Why are Chinese university teachers (not) confident in their competence to teach? The relationships between faculty-perceived stress and self-efficacy

International Journal of Educational Research 100 (2020) 101529

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Why are Chinese university teachers (not) confident in their competence to teach? The relationships between faculty-perceived stress and self-efficacy

T

Hongbiao Yina, Jiying Hanb,*, Brian E. Perronc a

Department of Curriculum & Instruction, Faculty of Education, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong Special Administrative Region b School of Foreign Languages and Literature, Shandong University, Jinan, Shandong, 250100, China c School of Social Work, University of Michigan, Ann Arbor, MI, 48109, USA

ARTICLE INFO

ABSTRACT

Keywords: Stress Self-efficacy Social cognitive theory University teacher China

This study explored the relationships between university teachers’ perceived stress and their selfefficacy beliefs, and the differences in the relationships across teachers from different tiers of institutions. A sample of 2758 teachers from 25 higher education institutions in China participated in the study. This study shows that stress from organisational inadequacy and new challenges were negatively associated with self-efficacy. Although stress from financial inadequacy and undesirable student quality were positively related to self-efficacy, the effect sizes were very small and have no practical significance. The results of multi-group analysis revealed significant differences in the relationships between perceived stress and self-efficacy beliefs among teachers from different tiers of institutions. These results provide some implications for improving university teachers’ self-efficacy.

1. Introduction Self-efficacy refers to ‘beliefs in one’s capabilities to organise and execute the courses of action required to produce given attainments’ (Bandura, 1997, p. 3). Self-efficacy is a widely studied construct that has been integrated in various cognitive motivation theories including attribution theory, expectancy-value theory, and goal theory (Bandura, 1993). In educational settings, teachers’ self-efficacy beliefs have been found to play a key role in the outcomes of students (e.g., achievement and motivation) and teachers (e.g., motivation and effective instructional methods) (see Skaalvik & Skaalvik, 2007; Tschannen-Moran & Hoy, 2001). Bandura (1997) has postulated four principal sources contributing to self-efficacy: mastery experience, vicarious experience, verbal persuasion, and physiological /affective states. Educational researchers have wide agreement that studies exploring the sources of teacher efficacy are essential building knowledge regarding the formation of teacher efficacy (Goddard, Hoy, & Hoy, 2004). However, empirical evidence on the sources of teacher efficacy is limited (Klassen, Durksen, & Tze, 2014). Stress is a common indicator of teachers’ psychological state. The literature on faculty stress in different countries has shown to be a key feature of occupational life for university teachers, which is related to teacher wellbeing, work performance, emotional exhaustion, and engagement (Han, Yin, Wang, & Bai, 2019; Winefield & Jarrett, 2001). As one of the principal sources of self-efficacy, psychological changes influence the level and strength of self-efficacy (Bandura, 1987). However, studies to date have revealed

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Corresponding author. E-mail addresses: [email protected] (H. Yin), [email protected] (J. Han), [email protected] (B.E. Perron).

https://doi.org/10.1016/j.ijer.2019.101529 Received 31 January 2019; Received in revised form 8 November 2019; Accepted 28 December 2019 0883-0355/ © 2019 Elsevier Ltd. All rights reserved.

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inconsistent findings concerning the effects of psychological changes (Klassen & Durksen, 2014; Schwarzer & Hallum, 2008). The influence of psychological changes on self-efficacy has received the least attention in educational settings (Morris, Usher, & Chen, 2017). Empirical evidence is expected to help clarify the relationship between university teachers’ perceived stress and self-efficacy. To date, the majority of the research on teacher efficacy has been conducted in Western settings, focusing on primary and secondary school teachers. A critical gap in knowledge exists regarding efficacy among teachers in higher education institutions (HEIs) in nonWestern settings (Klassen, Usher, & Bong, 2010). The contextual changes in China’s higher education system reinforce the necessity of this study. In China, the need to raise the country’s international competitiveness and its international reputation for its higher education and quality teaching in higher education have posed increasing challenges for university teachers (Lai, Du, & Li, 2014). Consequently, the excessive expectations of university teachers have led to high levels of stress (Rhoads, Wang, Shi, Chang, & Ji, 2014). Employment reform in Chinese higher education, with an emphasis on privileged research over teaching, has intensified the pressure (Tian & Lu, 2017). Since 2017, the implementation of ‘Double First Class’ initiative, a programme aiming at developing numerous world-class universities and disciplines by the end of 2050, has made teaching in Chinese higher education institutions more demanding (Peters & Besley, 2018). However, very little is known about how university teachers in China, especially those from different tiers of HEIs, perceive the stress of university teaching and their self-efficacy beliefs. This study addressed such research gaps by investigating the relationships between perceived stress from different sources and self-efficacy beliefs among teachers from different tiers of Chinese HEIs. 2. Literature 2.1. Teacher efficacy Teachers’ self-efficacy, a powerful mechanism in explaining human motivation (Bandura, 1997), plays a significant role in teachers’ motivation to positively influence the outcome for teachers and students (Klassen et al., 2014). There are two conceptual strands of theory and research contributing to the concept of teacher efficacy (Tschannen-Moran, Woolfolk Hoy, & Hoy, 1998): studies influenced by the early work of the RAND organisation using the theoretical orientation of Rotter’s (1966) social learning theory, and studies grounded in Bandura’s (1997) social cognitive theory. Elaborating on these theories, Gibson and Dembo (1984) introduced two influential dimensions of teacher efficacy. The first is personal teaching efficacy, which reflects teachers’ beliefs about their skills to bring about student learning. The second is general teaching efficacy, which focuses on teachers’ belief that the external constraints would be overcome. Given that the focus of general teaching efficacy is external orientation rather than teachers’ belief about their capabilities, criticism has arisen (Tschannen-Moran & Hoy, 2001) and subsequently led to the increased call for adherence to Bandura’s social cognitive conceptualisation of self-efficacy (Tschannen-Moran et al., 1998). According to Bandura’s (1997) definition of self-efficacy, individuals’ sense of self-efficacy is closely related to their confidence in themselves, and expected outcomes are positively related to one’s self-efficacy beliefs (McCormick, 2001). In educational settings, teachers’ self-efficacy refers to the beliefs teachers hold about their capabilities to affect students’ learning (Tschannen-Moran et al., 1998). Teachers’ self-efficacy is positively associated with positive attitudes about teaching and confidence in teaching abilities. Over the past couple decades, considerable attention has been devoted to examining the influence of teachers’ self-efficacy on students’ achievement and motivation (e.g., Klassen, Tze, Betts, & Gordon, 2011; Morris et al., 2017). Self-efficacy beliefs are different from other characteristics of the self (e.g., self-concept, self-worth and self-esteem). More sepcifically, self-efficacy beliefs are, are goal-oriented, with a context-specific, task-dependent and future-oriented sense of competence (Schunk & Pajares, 2009; Tschannen-Moran et al., 1998). Despite a considerable number of studies exploring the role that teachers’ self-efficacy plays in the performance and outcomes of teachers and students, the complexities in educational settings have proposed major challenges for self-efficacy beliefs in general across different domains (Schunk & Pajares, 2009). Bandura (1997) postulated four principal sources of self-efficacy: (1) enactive mastery experiences that serve as a cognitive basis of capability; (2) vicarious experience that affects self-efficacy beliefs through the referential comparisons with others’ attainment; (3) verbal persuasion that one possesses the capabilities; and (4) physiological and affective states that act as somatic indicators relevant in judging capabilities and vulnerability to dysfunction. These four sources also contribute to teachers’ self-efficacy, which explains why educational researchers usually attach importance to the examination of sources of teachers’ self-efficacy beliefs (Tschannen-Moran & McMaster, 2009; Tschannen-Moran et al., 1998). Research into the sources of teachers’ self-efficacy can clarify our theoretical understanding into the formation and transformation of self-efficacy. This can inform practical strategies for improving teachers’ professional competence and teaching effectiveness (Goddard et al., 2004; Klassen et al., 2011). As most studies of teaching efficacy have focused on elementary- and secondary-school teachers, Chang, Lin, and Song (2011) attempted to integrate efficacy theory into studies of university teachers. Using a framework of six dimensions, this approach describes how competence develops and is functionally related to teachers’ knowledge and teaching philosophy (Biggs, 1989). The six dimensions include transmission of information, instructional strategy, technology usage, classroom management, interpersonal relations, and learning assessment. 2.2. Faculty stress Teacher stress is defined as the experience of unpleasant negative emotions, such as anger, anxiety, tension, frustration or depression, which results from the occupation demands of teaching and the mismatch between those demands and teachers’ coping 2

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strategies (Kyriacou, 2001). Durham (1992) identified three approaches to understanding the nature of teacher stress that focus on external pressures, unpleasant emotional and psychosomatic manifestations, and availability of coping resources. Each approach by itself has numerous limitations (see Durham, 1992). An interaction approach emphasises the importance of identifying the sources of stress and availability coping resources (e.g. self-efficacy beliefs). The environment stimuli or situations that evoke such stress are stressors, which are closely related to negative outcomes (Renshaw, Long, & Cook, 2015). A comprehensive understanding of stress among university teachers requires a careful exploration of the relationship between faculty-perceived stressors and their efficacy beliefs. University teachers experience stress when they perceive a lack of resources to deal with the stressors confronting them. Consequently, this experience of stress may lead to decreased levels of wellbeing and work performance (Han et al., 2019). Previous studies have identified a number of faculty stressors in higher education. One of the most influential studies in the Chinese context is the work of Leung, Siu, and Spector (2000). Specifically, using a Hong Kong sample of university teachers, they identify search sources, including recognition (stress caused by inadequate recognition of personal values), perceived organisational practices (stress caused by inadequate consultation and communication with university authorities), factors intrinsic to teaching (stress caused by teaching-related factors including teaching load and student evaluation of teaching), financial inadequacy (stress caused by inadequate financial support), home/work interface (stress caused by conflicting demands of family and work), student quality (stress caused by the declining quality of students), and new challenges (stress caused by new technology and innovation). Follow-up studies also reported that factors such as teaching research conflict, increased number of students and workload, contribute to faculty stressors in both Western and Chinese contexts (e.g. Kinchin & Hay, 2007; Lai et al., 2014). 2.3. The relationship between faculty stress and self-efficacy Prior research has shown teachers’ perceptions of stress influence their self-efficacy beliefs (Klassen & Chiu, 2010, 2011; Ross & Bruce, 2007). Thus, targeting stress levels is considered an effective strategy for enhancing teachers’ self-efficacy (Bandura, 1997). However, the direction of causality in this relationship is not entirely clear. For example, some researchers suggest teachers’ selfefficacy influences their job stress (Schwarzer & Hallum, 2008). Klassen and Durksen (2014) found that an increase in teachers’ selfefficacy beliefs did not result in a reduction of stress. Their qualitative analysis suggested that teachers’ coping strategies may moderate the relationship between perceived stress and self-efficacy beliefs. 2.4. Contextual factors influencing teachers’ self-efficacy Bandura’s (1997) social-cognitive perspective suggests that an ecologically valid evaluation of self-efficacy requires consideration of cultural and institutional factors. A majority of the early research and theory on teacher efficacy emerged from a Western context (Klassen et al., 2011). Cross-cultural studies of this construct have found notable variations in teaching practices and teaching environments influence teachers’ self-efficacy beliefs (Klassen et al., 2010; Pajares, 2007), which limits the generalizability of the Western research. Most of the cross-cultural research has focused on primary and secondary school teachers (Postareff, LindblomYlänne, & Nevgi, 2007), with few studies focusing on the university teachers. Further research is needed to identify sources on selfefficacy beliefs in the pedagogical, content, and technological knowledge of university teachers from diverse backgrounds (Morris et al., 2017). The present study helps address these gaps in knowledge by examining the influence of institutional context on the relationship between university teachers’ perceived stress and self-efficacy. In mainland China, HEI’s are institutionally stratified and hierarchically structured (Hayhoe, Li, Lin, & Zha, 2012). The first tier is research-oriented institutions, which are operated by the Ministry of Education and fall under the banner of ‘Double World-Class’, a national key construction project of high-quality universities in China (Han, Yin, & Wang, 2018). The second tier is teaching-oriented institutions, which are operated by provincial governments. The third tier is profession-oriented vocational colleges, which are also operated by provincial governments. In the process of decentralizing authority and diversifying funding, Chinese university teachers of different tiers of HEIs have reported significant differences in their perceived self-efficacy beliefs (Han et al., 2018). Thus, we can expect differences in tiers to be associated with different sources and levels of stress. They are expected to encounter different sources and levels of stress due to variations in objectives of their professional development and availability of financial resources. In short, this study aims to examine the relationships between university teachers’ perceived stress and self-efficacy in the various tiers of Chinese HEIs. Specifically, this study is oriented around two specific research questions: 1) what is the association between stress and self-efficacy among Chinese university teachers? And, 2) are these associations stable across different tiers of HEIs? 3. Methodology 3.1. Participants The sample consisted of university teachers drawn from 25 HEIs across Shandong province, which is located in the eastern part of China. Teachers were selected by stratified random sampling and invited to voluntarily participate in an online questionnaire survey. The analysis was based on usable responses from 2758 university teachers of the invited sample. This included three researchoriented universities (n = 489 teachers), 12 teaching-oriented universities (n = 1416), and 10 vocational institutions (n = 853 teachers). Slightly more than half of the sample was female (56.1 %). Approximately, 11.5 % of participants had less than 3 years of teaching experience, 18 % had 3–6 years, 50.9 % had 7–15 years, and 12.8 % had more than 15 years. Regarding professional ranks, 3

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Table 1 The sub-scales and sample items. Sub-scales The Revised Sources of Faculty Stress Recognition inadequacy Organisational inadequency Factors intrinsic to teaching Financial inadequacy Teaching research conflict Unfavorable student quality New challenges The Faculty Teaching Efficacy Questionnaire Course design Instructional strategy Technology usage Classroom management Interpersonal relations Learning assessment

No. of items

Sample item

3 3 5 2 3 3 3

Inadequate opportunities for career advancement. Lack of consultation and communication with university authority. Too many assignments and papers to mark. Inadequate training or financial assistance for further study. Demands research makes on my teaching. The quality of students are declining. Applying modern education technology.

5 5 5 5 3 5

Select appropriate teaching material. Have confidence in inspiring and maintaining students’ learning motivation. Know how to utilize technology to enhance my teaching. Nurture a pleasant learning environment. Maintain a good relationship with my students. Utilize a variety of assessment methods to evaluate students’ learning outcomes.

13.1 % were classified as teaching assistants (the beginning rank of HEIs in China), 53.9 % lecturers, 27.4 % associate professors, and 5.6 % professors. 3.2. Measures The online survey was conducted in December 2015. In addition to items related to participants’ background information, two scales were included in the questionnaire. These scales included the Revised Sources of Faculty Stress (R-SFS) and the Faculty Teacher Efficacy Scale (FTE). Table 1 provides details of the subscales and sample items. 3.2.1. The Revised Sources of Faculty Stress (R-SFS) The original Sources of Faculty Stress (SFS) scale (Leung et al., 2000) consisted of 24 items and was developed to measure Hong Kong faculty members’ perceived stressors in seven dimensions. The scale is prefaced with the heading ‘As a university teacher, I felt stress because (of)…’ Scale items were modified based on the results of our pilot study. This included adding two more items to the ‘student quality’ and ‘new challenge’ constructs. We also replaced the ‘home/work interface’ construct with ‘teaching-research conflict.’ This change was made because the tension between teaching and research is regarded as one of the most significant challenges for Chinese faculty members in China (Lai et al., 2014). Finally, we deleted six items that are not relevant to higher education. The R-SFS used in this study consisted of 22 items on a 6-point Likert scale from 1 ‘strongly disagree’ to 6 ‘strongly agree’. The subscales of the measure include recognition inadequacy (RE), perceived organisational inadequacy (OI), factors intrinsic to teaching (IT), financial inadequacy (FI), teaching-research conflict (TRC), unfavourable student quality (SQ) and new challenges (NC). 3.2.2. The Faculty Teaching Efficacy Questionnaire (FTE) The 28-item FTE was developed by Chang et al. (2011) as a measurement for university teachers’ perceptions of efficacy. This measure taps six dimensions of self-efficacy related to course design (CD), instructional strategy (IS), technology usage (TU), classroom management (CM), interpersonal relations (IR) and learning assessment (LA). Each item is scored on a 4-point scale from 1 ‘strongly disagree’ to 4 ‘strongly agree’ where higher scores indicate a higher level of teacher-perceived efficacy. 3.3. Data analysis Less than 5 % of the data were missing, which were imputed using expectation-maximisation (EM). The internal reliability of the data was obtained by calculating Cronbach’s α coefficients, and the construct validity was verified by conducting confirmatory-factor analysis (CFA) using AMOS 22.0. Structural equation modelling (SEM) was then constructed to explore the relationship between teacher-perceived stress and teacher efficacy. Although the literature suggests that a well-fitting model fit requires CFI and TLI values of no less than.95 and RMSEA under .08 (Schreiber, Stage, King, Nora, & Barlow, 2006), a value higher than .90 was originally considered acceptable (Bentler, 1992). In addition, multi-group invariance analyses were conducted to test whether the measurement model was equivalent across different tiers of HEIs. The invariance testing included a series of hierarchical steps which began with the determination of a baseline model for each group separately. Following this preliminary work, tests for equivalence of parameters were conducted. This began with a configural model in which no parameters were constrained to be equal. This configural model was used as a baseline reference for comparing two other models (see Byrne, 2010). The first model is the measurements weights model, which constrained only the factor loadings to be equal. The second is the structural covariances model, which constrained factor loadings, factor variances and covariances to be equal. Based on the χ2 difference, the invariance-testing approach requires △χ2 to be statistically non-significant for 4

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Table 2 Estimates of internal consistency, mean values, standard deviation, and inter-factor latent correlations among study factors (N = 2758).

Stressors Recognition inadequacy (RE) Organisational inadequacy (OI) Factors intrinsic to teaching (IT) Financial inadequacy (FI) Teaching/research conflict (TRC) Unfavourable student quality (SQ) New challenges (NC) Self-efficacy Course design (CD) Instructional strategy (IS) Technology usage (TU) Classroom management (CM) Interpersonal relations (IR) Learning assessment (LA) M SD

RE

OI

IT

FI

TRC

SQ

NC

(.82) .73** .63** .59** .47** .44** .37**

(.87) .69** .58** .47** .47** .38**

(.86) .63** .55** .51** .44**

(.83) .51** .42** .34**

(.88) .36** .36**

(.92) .45**

(.86)

.01 −.20 .02 .00 .02 .00 4.16 1.10

−.01 −.03 −.02 −.04 −.04 −.04* 3.82 1.21

.03 .01 .02 .02 .02 .01 4.06 1.04

.05** .03 .05** .06** .05** .04* 4.47 1.16

.04 −.01 .03 .02 .01 .01 4.34 1.22

.02 −.04 .02 −.02 .02 .01 4.37 1.15

−.15** −.14** −.15** −.13** −.10** −.11** 3.87 1.17

CD

IS

TU

CM

IR

LA

(.91) .72** .70** .68** .63** .66** 3.48 .48

(.90) .68** .75** .64** .71** 3.27 .49

(.91) .74** .69** .73** 3.39 .48

(.90) .79** .78** 3.43 .47

(.87) .84** 3.44 .49

(.91) 3.39 .48

Note: ** p < .01, * p < .05 (two-tailed); Cronbach’s α coefficients in parentheses along the diagonal.

determining evidence of equivalence, and such a conclusion is based on the fact that △CFI never exceeds an absolute value of .01 in the practical approach (Cheung & Rensvold, 2002). 4. Results 4.1. Factorial validity and reliability The seven-factor R-SFS model and the six-factor FTS model exhibited strong empirical and conceptual fit. Specifically, the CFA fit indices of the R-SFS were within acceptable limits (χ2 = 2230.48, df = 188, p < .01, CFI = .95, TLI = .94, RMSEA = .063), with factor loadings ranging from .51 to .94. Internal consistency of the sub-scales ranged from .82 to .92 (see Table 2). The CFA fit indices of the FTS were also within acceptable limits (χ2 = 5462.67, df = 335, p < .01, CFI = .92, TLI = .91, RMSEA = .075). Factor loadings ranged from .75 to .86. Internal consistency of the subscales ranged from .87 to .91 (see Table 2). Omega values were nearly identical to Cronbach’s α values (Dunn, Baguley, & Brunsden, 2014). 4.2. Descriptive and correlation analyses Table 2 presents descriptive statistics and a correlation matrix for all factors. Results of one-way repeated measures ANOVA revealed significant differences between the mean scores on different sources of faculty-perceived stress (F(1,2757) = 1,466.04, p < .001) and factors of teacher efficacy (F(1,2757) = 1,069.76, p < .001). Post hoc comparison using the Bonferroni test showed that the mean score on stress from financial inadequacy (M = 4.47, SD = 1.16) was significantly higher than all other sources of stress. Additionally, mean scores on stress from organisational inadequacy (M = 3.82, SD = 1.21) and new challenges (M = 3.87, SD = 1.17) were significantly lower than all other sources of stress. As for teacher self-efficacy, the mean score on course design (M = 3.48, SD = 0.48) was significantly highest, and that on instructional strategy (M = 3.27, SD = 0.49) was significantly lower than other constructs of self-efficacy. However, although there were statistically significant differences, the effect sizes according to Cohen (1988) were quite small. Meanwhile, the mean score on stress from financial inadequacy was significantly higher than all other sources of stress, although the magnitude of the difference was small (η2 = .08). The standard deviation was also considerably larger than for other factors, suggesting a need to understand its variability and the mechanisms that account for differences in responding. The latent correlation matrix shown in Table 2 indicates that stress from organisational inadequacy negatively associated with self-efficacy in learning assessment. Financial inadequacy was positively associated with all self-efficacy constructs except instructional strategy. However, these associations were very small and we caution against making substantive interpretations. The stress of new challenges was the only stressor negatively correlated with self-efficacy constructs (see Table 2). 4.3. SEM and measurement invariance analyses The SEM results of the overall model including all participants exhibited an acceptable fit with the data (χ2 = 8727.41, df = 1097, p < .01, CFI = .93, TLI = .92, RMSEA = .050). The explained variance of self-efficacy factors ranged from .04 to .07. Fig. 1 shows the significant path coefficients. Non-significant paths are excluded to facilitate readability. The results suggest that stress from organisational inadequacy and new challenges negatively related to all self-efficacy constructs, and stress caused from financial inadequacy and unfavourable student quality were positively related to self-efficacy constructs. Factors intrinsic to teaching were positively related to self-efficacy for instructional strategy and classroom management, and negatively related to interpersonal 5

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Fig. 1. SEM model results showing path coefficients for all participants (N = 2758). Note: Goodness-of-fit indices: χ2 = 8727.41, df = 1097, p < .01, CFI = .93, TLI = .92, RMSEA = .050. Paths with non-statistically significant associations (p > = .05) are not reported; latent correlations among dependent variables were included; all constructs were specified as latent, but measurement models are not presented because this adds too much complexity to the figure.

relations. Recognition inadequacy was positively related to self-efficacy for interpersonal relations, and no significant relationships were found between stress from teaching-research conflict and self-efficacy factors. To examine whether the measurement model was invariant across university teachers from different tiers of institutions, three models were tested following Byrne’s (2010) approach. Table 3 presents the fit indices for these models. The configural model yielded an acceptable model fit (χ2 = 11796.72, df = 3295, p < .01, CFI = .92, TLI = .91, RMSEA = .031), indicating that the baseline model exhibits an acceptable fit across the different university tiers. When comparing with this baseline model, △CFI values for the measurement weights and structural covariances models reached the criterion of less than .01. However, computation of the χ2 difference value between the configural model and the measurement weights model (△χ2(70) = 130.87, p < .001) and that between the measurement weights model and the structural covariances model (△χ2(240) = 1123.94, p < .001) were statistically significant. These results suggest that the measurement model was not equivalent across university teachers of different tiers of institutions. Table 3 Goodness-of-fit statistics for structural equation models (N = 2758). Model

χ2

df

△χ2

△df

p

CFI

△CFI

TLI

RMSEA

AIC

ECVI

Moverall Configural model Measurement weights Structural covariances

8727.41 11796.72 11927.58 13051.53

1097 3295 3365 3605

– – 130.87 1123.94

– – 70 240

.00 .00 .00 .00

.93 .92 .92 .91

– – .000 −.008

.92 .91 .91 .91

.050 .031 .030 .031

– 13156.72 13147.58 13791.53

– 4.78 4.77 5.01

Note: △χ2 and△df represent the changes in chi-square and degrees of freedom, respectively, between each hierarchical model; Configural model: Factor structure constrained to be equal, Measurement weights: Factor loadings constrained to be equal, Structural covariances: factor loadings, factor variances and covariances constrained to be equal. 6

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Fig. 2. SEM results showing significant regression paths (p < .05) for teachers from research-oriented universities (N = 489). Note: Goodness-of-fit indices: χ2 = 2619.40, df = 1097, p < .01, CFI = .91, TLI = .90, RMSEA = .053. Paths with non-statistically significant associations (p > = .05) are not reported.

4.4. Comparison of SEM models among three groups Considering the measurement model was not invariant, three models for teachers from different tiers of HEIs were tested to clarify the differences in the relationships between faculty stressors and self-efficacy beliefs. SEM analyses resulted in acceptable model fit for teachers in research-oriented universities (χ2 = 2619.40, df = 1097, p < .01, CFI = .91, TLI = .90, RMSEA = .053), teachingoriented universities (χ2 = 5591.09, df = 1097, p < .01, CFI = .92, TLI = .91, RMSEA = .054) and vocational institutions (χ2 = 3574.48, df = 3295, p < .01, CFI = .93, TLI = .93, RMSEA = .051). However, the significant paths and path coefficients for each group of university teachers were different. Figs. 2–4 show the estimates of the three models. 5. Discussion This study contributes to knowledge of how university teachers’ self-efficacy beliefs are informed by their perceived stress in higher education. The results of the study, with a large sample of Chinese university teachers, provide some evidence on how different stressors affect perceptions of self-efficacy. Multi-group analyses suggest some differences in the strength of these associations across different tiers of HEIs. The results of the multi-group analyses reveal how the relationships between stress and selfefficacy beliefs vary across teachers of different tiers of HEIs. 5.1. Factors influencing university teachers’ self-efficacy University teachers’ perceived organisational inadequacy may be a stressor when there is a lack of consultation and communication with university authorities (Leung et al., 2000). This is consistent with prior research that shows a positive influence of organisational factors such as open communication, free exchange of ideas, leaders providing feedback, joint decision-making by superiors and employees, and a climate of trust in teachers’ teaching performance (Thoonen, Sleegers, Oort, Peetsma, & Geijsel, 2011). The above-mentioned factors were found to provide support to teaching, increase teachers’ ownership of organisational goals, link teachers’ needs to schools’ goals and mission, and facilitate teachers’ internalisation of organisational goals as personal goals and their sense of self-efficacy (Sleegers, Bolhuis, & Geijsel, 2005; Sleegers, Berg, & Geijsel, 2000). Our results provide further evidence 7

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Fig. 3. SEM results showing significant regression paths (p < .05) for teachers from teaching-oriented universities (N = 1416). Note: Goodness-of-fit indices: χ2 = 5591.09, df = 1097, p < .01, CFI = .92, TLI = .91, RMSEA = .054. Paths with non-statistically significant associations (p > = .05) are not reported.

for the significant link between stress and self-efficacy. This also echoes the findings of a previous study indicating that higher levels of administrative interventions might become stressors leading to negative consequences (Naghieh, Montgomery, Bonell, Thompson, & Aber, 2015). We found stress from new challenges had a negative impact on various dimensions of self-efficacy. Regarding new technology, previous studies provide evidence that teachers’ perceptions of their knowledge of educational technology and their pressure to demonstrate competency in integrating technology into teaching correlate directly with lower self-efficacy beliefs (Moorehayes, 2011; Wang, Ertmer, & Newby, 2004). As the rapid development of technology and the need to integrate it into teaching has become one of the prominent challenges to teachers in the 21 st century (Cennamo, Ross, & Ertmer, 2010), prior studies suggest that teachers’ low self-efficacy may be caused by their lack of confidence, willingness and preparedness to use technology (Moorehayes, 2011; Wang et al., 2004). From Bandura’s (1997) perspective, positive change in self-efficacy requires “explicit, compelling feedback that forcefully disputes the preexisting disbelief in one’s capabilities” (p. 82). As such, out study found that university teachers’ perceived stress of new technology and challenges exerted a negative impact on their sense of self-efficacy. Prior research indicates that teachers’ self-efficacy is based on both perceptions of the teaching context and student achievement (Caprara, Barbaranelli, Steca, & Malone, 2006; Tschannen-Moran et al., 1998). The current study revealed a positive association between financial inadequacy and various dimensions of self-efficacy, which is contrary to the existing self-efficacy theory and prior research. In the views of our participants, a condition of financial inadequacy may serve as a foil to the importance of human resources or teachers’ professional competency. Moreover, although all our study participants have some pressures to publish, the pressure to secure external funding to conduct empirical research is not equivalent across ranks or institutional tiers. This suggests a need to develop a more nuanced strategy for measuring stressors across different groups of teachers. Students’ misbehaviour and teaching workload, two constantly mentioned factors contributing to teachers’ overall stress, have been found to be associated with several negative outcomes including teachers’ reduced sense of efficacy (Klassen & Chiu, 2010). In the current study, we found significant positive effects of these stressors on teachers’ self-efficacy. While this may contradict prior 8

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Fig. 4. SEM results showing significant regression paths (p < .05) for teachers from vocational institutions (N = 853). Note: Goodness-of-fit indices: χ2 = 3574.48, df = 1097, p < .01, CFI = .93, TLI = .93, RMSEA = .051. Paths with non-statistically significant associations (p > = .05) are not reported.

research (e.g., Betoret, 2006; Klassen & Chiu, 2010), we want to highlight that our effect sizes were very small and have almost no practical significance. The statistical significance is largely determined by the significant statistical power from our sample size. Thus, we caution the reader from making substantive interpretations of these seemingly contradictory findings. We found that stress from teaching-research conflict was not associated with self-efficacy, indicating that teaching-research conflict has not caused negative influence on teacher self-efficacy in China Although it sounds like a good news, we have noted that more and more university teachers are giving their teaching less priority in order to meet research demands across countries (Rhoads et al., 2014). This trend is obvious in Western contexts in which academics gave research a higher priority, while devoting a limited amount of time and energy to teaching energy (Lucas, 2007; Parker, 2008). A recent study on the present employment reform among Chinese HEIs also found that research pressures resulted in lower motivation to teach among young teachers (Tian & Lu, 2017). 5.2. The differences across university teachers from different tiers of HEIs Results of multi-group analyses indicated that the structural model exhibited a good fit to the data for teachers from different tiers of HEIs. First, the positive relationship between teachers’ perceived stress caused by factors intrinsic to teaching and self-efficacy beliefs was only significant for teachers from research-oriented universities. This may be because teachers from research-oriented universities are more likely to perceive the stress caused by teaching as challenges rather than hindrances. Macey and Schneider (2008) indicated that challenging situations promote engagement when employees believed that their investment of effort and time would be rewarded in a meaningful way. When teachers from research-oriented universities felt increased stress from factors intrinsic to teaching, such as the increased teaching loads and requirements of quality teaching, they would be willing to engage themselves in efforts to successfully meet the challenging demands because they would like to feel more confident and view such efforts as an opportunity for growth and achievement (Crawford, Lepine, & Rich, 2010). Second, this study revealed negative relationships between the perceived stress from organisational inadequacy and self-efficacy 9

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beliefs among teachers of teaching-oriented and vocational HEIs. These findings highlight the importance of smooth consultation and communication with university authorities. Meanwhile, these findings partly echo Han et al.'s (2018) results that the provision of administrative support, especially the rewarding mechanism of developing university teachers’ competence in teaching and practice rather than the privileged emphasis on research output, facilitated faculty members’ self-efficacy beliefs in vocational institutions. 5.3. Limitations and directions for future research Two limitations have to be addressed to highlight the directions for future research. First, although the tested model is based on well-established theory, the cross-sectional design of this study makes it impossible to confirm the causal relationships between university teachers’ perceived stress and self-efficacy beliefs. Meanwhile, the findings of this study cannot reveal the dynamic process of university teachers’ perceived stress and self-efficacy beliefs. Some studies have examined the dynamic nature of teachers’ perceived stress and self-efficacy and have indicated that they both developed with the passage of time (e.g., Klassen & Durksen, 2014; Klassen et al., 2014). These gaps are expected to be addressed by longitudinal designs in the future. Second, the participants of this study were university teachers from one developed province in East China. Considering the regional differences of higher education in China, such as imbalanced development and financial investment due to regional disparities, it is suggested that future studies should consider greater representativeness of participants to gain more insights into the research questions. In another related study (Han, Yin, Perron, & Liu, 2020), we tested the influence of demographic and background characteristics on university teachers’ perceptions of stress and self-efficacy, showing significant but small associations. Moreover, we do not have strong theory that makes clear the specific role of these variables. Future studies should continue both empirical and theoretical work to more fully develop this area of research. 6. Implications for practice This study helps to clarify the relationships between university teachers’ perceived stress and self-efficacy beliefs, with a sample from different tiers of HEIs in China. Results of this study shed light on why university teachers in different tiers of Chinese HEIs are confident, or not confident in their teaching competence. These findings also have some implications for improving university teachers’ self-efficacy to teach. First, identifying the negative sources of university teachers’ self-efficacy, i.e. the stress caused by perceived organisational inadequacy and new challenges, serves as a reminder for administrators to provide proper support and guidance for university teachers and make sure that consultations and communications with institutional authorities are available for those teachers. Such a favourable social climate is especially significant for teachers from vocational and teaching-oriented institutions to develop their teaching capabilities. Meanwhile, practical assistance in integrating new technology into teaching is particularly important to prepare university teachers for the challenges. University administrators may consider setting up a public service sector in support of faculty members’ personalised needs. Second, although stress caused by teaching workloads was constantly reported to have negative influence on university teachers’ self-efficacy beliefs, this study revealed the potential positive roles in enhancing university teachers’ self-efficacy to teach. Such results suggest that the decisions to adjust teaching loads and financial support for teachers are complex. On the one hand, university teachers’ increased stress could be reduced for the sake of their wellbeing. On the other hand, it might be premature to suggest that challenging job demands be increased to promote university teachers’ self-efficacy beliefs. Given the differences among teachers from different tiers of HEIs, the ‘one-size-fits-all’ policies might be tailor-made to fit the different tiers. Specifically, increased teaching workloads might be considered to facilitate self-efficacy beliefs for teachers from research-oriented universities. Funding This work was supported by China’s Cultivation Program of Top Talents in Fundamental Science under Grant number 20181004, Young Scholars Program of Shandong University under grant number 2017WLJH09, and General Research Fund of Hong Kong SAR under grant number CUHK 14618118. Declaration of Competing Interest The authors declare that they have no competing financial interests. References Bandura, A. (1987). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28(2), 117–148. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman. Bentler, P. M. (1992). On the fit of models to covariances and methodology to the bulletin. Psychological Bulletin, 112(3), 400–404. Betoret, F. D. (2006). Stressors, self-efficacy, coping resources, and burnout among secondary school teachers in Spain. Educational Psychology, 26(4), 519–539. Biggs, J. B. (1989). Approaches to the enhancement of tertiary teaching. Higher Education Research & Development, 8(1), 7–25. Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). New York: Routledge. Caprara, G. V., Barbaranelli, C., Steca, P., & Malone, P. S. (2006). Teachers’ self-efficacy beliefs as determinants of job satisfaction and students’ academic achievement: A study at the school level. Journal of School Psychology, 44(6), 473–490.

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H. Yin, et al.

Cennamo, K., Ross, J., & Ertmer, P. (2010). Technology integration for meaningful classroom use: A standards-based approach (2nd ed.). Belmont, CA: Wadsworth Cengage Learning. Chang, T. S., Lin, H. H., & Song, M. M. (2011). University faculty members’ perceptions of their teaching efficacy. Innovations in Education and Teaching International, 48(1), 49–60. Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York: Routledge. Crawford, E. R., Lepine, J. A., & Rich, B. L. (2010). Linking job demands and resources to employee engagement and burnout: A theoretical extension and metaanalytic test. The Journal of Applied Psychology, 95(5), 834–848. Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 399–412. Durham, J. (1992). Stress in teaching (2nd ed.). London: Routledge. Gibson, S., & Dembo, M. H. (1984). Teacher efficacy: A construct validation. Journal of Educational Psychology, 76(4), 569–582. Goddard, R. D., Hoy, W. K., & Hoy, A. W. (2004). Collective efficacy beliefs: Theoretical developments, empirical evidence, and future directions. Educational Researcher, 33(3), 3–13. Han, J., Yin, H., & Wang, J. (2018). A case study of faculty perceptions of teaching support and teaching efficacy in China: Characteristics and relationships. Higher Education, 76, 519–536. Han, J., Yin, H., Wang, J., & Bai, Y. (2019). Challenge job demands and job resources to university teacher well-being: The mediation of teacher efficacy. Studies in Higher Education. https://doi.org/10.1080/03075079.2019.1594180. Han, J., Yin, H., Perron, E. B., & Liu, Y. (2020). Faculty stressors and their relations to teacher efficacy, engagement and teaching satisfaction. High Education Research and Development (under review and revision). Klassen, R. M., & Chiu, M. M. (2010). Effects on teachers’ self-efficacy and job satisfaction: Teacher gender, years of experience, and job stress. Journal of Educational Psychology, 102(3), 741–756. Klassen, R. M., & Chiu, M. M. (2011). The occupational commitment and intention to quit of practicing and pre-service teachers: Influence of self-efficacy, job stress, and teaching context. Contemporary Educational Psychology, 36(2), 114–129. Klassen, R. M., & Durksen, T. L. (2014). Weekly self-efficacy and work stress during the teaching practicum: A mixed methods study. Learning and Instruction, 33(9), 158–169. Klassen, R. M., Durksen, T. L., & Tze, V. M. C. (2014). Teachers’ self-efficacy beliefs. In P. W. Richardson, S. A. Karabenick, & H. M. G. Watt (Eds.). Teacher motivation: Theory and practice (pp. 109–115). New York: Routledge. Klassen, R. M., Tze, V. M. C., Betts, S. M., & Gordon, K. A. (2011). Teacher efficacy research 1998–2009: Signs of progress or unfulfilled promise? Educational Psychology Review, 23(1), 21–43. Klassen, R. M., Usher, E. L., & Bong, M. (2010). Teachers’ collective efficacy, job satisfaction, and job stress in cross-cultural context. Journal of Experimental Education, 78, 464–486. Kinchin, I. M., & Hay, D. B. (2007). The myth of the research‐led teacher. Teachers and Teaching, 13(1), 43–61. Kyriacou, C. (2001). Teacher stress: Directions for future research. Educational Review, 53(1), 27–35. Lai, M., Du, P., & Li, L. (2014). Struggling to handle teaching and research: A study on academic work at select universities in the Chinese Mainland. Teaching in Higher Education, 19(8), 966–979. Leung, T. W., Siu, O. L., & Spector, P. E. (2000). Faculty stressors, job satisfaction, and psychological distress among university teachers in Hong Kong: The role of locus of control. International Journal of Stress Management, 7(2), 121–138. Lucas, L. (2007). Research and teaching work within university education departments: Fragmentation or integration? Journal of Further and Higher Education, 31(1), 17–29. Macey, W. H., & Schneider, B. (2008). The meaning of employee engagement. Industrial and Organizational Psychology, 1(1), 3–30. McCormick, M. J. (2001). Self-efficacy and leadership effectiveness: Applying social cognitive theory to leadership. The Journal of Leadership Studies, 8(1), 22–33. Moorehayes, C. (2011). Technology integration preparedness and its influence on teacher-efficacy. Canadian Journal of Learning and Technology, 37(3), 1–15. Morris, D. B., Usher, E. L., & Chen, J. A. (2017). Reconceptualizing the sources of teaching self-efficacy: A critical review of emerging literature. Educational Psychology Review, 29(4), 795–833. Naghieh, A., Montgomery, P., Bonell, C. P., Thompson, M., & Aber, J. L. (2015). Organisational interventions for improving wellbeing and reducing work-related stress in teachers. The Cochrane Database of Systematic Reviews, 4. https://doi.org/10.1002/14651858.CD010306.pub2. Pajares, E. (2007). Culturalizing educational psychology. In F. Salili, & R. Hoosain (Eds.). Culture, motivation and learning (pp. 19–42). Charlotte: Information Age. Parker, J. (2008). Comparing research and teaching in university promotion criteria. Higher Education Quarterly, 62(3), 237–251. Peters, M. A., & Besley, T. (2018). China’s double first-class university strategy. Educational Philosophy and Theory, 50(12), 1075–1079. Postareff, L., Lindblom-Ylänne, S., & Nevgi, A. (2007). The effect of pedagogical training on teaching in higher education. Teaching and Teacher Education, 23(5), 557–571. Renshaw, T. L., Long, A. C., & Cook, C. R. (2015). Assessing teachers’ positive psychological functioning at work: Development and validation of the Teacher Subjective Wellbeing Questionnaire. School Psychology Quarterly, 30(2), 289–306. Rhoads, R. A., Wang, X., Shi, X., Chang, Y., & Ji, B. (2014). China’s rising research universities: A new era of global ambition. Baltimore: The Johns Hopkins University Press. Ross, J., & Bruce, C. (2007). Professional development effects on teacher efficacy: Results of randomized field trial. The Journal of Educational Research, 101(1), 50–60. Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs, 80(1), 1–28. Hayhoe, R., Li, J., Lin, J., & Zha, Q. (2012). Portraits of 21st century Chinese universities: In the move to mass higher education. Dordrecht, Netherlands: Springer. Schreiber, J. B., Stage, F. K., King, J., Nora, A., & Barlow, E. A. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research, 99(6), 323–338. Schunk, D. H., & Pajares, F. (Eds.). (2009). Self-efficacy theory. New York: Routledge. Schwarzer, R., & Hallum, S. (2008). Perceived teacher self-efficacy as a predictor of job stress and burnout: Mediation analyses. Applied Psychology: An International Review, 57, 152–171. Skaalvik, E. M., & Skaalvik, S. (2007). Dimensions of teacher self-efficacy and relations with strain factors, perceived collective teacher efficacy, and teacher burnout. Journal of Educational Psychology, 99(3), 611–625. Sleegers, P., Berg, R. V. D., & Geijsel, F. (2000). Building innovative schools: The need for new approaches. Teaching and Teacher Education, 16(7), 801–808. Sleegers, P., Bolhuis, S., & Geijsel, F. (2005). School improvement within a knowledge economy: Fostering professional learning from a multidimensional perspective. In N. Bascia, A. Cumming, A. Datnow, K. Leithwood, & D. Livingstone (Eds.). International handbook of educational policy (pp. 527–543). Dordrecht, Netherlands: Kluwer. Thoonen, E. E. J., Sleegers, P. J. C., Oort, F. J., Peetsma, T. T. D., & Geijsel, F. P. (2011). How to improve teaching practices: The role of teacher motivation, organizational factors, and leadership practices. Educational Administration Quarterly, 47(3), 496–536. Tian, M., & Lu, G. (2017). What price the building of world-class universities? Academic pressure faced by young lecturers at a research-centered university in china. Teaching in Higher Education, 22(3), 1–18. Tschannen-Moran, M., & Hoy, A. W. (2001). Teacher efficacy: Capturing an elusive construct. Teaching and Teacher Education, 17(7), 783–805. Tschannen-Moran, M., & McMaster, P. (2009). Sources of self-efficacy: Four professional development formats and their relationship to self-efficacy and implementation of a new teaching strategy. The Elementary School Journal, 110(2), 228–245. Tschannen-Moran, M., Woolfolk Hoy, A., & Hoy, W. K. (1998). Teacher efficacy: Its meaning and measure. Review of Educational Research, 68(2), 202–248. Wang, L., Ertmer, P. A., & Newby, T. J. (2004). Increasing preservice teachers’ self-efficacy beliefs for technology integration. Journal of Research on Technology in Education, 36(3), 231–250. Winefield, A. H., & Jarrett, R. (2001). Occupational stress in university staff. International Journal of Stress Management, 8(4), 285–298.

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