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Article

Cross-Regional Students’ Engagement and Teacher Relationships Across Online and In-School Learning

by
Huiqi Hu
1,2,*,
Yijun Wang
2,* and
Wolfgang Jacquet
1,3
1
Department of Educational Sciences EDWE-LOCI, Faculty of Psychology and Educational Sciences, Vrije Universiteit Brussel, 1050 Brussels, Belgium
2
Institute of Vocational Education, Tongji University, Shanghai 200070, China
3
Department of Surgical Clinical Sciences CHIR-ORHE, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, 1050 Brussels, Belgium
*
Authors to whom correspondence should be addressed.
Educ. Sci. 2025, 15(8), 993; https://doi.org/10.3390/educsci15080993
Submission received: 21 June 2025 / Revised: 24 July 2025 / Accepted: 25 July 2025 / Published: 5 August 2025
Review Reports Versions Notes

Abstract

This study examines how teacher–student relationships and school engagement change across online and in-school learning, based on the experiences of 105 cross-regional secondary vocational students in China. Using questionnaire surveys, the study explores students’ perceptions and learning needs in both settings. The findings confirm that teachers play a consistently positive role in promoting student engagement across both online and in-school learning modalities. While affective engagement was higher during online learning, driven by stronger teacher responsiveness and improved student–teacher relationships, students reported increased pride in their schools after returning home, reflecting a renewed appreciation. In-school learning was associated with higher behavioral engagement and greater motivation, despite tensions over intensified academic tasks. Online learning facilitated cognitive engagement through easier vocabulary searches; nevertheless, poor home environments reduced motivation. Enhancing engagement may require offering students autonomy, valuing their input, and clarifying the relevance of the learning content.

1. Introduction

High-quality interactions between teachers and students serve as a crucial foundation for students’ academic learning, psychological development, and overall mental well-being (Doyle et al., 2022). Teachers not only facilitate the acquisition of knowledge but also play a central role in shaping students’ affective and behavioral engagement with school (Moreira et al., 2018). School engagement itself is a multidimensional construct encompassing students’ behavioral, emotional, and cognitive involvement in learning, and has been consistently linked to positive educational outcomes, including higher academic achievement and a reduced risk of school dropout (Wang et al., 2019). In virtual settings, the absence of a physical presence, limited non-verbal communication, and increased technological mediation may weaken relational bonds between teachers and students, potentially affecting students’ motivation and sense of belonging in school (Chamberlain et al., 2020; Walters et al., 2022).
Immigrant students often face strained relationships with teachers (Cerdà-Navarro et al., 2020). In China, the government’s targeted poverty alleviation policies, such as the National Student Aid System, have played a pivotal role in expanding access to vocational education for students from underprivileged western provinces (Zhi & Zhao, 2021). These efforts have facilitated the organized relocation of students, many of whom from rural western regions to vocational schools in the more developed eastern provinces. By encouraging high school students in poor western areas to pursue vocational training in the east, the policy aims to enhance youth employability and create job opportunities that help lift low-income families out of poverty (Zhi & Zhao, 2021). As a result, there has been a government-led, cross-regional relocation of students from western China to eastern regions (Y. Yang et al., 2020). Engaging in school may be more challenging for those cross-regional students when transitioning between different learning methods (Cederberg & Hartsmar, 2013).
High school students, especially, being in adolescence, are in a transitional stage of development where both school relationship quality and engagement typically experience a normative decline (Archambault et al., 2009; Duong et al., 2019). Moreover, vocational education is special, because of the focus on job-oriented vocational programs for adolescences, requiring more active school engagement from students (Elffers, 2013). Secondary vocational students’ school engagement relies more on the support of teachers and school staff (Fredricks et al., 2005; Elffers, 2013). Therefore, in this study, we choose cross-regional secondary vocational education students in China, and focus on their relationships with teachers and their school engagement.
By studying the teacher–student relationships and students’ engagement in both online learning and in-school environments, we can better understand learning needs and whether students evaluate their learning experiences differently across modalities, ultimately contributing to efforts to promote stronger teacher–student relationships and higher school engagement.

2. Literature Review

2.1. Teacher–Student Relationship During Online Learning and In-School Learning

The relationship between teachers and students is different and depends on students’ age and vulnerability: students rely more on teachers when they are younger or more vulnerable (Verschueren & Koomen, 2012). Teacher–student relationships have been defined in three dimensions: closeness, conflict, and dependency (Verschueren & Koomen, 2012). An approach is to apply attachment theory to secondary school students’ interaction with teachers (Chong et al., 2010). Attachment theory explains how teachers’ and students’ relationships may work; teachers play the roles of being a secure base and a safe haven. When students feel stress, a positive teacher–student relationship will give them support and make them feel comfortable; in addition, teachers can provide a safe classroom environment for students (Verschueren & Koomen, 2012). Students’ perceptions of interactions with teachers can be used as a sign of teacher–student relationships (Fatou & Kubiszewski, 2018).
Debates over teacher–student relationships in online and in-school learning remain unresolved (Vagos & Carvalhais, 2022; Akram & Li, 2024). Online leaning between students and teachers are often viewed as less authentic and spontaneous compared to those in school settings (Vagos & Carvalhais, 2022). However, Chamberlain et al. (2020) found online learning can help teachers and students create a new communicative space and continuously developed it to enhance students’ learning quality. Comparing teacher–student relationships in online and in-school learning can help us better understand students’ perceptions of different learning environments and inform improvements in future teaching methods.
Therefore, this study proposes the following:
Hypothesis 1.
There are differences in teacher–student relationships between online learning and in-school learning.

2.2. School Engagement During Online Learning and In-School Learning

School engagement has been a topic for many years in analyzing the results of many educational systems, such as student dropout issues and academic development, as an element in understanding student learning and achievement (Fredricks et al., 2005; Archambault et al., 2009; Fatou & Kubiszewski, 2018). Students’ school engagement reflects their interaction with school staff, activities, environment, goals, and values, showing their level of involvement or connection with school (Roorda et al., 2019).
School engagement is a multidimensional concept, which has been divided into three dimensions in the literature: cognitive, affective, and behavioral engagement (Fredricks et al., 2005; Moreira et al., 2018; Del Toro & Wang, 2021). Students’ self-concepts about conquering complex or difficult questions, and perceptions of schooling tasks are summarized as cognitive engagement (Fredricks et al., 2005); students’ subjective feelings, intrinsic motivation, and optimistic attitudes in the school and learning process are summarized as affective engagement (Del Toro & Wang, 2021); and, students’ classroom behavior, extracurricular participation, and schoolwork efforts in the school activities are summarized as behavioral engagement (Wang et al., 2019; Moreira et al., 2018). Especially, affective engagement is an indicator of students’ experiences of the transition from in-school to online schooling (Chzhen et al., 2022). It also reflects their relationships with teachers and experiences in the learning process (Symonds & Hargreaves, 2016).
Numerous studies have discussed the effects of online learning on students’ engagement (Walters et al., 2022; Ariyo et al., 2022; Khlaif et al., 2021). Most researchers have found that online learning causes learning resource inequality (Khlaif et al., 2021) and students need mental support (Salayo et al., 2020; Teuber et al., 2021), especially for more disadvantaged students (Ariyo et al., 2022), such as secondary vocational students. Research has shown that students’ engagement with online learning is often less positive, partly because teachers feel less competent in delivering online instruction (Salayo et al., 2020) and due to the reduced effectiveness in teacher supervision (Walters et al., 2022). However, Miao et al. (2022) found that online learning can also be an effective way to promote student engagement.
Therefore, this study proposes the following:
Hypothesis 2.
There are differences in students’ school engagement during online learning and in-school learning.

2.3. Teacher–Student Relationships and School Engagement Across Learning Methods

The quality of teacher–student relationships play a critical role in students’ overall school functioning and is closely linked to their school engagement (Roorda et al., 2019; Duong et al., 2019). When teachers act as a secure base and a safe haven, students are more likely to engage in school-related activities, including learning tasks and academic performance (Roorda et al., 2019; Verschueren & Koomen, 2012). Research has shown a strong association between teacher–student relationships and secondary school students’ levels of engagement (Roorda et al., 2017, 2019).
In the context of online learning, students describe their engagement as shaped by both technological factors and their sense of connectedness with teachers (Chzhen et al., 2022). In vocational education settings, perceived teacher support has been found to influence student engagement both directly and indirectly, mediated by the satisfaction of basic psychological needs and learning motivation (Xu et al., 2023). Students’ subjective perceptions of their relationships with teachers significantly shape how teacher support affects engagement; for instance, a positive emotional connection, such as liking their teachers, can enhance active participation in online learning (Vagos & Carvalhais, 2022). Conversely, when teachers fail to establish positive relationships or employ effective relational practices, student engagement may decline across both online and in-person learning contexts (Duong et al., 2019).
To investigate how different learning modalities affect these dynamics, this study proposes the following:
Hypothesis 3.
There are differences in the relationship between teacher–student relationships and student engagement during online learning and in-school learning.
Moreover, creating a supportive physical and virtual learning environment is essential for effective education (Reynolds & Sokolow, 2022). The availability of adequate space and learning resources significantly influences academic outcomes among secondary school students (Baucum, 2022), and overall learning effectiveness is closely tied to the quality of the study environment (Means et al., 2009). Therefore, the study environment is also considered an important factor influencing both teacher–student relationships and student engagement.
Therefore, this study proposes the following:
Hypothesis 4.
There are differences in the learning environments during online learning and in-school learning.

2.4. The Present Study

This study surveyed students in China to examine whether teacher–student relationships and student engagement differ between online and in-school learning, with a particular focus on disadvantaged students, specifically, on cross-regional secondary vocational education students, a population largely overlooked in prior studies on engagement and teacher–student dynamics.
It contributes to the existing literature by addressing the learning needs of underserved students through the lens of learning methods, aiming to enhance teacher–student relationships and foster positive school engagement.
By comparing learning methods, this research offers valuable insights into how educational practices can be adapted to better support student connection and active engagement, both online and in school.

3. Methodology

3.1. Collection and Samples

The study conducted two anonymous pre- and post-sample digital surveys in 2022: the pre-sample survey was collected in October 2022 for students who studied via learning online for one consecutive month, and the post-sample survey was collected in December 2022 for students who returned to school and studied at school for one consecutive month. The students were cross-regional education students who received online learning at home in western China during the epidemic and returned to school in eastern China to receive their education after the restrictions were canceled.
First, students were asked to complete the questionnaire through an online meeting organized by their teacher during their online learning at home, which was monitored and guided by researchers and teachers through online meetings. The teachers were responsible for organizing the students to fill in the questionnaire during learning at school; researcher trained the teachers to answer questions and monitor the quality of the questionnaires during students’ filling. In the pre- and post-survey, 120 students participated in two questionnaire surveys. In the end, 240 questionnaires were collected. A total of 105 students provided complete pre- and post-test data through one-to-one matching. The analysis was conducted based on these responses.
The student sample was collected from second- and third-year students who had been in school for at least one year and had more perceptions of teacher–student relationships and school engagement during different periods; 48 in the second year and 57 in the third year participated in full. The sample consisted of 82 male and 23 female students, aged 15–20 years. A higher proportion of male students participated, which reflects the gender distribution associated with the school’s academic major.

3.2. Questionnaire Design and Measures

The questionnaire was designed mainly in three parts based on the published literature research, and tested by structural reliability. The first part is about the teacher–student relationships (TSC), aligning with existing scale (Grazia & Molinari, 2021) and adapting the context of online learning (Núñez-Regueiro et al., 2022), TSC was measured by students’ self-evaluation interaction with teachers and the learning tasks by teachers, and was composed of 7 items rated on a 5-point Likert scale, with “1” meaning “strongly disagree” and “5” meaning “strongly agree”, and α = 0.926 for online learning, and α = 0.950 for in-school learning, such as “In general, relations between students and teachers are friendly”, “Teachers respond to the needs of my when difficulties arise”, and “Our teacher chooses school assignments well during online/school course”.
The second part is about student school engagement (SE), which was measured for the three domains identified in the literature review (Hart et al., 2011; Fredricks et al., 2005), and adapting it to the context of online learning (F. Yang & Tu, 2020). SE was composed of student affective engagement, behavioral engagement, and cognitive engagement; there were 19 main items in total rated on a 5-point Likert scale, with 5 items for affective engagement (AE, α = 0.747 for online learning, and α = 0.917 for in-school learning), such as “I like what I am learning in online/school course”; 6 items for behavioral engagement (BE, α = 0.903 for online learning, and α = 0.933 for in-school learning), such as “I try hard to do well in online/school course”; and 8 items for cognitive engagement (CE, α = 0.915 for online learning, and α = 0.934 for in-school learning), such as “I check my schoolwork for mistakes” and “I set priority and plan ahead, keep track of what remains to be done, like Turn off the TV”. “1” means “strongly disagree” and “5” means “strongly agree”.
Lastly, the third part is about study environment factors affecting student school engagement during the epidemic (F. Yang & Tu, 2020; Ye et al., 2022), including 5 items which were rated on a 5-point Likert scale, with “1” meaning “strongly disagree” and “5” meaning “strongly agree”, such as “I can’t find a quiet area to study when I study at home/at school”, and “I don’t have enough time to finish my tasks when I study at home/at school”.
The latent items of each construct were validated by confirmatory factor analyses (CFAs), which showed that factor loadings of each item are more than 0.60 under online learning constructs and more than 0.72 under in-school learning constructs. The scales in online learning have adequate reliability (>0.83) and AVEs (>0.49); in addition, in-school learning showed adequate reliability (>0.93) and AVEs (>0.68). The square root of AVEs in each diagonal showed adequate discriminant validity, proving no multicollinearity between the questions.

3.3. Analytic Strategy

In order to verify the difference in the pre- and post-survey of the relevant variables towards the different learning methods of students, this study used SPSS 29.0 to apply a test of variance to determine whether the differences in the variables were significant. Moreover, structural equation modeling was applied using SmartPLS 3.3.9. Finally, the study compared regression coefficients across groups to test the difference in the association between teacher–student relationships and school engagement.

4. Results

4.1. Difference in Teacher–Student Relationships, School Engagement, and Other Factors

The results of the descriptive analyses and tests of variance for teacher–student relationships and school engagement can be seen in Table 1 (Hypothesis 1 and 2 were tested). The data showed significant differences in students’ affective engagement during the epidemic in the comparison of students’ online learning and school learning, while the results of the one-way ANOVA were consistent with the Kruskal–Wallis test (p < 0.05), with a significant difference for online learning and school learning in students’ affective engagement.
In terms of the teacher–student relationships, cognitive engagement, and behavioral engagement, the differences between online and in-school learning of each construct were not significant. Continuing the analysis of the latent variables, students evaluated the teacher–student relationships during in-school learning higher (the results are shown in Table 1: mean 3.68 during online learning, and mean 3.85 during school learning, p < 0.05). Furthermore, in the teacher–student relationships scale, the main latent variables’ differences were the teacher’s response when students encountered difficulties (mean 4.16 during online learning, and mean 3.83 during school learning, p < 0.05), and the atmosphere in which students felt the teacher–student relationships (mean 4.07 during online learning, and mean 3.78 during school learning, p < 0.05). In cognitive engagement, the ratings were higher during online learning. The main difference was in whether students would search for words or vocabulary they did not know (mean 3.78 during online learning and 3.57 during school learning, p < 0.05). The main difference in behavioral engagement was whether the students tried to do well while studying (mean 3.61 during online learning and 3.83 during school learning, p < 0.05).
Based on the results in Table 1, there was a significant difference in the students’ affective engagement in school towards online and in-school learning. Therefore, a specific analysis of each latent variable under affective engagement was conducted. The results in Table 2 have shown that the differences in each latent variable of students’ affective engagement were significant (p < 0.05). During in-school learning, students preferred the interestingness of in-school learning (3.74 > 3.46), the content that they learned (3.77 > 3.28), and the way the classes were organized (3.88 > 3.03), indicating that students preferred the way they attended classes at school and the learning content. On the other hand, students’ liking for school (4.30 > 3.93), feeling of pride towards school (4.08 > 3.86), and happiness with school (4.28 > 3.96) were higher during online learning, indicating a decrease in students’ liking when returning.
Based on the literature, this study explores other factors that influence students between different learning methods. Therefore, the study investigated the environmental factors that influence students’ learning. Table 3 shown the statistical percentage and one-way ANOVAs results of the environmental factors (Hypothesis 4 was tested). Meanwhile, the study recoded the environmental factors, and the students who reported such factors were grouped. The percentages in Table 3 are the percentage of students who scored “4 agree–5 strongly agree” for this factor. From Table 3, there were significant differences in whether students could find learning materials, learning space, and complete learning tasks during online learning at home and in-school learning at school (p < 0.05). During online learning, there were more cases of students not being able to find the materials needed (10.8%) and not having enough learning space (10.0%), while, during in-school learning, students more often encountered not having enough time to complete their learning tasks (45%).

4.2. Structural Equation Model of Teacher–Student Relationships and School Engagement

This study conducted a structural equation model analysis based on the association between teacher–student relationships and school engagement. During the online learning, the factor loadings for each item were above 0.70 in teacher–student relationships, cognitive engagement, and behavioral engagement, and above 0.60 for each item in affective engagement. The average extracted variance (AVE) was above 0.6 for behavioral engagement, cognitive engagement, and teacher–student relationships, and the affective involvement AVE index was 0.498. And the AVE square root has shown adequate discriminant validity among each construct. Fornell and Larcker (1981) explained that the AVE index of 0.4 or higher is acceptable. During in-school learning, the factor loadings for each item were above 0.8 in teacher–student relationships and affective engagement, and above 0.7 in cognitive engagement and behavioral engagement. The AVE was above 0.6 for all constructs, showing adequate discriminant validity.
All data in this study passed the model test, indicating that the model of this study is acceptable. The structural path coefficients were analyzed, as shown in Table 4: all path coefficients were significant (p < 0.001), and the most significant effect was shown in the association of TSC on students’ AE (online learning: 0.619 ***; in-school learning: 0.735 ***). The association between TSC and AE was explained to be 37.8% during online learning and 53.6% during in-school learning, followed by the effect of the TSC on BE (online learning: 0.600 ***; in-school learning: 0.610 ***), and, finally, the effect of the TSC on CE (online learning: 0.521 ***; in-school learning: 0.566 ***). All coefficient indices of in-school learning were higher.
From the path coefficients in Table 4, the path coefficients showed differences in the effects of teacher–student relationships on students’ school engagement towards different learning methods. To test whether these coefficient differences were statistically significant, this study compared regression coefficients across learning method groups. As shown in Table 5 (Hypothesis 3 was tested), the associations between TSC and SE were significant as in the structural equation model analysis, but the difference between the group comparisons was not significant (p > 0.05). This indicated that the effect of teacher–student relationships on school engagement towards different learning methods does not differ significantly.

5. Discussion

This study conducts a comparative analysis of teacher–student relationships and school engagement among cross-regional students who have experienced different learning methods. It aims to explore how the students’ subjective perceptions of their learning environments across various instructional formats influence their engagement and relationships with teachers. The findings are intended to enhance our understanding of the cross-regional students’ learning needs and to inform strategies that improve teacher and student relationships as well as school engagement. Furthermore, the study offers a basis for future research on effective learning approaches for students.

5.1. The Results of Teacher–Student Relationships During Online Learning and In-School Learning

First, for students’ subjective evaluations of the teacher–student relationships, we did not find differences depending on the learning method. The limited observed differences indicated that teacher–student relationships were noticed during both online and in-school learning. Hypothesis 1 was rejected. The results could be due to teachers trying to provide organized and planned teaching content (Chamberlain et al., 2020), and teachers actively playing the roles of being a secure base and a safe haven (Verschueren & Koomen, 2012), since the targeted cross-regional migrant students have consistently received attention from teachers and schools. The results from specific items also indicate that teachers’ timely responses to students’ difficult situations during school and enhanced responses are more conducive to enhancing the quality of teacher–student relationships. Consistent with existing studies, teachers’ effective response to students’ needs is important (Wink et al., 2021; Sandilos et al., 2018). Therefore, when teachers are more responsive to students’ needs, students are likely to report more positive perceptions of their relationships with teachers during the online learning period. In retrospective studies, online teaching practices were found to have a notably positive impact on student satisfaction, irrespective of demographic differences (Russo, 2025).
A positive teacher–student relationship is a key to classroom teaching, which is related to students’ school success; however, teachers may lack specific strategies for caring for their students (Claessens et al., 2016). Teachers’ cognitive empathy, reduced work stress, and management of anxiety are related to effective problem-solving strategies, which are associated with handling students’ problem behaviors and the closeness of teacher–student relationships (Wink et al., 2021; Sandilos et al., 2018).

5.2. The Results of School Engagement During Online Learning and In-School Learning

Based on school engagement, the main significant changes were reflected in affective engagement during different learning methods. Hypothesis 2 was partially supported. In terms of specific items in affective engagement, the main differences in latent variables were observed in how teachers responded when students encountered difficulties. The results indicated that teachers were more efficient in addressing students’ questions during online learning. During in-school learning, students expressed a stronger preference for the interest level of the lessons, the content they learned, and the way classes were organized. This suggests that cross-regional students favored the structure and instructional methods of classroom-based learning. In contrast, the students reported higher levels of school liking, pride in their school, and happiness with school during online learning, indicating a decline in these positive attitudes upon returning to in-person classes. This may be because our target group consists of cross-regional students from underprivileged areas, and, when they are at home, they often receive high praise from their families and neighbors. We see the increased appreciation students develop for their school environment when they are physically away from it (Li et al., 2023), especially for cross-regional students. Similar effects have been observed during vacations or school breaks, which can enhance students’ positive perceptions and emotional attachment to their school (Herrera Bernal, 2023).
Moreover, in relation to specific items within cognitive engagement, students reported that, during online learning, it was easier to search for unfamiliar words or vocabulary. Sultan (2021) found that students perceived online learning platforms as user-friendly, which supported the easier access to vocabulary resources and improved their learning experience. Moreover, cross-regional students may struggle with a lower language proficiency and cultural integration when in school (Cederberg & Hartsmar, 2013).
In terms of behavioral engagement, students reported making greater efforts to perform well when studying in school settings. González-Gómez et al. (2016) compared student motivation and satisfaction in online and classroom-based learning, showing that students in traditional classrooms demonstrated higher levels of motivation. Wang and Eccles (2013) also found that the structured environment of in-person education plays an important role in fostering student motivation and engagement.
These findings are also in line with the review studies of Admiraal et al. (2022) and Assor et al. (2002). As well, students tend to develop tension towards aggravated learning tasks in school (Núñez-Regueiro et al., 2022), and have more freedom to learn remotely and use technology to assist them in their studies. On the other hand, when studying at school, visual teaching formats and teaching materials are conducive to increased interest and knowledge gain in the student’s learning process; at the same time, students have more space to learn and promote increased interest in learning, consistent with existing studies (Bray et al., 2021).
Therefore, to improve their engagement in the learning process, teachers can offer autonomy in choice to allow students to choose how they want to learn study works, listen to students’ opinions, and explain the importance of learning topics (Assor et al., 2002; Núñez-Regueiro et al., 2022). An autonomy-supportive classroom climate is positively associated with students’ higher learning motivation and achievement, which means students can connect themselves with activities, with even more feeling of ownership and volition to perform tasks instead of a sense of being controlled or coerced, especially for cross-regional students (Admiraal et al., 2022). Accordingly, learning tasks should be assigned in a way that stimulates student autonomy to improve students’ concentration during the learning process and better plan their learning content (Vansteenkiste et al., 2005).

5.3. The Association Between Teacher–Student Relationships and School Engagement During Online Learning and In-School Learning

Finally, teacher–student relationships consistently had a significant positive effect on students’ school engagement. Hypothesis 3 was rejected. The difference in the effect of teacher–student relationships on students’ school engagement during the different learning methods was not significant, which also verified that teacher–student relationships always play a positive role in students’ school engagement. Walters et al. (2022) indicated that student engagement and concentration may improve as teachers adapt to online delivery, as learners become familiar with online learning technologies, and as providers of online learning platforms improve functionality. Therefore, many schools may keep choosing to use online learning platforms in the future. Teachers need to be trained in online teaching skills to ensure that they promote students’ school engagement while preventing students from avoiding effortful learning (Walters et al., 2022).

5.4. The Effects of Other Factors on Teacher–Student Relationships and School Engagement

When students study online at home, they may not have enough study space, which is especially the case for students from poor areas who have a poor family environment. Hypothesis 4 was supported. Fabito et al. (2020) identified the absence of dedicated study or workspaces at home as one of the three primary barriers to effective online learning, along with challenges in communicating with instructors and unreliable Internet connectivity. The lack of appropriate learning environments at home was linked to decreased motivation and engagement (Costa, 2024). On the other side, during in-school learning, students more frequently reported a lack of sufficient time to complete their learning tasks. Lavy (2020) demonstrated that expanding school resources and allocating more time to academic activities can significantly enhance academic achievement. Schools that provide fewer but more effective learning materials can enhance student motivation and improve academic outcomes.

6. Conclusions

Overall, the findings reveal that differences in students’ engagement across learning methods are reflected in specific aspects: while online learning was associated with more efficient teacher support, improved access to vocabulary resources, and enhanced emotional attachment to school, in-person learning fostered higher behavioral engagement, greater motivation, and stronger preferences for classroom structure and content.
Moreover, however, limited home learning environments during online learning negatively impacted student motivation and engagement.
The findings of this study highlight the importance of enhancing educators’ digital competencies and strengthening the digital infrastructure to support student engagement (Aldhaen, 2024). Effective teacher guidance and timely feedback play a critical role in fostering engagement, particularly among disadvantaged students. Moreover, digital technologies can enhance students’ ability to access and process knowledge efficiently. Therefore, it is essential for schools and educators to develop strategies for effectively integrating digital tools into the learning process and guiding students in their use.

7. Limitation

This study has the following limitations. First, the survey in this study was collected during and after the epidemic, which did not investigate the data of students before the epidemic, so the comparative analysis is not comprehensive. Second, the sample size is small, and, for analyzing the situation of China, a larger sample size is needed in order to confirm the findings, representing the east, middle, and west of China, respectively.

Author Contributions

Conceptualization, H.H.; Methodology, H.H. and Y.W.; Software, H.H. and Y.W.; Formal analysis, H.H.; Investigation, Y.W. and W.J.; Resources, Y.W.; Writing—original draft, H.H.; Writing—review & editing, Y.W. and W.J.; Supervision, Y.W.; Project administration, Y.W.; Funding acquisition, Y.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Tongji University (code: 2019tjdx299; date: 11 December 2019).

Informed Consent Statement

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

Data Availability Statement

Data is unavailable due to privacy or ethical restrictions.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Descriptive statistics and one-way ANOVAs on teacher–student relationships (TSC) and school engagement (SE) varied by learning methods (Hypothesis 1 and 2 were tested).
Table 1. Descriptive statistics and one-way ANOVAs on teacher–student relationships (TSC) and school engagement (SE) varied by learning methods (Hypothesis 1 and 2 were tested).
VariablesLearning MethodsRangeMean ± SDFp-Value
Teacher–Student RelationshipsOnline Learning(1.29–5.00)3.90 ± 0.6461.8950.170
In-school learning(1.57–5.00)3.79 ± 0.613
School EngagementCognitive engagementOnline Learning(1.33–5.00)3.59 ± 0.6000.0740.786
In-school learning(2.00–5.00)3.56 ± 0.561
Behavioral engagementOnline Learning(1.33–5.00)3.62 ± 0.6251.1820.278
In-school learning(2.00–5.00)3.71 ± 0.602
Affective engagementOnline Learning(1.86–5.00)3.68 ± 0.5735.0560.025
In-school learning(1.71–5.00)3.85 ± 0.599
Table 2. Descriptive statistics and one-way ANOVAs on latent variables of affective engagement (AE) varied by learning methods (Hypothesis 2 was tested).
Table 2. Descriptive statistics and one-way ANOVAs on latent variables of affective engagement (AE) varied by learning methods (Hypothesis 2 was tested).
Latent Variables in AELearning MethodsRangeMean ± SDFp-Value
I love my schoolOnline Learning(2–5)4.30 ± 0.68116.456<0.0005
In-school learning(2–5)3.93 ± 0.719
I am proud to be a student at this schoolOnline Learning(1–5)4.08 ± 0.8754.6410.032
In-school learning(2–5)3.86 ± 0.737
I am happy to come to this schoolOnline Learning(1–5)4.28 ± 0.75812.2470.001
In-school learning(2–5)3.96 ± 0.679
I think what we are learning in online/school course is interestingOnline Learning(1–5)3.46 ± 0.8887.8100.006
In-school learning(1–5)3.74 ± 0.667
I like what I am learning in online/school courseOnline Learning(1–5)3.28 ± 0.89823.421<0.0005
In-school learning(2–5)3.77 ± 0.658
I am happy to be at online/school courseOnline Learning(1–5)3.03 ± 0.99159.341<0.0005
In-school learning(2–5)3.88 ± 0.712
Table 3. Statistical percentage and one-way ANOVAs results of environmental factors variables varied by learning methods (Hypothesis 4 was tested).
Table 3. Statistical percentage and one-way ANOVAs results of environmental factors variables varied by learning methods (Hypothesis 4 was tested).
Environmental VariablesOnline LearningIn-School LearningFp-Value
When I learn at home/at school, I felt nervous, anxious, or tense to study26.70%38.30%3.7500.054
When I learn at home/at school, I cannot locate the materials I need for my homework10.80%2.50%6.8310.010
When I learn at home/at school, I cannot find a quiet area8.30%5.00%1.0670.303
When I learn at home/at school, I don’t have enough space for me to work10.00%3.30%4.3270.039
When I learn at home/at school, I don’t have enough time to finish my learning tasks17.50%45.00%22.965<0.0005
The percentage data is the percentage of students who rated the factor “4 Agree–5 Strongly Agree”.
Table 4. Path coefficient of association between TSC and school engagement varied by learning methods.
Table 4. Path coefficient of association between TSC and school engagement varied by learning methods.
Construct Path CoefficientT-Statisticp-ValueAdjusted R2
Online LearningTSC→AE0.61914.451<0.00050.378
TSC→BE0.6008.341<0.00050.355
TSC→CE0.5219.020<0.00050.265
In-school learningTSC→AE0.73511.373<0.00050.536
TSC→BE0.6108.289<0.00050.367
TSC→CE0.5668.043<0.00050.315
TSC: teacher–student relationships; AE: affective engagement; BE: behavioral engagement; CE: cognitive engagement.
Table 5. Compared regression coefficients across learning method groups (Hypothesis 3 was tested).
Table 5. Compared regression coefficients across learning method groups (Hypothesis 3 was tested).
Online LearningIn-School Learningp-Value
TSC→CE0.468 ***0.527 ***0.597
TSC→BE0.576 ***0.572 ***0.969
TSC→AE0.576 ***0.724 ***0.160
TSC: teacher–student relationships; AE: affective engagement; BE: behavioral engagement; CE: cognitive engagement. *** p ≤ 0.001.
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Hu, H.; Wang, Y.; Jacquet, W. Cross-Regional Students’ Engagement and Teacher Relationships Across Online and In-School Learning. Educ. Sci. 2025, 15, 993. https://doi.org/10.3390/educsci15080993

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Hu H, Wang Y, Jacquet W. Cross-Regional Students’ Engagement and Teacher Relationships Across Online and In-School Learning. Education Sciences. 2025; 15(8):993. https://doi.org/10.3390/educsci15080993

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Hu, Huiqi, Yijun Wang, and Wolfgang Jacquet. 2025. "Cross-Regional Students’ Engagement and Teacher Relationships Across Online and In-School Learning" Education Sciences 15, no. 8: 993. https://doi.org/10.3390/educsci15080993

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Hu, H., Wang, Y., & Jacquet, W. (2025). Cross-Regional Students’ Engagement and Teacher Relationships Across Online and In-School Learning. Education Sciences, 15(8), 993. https://doi.org/10.3390/educsci15080993

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