The attention, relevance, confidence, and satisfaction model improves Chinese students’ English listening
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Cite this article:
Wang, Z., & Lu, J.
(2025). The attention, relevance, confidence, and satisfaction model improves Chinese students’ English listening.
Social Behavior and Personality: An international journal,
53(11),
e14749.
Abstract
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We explored the impact of the attention, relevance, confidence, and satisfaction (ARCS) model on Chinese college students’ English listening proficiency. Participants were 76 sophomores, whom we divided between an experimental class and a control class. The experimental class was systematically taught using the ARCS model for 4 months, while the control class adhered to traditional grammar translation methods. We developed the Learning Motivation Questionnaire of English Listening and used this before and after the teaching block to measure listening motivation. We also tested listening ability. The experimental group demonstrated a statistically significant increase in total English listening motivation across all four dimensions of the ARCS-based scale, accompanied by a significant improvement in listening scores. Our newly developed and validated scale serves as a reliable tool for research purposes. Considering the significant correlations we observed between the ARCS dimensions and listening achievement, our findings have practical implications for enhancing college English listening instruction.
Article Highlights
- We developed a new scale specifically designed to measure Chinese college students’ English listening motivation and performance.
- Teaching listening in English to college students using the attention, relevance, confidence, and satisfaction model significantly enhanced their listening motivation level.
- The attention, relevance, confidence, and satisfaction model-based teaching method had a significant positive impact on improving college students’ English listening scores between pretest and posttest.
- Confidence and satisfaction significantly predicted students’ proficiency of listening in English.
Teaching listening in English at colleges in China nurtures students’ language skills and enhances their critical thinking abilities (Zhao et al., 2019). However, the traditional teaching model has some issues. For instance, the main approach—where a teacher plays a recording and the students complete exercises and check their answers—lacks interaction, making it challenging to stimulate students’ enthusiasm (Cui, 2014). Our study explored the impact of the attention, relevance, confidence, and satisfaction (ARCS) teaching model on the performance and learning motivation of college students learning listening in English, analyzed its mechanism, and verified its effectiveness. We developed an ARCS-based questionnaire to measure the listening motivation of students. It is of significance for teaching practice, with the aim of improving the current teaching situation in China.
Definition of the Attention, Relevance, Confidence, and Satisfaction Teaching Model
The ARCS teaching model was proposed to stimulate and sustain students’ motivation (John & Thomas, 2018). Its four components are attention, which refers to arousing and maintaining students’ focus on the learning content; relevance, which emphasizes the connection between the teaching content and students’ experiences, interests, future goals, and practical needs; confidence, which aims to assist students in building self-confidence in accomplishing learning tasks; and satisfaction, which focuses on their sense of achievement (Tsai et al., 2022). The four elements of the ARCS teaching model are interrelated and interact with each other to enhance students’ learning motivation and outcomes (Chang et al., 2016).
Theoretical Basis of the Attention, Relevance, Confidence, and Satisfaction Teaching Model
The theoretical foundation of the ARCS teaching model is rooted in two educational psychology theories. From the perspective of cognitive theory, this model emphasizes students’ active cognitive processing (Manurung et al., 2018). The first element in the ARCS is attention, which prompts students to concentrate on the learning content, thereby initiating cognitive processing (Shishido, 2015). The element of relevance ensures that the learning content is connected with students’ existing knowledge structures and experiences, which facilitates the assimilation of new knowledge (Loukomies et al., 2013).
According to Rosenzweig et al. (2022), expectancy-value theory also offers significant support for the ARCS model. For example, an individual’s motivation depends on their expectations of success and perception of the value of the task. The element of confidence in the ARCS model helps students establish expectations of success, making them believe they can complete learning tasks, while the satisfaction element enhances students’ perception of the value of the tasks, enabling them to experience the pleasure of learning, thereby strengthening their motivation (Nasser et al., 2008).
Research Gap in Teaching English Listening at Colleges in China
The ARCS model has been extensively employed in the educational realm (Li & Keller, 2018). Nevertheless, according to Ma and Lee (2021), the majority of current studies in China have concentrated on its efficacy within science and engineering teaching contexts. Jia et al. (2023) stated that there remains a paucity of comparative investigations concerning the ARCS approach and traditional teaching methodologies with regard to the elevation of English listening motivation. Hence, our research probed into the effectiveness of the ARCS method in contrast to traditional teaching patterns in bolstering students’ motivation for English listening. Thus, we proposed the following research questions:
Research Question 1: What is the impact of English listening teaching on the basis of attention, relevance, confidence, and satisfaction model on university students’ English listening motivation?
Research Question 2: What is the impact of English listening teaching on the basis of attention, relevance, confidence, and satisfaction model on university students’ English listening ability?
Research Question 3: What is the impact of English listening motivation on the basis of attention, relevance, confidence, and satisfaction model on university students’ English listening ability?
Method
Participants and Procedure
We recruited 76 sophomore students from a university in Shanghai, China, encompassing 28 (36.8%) men and 48 (63.2%) women. Regarding academic major, 24 (31.6%) students were enrolled in business administration, 16 (21.1%) in accounting, 14 (18.4%) in finance, 12 (15.8%) in information technology, and 10 (13.2%) in applied mathematics. The mean age was 20.0 years (SD = 1.3).
This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of School of Foreign Languages, Shanghai Lixin University of Accounting and Finance. Informed consent was obtained from all participants. We conducted a teaching experiment as part of an English course that is compulsory for non-English-major students. Central to the curriculum’s design is the cultivation of students’ holistic English proficiency, with a particular focus on the enhancement of listening, speaking, reading, writing, and translation capabilities.
First, we created a new scale to measure motivation for learning English. Second, we conducted a pretest using the Learning Motivation Questionnaire of English Listening and the listening section of the 2018 College English Test Band 4 to select second-year parallel classes with comparable levels of motivation and proficiency as our participants. We allocated them to either the experimental or control conditions, with 38 students in each group. Third, we conducted the teaching experiment in the two classes for a period of 4 months. The experimental class implemented English listening teaching based on the ARCS model, while the control class adopted the traditional teaching approach based on the grammar–translation method. Fourth, after completing the teaching experiment, we used the listening section of the 2019 College English Test Band 4 for the posttest. By comparing the posttest scores of the two classes, we could explore the impact of English listening teaching based on the ARCS model on students’ English listening proficiency. We also readministered the learning motivation questionnaire we developed, and by comparing the data before and after the teaching phase in the two classes, we explored the effect of English listening teaching based on the ARCS model on students’ learning motivation.
Measures
Learning Motivation Questionnaire of English Listening
We created the Learning Motivation Questionnaire of English Listening (18 items) which we based on the Course Interest Scale (Keller, 2010; 34 items) and the characteristics of the research participants. The first author, who is a certified proficient English speaker, translated the Course Interest Scale into Chinese using backtranslation techniques. The original scale was crafted for generic learning contexts, whereas our study focused on the English listening learning motivation of Chinese undergraduate students; thus, we undertook essential modifications to ensure the items were more relevant and impactful. Subsequently, we convened a panel of English education experts, seasoned frontline English teachers, and translation professionals with extensive experience. Our evaluation covered multiple crucial aspects: language fluency, semantic precision, and alignment with the cognitive capabilities of our respondents. By soliciting diverse perspectives, we amassed a wealth of feedback. On this basis, we iteratively refined and optimized the items.
According to the rotated component matrix, we classified the 18 items in the questionnaire into four factors: attention (four items), relevance (four items), confidence (seven items), and satisfaction (three items; see Appendix A). Items are rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). We examined the reliability and validity of the scale and conducted an exploratory factor analysis and a confirmatory factor analysis to determine its dimensions and corresponding items.
We administered the questionnaire to 680 students from six universities. The initiative achieved a response rate of 95%, enabling us to gather 646 completed questionnaires. After a rigorous screening process, we eliminated invalid questionnaires that had a substantial number of items remaining unanswered, highly suspicious response patterns, or jumbled and off-topic responses. This left 600 valid questionnaires.
Of these, we utilized 300 questionnaires for exploratory factor analysis and conducted a confirmatory factor analysis with the remaining 300 questionnaires. The outcome of the reliability analysis conducted on the first 300 questionnaires showed a Cronbach’s alpha of .93, suggesting that the questionnaire possessed excellent reliability (Wadkar et al., 2016). Further, the Kaiser–Meyer–Olkin measure of sampling value was .92, and Bartlett’s test of sphericity reached a significant level (p < .05). Considering these results, we determined that the data collected were suitable for exploratory factor analysis. We utilized the principal component analysis method and maximum variance orthogonal rotation for factor extraction with the following criteria: the eigenvalue of the factor was greater than 1 (Ledesma & Valero-Mora, 2007), the cumulative variance explained by all the factors was above 60% (Huang et al., 2006), and the factor loading of each item was not less than .50 (Cudeck & O’Dell, 1994). Finally, we extracted four factors and the cumulative variance explained by the four factors was 64.98%. Taking all indicators into account, the result of the exploratory factor analysis was acceptable.
After the questionnaire showed good construct validity, we conducted a reliability test on the items contained in each factor. The test results showed that the reliability coefficients of the four dimensions were all above .80, and the corrected item–total correlations of all items involved in all factors were above .50. Thus, the items within each factor had good internal consistency (Suhr, 2005).
Next, we conducted a confirmatory factor analysis of the remaining 300 questionnaires. Since the factor of satisfaction contained only three items, this measurement model was saturated, and the fit between the saturated model and the data was optimal; thus, there was no need for further fit testing (Raykov et al., 2013). Confirmatory factor analysis of the three factors (confidence, attention, and relevance) indicated that the fit indicators of these models were all within the reference range (see Table 1); therefore, the three single-factor measurement models were statistically stable and reliable.
Table 1. Fit Indicators of Attention, Relevance, and Confidence
Note. CMIN/df = minimum discrepancy; GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; CFI = comparative fit index; RMR = root-mean-square residual; RMSEA = root-mean-square error of approximation.
The final step of the confirmatory factor analysis was to examine the measurement model composed of all four factors. As illustrated in Table 2, the fit indices of the modified model were all within the reference range, and all standardized regression coefficients exceeded .70, as shown in Figure 1. However, due to the large sample size, the p value was less than .05. Taking all the indicators into consideration, the English listening motivation model composed of the four factors of attention, relevance, confidence, and satisfaction was reliable, and could be employed in subsequent empirical research.
Table 2. Goodness of Fit of the English Listening Motivation Model
Note. CMIN/df = minimum discrepancy; GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; CFI = comparative fit index; RMR = root-mean-square residual; RMSEA = root-mean-square error of approximation.
Figure 1. Confirmatory Factor Analysis of English Listening Motivation Model
Thus, the dimensions and item distribution of the questionnaire regarding learning motivation for listening in English are shown in Table 3.
Table 3. Dimensions and Corresponding Items in the English Listening Motivation Scale
Listening Test Questions of the College English Test Band 4
We conducted a pretest and posttest of English listening comprehension using the listening sections in the 2018 and 2019 versions of the College English Test Band 4 (China Education Examinations Authority, 2018, 2019). The specific sections, question types and respective scores in this research are shown in Table 4.
Table 4. Structure and Format in Listening Test
Teaching Design
The teaching experiment involved one experimental class and one control class. The experimental class adopted the listening teaching method of the ARCS model (see Appendix B), while the control class employed the grammar–translation method for listening teaching (see Appendix C). Table 5 shows the pre- and posttest scores for each group.
Results
The Impact of the Attention, Relevance, Confidence, and Satisfaction-Based Teaching on English Listening Motivation
This research employed a mixed-methods analysis of variance to investigate the influence of teaching based on the ARCS model on different dimensions and the overall level of English listening motivation (see Table 5). We referred to the classification criteria put forward by Cohen (1988) to elucidate the magnitude of the effect size. The reference values of ηp² are defined as follows: a small effect is .01, a medium effect is .06, and a large effect is .14.
Table 5. Descriptive Statistics of Each Dimension of English Listening Motivation for the Experimental and Control Groups at Pre- and Posttest
As shown in Table 6, both the main effect of time and the interaction effect of time × group were significant for each dimension.
Table 6. Results of Mixed Analysis of Variance for Main Effects of Time and Interaction Effects for English Listening Motivation
The least significant differences post hoc test results depicted in Table 7 demonstrate the scores of the experimental group across all dimensions in the posttest exhibited a significant increase compared to those in the pretest. In contrast, the control group showed no substantial change. The intergroup comparison results revealed no divergence in the scores of the two groups across each dimension during the pretest. However, at posttest the scores of the experimental group were significantly higher than those of the control group. This finding indicates the superiority of the ARCS-based teaching method in boosting English listening motivation.
Table 7. Post Hoc Multiple Comparison of English Listening Motivation
Among the four dimensions, the effect of time on confidence was the most pronounced (see Table 6) Moreover, the interaction effect of time × group was also significant. The least significant differences post hoc test outcomes concerning the dimension of confidence indicate that the improvement of the experimental group from pretest to posttest was highly significant. Conversely, the change in the control group was not significant. There was no difference between the groups at pretest, whereas the experimental group showed a distinct advantage at posttest.
Regarding the total score of English listening motivation, the main effect of time was extremely significant. Additionally, the interaction effect of time × group was significant. The least significant differences post hoc test shows that the experimental group’s improvement from pretest to posttest was significant (see Table 7). The control group had no notable change. There was no difference between the groups in the pretest, whereas at posttest the experimental group scored higher than the control group.
Impact of Attention, Relevance, Confidence, and Satisfaction-Based Teaching on English Listening Performance
We conducted a mixed analysis of variance on the students’ English listening scores (see Table 8).
Table 8. Descriptive Statistics of Pre- and Posttest Scores on English Listening for the Experimental and Control Groups
As can be seen in Table 9, the main effect of time was significant. This indicates that students’ overall English listening scores improved over time. Meanwhile, the interaction effect of time × group was significant, implying that there was an interactive effect between time and group on students’ English listening scores.
Table 9. Results of Mixed Analysis of Variance for Main Effects of Time and Interaction Effects for Scores of English Listening
Later, we conducted a least significant differences post hoc test. As shown in Table 10, comparison of the pre- and posttest scores of the experimental group revealed that the difference was statistically significant. This indicates that the ARCS teaching method led to a significant enhancement in the English listening scores of the experimental group. In contrast, for the control group, comparison of pretest and posttest scores showed no significant difference, which suggests that the traditional teaching method did not significantly alter the English listening scores of the control group. In a comparison of posttest scores between groups, the difference was statistically significant. This further validates that the ARCS teaching method was superior to the traditional teaching method in improving English listening scores. Overall, the posttest results clearly demonstrate the superiority of the ARCS-based teaching approach over the traditional teaching method in improving students’ English listening proficiency.
Table 10. Post Hoc Multiple Comparisons of English Listening Scores
Predictability of Motivational Factors in English Listening Proficiency
We conducted a correlation analysis between attention, relevance, confidence, and satisfaction dimensions and the students’ English listening test scores. To investigate whether English listening proficiency could be predicted by these four factors, we conducted a multiple linear regression analysis using the posttest data of the two classes. The Pearson correlation coefficients presented in Table 11 indicate that listening performance was significantly and positively correlated with attention, relevance, confidence, and satisfaction. Moreover, there were significant positive interrelationships among these four factors of English listening motivation.
Table 11. Correlation Analysis of English Listening Motivation and Posttest Listening Scores of the Two Classes
Note. ** p < .01.
For the linear regression analysis, we regarded attention, relevance, confidence, and satisfaction as independent variables, while the dependent variable was the English listening test score. According to the data in Table 12, the enter-regression approach suggests that the combination of the four independent variables had a significant predictive effect on students’ English listening proficiency. Among them, confidence and satisfaction contributed significantly to the predictive effect. By contrast, the regression coefficients of attention and relevance did not reach a statistically significant level. The four independent variables had variance inflation factor values below 5, indicating the absence of multicollinearity (Kim, 2019).
Table 12. Summary of Multiple Linear Regressions of Motivational Factors on Listening Test Scores
Note. Dependent variable = English listening test score. VIF = variance inflation factor.
* p < .05. ** p < .01.
Discussion
Theoretical Implications
In this study we found that the ARCS-based teaching design effectively improved the learning motivation of participants listening to English. First, teachers using the ARCS model attracted students’ attention by incorporating diversified teaching methods and resources, such as engaging multimedia materials. Content with visual and auditory stimulation draws focus and promotes students’ desire to learn (Olmstead, 2005). Moreover, in terms of relevance, the ARCS model focuses on combining English listening with students’ majors, career planning, or daily life experiences (Ho et al., 2017). When learning content is correlated with students’ personal needs, their learning motivation is enhanced (Hao, 2023). As for confidence, the ARCS model features a step-by-step difficulty setting so that students can continuously experience success and enhance self-confidence (Buckingham, 2009). Last, in the satisfaction dimension, the ARCS model enables students to feel the value of their efforts through improved scores or public praise, as well as internal satisfaction arising from knowledge growth (Ebrahimi et al., 2013).
The results of a multiple regression analysis showed that confidence and satisfaction significantly predicted students’ English listening performance. When they had higher confidence, students engaged more actively in learning. Further, confidence equipped students with the courage to overcome difficulties (Kosterlitz, 2015). In addition, the factor of satisfaction further strengthened students’ confidence, motivating them to study even harder and thereby achieve better results (Aljohani et al., 2016). This then reinforced their sense of satisfaction, forming a positive virtuous cycle.
Practical Implications
There were significant positive correlations between each of the four scale dimensions and test scores for English listening. Thus, improvement in students’ English listening ability can be achieved by enhancing their listening motivation from these four perspectives. The factors of confidence and satisfaction played particularly significant predictive roles in English listening performance, so priority might be given to these for the enhancement of students’ listening proficiency.
In relation to the dimension of confidence, teachers could design a hierarchical teaching plan based on students’ actual ability levels, classifying listening materials by difficulty. Moreover, teachers should closely follow students’ efforts, give timely affirmation, and offer specific praise for progress. This will allow students to understand that effort pays off, strengthening their belief in learning English listening, and encouraging them to engage with a positive attitude (Amiryousefi, 2019).
In terms of the dimension of satisfaction, teachers should guide students to notice even slight progress in English listening learning. When students achieve understanding of complex structures or capture key information, teachers should encourage self-affirmation, enabling students to sense the satisfaction from internal ability improvement. Teachers need to build diverse display platforms, like organizing regular listening achievement sharing sessions for students to show their comprehension and retelling skills. Further, they should ensure an equitable evaluation system with clear criteria, giving timely and specific feedback. This will help students perceive the evaluation as objective and beneficial, leading to a genuine sense of satisfaction and continuous learning motivation (Lane et al., 2021).
Limitations and Directions for Future Research
Although this study has demonstrated that the ARCS model can stimulate students’ English listening motivation in the short term, research on the long-term effects is required to establish the validity of this model. Future research could integrate other related theories such as those in autonomous learning and cooperative learning to explore more comprehensively how to stimulate students’ English listening motivation. Researchers could also study other populations from different regions at different levels of institutions, and with diverse cultural backgrounds. Future studies could also use our Learning Motivation Questionnaire of English Listening on different groups to further test its reliability.
Appendices
Appendix A. Items in the Learning Motivation Questionnaire of English Listening
Appendix B. The Listening Teaching Design Based on the Attention, Relevance, Confidence, and Satisfaction Model
Appendix C. The Process of College English Listening Teaching in the Control Class
Note. In this teaching process, teachers assist students in understanding the listening content through detailed explanations and translations, and students passively acquire knowledge.
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Table 1. Fit Indicators of Attention, Relevance, and Confidence
Note. CMIN/df = minimum discrepancy; GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; CFI = comparative fit index; RMR = root-mean-square residual; RMSEA = root-mean-square error of approximation.
Table 2. Goodness of Fit of the English Listening Motivation Model
Note. CMIN/df = minimum discrepancy; GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; CFI = comparative fit index; RMR = root-mean-square residual; RMSEA = root-mean-square error of approximation.
Figure 1. Confirmatory Factor Analysis of English Listening Motivation Model
Table 3. Dimensions and Corresponding Items in the English Listening Motivation Scale
Table 4. Structure and Format in Listening Test
Table 5. Descriptive Statistics of Each Dimension of English Listening Motivation for the Experimental and Control Groups at Pre- and Posttest
Table 6. Results of Mixed Analysis of Variance for Main Effects of Time and Interaction Effects for English Listening Motivation
Table 7. Post Hoc Multiple Comparison of English Listening Motivation
Table 8. Descriptive Statistics of Pre- and Posttest Scores on English Listening for the Experimental and Control Groups
Table 9. Results of Mixed Analysis of Variance for Main Effects of Time and Interaction Effects for Scores of English Listening
Table 10. Post Hoc Multiple Comparisons of English Listening Scores
Table 11. Correlation Analysis of English Listening Motivation and Posttest Listening Scores of the Two Classes
Note. ** p < .01.
Table 12. Summary of Multiple Linear Regressions of Motivational Factors on Listening Test Scores
Note. Dependent variable = English listening test score. VIF = variance inflation factor.
* p < .05. ** p < .01.
Appendix A. Items in the Learning Motivation Questionnaire of English Listening
Appendix B. The Listening Teaching Design Based on the Attention, Relevance, Confidence, and Satisfaction Model
Appendix C. The Process of College English Listening Teaching in the Control Class
Note. In this teaching process, teachers assist students in understanding the listening content through detailed explanations and translations, and students passively acquire knowledge.
The authors declare no conflicts of interest.
The data that support the findings of this study are available on request from the corresponding author.
Zhonger Wang, School of Foreign Languages, Shanghai Lixin University of Accounting and Finance, No. 995 Shangchuan Road, Pudong New Area, Shanghai, 201209, People’s Republic of China. Email: [email protected]
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