Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6, 8554-8567 2024 Publisher: Learning Gate DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate © 2024 by the authors; licensee Learning Gate * Correspondence: Mulyoto_9911922016@mhs.unj.ac.id Innovative educators in the digital age: Analyzing the impact of school support, self-efficacy, and technology anxiety on teaching creativity Mulyoto1*, Rugaiyah2, Teguh Trianung Djoko Susanto3 1,2,3Doctoral program in educational management, Universitas Negeri Jakarta, Jakarta, Indonesia; Mulyoto_9911922016@mhs.unj.ac.id (M.) Rugaiyah@unj.ac.id (R.) Teguhtrianungdjokos@unj.ac.id (T.T.D.S.). Abstract: Rapid technological advancements require educators to integrate technology into the learning process, but obstacles such as anxiety about technology often hinder their creativity. This study aims to examine the influence of school innovation climate, technology self-efficacy (TSE), and technology anxiety (TAS) on the creativity of educators in Indonesia, as well as the mediating role of TAS in this relationship. The research method used is a quantitative approach with a cross-sectional survey design involving 248 educator respondents from nine National Police education centers. Data were collected through questionnaires and analyzed by structural equation modeling (SEM). The findings show that the school innovation climate has a positive effect on educators' creativity, which TSE mediates. In contrast, technology anxiety (TAS) acts as an inhibitor of creativity, with a negative influence on the use of technology in learning. Organizational incentives also have a positive effect on TSE but increase TAS, which ultimately reduces educator creativity. The study recommends giving educators greater work autonomy as well as ongoing technology training to improve TSE and reduce anxiety about technology. The implication of this study is the importance of creating a school environment that supports innovation, as well as designing incentive policies that do not burden educators psychologically. The weakness of this study is the limitation of the convenience sample selection, which affects the generalization of the findings. Future research is suggested to expand the sample with more representative sampling methods and deepen the study of other psychological factors that affect the use of technology in education. Keywords: Creative learning, School innovation, Teachers’ creativity, Technology anxiety, Technology self-efficacy. 1. Introduction Rapid technological advances have brought significant changes in the world of education. Schools are required to create an innovation climate that can encourage educators to adopt and integrate technology into the learning process [1], [2]. A supportive climate of school innovation not only allows educators to experiment with new teaching methods [3], [4], but also provides space to develop creativity [5], [6] in presenting a more dynamic and relevant learning experience for students [7]. In addition to the climate of innovation, technology self-efficacy (TSE) and technology anxiety self-efficacy (TAS) are important factors that influence educators' use of technology in their teaching [8], [9]. Technology self-efficacy (TSE) is educators' confidence in their ability to use technology in teaching effectively [10]. in contrast, technology anxiety reflects the worry or discomfort experienced by educators when faced with new technology [11], [12]. These two factors are interrelated and can affect the creativity of educators in designing innovative learning processes. Teacher's creativity (TC) is a key element in determining the quality of teaching. Creative educators are able to utilize technology [13] And create an engaging and interactive learning experience for students [14]. Teachers can design learning methods that are more relevant to the challenges of the modern world by combining technology and creativity [15]. 8555 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate The climate of innovation in the school environment has a significant influence on educators' ability to innovate in teaching. According to to Pietsch, Schools that support innovation create an environment conducive for educators to develop creative ideas [16]. In addition, technological self-efficacy also greatly affects educators' confidence in using technology [10]. The higher the self-efficacy of the educator, the more likely it is that the technology will be used innovatively [17]. Conversely, technology anxiety can be a barrier for educators in adopting technology [18], which ultimately reduces the creativity of educators in designing technology-based learning methods [19]. Although previous research has highlighted the importance of the innovation climate and technology-related factors [20]–[23], There are still some aspects that have not been fully understood. Research on the influence of technological self-efficacy and technological anxiety on educators' creativity, especially in the context of innovation in schools, is still rare. Studies that combine these two factors with the innovation climate to look at the impact on educators' creativity holistically are still limited. In addition, the mediating role of technological self-efficacy and technological anxiety in the relationship between innovation and creativity climate has not been widely explored. Further studies are needed to understand how technology and school innovation factors together affect educators' creativity, especially in developing countries such as Indonesia, where the impact of technology anxiety on creativity is still poorly studied. This study analyzes the influence of the school innovation climate on educators' creativity by exploring the mediating role of technology self-efficacy and technology anxiety. This study also assesses the direct impact of these two technological factors on educators' creativity in using technology as an innovative learning tool. The results are expected to provide important insights for schools in designing programs that encourage creativity and innovation among educators through the use of technology. 2. Literature Review 2.1. The Climate of School Innovation and Teachers' Creativity The school innovation climate is an important factor that affects the creativity of educators, especially in the context of dynamic and ever-evolving education. Previous studies have shown that a climate that supports innovation encourages individuals to actively participate in the process of change [24], [25], Experiment with new teaching methods [26], and finding creative solutions to learning challenges [27]. In addition, the climate of innovation can strengthen the self-efficacy of educators [28] and increase their confidence in using creative learning approaches and new technologies [29]. Thus, a climate that supports innovation acts as a catalyst in the process of increasing the creativity of educators, which has a positive impact on the effectiveness of teaching and the quality of learning in schools. Hypothesis1: The school innovation climate has a positive and significant effect on teachers' creativity. 2.2. School Innovation Climate and the Psychological Impact of Technology A school climate that supports innovation has an important role in improving teachers' ability to use technology and reducing teachers' anxiety about technology. A study that analyzed the influence of the innovation climate on teachers' technology competency found that the support schools provide, such as ongoing technology training and flexible innovation policies, can directly improve teachers' self-efficacy in using technology [30]. When teachers feel that the school supports the use of technology, teachers are more confident and motivated to apply technology in teaching [29], which in turn lowers teachers' anxiety levels about the use of technology [31]. A study mentions that high-tech anxiety can lead to emotional exhaustion and burnout [32], Especially when teachers do not feel competent to use the available technological tools [33]. Therefore, building a strong climate of innovation in schools is key to improving teachers' psychological well-being and the effectiveness of the use of technology in learning Hypothesis2: School Innovation Climate Has a Positive and Significant Effect on the Psychological Impact of Technology. 8556 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate 2.3. The Psychological Impact of Technology and Teachers' Creativity Empirical research on the psychological impact of teachers on technology, measured through technology self-efficacy and technology anxiety, shows a significant correlation with the level of teachers' creativity. Teachers who have high technology self-efficacy tend to be more open to the use of new technology [10], explore a range of innovative teaching methods [34] and create more creative learning strategies [35]. Research by Brailovskaia shows that when teachers feel anxious or unconfident about using technology, they tend to continue to use safer conventional teaching methods [36]. These educators avoid using digital tools that can increase creativity and learning effectiveness. Hypothesis3: The psychological impact of technology has a positive and significant effect on teachers' creativity. 2.4. Mediation of the Psychological Impact of Technology Empirical research shows that teachers' psychological impacts on technology, such as technology self-efficacy and technology anxiety, play a significant role as a mediator in the relationship between the school innovation climate and educator creativity. A conducive school innovation climate characterized by support for flexibility in the use of technology can increase teachers' self-efficacy in technology [37]. As the self-efficacy of technology increases, teachers become more confident in exploring new technologies [38], which ultimately increases creativity in learning [39]. Conversely, high-tech anxiety tends to weaken the positive influence of the innovation climate on creativity [40], Because teachers with high anxiety are more likely to avoid using technology. Thus, technology self-efficacy and technology anxiety are mediating variables that bridge the influence of the school innovation climate on educators' creativity. Hypothesis4: The psychological impact of technology mediates the influence of the school innovation climate on teachers' creativity. Figure 1. Conceptual model. 3. Method Based on the background of the problem and the objectives of the research, and after confirming the topic of the climate relationship of school innovation, the literature explores the psychological impact of teachers in the application of educational technology and teacher creativity, and a hypothesis model is constructed with the perspective of social cognition theory. 8557 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate This study uses a quantitative approach with a cross-sectional survey design. According to Creswell, cross-sectional surveys are a method used to examine the relationship between variables in a population at a certain time [41]. Data is collected from participants at a predetermined time. This study targets the population of educators from nine educational centres in the "Lemdiklat Polri," with a total of 722 certified educators. To determine an adequate sample size, researchers used the Krejcie & Morgan, which recommended a sample size of 248 respondents for a population of about 700 people [42]. Respondents were selected using convenience sampling techniques. Data collection was carried out through a questionnaire distributed using the Google Form. Table 1. Sample characteristics (n = 248). Variables Participants Schools Diklat Reserse 7.25% Pusdik Binmas 9.68% Pusdik Sabhara 15.32% Pusdik Intelkam 10.48% Pusdik Lantas 4.03% Pusdik Polair 8.06% Pusdik Brimob 31.05% Pusdik Administrasi 6.45% Sebasa 7.66% Gender Male 89.11% Female 10.89% Age <29 20.97% 30-39 15.32% 40-49 43.15% 50-58 20.56% Experience <5 years 22.58% 5-10 years 41.53% 11-20 years 18.95% >20 years 16.94% Education level High school 21.77% Bachelor 49.19% Master 27.42% Doctoral 2.42% Based on Table 1, the characteristics of the sample, when viewed from the age of the respondents who are 40-49 years old, are dominated by 43.15%; when viewed in terms of experience or the length of time being an educator, the highest is respondents who have 5-10 years of experience, namely 41.53% of the respondents. In contrast, when viewed from the level of education, the bachelor's degree is strata-1 by 49.19%. The data from the questionnaire results were analyzed using the PLS-SEM method using SmartPLS 4, which has been used in many fields[43]. PLS-SEM (Partial Least Squares Structural Equation Modeling) is a very suitable method for this study because of its excellence in handling complex models with many latent variables as well as relationships between variables that are not directly observed [44]. This method is also capable of handling data with smaller sample sizes, which is often a constraint in educational research. In addition, PLS-SEM can be used to test moderation and mediation variables, which is crucial in understanding the complex mechanisms that affect a variable. Another advantage is its ability to overcome multicollinearity problems and produce stable estimates even though the data is not normally distributed. 8558 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate All variables were measured using scales adapted based on previous research. Each measurement item has been translated into Indonesian. All items are presented on a five-point scale, ranging from 1 = Strongly disagree to 5 = Strongly agree. To measure the relationship between the school innovation climate and educators' creativity through the psychological impact of technology, the exogenous variables of the school innovation climate were measured by 3 dimensions adapted fromDu & Chang[20] [20], namely work autonomy (AW) consisting of 3 items, teamwork (T) with 3 items and organizational incentives (OI) consisting of 4 items. The exogenous variables Technology Self-efficacy (TSE) and Technology Anxiety Self-efficacy (TAS) were adapted fromdarwis et al [9], each consisting of 4 items. Meanwhile, the endogenous variable of educator creativity (TC) is adapted fromDogbe et al [45], which consists of 5 items; the complete measurement items are presented in Table 2. Table 2. Measurement items. Variabel Code Item Loadings Autonomous working (AW) AW1 I can freely arrange the order of my subject matter 0.839 AW2 I can decide how to carry out learning in the classroom 0.907 AW3 I have room to work independently in my work 0.901 Organization incentive (OI) OI1 Schools will reward teachers who have innovative ideas 0.849 OI2 The school incentive system makes teachers innovative and enthusiastic 0.833 OI3 Schools encourage teachers to develop creative ideas 0.783 OI4 School incentive system effectively boosts work innovation 0.803 Teamwork (T) T1 Colleagues often communicate and discuss problems at work 0.837 T2 My peers will actively help me complete my assignments 0.915 T3 I feel the support and attention of my colleagues 0.925 Technology anxiety Self- efficacy (TAS) TAS1 I was worried that with technology, my thinking skills would be weak 0.784 TAS2 I think that technology can change a person's behaviour to be negative 0.812 TAS3 I was hesitant to use technology for fear of making mistakes that I could not fix 0.524 TAS4 Using technology while teaching makes me feel uncomfortable 0.814 Technology self-efficacy (TSE) TSE1 I can effectively use technology as an instructional tool 0.459 TSE2 I can expand my instructional options by using a computer 0.864 TSE3 I can expand my instructional options by using the internet 0.876 TSE4 I can use technology if someone can show me how to do it 0.827 Teacher creativity (TC) TC1 I was able to complete the task with minimal supervision 0.855 TC2 I thought deeply before I worked 0.866 TC3 I was able to complete the task without following 0.833 8559 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate the normal procedure TC4 I have innovative ideas 0.796 TC5 I have problem-solving abilities 0.789 4. Results and Discussion 4.1. Measurement Model The modeling analysis of structural equations is carried out in two stages. The first stage focuses on validating the measurement model aimed at ensuring that measurements of latent constructs are adequate and reliable before proceeding to the second stage, which is structural modeling [46]. Based on Table 3, in this study there are six latent variables; Autonomous working (AW) with three questions from AW1 to AW3 with an average of 4.58 to 4.62 and a standard deviation between 0.56 to 0.64; organization Incentive (OI) with four OI1-OI4 question items, with an average of 4.33-4.61 and a standard deviation between 0.56 to 0.79; Teamwork (T) consists of three questions with an average of 4.52-4.59 and a standard deviation of 0.59-0.62. Technology Anxiety Self-efficacy (TAS) consists of 4 questions, but only 3 questions are eligible, namely TAS1, TAS2 and TAS4 with an average of 4.43-4.53 and a standard deviation between 0.63-0.71; Teacher creativity (TC) with five questions with an average of 4.32-4.65 and a standard deviation between 0.51-0.78; and Technology Self-efficacy (TSE) with four questions but only three questions are qualified, namely TSE2, TSE3 and TSE4 with an average of 4.54-4.59 and a standard deviation between 0.58-0.64. Based on Table 3, the kurtosis value of each question item of all constructs is between -4.67 and 1.136; skewness is between -1.214 and 1.021. This result corresponds to an absolute value of kurtosis of less than 7 and an absolute value of skewness of less than 2 [47]. In addition, the results also meet the statistical normative assessment criteria for one variable. Further, the highest loading value of each question corresponds to its potential configuration; according to the recommendations of experts, the highest loading value of each question should appear in the expected configuration [48]. Table 3. Analysis item. Item Mean (SD) Kurtosis Skewness Cross loading AW IO T TAS TC TSE 1. AW = Autonomous working AW1 4,61 (0,64) 0.638 0..325 0.839 -0.090 -0.064 0.048 0.331 0.124 AW2 4,62 (0,56) 0.351 0.153 0.907 -0.053 -0.035 -0.001 0.290 0.097 AW3 4,58 (0,59) 0.142 -1.068 0.901 -0.003 0.022 0.086 0.328 0.092 2. OI = Organization insentive OI1 4,50 (0,65) -0.217 -0.941 -0.043 0.849 0.756 0.626 - 0.021 0.602 OI2 4,33 (0,79) -0.001 0.910 -0.084 0.833 0.528 0.581 - 0.071 0.507 OI3 4,42 (0,69) -0.170 -0.842 -0.147 0.783 0.478 0.491 - 0.123 0.493 OI4 4,61 (0,56) 0.201 -1.091 0.059 0.803 0.575 0.678 0.067 0.655 3. T = Teamwork T1 4,52 (0,62) -0.154 -0.937 0.038 0.589 0.837 0.496 - 0.008 0.501 T2 4,59 (0,59) 0.045 -1.017 -0.079 0.664 0.915 0.484 0.032 0.520 T3 4,53 (0,62) -0.100 0.969 -0.035 0.680 0.925 0.554 0.020 0.513 4. TAS = Technology anxiety self-efficacy TAS1 4,53 (0,63) -0.059 -1.012 0.048 0.595 0.443 0.784 - 0.034 0.606 TAS2 4,46 (0,71) -0.437 -0.951 0.020 0.617 0.472 0.812 - 0.526 8560 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate Item Mean (SD) Kurtosis Skewness Cross loading AW IO T TAS TC TSE 0.026 TAS4 4,43 (0,71) -0.591 -0.834 0.061 0.560 0.468 0.814 0.017 0.537 5. TC = Teacher creativity TC1 4,65 (0,51) -0.229 -0.992 0.317 -0.066 -0.046 -0.061 0.855 0.060 TC2 4,61 (0,53) -0.467 -0.840 0.363 0.014 0.030 0.046 0.866 0.144 TC3 4,39 (0,73) 0.520 1.021 0.291 0.004 0.065 0.003 0.833 0.076 TC4 4,32 (0,78) 0.201 -0.942 0.241 -0.044 0.045 -0.053 0.796 0.068 TC5 4,60 (0,55) 0.038 -1.025 0.261 -0.068 -0.023 -0.030 0.789 0.059 6. Technology self-efficacy TSE2 4,54 (0,61) -0.009 -1.011 0.114 0.601 0.475 0.596 0.102 0.864 TSE3 4,59 (0,58) 1.136 -1.214 0.109 0.618 0.570 0.573 0.154 0.876 TSE4 4,54 (0,64) 0.659 -1.173 0.081 0.574 0.415 0.614 - 0.008 0.827 Note: AW= Autonomous working, TC= Teacher creativity, T=Teamwork, OI=Organizational incentive, TSE= Technology self- efficacy, TAS= Technology anxiety self-efficacy. Based on Table 4, in order to meet the criteria of the measurement model according to [44], [49], the loading factor >0.7, Composite Reliability >0.7 and Average Variance Extractions (AVE) >0.5. When checking the loading factor value on each construct, two items, namely TAS3 and TSE1, do not meet the requirements. After the ineligible items are removed from the construction, the loading factor value is in the range of 0.783 to 0.925, the composite reliability value is in the range of 0.726 to 0.897, and the average AVE is between 0.646 and 0.798. Moreover, to test whether there is multicollinearity, the Inflation Factor Variant (VIF) test is carried out, where the VIF value should not be more than 3.3 [50] and based on the results of the VIF test no one exceeds 3.3. Table 4. Measurement model. Item Loadings T value P-value Cronbach's alpha CR AVE VIF 1. AW = Autonomous working 0.858 0.861 0.780 1,67-3,22 AW1 0.839 8.035 0.000 AW2 0.907 10.395 0.000 AW3 0.901 10.567 0.000 2. OI = Organization insentive 0.835 0.843 0.668 1,71-2,20 OI1 0.849 19.673 0.000 OI2 0.833 19.923 0.000 OI3 0.783 15.852 0.000 OI4 0.803 18.667 0.000 3. T = Teamwork 0.872 0.874 0.798 1,75-3,23 T1 0.837 14.775 0.000 T2 0.915 19.689 0.000 T3 0.925 21.734 0.000 4. TAS = Technology anxiety self-efficacy 0.726 0.726 0.646 1,36-1,52 TAS1 0.784 14.321 0.000 TAS2 0.812 15.635 0.000 TAS4 0.814 15.851 0.000 5. TC = Teacher creativity 0.886 0.897 0.686 1,90-3,11 TC1 0.855 9.291 0.000 TC2 0.866 9.452 0.000 8561 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate Item Loadings T value P-value Cronbach's alpha CR AVE VIF TC3 0.833 7.937 0.000 TC4 0.796 6.533 0.000 TC5 0.789 7.353 0.000 6. Technology self-efficacy 0.818 0.823 0.733 1,70-1,92 TSE2 0.864 16.418 0.000 TSE3 0.876 17.171 0.000 TSE4 0.827 14.708 0.000 Note: AW= Autonomous working, TC= Teacher creativity, T=Teamwork, OI=Organizational incentive, TSE= Technology self-efficacy, TAS= Technology anxiety self-efficacy. Based on Table 5, the construct has met the criteria for discriminant validity. According to Henseler that, a construct has discriminatory validity if the HTMT coefficient is <0.85 [51]. As shown in Table 5, no HTMT coefficient value exceeds 0.85, so it can be concluded that the construct has sufficient discriminatory validity. Table 5. Discriminant validity. AW OI T TAS TC TSE AW OI 0.124 T 0.074 0.836 TAS 0.072 0.827 0.720 TC 0.405 0.106 0.058 0.074 TSE 0.140 0.834 0.674 0.801 0.124 4.2. Structural model After the convergent validity and discrimination of each construct are met, then an analysis of the structural model is carried out. The SRMR value on this model is 0.068, less than 0.08. According to Hu & Bentler, a model is said to have a good model fit if the SRMR value is less than 0.08[52]. In addition, the goodness of the structural equation model can also be seen from the NFI; the model is said to meet the standard if the NFI value is at least 0.8 [53]. In this model research, the NFI value is 0.82, so it can be concluded that the model meets the standard. 4.3. Hypothesis Testing 4.3.1. Direct Effect In Table 6, the results of hypothesis testing can be seen. The results showed that autonomous work had a positive and significant influence on educators' creativity (H1a: ꞵ=0.352, p<0.05), educators' self- confidence in using technology (H2a1: ꞵ=0.156, p<0.05), educators' self-anxiety in using technology (H2b1: ꞵ=0.093, p<0.05). Teamwork did not have a significant effect on educators' creativity (H1b: ꞵ=0.032, p=0.669>0.05), educators' confidence in using technology (H2a2: ꞵ=0.137, p=0.104>0.05), Educators' anxiety in using technology (H2b2: ꞵ=0.086, p=0.278>0.05). The results of the data analysis also showed that organizational incentives did not have a significant effect on educators' creativity (H1c: ꞵ=-0.096, p=0.334>0.05), but organizational incentives affected educators' self-confidence in using technology (H2a3: ꞵ=0.608, p<0.05), educators' anxiety in using technology (H2b3: ꞵ=0.679, p=0.000<0.05). The results of the analysis also showed that educators' confidence in using technology had a positive and significant effect on educators' creativity (H3a: ꞵ=0.154, p=0.049<0.05). However, it turned out that anxiety about using technology had a negative and significant effect on educators' creativity (H3b: ꞵ=-0.163, p=0.035<0.05). The value of f2 indicates the value of the relationship between factors. According to Cohen, if f2 ≤0.02= small effect, f2>0.15 = medium, f2>0.35=big effect [54]. In Table 5, the value of f2 is also presented, which is between 0.013 and 0.492; there are two pathways that 8562 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate have a large effect, namely the H2a3 and H2b3 hypotheses; the other pathway has a small influence effect. 4.3.2. Indirect Effect In this study, data analysis uses a bootstrapping approach [55], bootstrapping 5000 times to verify the mediating effect of the psychological impact of technology use. Based on the analysis of the research results presented in Table 5, the self-efficacy of educators does not mediate the influence of the school innovation climate (Autonomous Working, Teamwork and Organizational Incentive) on the creativity of educators. Likewise, the anxiety of educators in using technology did not mediate the influence of autonomous work (H4d: ꞵ=-0.015, p=0.099>0.05), teamwork (H4de ꞵ=-0.014, p=0.374>0.05) on the creativity of educators, but mediated organizational incentives (H4f ꞵ=-0.110, p=0.038<0.05) on the creativity of educators, but the mediation effect was negative. Table 6. Hypothesis testing. Hypothesis Estimate Sample mean (M) Bias corrected 95% Support t-value p-value 2.5% 97.5% f2 Direct effect H1a: AW -> TC 0.352 0.359 5.892 0.000 0.240 0.474 0.141 Yes H1b: T -> TC 0.032 0.033 0.427 0.669 - 0.113 0.184 0.001 No H1c: OI->TC -0.096 -0.099 0.966 0.334 - 0.292 0.093 0.003 No H2a1:AW -> TSE 0.156 0.157 3.885 0.000 0.078 0.237 0.051 Yes H2a2: T -> TSE 0.137 0.140 1.624 0.104 - 0.022 0.311 0.019 No H2a3: OI -> TSE 0.608 0.610 8.853 0.000 0.472 0.741 0.369 Yes H2b1: AW -> TAS 0.093 0.090 2.455 0.014 0.015 0.165 0.019 Yes H2b2: T -> TAS 0.086 0.088 1.084 0.278 - 0.061 0.246 0.008 No H2b3: OI -> TAS 0.679 0.680 9.944 0.000 0.538 0.807 0.492 Yes H3a: TSE -> TC 0.154 0.155 1.973 0.049 - 0.005 0.302 0.013 Yes H3b: TAS -> TC -0.163 -0.163 2.114 0.035 - 0.307 -0.010 0.015 Yes Mediation H4a: AW -> TSE - > TC 0.024 0.025 1.619 0.105 - 0.001 0.057 No H4b: T -> TSE -> TC 0.021 0.021 1.201 0.230 - 0.006 0.061 No H4c: OI -> TSE -> TC 0.094 0.095 1.875 0.061 - 0.003 0.194 No H4d: AW -> TAS - > TC -0.015 -0.014 1.648 0.099 - 0.035 0.000 No H4e: T -> TAS -> TC -0.014 -0.014 0.889 0.374 - 0.052 0.011 No H4f: OI -> TAS -> TC -0.110 -0.111 2.071 0.038 - 0.215 -0.007 Yes Note: AW= Autonomous working, TC= Teacher creativity, T=Teamwork, OI=Organizational incentive, TSE= Technology self-efficacy, TAS= Technology anxiety self-efficacy. 8563 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate In Table 7 and Figure 2, the R2 value is presented, which explains that educators' anxiety about the use of technology is positively influenced by autonomous work (H2b1) and organizational incentives (H2b3) with an R2 value = 0.554, which is believed to be moderate explanatory, because according to Chin, the R2 value between 0.33 to 0.67 is classified as moderate explanatory [48]. In addition, educators' self-confidence in using technology is also influenced by autonomous work (H2a1) and organizational incentives (H2a3), which are classified as moderately explanatory because the R2 value = 0.522 (between 0.33-0.67). In addition, educators' creativity is also influenced by autonomous work (H1a), technological confidence (H3a) and technology anxiety (H3b) with a weak criterion of R2<0.33. Table 7. Coefficient of determinant. Variable R-square R-square adjusted TAS 0.554 0.548 TC 0.146 0.132 TSE 0.522 0.517 Figure 2. Structural model assessment. The results of the study show that autonomous work has a positive and significant influence on the creativity of educators. These findings are consistent with previous research that states that autonomy in work increases individual creativity [56]. Autonomous work provides many advantages for educators, especially in terms of freedom and flexibility in designing teaching [57]. Empirical findings from various studies show that when educators are given the freedom to choose teaching methods and approaches, they will be more innovative and create more engaging and effective learning strategies [58]. According to Ahakwa, teachers' work autonomy also increases a sense of responsibility and involvement in their work, which contributes to increased creativity in the teaching environment [59]. In the context of education in Indonesia, granting greater autonomy to teachers can be an important strategy to promote innovation in schools and improve the overall quality of teaching. On the other hand, teamwork did not show a significant influence on educators' creativity. This is due to the existence of team dynamics that are less supportive or interpersonal conflicts that hinder creativity [60]; teams that are not harmonious tend to suppress innovative ideas [61]. Meanwhile, the research of Owolabi et al found that conflicts within teams often undermine collaborative processes, reducing the open communication necessary for creative ideas to flourish [62]. In addition, Farid revealed that a lack of trust among team members can decrease motivation to share new ideas [63]. Educators who work in a less supportive team environment feel less free to express their creative views. 8564 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 8554-8567, 2024 DOI: 10.55214/25768484.v8i6.3845 © 2024 by the authors; licensee Learning Gate In the context of education, this can happen if educators are not empowered or if rigid hierarchies curb the contribution of ideas [64]. Collaboration that is forced without trust and support actually hinders innovation [65]. This is relevant in the context of education in Indonesia, where hierarchical structures and less flexible work cultures are barriers to effective creative collaboration among educators. Thus, although teamwork can encourage creativity, it must be done in a supportive manner. If in a less-than- ideal situation, it is the opposite; ineffective collaboration can hinder creativity. Organizational incentives also do not have a significant effect on educators' creativity. This happens because the incentives provided are not in accordance with the needs or expectations of educators, so they do not motivate educators to innovate [66]. However, organizational incentives have a positive effect on technological self-efficacy and technological anxiety. Incentives can increase educators' confidence in using technology [67]. However, incentives can also increase educators' anxiety regarding the application of technology in learning [68]. This happens because there is pressure on educators to adapt to new technology. The self-efficacy of technology has a positive and significant effect on the creativity of educators, which is in line with the social cognitive theory, which states that an individual's belief in his or her ability affects creative behavior [69]. On the other hand, technology anxiety has a negative effect on creativity, suggesting that feelings of anxiety or fear of technology can hinder educators from innovating [70]. Mediation analysis shows that technological self-efficacy does not mediate the relationship between the innovation climate and the creativity of educators. However, technology anxiety mediates the influence of organizational incentives on educator creativity negatively. This suggests that despite incentives provided if educators feel anxious about technology, their creativity remains stimulated. 5. Conclusion This study shows that the school innovation climate significantly affects teachers' creativity, especially by increasing self-efficacy and reducing technology anxiety. Work autonomy has been shown to positively influence teachers' creativity, while collaboration in teams and organizational incentives have not had a significant impact. Organizational incentives can increase anxiety about technology, which negatively impacts creativity. Self-confidence in using technology increases teachers' creativity, while anxiety about technology inhibits it. Mediation analysis shows that anxiety about technology mediates the influence of organizational incentives on teachers' creativity negatively. These findings underscore the importance of creating a supportive innovation climate, giving teachers greater autonomy, and reducing anxiety about technology to encourage creativity in learning. Theoretically, this study enriches the literature on the role of the innovation climate and the psychological factors of technology in influencing the creativity of educators. These findings support social cognitive theory and highlight the complexity of the relationship between these variables in the context of education in developing countries. Practically, schools and educational institutions need to give more autonomy to educators in the teaching process. A comprehensive technology training program is also needed to improve self-efficacy and reduce technology anxiety. Organizational incentives should be designed in such a way that they are effective in driving innovation without increasing stress or anxiety. Copyright: © 2024 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). References [1] I. 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