The integration of technology into teaching is crucial for effective 21st-century education. Pre-service teachers need digital and teaching competence to thrive in a digital society. This study addresses the need to understand factors influencing pre-service teachers' digital teaching competence, particularly given the growing importance of data in education. While pre-service teachers may have favorable impressions of digital competence, they may lack the proficiency to effectively use technology in teaching. Therefore, understanding the factors influencing their digital teaching competence is critical for designing effective teacher training programs. Existing research suggests that external environmental factors (school climate, support, facilitating conditions) and teachers' characteristics (technology attitudes, competencies, data literacy, technology ethics) influence teachers' digital teaching competence. However, research on the influence of data literacy and technology ethics on pre-service teachers' digital teaching competence is limited. Data literacy is increasingly important for teachers to make informed decisions and meet students' needs. It is essential to understand its role in enhancing digital teaching competence. Furthermore, technology ethics are crucial in the responsible use of digital tools in education, and their impact on both data literacy and digital teaching competence needs further exploration. This study aims to address these gaps by investigating the direct and mediating effects of technology attitudes, technology operations, technology ethics, and data literacy on pre-service teachers' digital teaching competence.

The literature review examines existing research on several key constructs: technology attitudes, technology operations, technology ethics, and data literacy. Technology attitudes encompass teachers' overall views on technology use in education, impacting data literacy, technology operations, and technology ethics. Technology operations refer to teachers' proficiency in using ICT hardware and software, and their effect on data literacy and digital teaching competence. Technology ethics involve the ethical guidelines and legal standards for technology use in education, impacting data literacy and digital teaching competence. Data literacy is defined as the ability to understand and apply data to make informed decisions, affecting digital teaching competence. The review highlights the need for empirical evidence on the relationships between these constructs, particularly the mediating role of data literacy and the effect of technology ethics. The research model proposed in the study hypothesizes the relationships between these variables, including the mediating effect of data literacy on the relationships between the other variables and digital teaching competence.

This quantitative study employed a survey design using a questionnaire administered to 244 pre-service teachers at a normal university in Hangzhou, China, between 2021 and 2022. Data was collected through an online platform (Wenjuanxing). The questionnaire comprised demographic information and five dimensions: Technology Attitudes, Technology Operations, Technology Ethics, Data Literacy, and Digital Teaching Competence. Each dimension was measured using a five-point Likert scale. Exploratory factor analysis (EFA) was conducted on data from 130 participants in 2021 to determine the factor structure, followed by confirmatory factor analysis (CFA) on data from 114 participants in 2022 to assess the measurement model's validity and reliability. Structural equation modeling (SEM) using SmartPLS version 3 was employed to test the hypothesized relationships between the variables and assess the mediating effects of data literacy. SPSS version 26 was used for EFA and demographic analysis. The study employed various indicators of validity and reliability, such as KMO, Bartlett's test, AVE, Cronbach's alpha, and composite reliability. Discriminant validity was assessed using the Fornell-Larcker criterion and HTMT. Mediation analysis was performed to examine the mediating effects of data literacy on the relationships between predictor variables and digital teaching competence. The study used Variance Accounted For (VAF) to assess the degree of mediation.

The SEM analysis revealed significant direct effects of technology attitudes, technology ethics, and data literacy on digital teaching competence. Technology attitudes positively influenced data literacy, technology operations, and technology ethics. Technology operations positively impacted data literacy, but unexpectedly, not digital teaching competence. Technology ethics positively affected data literacy and digital teaching competence. Data literacy significantly predicted digital teaching competence. Mediation analysis showed that data literacy fully mediated the relationship between technology operations and digital teaching competence. Data literacy partially mediated the relationships between technology attitudes and digital teaching competence, and between technology ethics and digital teaching competence. Technology ethics acted as a partial mediator between technology attitudes and data literacy and between technology attitudes and digital teaching competence. R-squared values indicated substantial predictive power for digital teaching competence (0.739), moderate predictive power for data literacy (0.556), and weak predictive power for technology ethics and operations. Q-squared values confirmed the predictive relevance of the model. The study supported hypotheses H1, H2, H3, H4, H5, H7, H8, and H9, but not H6. Table 8 summarizes the path coefficients and t-values for each hypothesis. Table 10 details the mediation analysis results, indicating full mediation for technology operations-data literacy-digital teaching competence and partial mediation for other pathways.

The findings confirm the importance of technology attitudes, technology ethics, and data literacy in developing pre-service teachers' digital teaching competence. The unexpected lack of direct influence from technology operations on digital teaching competence highlights the need for teacher training programs to emphasize pedagogical knowledge and skills in addition to technical proficiency. The mediating role of data literacy underscores its significance in translating technology attitudes, operations, and ethics into effective teaching practices. The mediating role of technology ethics emphasizes the importance of including ethical considerations in technology integration in education. The results suggest that teacher training programs should focus on cultivating positive attitudes towards technology, developing strong technology operations skills within a pedagogical framework, fostering ethical use of technology, and enhancing data literacy skills. By addressing these factors, teacher education programs can better prepare pre-service teachers for effective technology integration in their future classrooms.

This study provides valuable insights into the factors influencing pre-service teachers' digital teaching competence and the critical mediating role of data literacy. The findings emphasize the importance of a holistic approach to teacher training that integrates technology attitudes, operations, ethics, and data literacy. Future research could investigate these relationships in different cultural contexts, compare pre-service and in-service teachers, and explore the combined effects of multiple factors using methods such as Qualitative Comparative Analysis. Addressing the limitations of this study, such as the sample's size and composition, is also crucial for future research to strengthen the generalizability of the findings.

The study's limitations include its reliance on a single university sample from China, potentially limiting the generalizability of findings to other contexts. The sample also exhibited a gender imbalance (82% female), potentially influencing the results. The use of a self-report questionnaire might introduce response biases. Future research could employ mixed methods, involving interviews or observations, to triangulate data and enhance the robustness of the findings, and to include broader, more diverse samples.