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Article

The Effects of Blended Learning on Learning Engagement in Physical Education Among University Students in China: The Mediating Role of Attitudes

by
Yanan Yu
1,2,*,
Khairudin Bin Che Tak
2,
Richard Peter Bailey
2,
Nadia Samsudin
2 and
Ce Ren
2
1
College of Physical Education, Shandong Normal University, Jinan 250014, China
2
Faculty of Social Sciences and Liberal Arts, UCSI University, Kuala Lumpur 56000, Malaysia
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(2), 378; https://doi.org/10.3390/su17020378
Submission received: 30 October 2024 / Revised: 24 December 2024 / Accepted: 2 January 2025 / Published: 7 January 2025
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Abstract

:
Under the pedagogical concept of sustainable development, an increasing number of interdisciplinary pedagogies are being applied in physical education, moving away from traditional face-to-face teaching methods. This study investigated the influence of blended learning on students’ engagement in physical education and the role of attitudes in this process. A questionnaire was used to validate the model based on a comprehensive literature review. PLS-SEM was used to assess the direct relationship between blended learning and learning engagement in physical education and the mediating influence of attitudes toward blended learning on these factors. The findings revealed that face-to-face sessions and students’ attitude toward blended learning positively affect their engagement in physical education. The results also indicated that students’ attitudes significantly mediate course design, learning experience, and face-to-face sessions with learning engagement. Based on the variable relationship, this study proposes a blended learning strategy rooted in the Five-star Teaching Model. By stimulating students’ initiative in learning, their attitude improved, enhancing their engagement in physical education classes. This research holds both theoretical and practical significance by improving the quality of physical education teaching and learning methods, offering novel insights into instruction in this field.

1. Introduction

Integrating physical education (PE) into school curricula as a compulsory course is critical for developing healthy citizens. Student engagement is considered a key educational and behavioral outcome that provides insight into students’ motivational processes in PE classes [1]. It is widely recognized as an area in the school curriculum related to fostering students’ physical abilities and confidence and their ability to use them in various activities [2]. Appropriate instruction is an essential component of quality PE, which integrates students’ learning engagement and achieves grade-level learning outcomes [3]. Modern active learning techniques, especially those that support student-centered teaching and learning approaches, are currently conventional classroom teaching methods.
The development of digital technology has affected the teaching-learning process in higher education institutions. Blended learning (BL) as a learning method has been described as a part of face-to-face (F2F) coaching and technology-enhanced learning [4]. In this type, the teacher and the students are physically in the class but interact virtually using a chosen e-learning platform. Rich course materials and learning resources are available to students, which can support individualized instruction and make up for the time and space constraints in traditional classroom settings [5].
The central goal of the school should be to enable students to participate in valuable relationships, activities, and experiences independently, wholeheartedly, and successfully [6]. Teachers’ actions and interactions determine whether students experience positive aspects of PE and know their great potential [2]. Positive outcomes of PE require specific conditions, such as a high-quality teaching strategy, appropriate curriculum content, and a supportive social environment [7]. Currently, most PE teachers still use traditional teaching methods in the classroom. This teacher-centered learning method is based on teachers’ explanation and demonstration, with students primarily imitating and following along, and acquiring physical skills through repeated practice [8]. While this mode of learning can help students successfully master physical skills, it lacks in-depth thinking and reflection on the part of students. Instead, they rely solely on the teacher’s guidance and demonstration for practice, which reduces students’ engagement and makes it difficult to improve the quality of PE [9]. Furthermore, this teaching method caters to all students, which does not allow individual differences and cannot address teachers’ limitations in providing personalized guidance and tutoring [10]. Therefore, there is a need for a more holistic, interdisciplinary approach to PE, which ensures qualitative access to knowledge and contributes to the development of key competencies [11].
Advances in digital technology have significantly impacted the teaching methods and learning outcomes in higher education. Recently, the development of educational reform calls for a more effective and urgent integration of technology and higher education [12]. As emphasized by D’Angelo [13], technology plays an important role in promoting students’ engagement in learning, which further enhances academic success. Technology provides students with more opportunities for multimodal learning and a range of interactive behaviors that can enhance their learning experience and facilitate their understanding of more complex concepts [14]. Incorporating more technology into the curriculum can promote opportunities for student engagement in learning and promote academic success by facilitating active inquiry-based learning, synthesizing information knowledge, and enhancing student interaction. This can make the learning environment more learner-centered, with teachers playing a facilitating role to help students achieve their learning goals [15].
The integration of technology into the curriculum not only provides teachers with the opportunity to amplify learning engagement [16] but also facilitates inquiry-based learning, in line with the findings from [14]. Although digital technology provides a toolkit, it also requires appropriate teaching methods to enable students to fully engage in these technological spaces and improve learning efficiency [17].
Students’ attitudes are pivotal in shaping their learning outcomes and academic performance [18]. Negative attitudes are negatively related to engagement [19]. Meanwhile, students’ attitudes are formed by various direct and alternative means [20]. Research has shown that in an English-speaking environment, students have a moderately positive attitude toward BL compared to traditional classrooms [21]. However, Candarli and Yuksel [22] argued that students had negative attitudes toward using online instruction at school. Therefore, what attitudes do in different disciplines needs to be confirmed accordingly.
To achieve the study’s goals, interviews were conducted with 10 PE teachers and 30 students from three universities. The interviews with the teachers revealed that students often exhibit low engagement levels in PE, primarily manifested through factors such as low motivation and avoidance behaviors [23]. This disengagement is particularly evident in students’ attendance records and their performance in physical fitness assessments. While students generally expressed positive attitudes toward PE, they were found to be inactive during class and rarely completed their homework assignments. Several factors contributing to this lack of engagement in PE were identified, including past experiences, curriculum design, socio-demographic factors, perceived self-efficacy, and social interactions [24].
In this context, this study explores the role of the BL method in enhancing university students’ learning engagement in PE. It investigates the mediating role of students’ attitudes toward the BL in PE. The following research topic served as the basis for the investigation:
RQ1—How do students’ attitudes toward BL affect learning engagement in PE among university students?
RQ2—How does BL affect learning engagement in PE among university students?
RQ3—How does BL affect students’ attitudes?
RQ4—How do students’ attitudes toward BL in PE influence their engagement in BL approaches and their engagement in PE classes at the university level?

2. Literature Review

The research variables for this study were selected based on the theory of planning behavior theory and constructivism.

2.1. Learning Engagement

The pedagogically related construct of learning engagement has been of concern to scholars since the 1990s, especially to factors that encourage student participation in learning activities and the involvement of institutions and educators in this process [25]. In the context of PE, learning engagement is viewed as a behavioral reflection of a student’s motivational processes that can be measured, thus emphasizing its significance in educational research [26]. Participation in PE is not a distortion of focus phenomena, but it is emergent from the complex interrelations that exist between a learner and the educational context within which they are placed and the contextual factors that are taken for granted [27]. As a result of the evolution of educational technology, teachers have started to try new ways of online teaching to increase learners’ level of satisfaction and their level of participation [28]. Such endeavors fit into the wider context of educational reforms that are seeking to harness technology to drive sustainable development in education [29]. For example, it is argued that the experience of learning engagement at the college and university education levels can be greatly enhanced through the use of digital resources [30]. The online learning engagement issue, particularly in subjects that rely on active participation, such as PE, has become more pronounced within these broader dynamics. Finding ways to encourage learner engagement in online PE classes is paramount for advancing both the theory and practice of education in the age of technology.

2.2. Teaching Strategy

Constructing effective teaching practices is essential in boosting the retention and engagement of students within any educational system. Factors such as the profile of the learners, the functional use of some e-learning tools, and the degree of independence among learners are crucial. The use of technology in education has also been positively correlated with the effective implementation of such approaches as inquiry-based approaches, which focus on critical and engaging learning experiences (LEs) [15]. Several studies suggest that any technology-enhanced instruction can help acquire higher-level skills such as evaluation, comprehension, and application appropriate for the 21st-century learner [31]. However, for the successful use of education with digital technologies, there has to be a very careful, purposeful use of instruction. This approach should focus on creating an environment for students’ effective attention and motivation, enhancing understanding of the content, and meeting the requirements of the respective learning environment [14].

2.3. Attitudes

An individual’s objectives, perspectives, perceived abilities, and social interactions, such as those with peers or others, influence the behavioral decisions one makes [6,32]. An individual’s attitude toward BL is the readiness to use a mix of online and F2F methods for content delivery, including F2F teaching [33]. A favorable attitude toward BL has been shown to enhance students’ preferences for learning in this framework, particularly by promoting interactivity, autonomy, and engagement [34].
Students can access learning materials from their own equipment at any time, allowing them to learn at their own pace [35]. In addition, the relationship patterns observed through empirical data indicate a close linkage between one’s attitude toward digital technology and their learning engagement factors, which concern the student’s attitude toward the educational process as a whole [36]. Hence, these results underscore the need to investigate attitudes not only as potential moderators but also as potential agents of engagement across various educational settings. To further explore the role of attitudes in the adoption of BL and their impact on learning engagement, the following hypotheses were formulated:
H1: 
Attitude towards BL has a positive impact on learning engagement in PE.

2.4. Blended Learning

The combination of computer-mediated instruction and F2F learning in BL develops an educational environment that is somewhere in between physical and virtual learning spaces [37]. This variability in the structure of the combination allows teachers to vary their approach to the instruction as well as enhance the level of personalized and flexible education that learners receive [38]. Owing to the fact that BL approaches tend to involve students more in the educational processes coupled with better academic achievement, it has gained wider acceptance in the post-secondary systems [39]. Since engagement is fundamental to effective learning, it is necessary to encourage students to engage in both F2F and online environments consistently to address the challenges related to the effective engagement of learners [40].
H2: 
BL has a positive impact on learning engagement in PE.
Nonetheless, it is important to note that not every student, nor every group, responds positively to the use of technologies, nor does every group respond positively in the same way. This issue clearly shows that teachers and students must adapt to the challenges posed by the education technique and use other forms of communication, motivation, and learning strategies [41]. As a result, it has become important to study how BL can be instrumental in increasing student engagement in modern educational research [42,43]. The factors deemed to be the cornerstones of the success of BL are the F2F interaction, effective course design (CD), and augmentation of learning activities.
H3: 
BL has a positive impact on attitude towards BL.

2.4.1. Face-to-Face

In F2F teaching models, lectures tend to be the primary method of instruction, while the time spent on activities and group work tends to be somewhat limited [44]. In the context of addressing problems and practicality, F2F learning is greatly preferred by many students [45]; however, this model unintentionally seems to stunt critical thinking development and other possibilities of the students [46]. While BL is not a universal remedy, it addresses some of the issues mentioned above by integrating the best features of F2F and online learning. Where F2F instruction is used to fill in the gaps created when teaching materials or formats are unavailable online. In particular, it has been found that greater amounts of F2F learning in BL settings are accompanied by more learning activities in a virtual environment, thus establishing the interdependence between both forms of learning [47]. This interaction illustrates the need to rethink existing conceptions of learner engagement to fit the two-sided nature of BL. This leads us to the following hypothesis:
H2a: 
F2F teaching has a positive impact on learning engagement in PE.
Attitudes toward BL are closely related to both the F2F education and the online learning models, which enhances the possibility of more diverse and creative instructional strategies [48]. For instance, the use of cooperative learning tasks and problem-based activities within blended courses has been reported to improve the students’ attitudes toward teaching and learning [49]. To find out how the incorporation of F2F instruction in BL affects these attitudes, the following hypothesis is proposed:
H3a: 
F2F in BL has an active and positive impact on attitude.

2.4.2. Course Design

In BL, it is described how CD supplements F2F teaching and online teaching to attain the desired productivity. This integration is anchored on quality content, interactions between teachers and students, collaborations between students, and other fruitful LE [50]. Properly developed CD preparatory work corresponds to the competencies of the online students, thus providing them with more opportunities for participation in the process [51]. When CD includes basic course details even in an online format, such as the course description, course rationale, learning objectives, scope of learning, and expected results, there are higher chances for students to understand the significance of CD in relation to the entire course [52]. Additionally, including the affective, cognitive, and behavioral aspects of engagement in CD would assist students’ further academic success [53]. In the context of the integration of CD of PE, it is necessary to consider the suitability of the content, the specification of the teaching goals, and the alignment with the student’s needs to enhance the personalized features of LE [6]. Furthermore, designing activities that promote students’ higher levels of engagement and more positive attitudes also seems to help improve learning outcomes. In order to particularly understand the role of CD in engaging students in learning PE through BL models, we put forward the following hypothesis:
H3b: 
CD in BL has an active impact on attitude.

2.4.3. Learning Experience (LE)

LE is an important aspect of the BL model as it combines teachers’ interactions with students in a classroom as well as contextual factors that enhance all the learning and interactions [54]. It emphasized the role of aspects such as the course’s structure and organization, the content development level, and the complexity of assignments for students’ assessments of satisfaction with the online course [55]. It has been shown that LE can increase students’ perception of BL, as well as their satisfaction with technology use in coursework activities [56]. Additionally, it has been found that the use of technology and interactive activities increases the level of participation of the learners [57].
In the context of PE, the specific role of LE in influencing learning engagement in BL environments remains underexplored. Addressing this gap, the following hypothesis is proposed:
H3c: 
LE in BL has an active impact on attitude.

2.5. The Intermediary Role of Attitude

Attitude is often seen as the most important intervening variable in learning. In the case of BL, attitudes act as a moderating variable that helps to explain the relationship between learning and interest in performing it. In order to study the mediator role of attitude, the following hypothesis is proposed:
H4: 
Attitude mediates between BL and learning engagement in PE.
Particularly, the conversations that students have with their teachers’ F2F are important in influencing students’ views and attitudes about particular subjects and their intensity of participation. However, some of the research suggests that, compared to distance learning, learners’ achievement and motivation levels seem to be lower in normal F2F learning classrooms [58]. On the contrary, positive attitudes strongly relate to increased school persistence and lowered burnout scores at the same time [59]. To make the relationship between F2F interactions and learning engagement in PE clearer, the mediating factor of attitude needs to be examined closely, which leads us to the following hypothesis:
H4a: 
Attitude mediates between F2F and learning engagement in PE.
A well-articulated CD can manipulate attitudes through the appropriate offering of information about the course ideas, which allows the students to possess the skills needed to ensure consistency between desirable behaviors and practiced ones [60]. Students tend to pay more attention to, among others, the instructor, the course materials, and the classroom environment [61]. The other is the degree to which attitude acts as an intermediary between CD and learning engagement, which remains scanty. This gap in understanding forms the basis for the following hypothesis:
H4b: 
Attitude mediates the relationship between CD and learning engagement in PE.
It is also important that students’ attitudes toward technology are shaped in the process of LE. By adopting a positive attitude, students are more willing to utilize different technological tools, making them work and learn actively. This is all the more apparent in students’ attitudes toward technology as LE encourages positive actions toward using technology in learning, creating an interdependent relationship [62]. Additionally, the impact of technology and other practices on learning engagement has been widely studied and is positive [57]. Nonetheless, there is still a gap in the literature about the role of attitude in the relationship between LE and learning engagement in PE, which necessitates the following hypothesis:
H4c: 
Attitude plays a mediating role between LE and learning engagement in PE.
These hypotheses form the foundation for a conceptual research model, depicted in Figure 1, which integrates the mediating role of attitude across key relationships in the BL context.

3. Research Methodology

This study employed quantitative approaches to resolve the research questions. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used as a quantitative approach to explore the relationship between BL and learning engagement in PE and the mediating role of the attitude toward the BL.

3.1. Population and Sampling

There are 1238 general undergraduate universities in China, with up to 4.59 million undergraduates enrolled as of 2023. Three schools that had been adopting BL methods in PE classes among non-PE major students for several years were selected. There are 28,587 first-year and second-year students in these schools who have a 90 min PE class once a week. Following the recommendation on the minimum sample size requirement, known as the 10 times rule by Hair [63], the number of samples should be at least 10 times the number of indicators. The sample size for the current study was established to be at least 250 individuals, which is more than 101 calculated by G-power. This determination was made based on the number of items included in the questionnaire. Convenience sampling is a non-probabilistic technique where researchers aim to select easily accessible participants [64]. The study employed a convenience sampling method to identify a final sample size of 351 respondents, which was considered sufficient for conducting PLS-SEM. The entire class was chosen from different sports programs.

3.2. Participants

The study involved 351 first-year and second-year students (165 males and 185 females) from three universities that offer BL of PE courses in China. These students participated in a PE course with BL lasting one to three semesters, which included weekly 90 min F2F sessions. The online component of the BL was administered through the Superstar platform and designed to grant students the autonomy to engage in self-directed learning. The sample indicated that 53% of the students were female, while 47% were male. According to the sample description, 69.3% of participants were aged between 19 and 20 years, 23.5% were under 19, and 7.2% were over 20.

3.3. Measurements

All participants actively engaged in the study and completed self-report questionnaires, assessing key variables such as CD, LE, F2F, attitudes, and learning engagement in PE. A five-point Likert scale was used to measure all the variables. It is the most basic scale, which requires participants to indicate their consent or disapproval or believe that it is true or false, consisting of five main response categories: 1 represents strongly disagree, 2 represents disagree, 3 is the meaning of neutral, 4 represents agree, and 5 represents strongly agree. Participants expressed their perceptions, with each question structured around the common stem, “In my PE class…”. Additionally, participants furnished demographic information, including age, gender, and grade level.
The structure of CD was assessed through five items adapted from Bhagat et al. [65]. The LE’s structure was adapted from Bhagat et al. [65]; three items were used to assess this construct. The structure of F2F was evaluated through three items adapted from Akkoyunlu and Yılmaz-Soylu [66]. In the structure of attitude adapted from Subramaniam and Silverman [67], five items were used to measure student perceptions of BL and PE classes, focusing on student preferences and the usefulness of PE classes. In the structure of learning engagement in PE adapted from Chi [68] and Xiang [69], nine items were used to assess students’ learning engagement of: behavioral engagement, cognitive engagement, and emotional engagement.
To ensure the validity and reliability of the self-reported measures for the Chinese student sample, the translation process followed three steps, as outlined by Agbuga et al. [26]. Initially, two researchers who were proficient in Chinese and English and a bilingual physical educator scrutinized all questionnaire items. A reverse translation from Chinese to English was then executed, revealing only minor word adjustments that did not significantly impact the content. Subsequently, a pilot study was conducted with 30 students who did not participate in the formal survey to validate the readability of the translated questionnaire items. No questions were raised.

3.4. Data Collection

The study’s questionnaire was distributed to the target students through Questionnaire Star, an online platform designed to facilitate the distribution and collection of data, similar to Google Forms. During regularly scheduled PE classes at three universities, participants were surveyed using Questionnaire Star. Written Informed Consent was obtained from all participants, and the subjects provided approval questionnaires. To obtain their honest and trustworthy feedback, the students were given a clear explanation of the purpose behind filling out these questionnaires prior to them doing so. To minimize Common Method Variance (CMV), as self-reported measures can introduce it, all evaluation was kept anonymous. Students were given 20 min to respond to the questionnaire, and no major problem appeared.

3.5. Data Analysis

The primary analytical technique employed in this study is Partial Least Squares Structural Equation Modeling (PLS-SEM). Specifically, this paper utilizes the variance-based PLS-SEM method, which is well-suited for exploratory research. In a multi-group PLS-SEM framework, the moderating effect is identified by comparing the heterogeneity among target groups with respect to causal relationships [70]. Additionally, PLS-SEM has a smaller sample size requirement than traditional regression analysis, making it an ideal choice for this study [71]. Accordingly, the PLS-SEM analysis was conducted using Smart PLS version 4.0.

4. Results

4.1. Assessment of Measurement Model

4.1.1. Internal Consistency Reliability and Convergent Validity

As shown in Table 1, the internal consistency of all indicators exceeds the recommended benchmark of 0.708 [63]. Three main criteria—the outer loading, composite reliability (CR), and the average variance extracted (AVE)—are considered to measure reliability in terms of convergent [72]. It can be seen in Table 1 that the range of CR is from 0.925 to 0.981, above the benchmark of 0.708. In addition, the results show that the range of AVE is from 0.800 to 0.873, exceeding the 0.500 [63]. Thus, the criteria for internal consistency and convergent validity are met. In addition, the mean value for all structures is above 4.000, t greater than 2.500 [71]. This indicates that the mean values based on the benchmark scale are valid.

4.1.2. Discriminant Validity

Distinguishing validity measures the uniqueness of each construct and ensures that it is different from the others. In this study, the Fornell–Larcker criterion was adopted for assessment. For the criterion of Fornell-Larcker, a construct is considered valid when the square root of its AVE is higher than its highest correlation with any other construct, indicating that it is distinct from other constructs [63]. Table 2 is the Fornell–Larcker criterion of the mode. It can be seen that the square AVE values of each construct bolded in the table are relatively higher than the correlation values with other constructs, and all are greater than 0.500 [71]. Therefore, the discriminant validity of this study is good.

4.2. Assessment of Structural Model

4.2.1. Direct Effect Assessment

Measurement and interrelationship of the latent construct are the main ways to evaluate the structural model. It is performed by solving for path coefficient values (β), which assess significant associations among structures taking the PLS technique, depending on the significance level noted in their corresponding coordination to each other. Standard errors of path coefficients are important and can be obtained by bootstrapping. The minimum recommended number of bootstrapping for this study is 5000 [63]. The Bootstrap Standard shows the empirical t-values and p-values of all structural path coefficients. At a significance level of 5%, the critical value for a one-tailed test is 1.650 [63]. For exploratory research, it is recommended that researchers typically assume a significance level of 10% (critical t-value = 1.280).
In addition, the coefficient of determination (R2) is an evaluation of the model’s predictive ability and is calculated based on the squared correlation between variables in the model. The range of R2 is from 0 to 1. The higher the R2, the higher the accuracy of the prediction. The value of R2 is 0.75, 0.50, or 0.25, representing substantial, moderate, or weak [63]. The results in Figure 2 indicate that the path coefficient of (H1) is 0.665 (t = 9.433, p = 0.000), and therefore, the support (H1) shows that attitude has a positive and significant effect on learning engagement in PE. Similarly, the path coefficient of (H2) is 0.234 (t =3.087, p = 0.001). Therefore, (H2a) is established, which indicates that F2F has a significant effect on learning engagement in PE. Next, (H3a) states that F2F positively and significantly affects attitude. The results of (H3a) are significant when the path coefficient is 0.561 (t = 7.717, p = 0.000). Similarly, the results in Table 3 indicate that CD has a positive effect on attitude (H3b) with a path coefficient of 0.154 (t = 1.859, p = 0.032). At last, the path coefficient of (H3c) was 0.238 (t = 2.710, p = 0.003), which indicates a statistically significant effect of LE on attitude.
A further evaluation for strengthening the R2 value can be conducted by assessing the magnitude of the f2 effect. Therefore, the results of f2 shown in Table 3 are used to validate the effect size. The value of f2 is 0.35, 0.15, or 0.02 for the exogenous latent construct indicating large, medium, or small [63]. The f2 for ATT has a large effect on LEPE (0.358). The medium effect size for F2F on ATT (0.343). The f2 has a small effect for F2F on LEPE (0.044). The f2 of 0.033 and 0.049 indicate the effect size for CD and LE, which both have a small effect on ATT.

4.2.2. Mediating Effect Assessment

Multiple mediation is a design that has received little attention in both the methodology and applied literature. In order to run a multiple mediation analysis, the current study utilized a bootstrapping method to obtain specific indirect effects. Indirect effects were calculated using Smart PLS sampling distributions for indirect effects with Smart PLS 4.0 software. Statistically significant indirect effects (t-value > 1.65, p < 0.050) should be taken as evidence of mediation caused by the directed hypothesis.
The bootstrapping results, as presented in Table 4, indicate that CD positively influences learning engagement in PE through attitude, with a path coefficient of 0.103 (t = 1.751, p = 0.040), thereby supporting Hypothesis 6 (H6) and confirming that attitude mediates the relationship between CD and learning engagement in PE. Similarly, the results show that the path coefficient for Hypothesis 4a (H4a) is 0.158 (t = 2.591, p = 0.005), further supporting H4b and validating the mediating role of attitude between LE and learning engagement in PE. Finally, the analysis reveals that attitude also mediates the relationship between F2F and learning engagement in PE, with a path coefficient of 0.373 (t = 5.834, p = 0.000), thus supporting Hypothesis 4b (H4b).

5. Discussion

Based on the analysis, our results indicate that students’ attitudes toward BL positively influence learning engagement in PE. This is consistent with the findings of many scholars. Learners’ positive attitude toward digital technology can facilitate their learning process in the classroom [73]. In addition, positive attitudes were correlated with the frequency of using technology to learn related subjects [74].
The study found that F2F significantly affected students’ learning engagement in PE. PE courses differ fundamentally from other academic subjects. While many courses focus on mastering theoretical knowledge and skills within a controlled environment, PE requires acquiring knowledge related to physical movement and repeated practice through physical and mental activities to develop proficiency in techniques and skills specific to the discipline [5]. Unlike other subjects, which primarily involve cognitive exercises and the mastery of theoretical concepts, PE allows students to acquire specialized knowledge, techniques, and skills through hands-on learning. Consequently, while BL offers numerous benefits, F2F instruction remains essential to the PE teaching process.
Meanwhile, F2F sessions were found to have a positive and significant correlation with students’ attitudes throughout the study. Among the many factors, F2F sessions had the strongest effect on attitude. However, studies found that F2F courses generally have a greater impact on attendance and performance than online formats [75]. However, in certain cases, online formats can yield superior results. It is essential to emphasize the creation of engaging learning environments that foster meaningful interactions between instructors and students, even within virtual spaces. This is particularly important when coupled with F2F instructional guidance. CD has a positive effect on students’ attitudes. This is consistent with Erdoğdu’s [59] research, which proved that the design of learning activities can foster a better attitude toward learning [59]. Online education using active learning methods can positively influence learning attitude compared to F2F education, and reduce learning avoidance. Therefore, a good CD can promote students’ active learning and positively influence their learning attitude. Finally, LE also promotes students’ attitudes. Prior LE can influence students’ readiness, attitude, and self-control in follow-up online learning environments. A good LE positively contributes to students’ attitudes, and conversely, a bad LE can negatively impact students’ attitudes. Creating a pleasant online learning environment can enhance students’ LE, thus improving students’ attitudes toward learning [76]. The LE can be enhanced by combining structured learning with flexibility.
The results of the study showed that attitude also had a significant role between F2F sessions and learning engagement in PE. Although attitude serves as a partial mediator in this case, the independent and dependent variables still exhibit a substantial association even after the inclusion of the mediating variable [77]. This also supports Marquardt and Happe’s [78] study that students generally have more positive attitudes toward F2F learning, which may affect their engagement in the program.
In addition, CD and LE can positively influence students’ attitudes. According to Baron and Kenny [77], when the mediation variable is added, the difference between the independent variable X and the dependent variable Y is no longer significant, and the relationship is completely mediated. In other words, the CD and LE in BL bring to students will indirectly affect PE learning through students’ attitudes. This fully demonstrates the important role of students’ learning initiative, consistent with Heflin and Macaluso’s previous research [79]. Students who exhibit higher levels of independence in BL courses will also have higher levels of engagement and effort. It can be seen that it is particularly important to enhance students’ initiative to improve their learning engagement in PE.
In the study, it employed factor analysis within a cross-sectional design and did not include a longitudinal comparative study. Furthermore, since PE emphasizes more physical activities, implementing the BL approach may not be consistent across schools. This could imply that while students may behave and learn similarly, teachers employ different teaching methods. To better play the role of BL, we propose the following strategies.

6. The Strategy of Blended Learning in Physical Education

Simulating students’ learning initiatives is a primary goal of BL instruction. Based on a quantitative study of the learning engagement in PE on BL, a personalized education teaching strategy for BL named the “Five-Star Teaching Model” is proposed. The Five-Star Teaching Model is an educational concept founded by educational psychologist and instructional designer, David Merrill. It emphasizes the significance of instructional cycles centered on problem-solving, which includes activating existing knowledge, demonstrating new knowledge, and engaging in applications to achieve comprehensive mastery (Figure 3).
The utilization of the Five-star Teaching Mode in PE aims to fulfill the goal of student-centered instruction, thereby producing high-quality teaching outcomes [80]. As illustrated in Figure 4, CD emphasizes a blend of online and offline activities, from task assignment to thorough mastery. Students should focus on the goal, activate their past experience to acquire new knowledge, and practice to demonstrate their learning in a group cooperative manner. In F2F, teachers answer questions, correct mistakes, and provide feedback and evaluation on students’ learning progress. Once students have fully mastered the knowledge, the teacher reflects on and improves the course [80] and begins the next teaching cycle. CD, LE, and F2F do not exist independently or sequentially. They are represented through mutual crossover.
To validate this educational strategy’s dependability, three distinguished experts from the Curriculum Evaluation Group and Curriculum Pedagogy Division of the Ministry of Education in China were invited to assess its effectiveness. They uniformly indicated that the BL approach fosters student engagement and enthusiasm for the subject matter and enhances their learning ATT and performance, making it a practical and viable option for academic advancement.

7. Implications of Study

7.1. Theoretical Implications

The findings of this study have theoretical implications for educators and PE practitioners in higher education institutions. They offer valuable insights into how students can adopt optimal strategies to maintain performance in PE and how teachers can implement problem-solving activities to enhance students’ active involvement and foster higher achievement. Our results emphasize the importance of stimulating students’ learning initiative and effectively integrating online resources with face-to-face instruction. Such integration fosters positive LE, which, in turn, contributes to changes in students’ attitudes and facilitates the development of desired behaviors. Therefore, we advocate for increased institutional support for both students and faculty, as such support is crucial in shaping attitudes toward adopting BL approaches.

7.2. Practical Implications

This study offers practical suggestions for teachers and educational institutions to enhance BL programs in China. In many countries, universities do not require PE courses. However, PE is compulsory across all faculties at colleges and universities in China. Implementing the BL system for PE in China is not uniform across all universities and colleges, and the availability of digital resources for this discipline is limited. Consequently, the design of BL must also be recognized and adopted by a greater number of PE teachers. In the era of digital network multimedia, universities are seeking to enhance their curriculum content by incorporating internet-based media resources in alignment with practices observed in other academic disciplines. However, the unique nature of the PE subject necessitates that the importance of traditional teaching methods is not overlooked. This study aims to integrate online learning resources with F2F instruction seamlessly. The innovative approach discussed herein has the potential to provide new insights and cognitive frameworks for the field of PE.

8. Conclusions

A research model has been developed to investigate the factors that influence learning engagement in PE within higher education settings. The results of this study confirmed that F2F sessions and attitudes toward BL positively affect students’ engagement in PE. And the attitude towards BL as the mediator between all the factors in BL and PE learning engagement. The empirical evaluation of the adoption of BL, utilizing PLS-SEM in this study, supported all hypotheses proposed in the study. Based on the results of this empirical evaluation, the “Five-Star Teaching Model” is proposed for implementation in PE classes with BL to enhance learning engagement in PE among university students.

9. Future Works

Building upon the findings of this study, future research should broaden its focus to include diverse populations, such as primary and secondary school students, educators, and educational institutions, to gain a more comprehensive understanding of the impact of BL on PE. In addition, it would be valuable to examine the implementation of BL in different cultural and geographical contexts, exploring how regional or national differences influence its effectiveness. Future studies should assess the pedagogical outcomes of BL and investigate other critical dimensions, such as the learning environment, students’ psychological needs, and overall learning outcomes. Furthermore, future research could benefit from exploring BL’s affective components and examining how emotional and motivational factors influence its success in PE settings. This multifaceted approach will provide a more nuanced and comprehensive understanding of the complexities of implementing BL in PE.

Author Contributions

Conceptualization, Y.Y.; Methodology, Y.Y.; Validation, R.P.B.; Investigation, N.S.; Resources, C.R.; Data curation, Y.Y. and C.R.; Writing—original draft, Y.Y.; Writing—review & editing, K.B.C.T. and R.P.B.; Visualization, N.S.; Supervision, K.B.C.T. All authors have read and agreed to the published version of the manuscript.

Funding

Shandong Normal University: 2024MJ13.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of School of Physical Education, Shandong Normal University (SDNUTYDW2024012).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Developed research model. Note: ATT = attitude; LEPE= learning engagement in physical education.
Figure 1. Developed research model. Note: ATT = attitude; LEPE= learning engagement in physical education.
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Figure 2. The results of the structural model. Note: ATT = attitude; LEPE= learning engagement in physical education.
Figure 2. The results of the structural model. Note: ATT = attitude; LEPE= learning engagement in physical education.
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Figure 3. Construction diagram of the five-star teaching method.
Figure 3. Construction diagram of the five-star teaching method.
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Figure 4. The strategy of blended learning in physical education. Note: Red dashed is what distinction between online and offline; blue dashed is the distinction between teacher and student tasks.
Figure 4. The strategy of blended learning in physical education. Note: Red dashed is what distinction between online and offline; blue dashed is the distinction between teacher and student tasks.
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Table 1. Reliability, convergent validity, and descriptive analysis.
Table 1. Reliability, convergent validity, and descriptive analysis.
VariablesIndicatorOuter LoadingsαCRAVEMeanSDRating
CDCD10.9210.951 0.952 0.873 4.377 0.809effective
CD20.936
CD30.935
CD40.946
F2FF2F10.9460.925 0.9250.870 4.366 0.770effective
F2F20.940
F2F50.911
LELE10.9280.951 0.951 0.872 4.345 0.813effective
LE20.940
LE30.937
LE40.929
ATTATT10.9090.966 0.966 0.831 4.313 0.792effective
ATT20.922
ATT30.907
ATT40.930
ATT50.929
ATT60.881
ATT70.901
LEPEBLE10.8750.981 0.981 0.800 4.369 0.693effective
BLE20.903
BLE30.888
BLE40.883
BLE50.908
CLE10.929
CLE20.897
CLE30.907
CLE40.912
CLE50.911
ELE10.894
ELE20.828
ELE30.920
ELE40.864
Note: SD = standard deviation; ATT = attitude; LEPE= learning engagement in physical education.
Table 2. Fornell–Larcker criterion.
Table 2. Fornell–Larcker criterion.
ATTCDF2FLELEPE
ATT0.911
CD0.8390.934
F2F0.9070.8480.933
LE0.8820.8810.9070.934
LEPE0.8780.7670.8380.8080.894
Note: ATT = attitude; LEPE= learning engagement in physical education.
Table 3. Direct effect assessment.
Table 3. Direct effect assessment.
HypothesisPath Description
(Standard β)		Path CoefficientStandard Errorf2t Valuesp ValuesDecision
H1ATT → LEPE0.6650.0710.3589.4330.000 **Accepted
H2aF2F → LEPE0.2340.0760.0443.0870.001 **Accepted
H3aF2F → ATT0.5610.0830.3436.7170.000 **Accepted
H3bCD → ATT0.1540.0830.0331.8590.032 *Accepted
H3cLE → ATT0.2380.0880.0492.7100.003 **Accepted
Note: *. This has met the significance level (p < 0.05); **. This has met the significance level (p < 0.01); Bootstrapping (n = 5000); t-value ≥ 1.28 to be significant; ATT = attitude; LEPE= learning engagement in physical education.
Table 4. Mediating effect assessment.
Table 4. Mediating effect assessment.
HypothesisPath Description
(Standard β)		Path CoefficientStandard Errort Valuesp ValuesDecision
H4aCD → ATT → LEPE0.1030.0591.7510.040 *Accepted
H4bLE → ATT → LEPE0.1580.0612.5910.005 **Accepted
H4cF2F → ATT → LEPE0.3730.0645.8340.000 **Accepted
Note: **. p < 0.010; *. p < 0.050; Bootstrapping (n = 5000); t-value ≥ 1.65 to be significant; ATT = attitude; LEPE= learning engagement in physical education.
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Yu, Y.; Che Tak, K.B.; Bailey, R.P.; Samsudin, N.; Ren, C. The Effects of Blended Learning on Learning Engagement in Physical Education Among University Students in China: The Mediating Role of Attitudes. Sustainability 2025, 17, 378. https://doi.org/10.3390/su17020378

AMA Style

Yu Y, Che Tak KB, Bailey RP, Samsudin N, Ren C. The Effects of Blended Learning on Learning Engagement in Physical Education Among University Students in China: The Mediating Role of Attitudes. Sustainability. 2025; 17(2):378. https://doi.org/10.3390/su17020378

Chicago/Turabian Style

Yu, Yanan, Khairudin Bin Che Tak, Richard Peter Bailey, Nadia Samsudin, and Ce Ren. 2025. "The Effects of Blended Learning on Learning Engagement in Physical Education Among University Students in China: The Mediating Role of Attitudes" Sustainability 17, no. 2: 378. https://doi.org/10.3390/su17020378

APA Style

Yu, Y., Che Tak, K. B., Bailey, R. P., Samsudin, N., & Ren, C. (2025). The Effects of Blended Learning on Learning Engagement in Physical Education Among University Students in China: The Mediating Role of Attitudes. Sustainability, 17(2), 378. https://doi.org/10.3390/su17020378

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