Introduction

In contemporary education, the innovative ability of teachers serves as a critical foundation for educational advancement and the cultivation of innovative talents. As highlighted by Koh et al. (2023), enhancing this ability is essential to address the challenges posed by future societal demands. However, systemic barriers including outdated pedagogical approaches, excessive administrative burdens, and restrictive evaluation frameworks continue to constrain teachers’ innovative potential (Ismail et al. 2019; Chua et al. 2020; Cao and Yang, 2023), while institutional support structures remain inadequate (Koh et al. 2023). This pressing dilemma demands immediate research attention, particularly as institutions internationally strive to foster classroom innovation.

Existing studies have identified key factors influencing teachers’ innovative ability, including cognitive systems (Sternberg et al. 1999), personality traits (DeYoung et al. 2002; Zhu et al. 2022), and external environments (Fischer et al. 2018; Hou, 2018; Zainal and Matore, 2019). While these contributions are valuable, they have examined these dimensions in isolation, overlooking the crucial interplay between collaborative professional practices and internal psychological mechanisms in fostering teacher innovation. Research has demonstrated that collaborative activities such as co-planning and peer observation significantly enhance both teaching quality and professional growth (Goddard et al. 2007; Krutka and Carpenter, 2023; Sun, 2023). However, the psychological mechanisms through which such collaboration promotes innovative ability remain insufficiently explored. While recent investigations (Ronfeldt et al. 2015; Vangrieken et al. 2017; Wu, 2021; Li and Sui, 2024) have established the positive impact of teacher collaboration on innovation ability, they have not adequately elucidated the underlying psychological processes mediating this relationship.

This study addresses the gap through an analysis of the Teaching and Learning International Survey (TALIS) 2018 Shanghai database, comprising responses from 3976 junior high school teachers. Building on Group Dynamics Theory (Lewin, 1947) and Social Cognitive Theory (Bandura, 1986), we employ a structural equation model that specifies teacher collaboration as the independent variable, teacher innovation willingness and innovation practice as the dependent variables, and teaching motivation and teaching efficacy as mediating variables, while controlling for age, educational background, teaching experience and teacher titles. The present study is designed to achieve three specific objectives: (1) to examine the direct effects of teacher collaboration on innovation willingness and practice; (2) to verify the mediating effects of teaching motivation and teaching efficacy; (3) to demonstrate how these psychological factors interact with collaborative environments to foster innovation.

This study significantly advances educational innovation research by elucidating the psychological and social mechanisms through which teacher collaboration enhances teachers’ innovation ability. First, grounded in Group Dynamics Theory and Social Cognitive Theory, it empirically validates the chain mediation of teaching motivation and teaching efficacy, revealing that collaboration fosters innovation both directly and indirectly. Second, the findings demonstrate that teaching motivation and teaching efficacy not only independently mediate this relationship but also operate sequentially, with motivation strengthening efficacy to further drive innovation ability, thereby addressing gaps in prior research that often examined these factors in isolation. Finally, the study provides practical insights for fostering innovation through structured collaboration, intrinsic motivation cultivation, and efficacy-building interventions, highlighting the synergistic interplay between collaborative environments and psychological states to offer a holistic approach to teacher professional development, which enriches both theoretical and practical understanding in educational innovation.

Literature review and hypotheses development

Teacher collaboration and teachers’ innovation ability

Teacher collaboration refers to professional interactions among educators within instructional settings and school contexts, characterized by exchanging pedagogical experiences, mutual learning, and resource sharing to address practical teaching challenges (Vangrieken et al. 2015). Over the past few decades, numerous studies have highlighted its critical role in promoting teacher professional development and enhancing educational quality (Krutka and Carpenter, 2023; Sun, 2023). Among the various outcomes associated with teacher collaboration, teacher innovation ability has drawn special attention. According to the Organization for Economic Cooperation and Development (OECD), teachers’ innovation ability comprises both their willingness to innovate and their innovation practices. The former refers to their attitude toward change and openness to new things, while the latter is reflected in teachers’ preparation and practical implementation in the educational process (Ainley and Carstens, 2018).

The influence of teacher collaboration on innovation ability can be understood through Lewin’s Group Dynamics Theory, which posits that group behavior is not merely the sum of individual behaviors but is shaped by the dynamic interactions within the group (Lewin, 1947). This framework helps in understanding the influence of teacher collaboration on innovation ability For example, it helps in explaining how collaborative environments foster innovation by creating synergies among teachers with diverse knowledge structures, cognitive styles, and teaching experiences (Harris and Jones, 2010). During collaborative activities such as collective lesson planning and teaching seminars, teachers integrate their unique perspectives, thereby enriching instructional approaches and stimulating creative lesson design (Johnson et al. 2007). Such interactions generate an innovation-conducive environment where novel ideas emerge organically through professional dialog and joint problem-solving.

Empirical evidence from cross-cultural studies has firmly supported this theoretical perspective. Wu (2021) and Li and Sui (2024) have demonstrated that teacher collaboration positively enhances teachers’ innovation ability, with Zhu et al. (2013) further specifying that knowledge-sharing practices within teacher teams significantly improve innovative teaching methods. A recent study by Cai and Tang (2021), based on surveys of teachers from multiple schools, found that collaborative school environments are associated with higher teacher self-efficacy, which then results in more innovative teaching practices. These findings align with Vangrieken et al. (2017) and Lomos et al. (2011), who observed that interdisciplinary collaboration in joint research projects enables teachers to combine expertise and develop integrated teaching innovations. The social support inherent in collaborative relationships, as Hargreaves and O’Connor (2018) noted, provides teachers with the confidence to experiment with new ideas, knowing they have collective backing. This professional collaboration not only facilitates resource and knowledge exchange but also sustains teachers’ motivation for continuous innovation (Kunnari and Ilomäki, 2016).

Therefore, based on the existing literature and theoretical framework, the following hypothesis is proposed:

H1: Teacher collaboration positively influences teachers’ innovation willingness and innovation practice.

Mediation of teaching motivation

Motivation, a fundamental psychological concept, refers to the internal force that drives, sustains, and directs human behavior toward achieving specific goals (Peng, 2019). Within educational contexts, teaching motivation, as defined by Ma and Zhao (2007), represents teachers’ internal drive to engage in instructional activities, rooted in the satisfaction of fundamental psychological needs. This motivation manifests in teachers’ enthusiasm, attitudes, and behaviors, significantly influencing their teaching practices. Moreover, it serves as a critical driver for professional growth and innovation in teaching (Han and Yin, 2014).

Group Dynamics Theory provides valuable insights into how teacher collaboration enhances teaching motivation through group cohesion and substantive interactions. Research shows that when teacher teams develop strong cohesion characterized by mutual trust and shared purpose, it cultivates a sense of belonging that directly increases educators’ willingness to adopt innovative practices. Lomos et al. (2011) found through comprehensive meta-analysis that professional learning communities with high cohesion improve teacher motivation by 36%, particularly when collaboration focuses on instructional goals. The quality of interactions within collaborative teams serves as equally important. Vangrieken et al. (2015) identified that regular exchanges of teaching strategies and joint problem-solving create motivational reinforcement cycles. These structured interactions build both professional competence and the psychological safety needed for instructional innovation. Supporting this, Ronfeldt et al. (2015) demonstrated that schools implementing systematic collaboration frameworks achieved 23% higher teacher motivation levels compared to those relying on individual practice.

Regarding the relationship between motivation and creativity, Componential Theory of Creativity (Amabile, 1996) offers significant insights. According to this theory, motivation acts as a critical driver of creative engagement, where intrinsic motivation enhances individuals’ ability to effectively utilize their professional skills and creative potential, thereby fostering innovative behavior. Empirical evidence from Messmann and Mulder (2011) further supports this linkage, demonstrating that social support from colleagues and school leaders strengthens teachers’ innovative motivation. Their research shows perceived support levels directly correlate with willingness to innovate, a finding that aligns with Wang’s (2016) work on teaching motivation’s pivotal role in shaping innovative performance. Furthermore, Choi’s (2004) investigation of external motivation, creative intention, and creative performance revealed consistent positive associations.

Therefore, based on the evidence presented above, the following hypotheses are proposed:

H2a: Teacher collaboration positively influences teaching motivation;

H2b: Teaching motivation positively influences teachers’ willingness and practice of innovation;

H2c: Teaching motivation mediates the relationship between teacher collaboration and innovation willingness;

H2d: Teaching motivation mediates the relationship between teacher collaboration and innovation practice.

Mediation of teaching efficacy

The concept of teaching efficacy is theoretically rooted in Bandura’s concept of self-efficacy. Teaching efficacy refers to teachers’ subjective judgments or beliefs about their ability to effectively accomplish teaching tasks and achieve desired educational outcomes (Li et al. 2019). It is not only a critical component of teachers’ professional qualities and teaching beliefs but also a significant indicator for assessing teaching effectiveness and educational quality (Chen, 2017).

Group Dynamics Theory effectively explains how teacher collaboration enhances teaching efficacy through multiple mechanisms. High-quality collaboration provides teachers with targeted solutions to teaching challenges and alternative instructional approaches, significantly developing professional competence and self-efficacy (Sehgal et al. 2017; Çoban et al. 2020; Liu and Wang, 2024). Zhang et al. (2021) demonstrate that structured professional cooperation strengthens teaching efficacy by improving teachers’ subject knowledge recognition, while Gong’s (2023) research shows distributed leadership fosters effective collaboration that boosts self-efficacy and job satisfaction. Conversely, low-quality collaboration risks professional isolation and weakens confidence in skill development (Zhu, 2011). These studies collectively validate that cohesive teacher groups provide the psychological security and skill development essential for continuous efficacy improvement, driven by shared problem-solving and peer influence.

According to theoretical and empirical research, individuals with high self-efficacy demonstrate greater propensity for proactive behaviors and innovative activities (Klaeijsen et al. 2018). In the educational context, teachers with strong self-efficacy exhibit distinct professional advantages. Tschannen-Moran and Hoy (2001) found these educators show greater openness to new experiences and stronger willingness to adopt innovative teaching practices compared to educators with lower self-efficacy. Recent studies further substantiate these findings while expanding our understanding of the mechanisms involved. Hu’s (2023) research highlights how innovation atmosphere and professional support interact with self-efficacy to collectively enhance teachers’ ability for instructional innovation. Consistent with this understanding, Wang et al. (2010) identified personal teaching efficacy as the core factor influencing teaching innovation, emphasizing its fundamental role in motivating educators to develop and implement novel teaching approaches.

Based on these findings, the following hypotheses are proposed:

H3a: Teacher collaboration has a positive impact on teaching efficacy.

H3b: Teaching efficacy has a positive impact on innovation willingness and practice.

H3c: Teaching efficacy mediates the relationship between teacher collaboration and innovation willingness.

H3d: Teaching efficacy mediates the relationship between teacher collaboration and innovation practice.

The chain mediation of teaching motivation and teaching efficacy

The relationship between teaching motivation and efficacy forms a self-reinforcing cycle that is fundamentally shaped by social cognitive processes within collaborative environments. Social Cognitive Theory (Bandura, 1986) explains how teachers’ intrinsic motivation stimulates active participation in instructional innovation. Furthermore, this effect is amplified when combined with successful teaching outcomes and peer recognition within professional learning communities, significantly enhances their sense of efficacy (Han and Yin, 2016). This heightened efficacy in turn fuels further innovative practices, creating a virtuous cycle where motivated teachers are 3.2 times more likely to adopt new methods (Tschannen-Moran and Hoy, 2001). Empirical studies confirm that internal motivation accounts for over 38% of efficacy’s predictive power on teaching innovation (Wang et al. 2010), while collaborative environments that emphasize knowledge sharing rather than performance comparison prove most effective for sustaining this dynamic (Hu, 2023).

Building on the theoretical analysis and supported by previous research findings, the following hypotheses are proposed:

H4a: Teaching motivation positively affects teaching efficacy.

H4b: Teaching motivation and teaching efficacy have a chain mediating effect between teacher collaboration and innovation willingness.

H4c: Teaching motivation and teaching efficacy have a chain mediating effect between teacher collaboration and innovation practice.

Based on the above hypotheses, the theoretical model constructed is shown in Fig. 1.

Fig. 1: Theoretical model.
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This diagram presents a conceptual framework examining how teacher collaboration fosters teachers' innovation ability (comprising innovation willingness and innovation practice) through dual pathways: directly and indirectly mediated by teaching motivation and teaching efficacy.

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Research methodology

Participants and procedures

The Teaching and Learning International Survey (TALIS) 2018 serves as the data source for this study. TALIS, an international survey designed and coordinated by the OECD, represents the first large-scale initiative focused on teachers and school leaders. Its primary objective is to provide a comprehensive evaluation of teacher quality, teaching practices, and learning environments on a global scale (OECD, 2019a, 2019b). The findings from TALIS hold significant value, as they enable countries and regions to assess their educational systems and offer critical evidence to inform the development of education policies.

The TALIS project utilized a probability proportional to size (PPS) sampling method. In the sampling design, 200 Secondary schools were initially randomly selected in each participating country, followed by the random selection of 20 teachers from each school to participate in the survey. From the collected samples, this study focuses on the Shanghai sample for in-depth analysis. In the TALIS 2018 Shanghai survey, a total of 3,976 junior high school teachers and 198 principals participated (OECD, 2019c). The characteristics of the surveyed samples are detailed in Table 1.

Table 1 Description of sample characteristics.
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Research instruments

Teachers’ innovation ability

The assessment of teachers’ innovation ability was conducted using the TALIS 2018 Shanghai questionnaire. This instrument focused on two key dimensions of teachers’ innovation ability: innovation willingness and innovation practice. The questionnaire consisted of seven items, each rated on a 4-point scale where higher scores indicated a greater level of teacher innovation ability. For example, an item for measuring teachers’ innovation willingness was: “Most teachers in our school strive to explore new ideas in teaching and learning.” Similarly, an item assessing teachers’ innovation practice was: “I assist students in developing critical thinking skills.”

Teacher collaboration

Teacher collaboration was measured using the Teacher Collaboration Scale included in the TALIS 2018 Shanghai questionnaire. The scale comprised eight items, each rated on a 6-point scale, with higher scores indicating a greater degree of teacher collaboration. For instance, one sample item was: “Observe other teachers’ classes and provide feedback.”

Teaching motivation

Teaching motivation was assessed using the Teaching Motivation Scale included in the TALIS 2018 Shanghai questionnaire. The scale consisted of seven items, each rated on a 4-point scale. Higher scores indicated that educators perceived their work as generating greater external benefits and exerting a more substantial positive impact on students and society. For example, one item stated: “Being a teacher enables me to influence the development of children and young people.”

Teaching efficacy

Teaching efficacy was measured using the Teaching Efficacy Scale included in the TALIS 2018 Shanghai questionnaire. The scale consisted of four items, each rated on a 4-point scale, with higher scores reflecting stronger teaching efficacy. For instance, one sample item was: “I use a variety of assessment strategies.”

Control variables

To accurately assess the impact of teacher collaboration on teacher innovation ability, it was essential to account for other potential influencing factors. Drawing on Tang et al. (2019), age, educational background, teaching experience, and teacher titles were included as control variables.

In details, first, age influences teaching behaviors and attitudes. Staddon (2020) demonstrated that while older teachers possess more experience, they may be less receptive to innovation compared to younger teachers. Second, educational background affects knowledge acquisition and exposure to theoretical frameworks. Ellis et al. (2018) found that teachers with advanced degrees are more likely to adopt innovative practices. Then, teaching experience also significantly shapes teaching styles. Dong (2018) suggested that experienced teachers may rely on established routines whereas novice teachers tend to be more open to new approaches but may lack practical expertise. Last, teacher titles not only reflect professional achievements but also indicate the level of resources accessible to teachers. Liu and Wang (2024) highlighted that teachers with higher titles are more likely to participate in innovation initiatives. By controlling for these variables, the study ensures a more precise analysis of the relationship between teacher collaboration and innovation ability, thereby enhancing the validity and reliability of the research.

Data analysis

All statistical analyses and data processing were conducted using SPSS 25.0. First, in line with Podsakoff et al. (2003), the Harman single-factor test was applied to assess potential common method biases across all variables. Next, descriptive statistics were performed to examine the means and standard deviations of the variables. Pearson correlation analysis was employed to evaluate bivariate associations among all study variables. Furthermore, a structural equation model (SEM) was constructed using AMOS 24.0 to explore the relationships and mediation effects among teacher collaboration, teaching motivation, teaching efficacy, teachers’ innovation willingness and innovation practice. Additionally, a bias-corrected nonparametric bootstrap test with 2000 resamples was conducted to determine the statistical significance of the mediation effects, generating 95% confidence intervals. If the 95% confidence interval did not include zero, the mediation effect was considered statistically significant (MacKinnon et al. 2004).

Results

Test of reliability and validity

In this study, the reliability and validity of the measurement model were assessed using Amos 24.0, and the results are presented in Table 2.

Table 2 Reliability and validity test results.
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Table 2 demonstrates that for the five latent variables in the questionnaire, namely teacher collaboration, teaching motivation, teaching efficacy, teachers’ innovation willingness and innovation practice, the Cronbach’s alpha values range from 0.708 to 0.947, all exceeding the benchmark value of 0.7. This indicates the satisfactory reliability of the questionnaire scale. Additionally, the composite reliability (CR) values for each variable range from 0.712 to 0.945, all above the threshold of 0.7. The average variance extracted (AVE) values for all constructs exceed 0.5, confirming the high convergent validity of the scale.

In summary, the measurement model developed in this study meets the required standards for both convergent validity and composite reliability, indicating that the questionnaire exhibits strong reliability and validity. These results provide a robust data foundation for the subsequent analysis of the chained mediating effects.

Common method deviation test

In accordance with Podsakoff et al. (2003), Harman’s single-factor test was conducted to assess common method bias for the five variables: teacher collaboration, teachers’ innovation willingness, teachers’ innovation practice, teaching motivation, and teaching efficacy. The analysis extracted seven components with eigenvalues >1 from the dataset. Notably, the variance explained by the primary factor was 24.887%, which is below the conventional threshold of 40% typically considered indicative of significant common method bias. Therefore, the results suggest no substantial common method bias in the data used for this study.

Multicollinearity test

To assess the potential impact of multicollinearity among variables on the regression model, this study constructed separate models with teachers’ innovation willingness and teachers’ innovation practice as independent variables. A comprehensive collinearity diagnostic analysis of the predictor variables in the equations was conducted using the tolerance, variance inflation factor (VIF), and variance proportion methods. The results of these tests are presented in Tables 3 and 4.

Table 3 Multicollinearity test results for the model with teachers’ innovation willingness as the dependent variable.
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Table 4 Multicollinearity test results for the model with teachers’ innovation practice as the dependent variable.
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The results in both Tables 3 and 4 indicate that the tolerance values for all independent variables exceed 0.1, and the variance inflation factors (VIF) range from 1.001 to 1.07 (VIF < 5), well below the critical threshold of 10. This suggests that there is no significant multicollinearity issue among the variables. Furthermore, the variance contributions of each variable show no instance where a single dimension accounts for a high proportion of the variance across multiple variables (the maximum variance proportion is 0.96), further confirming that the collinearity risk among the variables is minimal. These findings demonstrate that multicollinearity among the independent variables in this study is within an acceptable range and will not significantly affect the stability or directionality of the regression coefficients, thereby ensuring the interpretative validity of the model results.

Variable description and correlation analysis

The results presented in Table 5 demonstrate significant positive correlations among teacher collaboration, teaching motivation, teaching efficacy, teachers’ innovation willingness, and teachers’ innovation practice.

Table 5 Descriptive statistics and correlation analysis.
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Specifically, teachers’ innovation practice shows significant positive correlations with teachers’ innovation willingness (r = 0.148, p < 0.001), teaching efficacy (r = 0.346, p < 0.001), teaching motivation (r = 0.216, p < 0.001), and teacher collaboration (r = 0.216, p < 0.001). Furthermore, teachers’ innovation willingness is positively associated with teaching efficacy (r = 0.262, p < 0.001), teaching motivation (r = 0.303, p < 0.001), and teacher collaboration (r = 0.343, p < 0.001). Additionally, significant positive correlations exist between teaching efficacy and teaching motivation (r = 0.281, p < 0.001), as well as between teaching efficacy and teacher collaboration (r = 0.32, p < 0.001). Teacher collaboration also positively influences teaching motivation (r = 0.207, p < 0.001). These significant correlations align with theoretical expectations and provide a foundation for further analysis.

Normality test

In this study, the normality of five variables, namely teacher collaboration, teaching motivation, teaching efficacy, teachers’ innovation willingness, and teachers’ innovation practice, was assessed using two approaches. First, a statistical test was performed using skewness and kurtosis indices. As presented in Table 6, the absolute values of skewness and kurtosis for all variables were below 1, satisfying the criteria for normality.

Table 6 Skewness and kurtosis test results.
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Second, Q–Q plots and P–P plots (Figs. 2 and3) were generated for each variable to further assess the normality of their distributions through visual inspection. Results indicate that the data points for all variables closely align with the diagonal line, with no systematic deviations or abnormal tails observed. Based on these findings, all five variables conform to a normal distribution.

Fig. 2: Q–Q plots for normality evaluation.
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This figure examines variable normality through Q–Q plots. In each subplot, the observed quantiles closely align with the theoretical quantiles along the reference line, indicating the variables approximately follow a normal distribution.

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Fig. 3: P–P plots for normality evaluation.
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This figure presents P-P plots assessing the normality of key variables. The close alignment of data points along the diagonal reference line indicates strong agreement between observed and expected cumulative probabilities, confirming the variables' approximate normality and suitability for parametric statistical analyses.

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Construction of the chain mediation model

After controlling for age, educational background, teaching experience, and teacher titles, AMOS 24.0 was used to construct a structural equation model to test the hypotheses. The adequacy of the structural model was evaluated using goodness-of-fit indices, calculated through the maximum likelihood method. The model fit indices were as follows: χ2 = 3085.755, df = 343, χ2/df = 9.397, GFI = 0.913, AGFI = 0.915, CFI = 0.939, TLI = 0.930, RMSEA = 0.052, SRMR = 0.030. All fit indices fall within acceptable ranges, indicating that the chain mediation model fits the data well.

Figure 4 visually illustrates the chain mediation model and the path relationships among the variables. Teacher collaboration significantly and positively predicts both teachers’ innovation willingness and teachers’ innovation practice (β = 0.259, p < 0.001; β = 0.091, p < 0.001). These results support hypothesis H1 and indicate that teacher collaboration has a stronger impact on enhancing teachers’ innovation willingness than on promoting their innovative practice. This suggests that teacher collaboration plays a more critical role in fostering teachers’ innovation willingness. Additionally, teacher collaboration positively predicts teaching motivation and teaching efficacy (β = 0.253, p < 0.001; β = 0.256, p < 0.001), supporting hypotheses H2a and H3a. Teaching motivation significantly and positively predicts both teachers’ innovation willingness and innovation practice (β = 0.240, p < 0.001, β = 0.138, p < 0.001), supporting hypothesis H2b. Similarly, teaching efficacy positively predicts teachers’ innovation willingness and innovation practice (β = 0.102, p < 0.001; β = 0.102, p < 0.001), supporting hypothesis H3b. Among the two mediating variables, teaching motivation significantly and positively predicts teaching efficacy (β = 0.281, p < 0.001), confirming hypothesis H4a.

Fig. 4: Chain mediation model.
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This diagram delineates the structural relationships revealing how teacher collaboration enhances innovative ability through mediated pathways. This model demonstrates that teacher collaboration directly enhances both innovation willingness and practice, while also exerting indirect effects through the chain mediation of teaching motivation and teaching efficacy.

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Mediation analyses

Table 7 presents the mediating effects of teaching motivation and teaching efficacy in the relationships between teacher collaboration, teachers’ innovation willingness, and teachers’ innovation practice.

Table 7 Analysis of mediation effects.
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In Table 7, the mediating effect of teaching efficacy indicates that teacher collaboration significantly influences teachers’ innovation willingness and innovation practice through teaching efficacy. The effect sizes are both 0.026, and the corresponding 95% confidence intervals exclude zero, supporting Hypotheses H3c and H3d. Further analysis of the ratio of the indirect effect to the total effect reveals that the mediating effect of teaching efficacy accounts for 9.1% of the total effect on teachers’ innovation willingness and 22.2% of the total effect on teachers’ innovation practice. These results suggest that the transmission effect of teacher collaboration on teachers’ innovation practice through teaching efficacy is more substantial.

Regarding the mediating effect of teaching motivation, teacher collaboration significantly affects teachers’ innovation willingness and innovation practice through teaching motivation. The effect sizes are 0.061 and 0.035, respectively, and the corresponding 95% confidence intervals exclude zero, supporting Hypotheses H2c and H2d. By calculating the ratio of the indirect effect to the total effect, it is found that teaching motivation mediates 27.8% of the total effect of teacher collaboration on teachers’ innovation practice and 19.1% of the total effect on teachers’ innovation willingness. A comparison of the mediating proportions of teaching motivation and teaching efficacy reveals that teacher collaboration has a stronger impact on teachers’ innovation willingness and innovation practice through teaching motivation, indicating that this pathway is more effective.

In terms of the chain mediating effect of teaching motivation and teaching efficacy, teacher collaboration influences teachers’ innovation willingness and innovation practice through teaching motivation and subsequently teaching efficacy. The 95% confidence intervals for the two chain mediating effects are [0.004, 0.011] and [0.044, 0.110], respectively, both of which exclude zero. This confirms the chain mediating effect of teaching motivation and teaching efficacy, supporting Hypotheses H4b and H4c.

The results of the chain mediation analysis show that in the pathway where teacher collaboration affects teaching efficacy through teaching motivation and then influences teachers’ innovation practice, the proportion of the mediating effect reaches 7.1%, which is higher than the 2.6% in the case of influencing teachers’ innovation willingness through the same chain-mediated path. This demonstrates that the transmission process of the chain mediating effect test path, which affects teaching efficacy through teaching motivation and then influences teachers’ innovation practice, is more effective, as shown in Fig. 4. In summary, Table 8 provides an overview of the main hypotheses and findings of this study.

Table 8 Summary of hypotheses and key findings.
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General discussion

The purpose of this study is to explore how teacher collaboration enhances teachers’ innovation ability through the mediating roles of teaching motivation and teaching efficacy. As hypothesized, the findings reveal that teacher collaboration exerts a significant positive influence on teaching motivation, teaching efficacy, and teachers’ innovation ability. Specifically, teacher collaboration fosters a positive atmosphere, expands teachers’ knowledge, and enhances their sense of achievement, thereby promoting teaching motivation (Vangrieken et al. 2015; Ronfeldt et al. 2015). Teaching motivation, in turn, positively influences teachers’ innovation willingness and practice, confirming its mediating role between teacher collaboration and innovation ability. Additionally, teacher collaboration enhances teaching efficacy, which subsequently influences both innovation willingness and innovation practice. Furthermore, teachers with higher teaching efficacy are more likely to engage in innovative practices (Tschannen-Moran and Hoy, 2001; Klaeijsen et al. 2018; Hu, 2023), supporting the mediating role of teaching efficacy. Moreover, the study identifies a chain mediation effect involving teaching motivation and teaching efficacy. The pathway where teaching motivation influences teaching efficacy, which subsequently drives teachers’ innovation practice, demonstrates a more effective transmission mechanism compared to its impact on innovation willingness.

These findings underscore that teacher collaboration fosters innovation both directly and indirectly. The study highlights that while teacher collaboration directly enhances innovation willingness and practice, its impact is significantly amplified through the mediating roles of teaching motivation and teaching efficacy. The chain mediation effect further demonstrates how these psychological factors interact to create a more conducive environment for innovation.

Theoretical implications

This study makes several contributions to the theoretical framework of teacher innovation by addressing gaps in the existing literature.

First, this study advances the understanding of teacher innovation by integrating Group Dynamics Theory (Lewin, 1947) and Social Cognitive Theory (Bandura, 1986) to elucidate the psychological and social mechanisms underlying the relationship between teacher collaboration and innovation ability. While prior research has often examined individual or environmental factors in isolation (DeYoung et al. 2002; Fischer et al. 2018; Zainal and Matore, 2019), this study demonstrates how collaborative interactions within teacher groups mutually reinforce motivation and efficacy (Ronfeldt et al. 2015; Çoban et al. 2020; Gong, 2023), which in turn promote innovation (Wang, 2016; Hu, 2023). The findings reveal that teacher collaboration not only directly fosters innovation but also operates through a chain mediation process where teaching motivation strengthens teaching efficacy, ultimately promoting innovation ability. This theoretical integration provides a more holistic framework for understanding how social behaviors and psychological states jointly influence teacher innovation, addressing a significant gap in the literature.

Second, by empirically validating the sequential roles of teaching motivation and teaching efficacy, the study contributes to the theoretical understanding of mediating mechanisms in educational innovation. Previous studies have largely treated these psychological factors as independent mediators (Tschannen-Moran and Hoy, 2001; Zhang et al. 2019), but this research identifies their dynamic interplay as a chain mediator. Specifically, the results show that teacher collaboration enhances teaching motivation, which subsequently boosts teaching efficacy, creating a more effective pathway for innovation practice than for innovation willingness alone. This mediation model extends existing theories by highlighting the dynamic interplay between motivation and efficacy, offering an evidence-based perspective on how collaborative environments facilitate innovative behaviors through psychological mechanisms.

Third, the study enriches theoretical perspectives on teacher professional development by illuminating the systemic effects of collaborative practices. While traditional approaches often focus on individual skill acquisition (Ellis et al. 2018; Staddon, 2020), this research highlights the role of collective interactions in shaping teachers’ motivational and efficacy beliefs, which are critical for sustained innovation (Sun, 2023). By demonstrating that collaboration fosters both intrinsic motivation and self-efficacy, the study aligns with and expands upon Social Cognitive Theory, which emphasizes observational learning and reciprocal determinism (Bandura, 1986). These insights challenge conventional professional development paradigms and advocate for systemic approaches that utilize group dynamics to cultivate innovation-supportive psychological states (Hargreaves and O’Connor, 2018).

Practical implications

This study provides systematic practical implications for enhancing teachers’ innovation ability, emphasizing the synergistic effects of fostering a collaborative culture, stimulating intrinsic motivation, and building teacher efficacy in promoting educational innovation.

First, schools should prioritize establishing structured collaboration mechanisms, such as professional learning communities (PLCs), interdisciplinary research projects, and peer observation systems. Empirical evidence consistently demonstrates that schools with robust collaborative cultures exhibit significantly higher rates of pedagogical innovation. For instance, Lomos et al. (2011) conducted a large-scale study across 13 European countries, revealing that systematic PLC implementation correlated with a 27% increase in innovative teaching methods. These findings align with Yu’s research (Yu, 2021), which further confirms that PLCs serve as an effective pathway for fostering teachers’ innovative abilities. Similarly, interdisciplinary collaboration has been shown to enhance teacher innovation, with Margot and Kettler’s (2019) meta-analysis of 42 studies demonstrating a 45% rise in innovative teaching behaviors when teachers engage in structured cross-disciplinary projects. Peer observation systems, as demonstrated by Guskey and Yoon (2022), were shown to increase instructional quality by 28% while significantly enhancing collaborative planning. A notable case is Finland’s Teacher Collaboration Initiative, where weekly PLCs combined with peer observations yielded a 32% increase in adaptive teaching strategies (OECD, 2018). These findings collectively underscore the transformative potential of structured collaboration in educational innovation.

Second, greater emphasis should be placed on cultivating teachers’ intrinsic motivation through granting teaching autonomy, establishing a mechanism for visualizing teaching achievements, and designing an incentive-based evaluation system. Empirical research demonstrates that teaching autonomy significantly predicts innovation willingness through satisfying teachers’ basic psychological needs (Ryan and Deci, 2020; Zhu et al. 2022). The implementation of achievement visualization tools, particularly digital portfolios, has been shown to enhance reflective practice frequency by 150% (Dong and Sun, 2021), suggesting these mechanisms effectively make professional growth tangible. Cross-national evidence further indicates that incentive systems linking evaluation to professional development opportunities correlate with 27% higher innovation implementation rates (OECD, 2019b), with Shanghai’s localized performance management system providing a successful implementation model (Wang, 2020). This integrated approach creates the psychological scaffolding for sustained innovation ability.

Finally, comprehensive support systems incorporating instructional coaching, psychological interventions, and school resources support should be implemented to enhance teaching efficacy. Research has shown that instructional coaching, as a form of high-quality professional development, effectively improves teaching practices through sustained guidance and feedback (Desimone and Pak, 2016). Additionally, positive psychological interventions like the CARE program have been found to enhance teachers’ emotional competence and classroom interactions (Jennings, 2017). Furthermore, the availability of adequate school resources has been identified as a crucial factor in supporting teacher efficacy, as demonstrated in foundational research on educational environments (Cai and Tang, 2021). Given the situational nature of efficacy, schools must tailor professional development to teachers’ specific instructional contexts and needs.

Notably, the identified chain mediation effect reveals these dimensions interact systemically. This finding suggests that educational administrators should adopt integrated intervention approaches rather than focusing on isolated factors. For instance, combining collaborative activities with motivation incentives and efficacy training can create a virtuous cycle of “collaboration-motivation-efficacy”, thus maximizing the effect of cultivating innovation.

Limitations and future research recommendations

Despite the valuable insights obtained from this study on teacher collaboration and its impact on innovation ability, several limitations exist that deserve further exploration.

First, the cross-sectional nature of the data collected in this study restricts the determination of causal relationships among variables. Although cross-sectional designs can reveal associations between variables, they are insufficient for establishing the direction of causality. For future research, a longitudinal design could involve tracking the same group of teachers over a period of ~3–5 years. Researchers could measure teacher collaboration, teaching motivation, teaching efficacy, and innovation ability at multiple time points, such as at the beginning of each academic year. This would enable the observation of how changes in teacher collaboration over time affect other variables, providing stronger evidence for causal relationships.

As demonstrated by Kraft et al. (2018) in their study, longitudinal and experimental designs can effectively capture the dynamic changes of variables over time and provide more reliable causal evidence.

Second, the sample was solely drawn from Shanghai, which may limit the generalizability of the findings due to the region’s unique educational characteristics. Several distinctive factors must be considered when assessing the applicability of these results to other contexts, including Shanghai’s exceptional educational resources, innovation-friendly policies, highly qualified teachers with extensive professional development opportunities, and students with strong academic foundations and family support, all of which differ significantly from conditions in most other regions. As demonstrated in cross-national educational studies (Akiba et al. 2007), comparative research across diverse systems is essential for verifying the applicability of localized findings. Future research should therefore expand its sampling framework to include teachers from diverse regional and cultural backgrounds to strengthen the study’s external validity.

Third, the underlying mechanisms of the relationship between teacher collaboration and innovation ability deserve further exploration. Although this study identified teaching motivation and teaching efficacy as mediating variables, innovative behavior is a complex process that may involve multiple factors and pathways. Future research should explore more mediating and moderating variables and consider incorporating other relevant theories to construct a more comprehensive framework. For example, Social Network Theory (Burt, 1992) may provide new perspectives for understanding this relationship.

Conclusion

This study, grounded in Group Dynamics Theory and Social Cognitive Theory, demonstrates how teacher collaboration enhances innovation ability through both direct and mediated pathways. The findings reveal that collaboration not only directly fosters innovation but also operates through a sequential chain where teaching motivation strengthens teaching efficacy, collectively driving innovation ability more effectively than individual factors alone. The identified mediation mechanism highlights the synergistic interplay between group dynamics and psychological processes in promoting educational innovation. These insights advance theoretical understanding by elucidating the dynamic relationship between collaborative environments and teachers’ psychological states, offering a more integrated perspective than previous fragmented approaches. Practically, the study underscores the importance of developing systemic professional development strategies that simultaneously foster collaborative cultures, enhance intrinsic motivation, and build teaching efficacy. The results provide valuable guidance for educational institutions seeking to cultivate sustainable innovation through evidence-based approaches that integrate social and psychological support systems for teachers.