng, 2004; Tong & Shi, 2009; Yin, 2010; Zhou & 

Qin, 2005), as well as the study of assessment systems in different aspects, such as the English 

composition network scoring system (Tan, 2008; Wan, 2005; Zhang &Yin, 2010; Zhou et al., 2009). 

Although prior existing research of the assessment of online college English teaching has focused on 

teaching purposes, teaching methods, and teaching practices , relatively few studies have been 

conducted on online teaching assessments and fewer quantitative analyses of the evaluation standards 

have been adopted on the issue. In addition, due to the lack of sufficient attention on the information 

feedback mechanism from teaching practice process, student cognitive process and interaction 

platforms, online college English teaching is still constrained by the traditional English teaching model. 

Therefore, the possible contributions of this study might be as follows: first, to fill in the gap of the 

evaluation system research in a network environment in China by building up a multi-evaluation index 

system for online college English teaching; second, to supplement the literature of quantitative research 

on the evaluation criteria by utilizing the Analytic Hierarchy Process (AHP) to quantitatively study the 

evaluation criteria of online college English teaching; third, to add onto the literature on evaluation 

feedback mechanism by selecting experts, teachers, and students as questionnaire participants to 

provide feedback.  

 

 



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3. Theoretical Framework 

The multi-dimensional approach of evaluation of college English language teaching in a network 

environment is based on the theoretical framework of the Constructivism and the Interaction 

Hypothesis (IH). Constructivism holds that teaching media should be a cognitive tool for students to 

study actively and explore cooperatively, rather than just a means to help teachers impart knowledge 

(Chen, 2007; Koohang et al., 2009; Lutz & Huitt, 2004; Perkins, 1991; Saunders & Goldenberg, 1996). 

According to the constructivist learning theory, on the one hand, online learners independently choose 

the learning contents and ways to control the learning process; on the other hand, it is also necessary to 

evaluate the learning process and results of self-construction through self-diagnosis and self-reflection 

since constructivist learning is cumulative and goal-directed (Yang, 2012). In the online teaching 

process, evaluation should be focused on formative assessment, including participation, homework 

submission, online discussion, online recording of the learning process, students’ self-evaluation, and 

peer review (Yang, 2012). Besides, communication with teachers and group cooperative learning 

should also be included to comprehensively evaluate the students’ learning effect and ensure the 

effectiveness and practicality of online teaching (Yang, 2012). 

The Interaction Hypothesis (IH), one of the most important Second Language Acquisition (SLA) 

hypotheses, has also laid the theoretical foundation of the current study. The IH claims that second 

language development is better facilitated when learners participate in negotiated interaction, and a 

second language is acquired more effectively through interaction and communication (Auquilla et al., 

2019). A substantial body of studies has shown that interaction is inseparable from second/foreign 

language learning (Ellis, 1994; Gass, 2005; Long, 1981, 1983). There are mainly two kinds of 

interactive activities in a multimedia and a network environment: teaching interactive activities and 

social interactive activities. Li (2001) pointed out that teaching interaction refers to using computer 

network information from teaching resources, linking content, downloading information, publishing 

information, and so on. Such interactive activities provide learners with a dynamic control of 

information and the opportunity to control the learning situation. Social interaction is the use of e-mail, 

chat rooms, bulletin boards, online meetings, or other online media resources to communicate with 

others. Through these communication activities, asking questions, offering answers, discussions, and 

debates can be conducted online between learners and teachers as well as between learners and learners. 

In a network environment, interactive activities are a dynamic process, which runs through the whole 

learning process (Li, 2001). 

Previous second language acquisition researchers have identified and emphasized the importance of 

online communication and interaction in the target language, which provides opportunities for 

authentic social interaction (Auquilla et al., 2019; de la Fuente, 2003; Sachs & Suh, 2007; Smith, 2004). 

Many researchers have claimed that online communication offers learners many opportunities (Jepson, 

2005; Smith, 2004). For example, de la Fuente (2003) found that face-to-face and computer-mediated 



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interaction appeared equally effective in promoting vocabulary acquisition. Therefore, it will be of 

great significance to investigate the main factors of the multiple evaluation system of online college 

English teaching in China and their relative importance based on those conceptual foundations. 

 

4. The Present Study 

The construction of the multiple evaluation index system for online college English teaching in China 

conforms to three basic principles of course evaluation (Tu, 2007): orientation, feasibility, and 

acceptability (Hu, 2008; Wang, 2002; Jin & Wang, 2007). In terms of orientation, a multiple evaluation 

system should embody the correct teaching values (Jin & Wang, 2007): social-service-orientated and 

student-development-orientated. Besides, feasibility requires evaluation to be consistent with the 

teaching context and be understood and accepted by evaluation objects (Hu, 2008). The main factors of 

multiple evaluation systems should be described clearly and accurately, and indicators should be 

measurable. Besides, the numerical value of each index should be evidence-based and reasonable, and 

the methods and the procedures of constructing the numerical value have to be widely accepted. 

Moreover, acceptability requires the indexes in this system to be accepted by most objects and subjects 

(Wang, 2002). Thus, the difficulties of the indexes should be moderate and fair to every participant. 

Each index in the system is relevant and relatively independent (Hu, 2008). 

To identify the main factors of multiple evaluations of online college English teaching in China, we 

selected articles from CSSCI journals published in the past ten years. The qualitative data coding 

(Huang, 2008) was employed to identify the specific indexes. Then the frequency and percentage of 

each index was counted. The multiple evaluation index system was designed from three levels: network 

interaction, autonomous learning, and English practice, which belong to the first level. The second 

level includes 12 indicators: teacher-student interaction, interaction among students, human-computer 

interaction, social interaction, learning resources, learning freedom, information acquisition, online 

teaching, oral English practice, English writing practice, English listening practice, and English reading 

practice. The third level includes 39 evaluation indicators, such as teacher-organization interaction, 

students’ question and answer interaction, group cooperation interaction, and group confrontation 

interaction, and so on. Twelve evaluation indicators belong to the network interaction dimension, 13 

evaluation indicators belonging to autonomous learning, and 14 evaluation indicators belonging to 

network English practice (See Table 1). The AHP was used to analyze the relative importance of 

different hierarchical indicators. This study aimed to examine the relative importance of the evaluation 

index at each level to determine the main factors of the online college English teaching evaluation 

system in China.  

 

 

 



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Table 1. Multiple Evaluation System of Online College English Teaching in China 

 

 

5. Methods 

5.1 Participants  

Considering the differential influence of regional educational resources on the generalizability of the 

results, we selected five colleges and universities from three provinces in the eastern region, the central 

region, and the western region, respectively. The survey was conducted from May 2017 to January 

2018 by online college English teaching experts and instructors as well as students who took the 

college English online courses. There was a total number of 5,639 respondents who finished and 

submitted the questionnaire, from which 35 were online English teaching experts, 102 were teachers, 

and 5,606 were students from those 15 colleges and universities. One hundred and fourteen 

questionnaires that were incomplete or carelessly filled out were eliminated. Therefore, finally, 5,525 

valid questionnaires were obtained, with an attrition rate of less than 10%. 

5.2 Questionnaire 

The questionnaire is mainly composed of four parts: The first part is demographic information of the 

participants, such as age, gender, affiliation, occupation, etc. The second part is the interactive network 

of college English teaching, which involves specifically the evaluation of 12 indicators. The third part 

is the evaluation of online autonomous learning of college English teaching, which involves 13 

indicators. The fourth part is the evaluation of English practice in college English teaching, which 

specifically involves 14 indicators. The questionnaire with a 5-point Likert scale ranging from 



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“strongly disagree”, “somewhat disagree”, “neutral/no opinion”, “somewhat agree”, to “strongly agree” 

for each item has been rated. 

5.3 The Analytic Hierarchy Process (AHP) 

The AHP, developed by Saaty (1980), is one of the Multiple-Criteria Decision-Making (MCDM) 

methods which helps to improve the effectiveness of numerical value distribution (Wang & Xu, 1990) 

and provide a simple method with multi-criteria for a complex system which is difficult to be 

quantified. It is widely applied to varied fields such as resource allocation, project design, maintenance 

management, and policy evaluation (Saaty, 1980; Cook et al., 1984; Shen et al., 1998; Cheng et al., 

2005; Banai, 2005). AHP has the following advantages over other methodologies: 1) including 

comparing to the relative importance of each index with one another based on the best benefit of an 

overall evaluation system, 2) simplifying the decision-making process, and 3) improving the accuracy 

of priorities by pairwise comparison between every two indexes at the same level. The comparability of 

the numerical value can be strengthened by comparing each index with one another at the same level 

from the lowest to the highest level in evaluation systems. Therefore, AHP was used to apply to 

construct the multiple evaluation system of online college English teaching that can be turned into a 

hierarchical decision model.  

AHP is a method to solve a complex decision problem by breaking it down into multiple factors, but it 

is widely criticized for a tedious process of pairwise comparison when a number of criteria or 

alternatives are involved. Experts’ judgments may be doubted, for they are very likely to feel tired and 

lose patience during this process. To avoid such a drawback, only reasonable and manageable amounts 

of criteria are contained in the model based on the previous related research articles published in the 

CSSCI journals. The authors of this study have acted as facilitators to take over the judgment process. 

Therefore, AHP was regarded as the most appropriate method for this study since the data input was 

straightforward and convenient. The primary goal was to determine which indexes have the highest 

numerical value and should be included in the system. In this paper, the complicated mathematical 

calculations of AHP were skipped, and only a brief description of this method was provided. 

 

6. Results 

6.1 Descriptive Characteristics of the Score Status 

Based on the results from the evaluation questionnaire of online college English teaching, this study 

summarized the features of online interaction (B1), online autonomous learning (B2), and English 

online practice (B3). There were 66,300 option level observations altogether in terms of the online 

interaction dimension, 71,825 for the autonomous learning dimension, and 77,350 for the English 

practice dimension. 

 

 



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The option level of the online interaction dimension presented right skew or positive skew distribution, 

with an average value of 2.83. Among them, there were 11,695 samples with option 1, accounting for 

17.64% of the total number. There were 17,699 samples with option 2, accounting for 26.70% of the 

total number. The number of samples with option 3 was 15,718, accounting for 23.71% of the total 

number. The number of samples with option 4 was 12,242, accounting for 18.46% of the total number. 

There were 8,946 samples with option grade 5, accounting for 13.49% of the total sample size (as 

shown in Figure 1). From the comprehensive comparison, the evaluation level of online interaction 

dimension is between “slightly important” and “relatively important”, which is inclined to the 

“relatively important” option.    

 

 

Figure 1. Descriptive Characteristics of the Scoring Status of Online Interaction 

 

The options of online autonomous learning dimension presented right skew or positive skew 

distribution, with a mean of 2.69. There were 16,425 with option 1, accounting for 22.87% of the total 

samples. The number of choosing other four following options was 19,682, 14,629, 11,902, and 9,187, 

respectively, accounting for 27.40%, 20.37%, 16.57%, and 12.79% of the total number, respectively (as 

shown in Figure 2). From the comprehensive comparison, the evaluation level of this dimension is 

between “slightly important” and “relatively important”, which was inclined to the “relatively 

important” option. 

 



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Figure 2. Descriptive Characteristics of the Scoring Status of Online Autonomous Learning 

 

The online English practice dimension options presented a normal distribution, with a mean value of 

3.01. There were 10,322 samples with option 1, accounting for 13.34% of the total samples. In terms of 

other four options from 2 to 5, there were 16,694, 21,485, 19,527, 9,322 samples, respectively. They 

accounted for 21.58%, 27.78%, 25.24%, 12.05% of the total number of samples, respectively (as 

shown in Figure 3). The evaluation level of this dimension is between “relatively important” and “very 

important,” which was inclined to the “relatively important”, similar to the dimensions of online 

interaction and autonomous learning.  

 

 

Figure 3. Descriptive Characteristics of the Scoring Status of Online English Practice 

 



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By using the AHP to analyze the questionnaire data, the results showed that the relative importance of 

the evaluation index at the first level was on the following order: English practice (B3) > network 

interaction (B1) > autonomous learning (B2). In terms of the network interaction dimension, the order 

of the relative importance of each index should be: communication between teachers and students (C1) 

> social interactions (C4) > interaction among students (C2) = human-computer interaction (C3). The 

situation of the relative importance of indicators in the autonomous learning dimension is as follows: 

learning resources (C5) > online teaching (C8) > information acquisition (C7) > learning freedom (C6). 

The relative importance of the indexes in the network English practice dimension: English listening 

practice (C11) > English writing practice (C10) = English reading practice (C12) > English speaking 

practice (C9). Therefore, the judgment matrix of the evaluation index at the first level: 

      

























132
3

1
1

2

1
2

1
21

A  

The judgment matrix of the evaluation index at the second level: 



























122
3

1
2

1
11

4

1
2

1
11

4

1
3441

1B ；



























123
2

1
2

1
12

3

1
3

1

2

1
1

4

1
2341

2B ；



























1
4

1
13

4124

1
2

1
13

3

1

4

1

3

1
1

3B 。 

Table 2 shows the weights of the first and second levels of the multiple evaluation index system. In the 

current paper, the relative importance and the evaluation index weight of the third level were not 

included and discussed because the application of the modern network technology varied at different 

levels in different colleges and universities, therefore, the more detailed quantitative score of the 

evaluation indexes at the third level may not apply. 

 

 

 

 

 

 

 

 

 

 



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Table 2. Weights of Multiple Evaluation Index System of Online College English Teaching in 

China 

 

 

The consistency test has been used to measure the internal stability and reliability of judgment matrices 

of different levels and dimensions. The lower the consistency test coefficient is, the higher the 

consistency of the judgment matrix will be, and the higher the accuracy of the conclusion obtained by 

AHP will be. In this paper, the consistency ratio C.R. was selected as the consistency test index of the 

multiple evaluation system. The ratio of the calculated C.I. index value and R.I. index value was used to 

test the consistency of the three dimensions variables: network interaction, network autonomous learning, 

and network English practice. The calculation formula of C.I. index is: 
max. .

1

n
C I

n

 


 , where max is the 

maximum eigenvalue of the judgment matrix. By checking the table, we got the results 

as 58.03.. ）（IR  and 90.04.. ）（IR . Results showed that the consistency ratio of the first level 

C.R.
A
 = 0.0079. In terms of the second level, the consistency ratio of the online interaction dimension 

C.R.
B1

 = 0.0076; the consistency ratio of the online autonomous learning dimension C.R.
B2

 = 0.0115; the 

consistency ratio of the English practice dimension C.R.
B3

 = 0.0076. The consistency ratios of the 



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evaluation indexes at all the levels were less than 0.05. It can be considered that the deviations of the 

maximum eigenvalue of the evaluation indexes at each level from the judgment matrix order is no more 

than 0.05 from the average random consistency index R.I. Therefore, the consistency of the judgment 

matrixes has been proved. In other words, the weights of the multiple evaluation index system of college 

English teaching obtained by the AHP were basically accurate since they conformed to the standards of 

consistency, stability, and reliability.  

 

7. Conclusion 

This study attempted to build a multi-dimensional assessment system frontline college English teaching 

in China from three aspects: online interaction, online autonomous learning, and English online 

practice, aiming to provide a reliable reference for further improving and optimizing the online college 

English teaching model, as well as making up for the lack of research on the assessment system in the 

online environment. The AHP was used to supplement the literature of quantitative research on 

assessment standards. Experts, teachers, and students were selected as the participants of the 

questionnaire, so as to form assessment feedback information and fill in gaps of assessment feedback 

mechanism research.  

The results revealed that the relative importance of the evaluation index at the first level is based on the 

following order: English practice (B3) > network interaction (B1) > autonomous learning (B2). In 

terms of the network interaction dimension, the relative importance of each index should be: 

communication between teachers and students (C1) > social interactions (C4) > interaction among 

students (C2) = human-computer interaction (C3). The relative importance of indexes in the 

autonomous learning dimension is as follows: learning resources (C5) > online teaching (C8) > 

information acquisition (C7) > learning freedom (C6). The relative importance of the indexes in the 

network English practice dimension is: English listening practice (C11) > English writing practice (C10) 

= English reading practice (C12) > English speaking practice (C9). Thus, the weight coefficients of 

teacher-student interaction, learning resources, and English listening practice are higher than those of 

learning freedom and English oral practice. 

Based on the findings, there are implications for college English teaching under China’s network 

environment. Administrators and policymakers of universities in China need to support and encourage 

online English courses by enhancing the curriculum design and providing professional development for 

teachers. In addition, it is suggested that the equipment input of college English teaching be 

strengthened. Modern college English network practice facilities play an important role in cultivating 

students’ comprehensive English application ability and enhancing their autonomous learning ability. 

Besides, the communication channels between teachers and students need to be strengthened. Teachers’ 

role should not only be embodied in the college English classroom, but also in the online interaction 

among students. The cognitive construction of English learning is a cyclic process in which teachers 



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help students from discovering problems to solving problems back and forth. Finally, great efforts need 

to be made to improve and enrich network teaching resources. Developing and building a variety of 

network teaching resources facilitates to provide students with a good language learning environment. 

The current study was the first to use AHP to examine the evaluation system of online English teaching 

in China. But as the other studies, there are limitations to this one. First, due to the shortcomings of 

ordinary AHP, such as uneasily estimated range of evaluation results, uneasily determined quantitative 

values, and strong subjectivity, future efforts are needed to be done on a more feasible online college 

English teaching system in China by a revised or improved AHP. Second, the specific indicators at the 

third level were not included and discussed in the current study due to the varied usage of the modern 

network technology in those colleges and universities and the paper length limit. Therefore, in the 

future studies, the relative importance of the indexes at the third level will be calculated and reported, 

such that the specific implication will be discussed for the online college English teaching in China. 

 

Acknowledgments 

This study was supported by A Philosophical and Social Science Foundation Project in Hunan Province 

in China: An Empirical Study on Multiple Evaluation System of College English Online Teaching (No. 

17WLH45), and the China Scholarship Council (201808430171) for Fan Zhang. 

 

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