How Social and Organizational Support Influence Online Teaching Experience in China? Exploring the Mediating Role of Technological Efficacy and Innovation Awareness

Abstract

The rapid shift to online education, accelerated by the COVID-19 pandemic, has fundamentally altered the landscape of teaching, and learning worldwide, making the exploration of factors influencing online teaching experiences increasingly vital. While existing research has examined the impact of instructional support on teaching efficacy and experience, a critical gap remains systematically exploring how personal, social, and organizational factors shape online teaching practices. This study aims to address this gap by investigating the relationships among social and organizational support, technological efficacy, innovation awareness, and online teaching effectiveness. Data collected from 3,154 university instructors across China were analyzed using structural equation modeling (SEM). The findings reveal that both technological efficacy and innovation awareness significantly mediate the relationship between social and organizational support and the online teaching experience. From the perspective of the standard total effect values, technological efficacy played a pivotal role in shaping the online teaching experience. These results contribute to the field by deepening our understanding of how support structures influence online teaching outcomes, providing empirical insights for strengthening support mechanisms that empower educators in technology-enhanced teaching environments.

Plain language summary

How support from others helps improve online teaching in China: Understanding the role of technological efficacy and innovation awareness

The COVID-19 pandemic forced a rapid switch to online education, which has made teaching and learning very different for educators worldwide. While we know that support from colleagues, institutions, and technology can influence how teachers experience online teaching, we still don’t fully understand how different types of support shape their teaching effectiveness. This study looked at how support from social networks (like colleagues and peers) and organizations (like universities) influences online teaching, focusing on two important factors: technological efficacy and awareness of innovation. We surveyed over 3,000 university teachers across China and found that both technological efficacy and awareness of innovation play a key role in how social and organizational support influences online teaching. In particular, technological efficacy was very important in shaping how teachers feel about their online teaching experience. Our study shows that when teachers receive strong support-whether from colleagues, their school, or through improved technological tools-they are more likely to feel confident and effective when teaching online. This research offers useful insights for schools and policymakers to strengthen the support teachers need, so they can succeed in the increasingly digital world of education.

Keywords

online education teaching experience teaching support technological efficacy innovation awareness

Introduction

The onset of the COVID-19 pandemic in early 2020 catalyzed an unprecedented shift from traditional face-to-face education to online learning, affecting over 90% of higher education institutions worldwide (UNESCO, 2021). Reports during this period highlighted the challenges of adapting to an online environment for teachers, underlining the complexities of remote learning and collaboration (Trust & Whalen, 2021). Although the immediate crisis has passed, online teaching is increasingly expected to become a mainstay in educational institutions, with scholars suggesting that it will remain a prominent mode of instruction moving forward (Núñez-Canal et al., 2022; Zimmerman, 2020).

Given teachers’ central role in the success of online education, understanding their experiences within virtual teaching environments is crucial for enhancing instructional effectiveness and student outcomes in technology-enhanced learning contexts (Larty & Hodgson, 2024; Mishra et al., 2020; van der Spoel et al., 2020). Recent research has delved into various dimensions of these experiences, such as the development of digital competencies, emotional well-being, and changes in pedagogical practices (Liu et al., 2020; Truzoli et al., 2021; Zhang et al., 2023). These factors are intricately linked to the quality of technological infrastructure, the extent of online tool utilization, and levels of student engagement and interaction, all of which shape the overall teaching experience (Scherer et al., 2023; Sidi et al., 2023).

One prominent factor influencing online teaching effectiveness is instructional support. Prior studies highlight that robust support systems can enhance instructors’ confidence and competence in managing digital tools and virtual classrooms (García-Morales et al., 2021; Martin et al., 2020). Such support includes technical assistance, professional development opportunities, and collaborative networks, all of which contribute to sustained teacher engagement and innovation (Cutri et al., 2020). Moreover, research suggests that social and organizational support structures play a crucial role in mitigating the isolation often reported by educators in online settings, fostering a sense of community and shared purpose (Ferri et al., 2020; Green et al., 2020).

However, while the positive effects of instructional support on teaching efficacy and innovativeness are well-documented (Celik & Yesilyurt, 2013; Orakcı, 2020), there remains a gap in understanding how these support structures interact with factors such as technological efficacy and innovation awareness to influence online teaching practices. Few studies have examined these dynamics in-depth, particularly within large-scale online teaching contexts (Baran et al., 2011; König et al., 2020). Addressing this gap, our study seeks to explore the mediating roles of technological efficacy and innovation awareness in the relationship between instructional support and teaching effectiveness.

Focusing on university instructors in China, this study investigates how social and organizational support impacts online teaching practices. Specifically, we examine the relationships between these forms of support and teachers’ perceived technological efficacy, and innovation awareness. By providing empirical insights into these relationships, we aim to inform educational administrators about effective support mechanisms, ultimately enhancing teachers’ readiness, and capacity for technology-supported instruction (Yiming et al., 2024).

Literature Review

Online Teaching Experience and Influential Factors

In the mid-1990s, when online teaching was first introduced in higher education, most university instructors were reluctant to change their teaching methods and adopt online teaching (Olcott & Wright, 1995). Many instructors lacked the skills to design and transition to online courses, making it a significant challenge to increase teacher engagement in distance education. With the widespread adoption of online teaching, more scholars began to explore instructors’ experiences in online teaching.

Online teaching experience refers to the experiences instructors have while using and integrating online technologies into their teaching practices. Specifically, it encompasses experiences related to improvements in teaching skills, increased autonomy in teaching, time-saving, academic research support, feelings of isolation, changes in student-teacher interaction, teaching quality, and the use of technological platforms and networks (Gay, 2016). As consumers of online teaching, instructors’ perceptions, teaching experiences, and the teaching environment all influence their willingness to adopt online teaching platforms. From a technological perspective, researchers generally agree that factors such as perceived usefulness, perceived ease of use, and the effectiveness of teaching platforms have a positive impact on teachers’ continued use of online teaching tools. Among these, perceived usefulness is found to have the most significant influence on instructors’ willingness to engage in online teaching, as it is closely linked to the extent to which online teaching meets teachers’ instructional needs and expectations for improving their teaching capabilities (Seok et al., 2010). From the perspective of individual teacher characteristics, research has shown that personal preferences, technological proficiency, and previous teaching experience have a positive influence on teachers’ online teaching experiences (Lao & Gonzales, 2005). In comparison to traditional teaching, teachers perceive online teaching as requiring more work, and the feedback provided to teachers differs in content and format (S. Silva et al., 2022). Other studies have found that performance expectations, effort expectations, online teaching motivation, and innovation levels significantly affect teachers’ intentions to engage in online teaching behavior (Seok et al., 2010). Scherer et al. (2021) also identify teachers’ profiles based on competence-related beliefs (such as self-efficacy and perceived online presence) and perceived institutional support for online teaching and learning. From the environmental perspective, personalized course design, rich teaching resources, and convenient teacher-student interaction are essential factors for instructors’ sustained use of online teaching platforms. Factors related to students, teachers, and the institution also influence teachers’ online teaching experiences (Bolliger & Wasilik, 2009).

After the COVID-19 crisis, the emergent scholarship highlighted that many instructors embraced online learning with varying degrees of motivation and commitment. The evolution of online teaching technologies further emphasized the role of prior teaching experience as a primary influence on instructors’ online teaching experiences. Moreover, researchers have stressed the importance of digital literacy, institutional support, and guidance in facilitating effective online teaching (Damşa et al., 2021; Hofer et al., 2021). Lohr et al. (2021) demonstrated that instructors’ basic digital skills, technology-related teaching skills, and external resources (including digitalization policies, university administration commitment, technical and educational support, and institutional infrastructure) were positively associated with the quality of digital learning opportunities provided to students.

Impact of Social and Organizational Support on Online Teaching Experience

Perceived Organizational Support (POS) theory, proposed by Eisenberger et al. (1986), stems from Social Exchange Theory and the Norm of Reciprocity (Eisenberger et al., 2001). It emphasizes the influence of supervisor support and organizational support on employee performance. In the context of higher education, social and organizational significantly support influence teachers’ adoption of educational technologies. Venkatesh et al. (2003) emphasize that teachers’ decisions and practices are shaped by social influences, particularly from colleagues and leadership, and by their perception of available organizational infrastructure. Social support involves interactions within a teacher’s professional network. Colleague influence encompasses peer communication and the exchange of best practices in online teaching, while leadership influence reflects the recognition and encouragement provided by institutional leaders (Hartwick & Barki, 1994; Islam & Haque, 2022; Ulan-Ulan & Miralles, 2023; Venkatesh & Davis, 2000). Organizational support, on the other hand, refers to the broader institutional framework, including policies, strategies, and resources that facilitate effective teaching. This encompasses clear organizational guidelines, infrastructure, technology, and professional development opportunities (Carbonell et al., 2013; Graham et al., 2013; Shanock et al., 2022).

Effective support systems are crucial in enhancing teachers’ online teaching experiences. From a social support perspective, Tschannen-Moran et al. (1998) built upon Bandura’s self-efficacy theory to develop a teacher efficacy model, asserting that teachers’ efficacy beliefs are influenced by their environment. Leadership and peer support are critical components in this regard. Encouragement and support for instructors are crucial, and instructors require relevant support and training to overcome periods of low efficacy caused by the use of new technologies (Kundu et al., 2020; Ren, 2024). Positive reinforcement from institutional leadership regarding new explorations in curriculum and teaching methods significantly enhances teachers’ online teaching experiences. Similarly, sharing new ideas, technologies, and teaching strategies among colleagues fosters a supportive environment conducive to online teaching adoption (Zone, 2013).

At the organizational level, Tschannen-Moran and Woolfolk Hoy (2002) highlighted the significant impact of resource support on teacher efficacy, findings echoed by Chang et al. (2010). Online teaching removes traditional classroom constraints, facilitating more flexible and open teaching environments. The integration of online and offline blended teaching strategies contributes to the effectiveness and efficiency of teaching practices. Moreover, online platforms enhance classroom management by integrating teaching, learning, and administrative activities into a cohesive network. During the COVID-19 pandemic, for instance, real-time monitoring of teaching, and learning activities significantly improved online teaching experiences. Many universities provided institutional support through rapid access to online resources, training, technical support, and feedback mechanisms, all of which positively influenced teachers’ experiences with online teaching (Atuahene et al., 2024).

In contrast, Han et al. (2018), based on data from university instructors, argued that administrative support had a significantly negative impact on the efficacy of local and vocational college instructors but no impact on key college instructors. These studies demonstrate the importance of teaching support for instructors and highlight that providing instructors with basic teaching support can enhance their sense of teaching efficacy, ultimately leading to improved teaching outcomes and overall teaching efficiency (Burić & Kim, 2020; Yaghi & Bates, 2020).

Impact of Technological Efficacy and Innovation Awareness on Online Teaching Experience

The Technology Acceptance Model (TAM), introduced by Davis (1989), explains and predicts individuals’ acceptance and use of information technology (Davis, 1989; García et al., 2024). Technological efficacy refers to teachers’ perceptions of technology’s value, ease of use, and applicability in teaching practices. According to TAM, actual technology usage depends on an individual’s behavioral intention, which is influenced by perceived usefulness and attitude toward usage. These attitudes, in turn, are shaped by perceived usefulness and perceived ease of use (Xiao et al., 2024). For teachers, technological efficacy signifies their belief that technology can resolve instructional challenges and enhance teaching efficiency and outcomes. When online teaching demonstrably improves instructional effectiveness, teachers are more inclined to adopt and consistently use it. The stronger their perception of a technology’s usefulness, the greater their intention to continue its use (Davis, 1989; Wingo et al., 2017). Additionally, the ease of use—or the extent to which a technology reduces effort—also impacts teachers’ online teaching experiences (Stritto & Aguiar, 2024).

Online teaching, as a novel instructional mode, necessitates a certain degree of innovation awareness among educators. Innovation awareness refers to the extent to which teachers apply new technologies creatively in their teaching practices (Kearns, 2016). Agarwal and Prasad (1998) define this innovativeness as the willingness to experiment with new information technologies. Innovation awareness enhances teachers’ effectiveness in utilizing online teaching tools, enabling them to complete instructional tasks more efficiently and achieve greater professional satisfaction, thereby improving their overall online teaching experience (Sanz et al., 2023). Empirical studies have demonstrated a significant positive correlation between teachers’ innovation awareness and their active use of technology (Lewis et al., 2003; Thompson et al., 2006). Moreover, innovation awareness affects teachers’ ability to leverage the full functionality of information technologies in classroom settings (Gu et al., 2013). Educators with higher levels of digital literacy and innovation awareness are more likely to adopt online teaching technologies proactively and adapt to technological changes, thereby influencing their distance learning teaching practice (Vidergor, 2023).

Based on the literature on teaching support and online teaching experience, this study aimed to investigate the impact of teaching support on online teaching experience by technological efficacy and innovation awareness as key intermediary factors, as illustrated in Figure 1. The study hypothesized direct effects of social support and organizational support on technological efficacy, innovation awareness, and online teaching experience, direct effects of technological efficacy and innovation awareness on online teaching experience, as well as indirect effect of teaching support on online teaching experience mediated by technological efficacy and innovation awareness. The research questions that guided the design of the study are as follows:

RQ1: What are the direct effects of social and organizational support on technological efficacy, innovation awareness, and online teaching experience?

RQ2: What are the direct effects of technological efficacy and innovation awareness on online teaching experience?

RQ3: Is the relationship between teaching support and online teaching experience mediated by technological efficacy and innovation awareness?

Figure 1.

Conceptual model describing the relationship between teaching support, technological efficacy, innovation awareness, and online teaching experience.

Method

Context and Procedure

The study employed quantitative research methods and the data was part of a large-scale research project on instructors’ teaching work in China, initiated in July 2020. The aim of the project was to understand instructors’ online teaching experiences through extensive questionnaire surveys and to provide decision-making references for universities and educational management departments. To enhance the representativeness, this study adopts stratified sampling according to five types Chinese universities: world-class university, university with world-class discipline, local university, local college and vocational college.

The data collection period for this study was from July 6th to 31st, 2020. The questionnaires were distributed online through the academic affairs offices of the respective colleges and universities. During this period, most universities had concluded their spring semester. Instructors had completed an entire semester of online teaching practice and had gained a comprehensive understanding of online technologies and course resources. Additionally, as the semester was nearing its end, instructors were relatively relaxed and had a more objective and calm perception of the advantages and disadvantages of online technologies and course resources.

The questionnaire was administered through an anonymous online survey to minimize any potential risks to research participants. A statement at the beginning of the survey explicitly informed participants that they could choose not to answer any question and that completing and submitting the questionnaire constituted their informed consent to participate. No identifiable data was collected, and participants had the right to withdraw from the study at any time without any consequences.

Participants

A total of 3,154 instructors filled in the questionnaire, and 3,008 valid questionnaires were collected, resulting in an effective response rate of 95.37%. Through stratified sampling based on school types, instructors from 85 local universities comprised the largest proportion, accounting for 34.91%, followed by instructors from 28 world-class universities (24.40%), instructors from 48 universities involved world-class discipline (14.43%), instructors from 110 local colleges (13.80%), and instructors from 31 vocational colleges (12.47%). Of this sample, there were 1,193 males and 1,815 females (see Table 1): 124 were teaching assistants or others, 1,204 were lecturers, 1,163 were associate professors, and 517 were professors. In terms of teaching experience, the distribution was as follows: 12.03% had taught for 0 to 3 years, 11.34% for 4 to 7 years, 29.85% for 8 to 15 years, 23.40% for 16 to 23 years, and 23.37% for over 24 years. In terms of geographical distribution within the overall sample, instructors from the western, central, and eastern regions of China accounted for 24.34%, 20.28%, and 55.39% respectively.

Table 1.

Frequency and Percentage of the Participants by Gender, Academic Title, Teaching Experience, School Location, and School Type.

Demographic factors	Reference	n	%
Gender	Male	1,193	39.66
Gender	Female	1,815	60.34
Academic title	Teaching assistant or others	124	4.12
	Lecturer	1,204	40.03
	Associate professors	1,163	38.66
	Professor	517	17.19
Teaching experience	0–3 years	362	12.03
	4–7 years	341	11.34
	8–15 years	898	29.85
	16–23 years	704	23.40
	over 24 years	703	23.37
School location	Western	732	24.34
	Central	610	20.28
	Eastern	1,666	55.39
School type	Vocational college	375	12.47
	Local college	415	13.80
	Local university	1,050	34.91
	University with world-class discipline	434	14.43
	World-class university	734	24.40

Instrument

The instruments of the study were adapted from existing validated scales (Carbonell et al., 2013; Gay, 2016; Graham et al., 2013; Gu et al., 2013; Rogers, 2003). Given that some instruments were originally in English and our participants were Chinese instructors, we consulted with researchers and experts in the field of education and conducted a pilot test before distributing the questionnaire. This process was necessary to make appropriate modifications to ensure the validity and relevance of the survey questions in the Chinese context.

The Online teaching experience scale, developed by Gay (2016), was originally designed to assess the integration of online technologies into the teaching process. This 4-item scale was adapted to suit the Chinese teaching context. A 7-point Likert-style format was used ranging from 1 = strongly disagree to 7 = strongly agree (α = .93). The Social support scale was divided into two subscales: colleague influence and leadership influence, based on the work of Carbonell et al. (2013). This scale also used a 7-point Likert format, ranging from 1 = strongly disagree to 7 = strongly agree (α = .90). The Organizational support scale was adapted from the framework proposed by Graham et al. (2013), which focuses on institutional adoption and the implementation of online-offline combined teaching models in higher education. It covers both organizational strategy and institutional support. This scale employed a 7-point Likert format, ranging from 1 = strongly disagree to 7 = strongly agree (α = .93). The Technological efficacy scale was developed based on Venkatesh and Davis’s (2000) Technology Acceptance Model (TAM), utilizing a 7-point Likert scale, ranging from 1 = strongly disagree to 7 = strongly agree (α = .88). The Innovation awareness scale, inspired by the research of Thompson et al. (2006) and Gu et al. (2013), was designed to assess aspects such as technology integration, extracurricular technology use, and early adoption of new tools. This scale also used a 7-point Likert format, ranging from 1 = strongly disagree to 7 = strongly agree (α = .80).

Data Analysis

The purpose of the study is to investigate the role of social and organizational support, technological efficacy, and innovation awareness in online teaching experience. Based on our conceptual model, we have derived the complex relationship between different constructs as dependent, mediating, and independent variables from theories and empirical evidence. Therefore, structural equation modeling (SEM) is appropriate for testing the model of multiple dependent variables (Hair et al., 2014).

The data analysis in this study involved three phases, including exploratory factor analysis (EFA) to explore the constructs and internal reliability of the instruments, confirmatory factor analysis (CFA) to further confirm the construct convergent and discriminant, and SEM to evaluate the hypothetical structural model. We performed the EFA using SPSS (version 22.0) to get the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity to verify whether the sample was appropriate for such analysis. CFA was performed with AMOS (version 26) using asymptotically distribution-free. Construct validity was examined through the standardized regression weights of measurement items, composite reliability (CR), and average variance extracted (AVE). Model fit was evaluated by the goodness of fit index (GFI), normed fit index (NFI), comparative fit index (CFI), incremental fit index (IFI), Tucker-Lewis index (TLI), and root-mean-square error of approximation (RMSEA), etc. The structural model was tested by examining the relationships among the latent variables and detecting the fitness of the proposed models.

Results

Measurement Validation

To evaluate the instrument validity and reliability, we used Cronbach alphas to assess internal reliability, the KMO to inspect whether the analyses yielded distinct, and reliable factors, CR to assess the construct reliability and AVE to assess convergent and discriminant validity criteria using confirmatory factor analysis (Hair et al., 2014). Table 2 illustrates the instrument’s validity and reliability. As shown, the internal reliability using Cronbach’s α indicates that all the items are above 0.80, indicating good reliability. All KMO values for individual items were above 0.70, which is well above the limit of 0.5. The CR for each construct ranged from 0.83 to 0.96, all higher than the recommended threshold of 0.60. The AVE of each construct ranged from 0.62 to 0.84 and exceeded the cut-off value of 0.5, demonstrating adequate construct validity because more than 50% variance is explained by the construct. The results indicate satisfactory internal reliability, convergent and discriminant validity.

Table 2.

Instrument Validity and Reliability.

Measures	Number of items	Factor loading	KMO	CR	AVE
Social support	4	0.79–0.85	0.80	0.90	0.68
Organizational support	5	0.73–0.92	0.83	0.93	0.72
Technological efficacy	4	0.65–0.94	0.81	0.90	0.70
Innovation awareness	3	0.70–0.83	0.70	0.83	0.62
Online teaching experience	4	0.85–0.97	0.78	0.96	0.84

Test of Structural Model

The test of the structural model includes examining the model fit and statistical significance of the hypothesized path among the five variables. The indices indicated that the hypothesized structural model fitted the data well ( $χ^{2} / df$ = 3.85; GFI = 0.95; AGFI = 0.93; PGFI = 0.63; NFI = 0.89; CFI = 0.92; IFI = 0.92; TLI = 0.89; RMSEA = 0.03). We employed SEM to test our hypothesis regarding the direct effects of social support and organizational support on technological efficacy and innovation awareness, as well as the direct effect of technological efficacy and innovation awareness on online teaching experience. Figure 2 shows the coefficients of model and the significant values were labeled with asterisks. The results of path analysis are shown in Table 3.

Figure 2.

Structural equation model analysis.

Table 3.

Path Analysis and Path Coefficients of Structural Relationship.

Path	Standardized coefficient (β)	SE	t
Social support→Technological efficacy	0.220	0.028	5.389***
Social support→Innovation awareness	0.215	0.033	5.127***
Social support→Online teaching experience	0.059	0.058	1.997*
Organizational support→Technological efficacy	0.300	0.029	7.838***
Organizational support→Innovation awareness	0.218	0.034	5.611***
Organizational support→Online teaching experience	0.080	0.064	2.717**
Technological efficacy→Online teaching experience	0.204	0.078	7.516***
Innovation awareness→Online teaching experience	0.070	0.066	2.623**

p < .05. **p < .01. ***p < .00.

Regarding RQ1, we found that social support and organizational support had significant positive effects on technological efficacy, innovation awareness and online teaching experience directly. Specifically, social support had a positive impact on the technological efficacy (β = .220) and innovation awareness (β = .215), indicating that the more that the instructors were aware of the supports from leaders and colleagues in the online course, the more they were willing to try new information techniques in teaching practice. In addition, the organizational support positively affected technological efficacy (β = .300), innovation awareness (β = .218), and online teaching experience (β = .080) directly, implying that greater financial support and enhanced institutional safeguards are conducive to fostering instructors’ awareness of technological innovation, acceptance, and their online teaching experiences.

With regards to RQ2 on the direct effect of technological efficacy and innovation awareness on online teaching experience, the results showed that technological efficacy (β = .204) and innovation awareness (β = .070) all positively affected online teaching experience. These findings suggest that instructors who had higher technological efficacy and innovation awareness were more likely to actively participate in online courses and demonstrate better teaching performance.

Mediation Analysis

Mediation analysis was conducted to address RQ3. In the analysis, the dependent variables (DVs) were online teaching experience, the mediator variable comprised technological efficacy and innovation awareness, while the independent variables (IVs) were social support and organizational support. The results indicated that technological efficacy and innovation awareness both significantly mediated the relationship between teaching support and the online teaching experience. These findings suggest that technological efficacy and innovation awareness partially mediate the connection between teaching support and the online teaching experience, underscoring its value in facilitating the translation of social and organizational support into a high-quality participation and experience within the online learning environment. Furthermore, when considering the standard total effect values, the impact of each dimension on the learning effect ranged from strong to weak as follows: technological efficacy (estimate = 0.204), organizational support (estimate = 0.157), social support (estimate = 0.119), and innovation awareness (estimate = 0.07), as Table 4 shows. This implies that technological efficacy and innovation awareness play pivotal roles in shaping the online teaching experience.

Table 4.

Results of Mediation Analysis for online teaching Experience: Total Effect, Direct Effect, and Indirect Effect.

Independent variables	Dependent variables	Social support	Organizational support	Technological efficacy	Innovation awareness
Standardized direct effects	Technological efficacy	0.220	0.300	—	—
	Innovation awareness	0.215	0.218	—	—
	Online teaching experience	0.059	0.08	0.204	0.07
Standardized indirect effects	Online teaching experience	0.060	0.077	—	—
Standardized total effects	Technological efficacy	0.220	0.300	—	—
	Innovation awareness	0.215	0.218	—	—
	Online teaching experience	0.119	0.157	0.204	0.07

Conclusion and Discussion

The goal of this study was to examine how teaching support affects online teaching experiences by including technological efficacy and innovation awareness as key teacher characteristics in a large-scale survey. Building on the literature surrounding teaching support and experience, we developed a conceptual model and hypothesized that teaching support would have both direct and indirect effects on online teaching experience, with technological efficacy, and innovation awareness mediating this relationship. The findings supported our model, highlighting the mediating roles of technological efficacy and innovation awareness in the connection between teaching support and actual online teaching experience. These results enhance our understanding of how teaching support influences instructors’ online teaching experiences and offer important insights for effectively encouraging teacher engagement in online teaching.

The Relationship Between the Teaching Support and Online Teaching Experience

Our study revealed that teaching support, encompassing both social and organizational support, exerted significant direct, and indirect effects on the online teaching experience. This aligns with previous research highlighting the critical role of teaching support in addressing the challenges faced by online educators. Prior studies show that robust instructional support systems—such as technical assistance, professional development, and collaborative networks—can alleviate barriers to effective online teaching (Cutri et al., 2020; Green et al., 2020). Specifically, teaching support mitigates obstacles such as unclear performance expectations (Hattangdi et al., 2010) and excessive workload (Lloyd et al., 2012).

From a social perspective, the practical experiences and feedback shared by colleagues significantly impact instructors’ online teaching experiences. Interaction and collaboration with colleagues who have experience in online teaching can provide invaluable insights and practical strategies, thereby enhancing overall teaching efficacy. Moreover, the support and encouragement from school leaders play a crucial role in promoting the adoption of online teaching methods. When instructors perceive that their efforts in online teaching are valued and supported by their superiors, they are more likely to engage positively with online teaching. Organizational support is equally vital. The encouragement, resources, and policies provided by the school administration directly influence instructors’ willingness and ability to engage in online teaching. Incentive measures, such as recognizing and rewarding effective online teaching practices, can motivate instructors to invest more effort, and creativity into their online courses. Similarly, ensuring job security and providing adequate technical and professional development support can alleviate anxieties related to the transition to online teaching.

The Mediating Role of Technological Efficacy and Innovation Awareness

The findings of this study highlight the significant mediating roles of technological efficacy and innovation awareness in the relationship between teaching support and online teaching experience. This finding is consistent with TAM proposed by Davis, which assesses instructors’ psychological states regarding their willingness to use specific technologies (P. Silva, 2015).

In the context of online teaching, perceived usefulness, ease of use, and the value that the technology brings are essential factors that determine whether instructors engage with the technology and subsequently influence their online teaching experiences (Stritto & Aguiar, 2024; Xiao et al., 2024). Additionally, the important role of innovation awareness in this study aligns with Vidergor’s (2023) findings, which suggest that when teachers perceive themselves as innovative, they are better able to implement effective online teaching practices. The results of this study indicate that when instructors perceive strong support from their institutions, including colleagues’ practical experiences, leadership support, and institutional policies, they are more likely to develop a higher sense of technological efficacy and innovation awareness. When instructors believe they can easily and efficiently use online teaching technologies, their confidence and competence improve, leading to a higher quality of online teaching experiences.

Implications for Educational Practices for Engaging Instructors in Online Learning

Teacher engagement is vital for the success of online and blended learning environments (Anderson, 2008). To thrive in online teaching, instructors must be proactive learners, embracing new technologies and innovative pedagogical approaches. This study highlights that insufficient instructional support, low innovation awareness, and limited technology acceptance significantly hinder instructors’ online teaching experiences. Therefore, efforts are needed to promote teacher engagement in online teaching in the following ways.

Firstly, instructional support from peers and leaders is crucial for improving online teaching experiences. Universities should promote collaboration among instructors to share resources and best practices. Leaders should create supportive communities that allow educators to discuss challenges and collaborate on solutions (Kearns, 2016). Institutions should also offer professional development tailored to varying expertise levels, and establish dedicated online teaching support teams to assist instructors with technical, pedagogical, and design challenges (DeCoito & Estaiteyeh, 2022). Secondly, with the constant evolution of online teaching technologies, instructors must stay informed about new tools and methods. Encouraging self-directed learning through online courses and seminars focused on emerging technologies can help instructors build confidence and innovation skills. Universities should provide access to resources, updates on new technologies, and encourage participation in professional learning communities. Thirdly, social and organizational support plays a significant role in enhancing technological efficacy. Universities should provide technical training and resources to help instructors stay current with online teaching trends. Additionally, continuous improvements to teaching platforms, focusing on user-friendliness and accessibility, can foster a culture of innovation. Sharing successful examples of technology integration can inspire instructors and provide practical strategies for enhancing online teaching practices (Ertmer & Ottenbreit-Leftwich, 2010).

Practical Implications

Enhancing instructors’ online teaching experiences has become a prominent topic in higher education research. This study systematically explored the mechanisms influencing online teaching experiences, utilizing data from a survey of instructors’ perceptions and practices. However, several limitations should be noted. First, the factors influencing instructors’ online teaching experiences are complex and multifaceted, including the nested effects of school types, regional characteristics, individual factors, and online teaching abilities (Bates, 2015). Exploring these influencing factors using multilevel linear models requires further investigation. Additionally, this research is based on data from China, suggesting the need for cross-cultural studies to understand how different cultural and institutional contexts impact online teaching.

To address the aforementioned limitations, future research can adopt the following approaches: (1) Cross-Cultural and Cross-Temporal Studies: Conduct research that spans different cultural backgrounds and timeframes to analyze instructors’ experiences and performance in using online teaching under various cultural and societal conditions. This comparative approach will shed light on how cultural and temporal factors influence online teaching experiences. (2) Mixed-Methods Research: A mixed-methods approach, combining large-scale surveys with qualitative methods (e.g., interviews, case studies, ethnography), can offer a richer, more nuanced understanding of the factors influencing online teaching. This approach allows for better triangulation of data and a more comprehensive exploration of the complex dynamics that shape instructors’ online teaching experiences (Creswell & Clark, 2017). By pursuing these research directions, future studies can contribute to a more nuanced understanding of online teaching dynamics, enhancing our ability to design more effective interventions and support systems for instructors across different contexts

Footnotes

Acknowledgements

We would like to thank the participating instructors for responding to the questionnaire truthfully and to the best of their abilities.

ORCID iD

Weitong Liu

Ethical Considerations

This study was conducted in accordance with the Declaration of Helsinki. Ethical approval was not required, as the research involved anonymous online surveys with no risk to participants’ confidentiality or employability. A statement at the beginning of the survey explicitly informed participants that they could choose not to answer any question and that completing and submitting the questionnaire constituted their informed consent to participate. No identifiable data was collected, and participants had the right to withdraw from the study at any time without any consequences. We affirm that this research adheres to ethical principles.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by: National Education Science Planning General Project “Research on Digital Modeling and Assessment of College Students’ Learning Processes Based on Multimodal Data” (BIA240130).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

According to the Non-Disclosure Agreement (NDA), the data cannot be disclosed through public channels. The corresponding author can provide the datasets used and/or analyzed during the current study upon reasonable request.

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