Structual Equation Modeling and Confirmatory Factor Analysis of Pre-service Teachers' Digital Literacy: An Empirical Study Conducted in Mainland China

• In Event: Highlighted Session: Digital Frontiers in Teacher Education

Proposal

Introduction and Rationale

The rapid development of Industry 4.0 and the COVID-19 pandemic have accelerated the digital transformation in the education field, which requires future teachers to possess stronger digital literacy to face the challenges of this digital society. The digital literacy required of pre-service teachers not only refers to digital skills and cognitive abilities but also involves specific knowledge, positive motivations, and appropriate attitudes (Roll & Ifenthaler., 2021).

More importantly, pre-service teachers, who embrace a dual role and mission, are a valuable sample for studying digital literacy among university students. On the one hand, they are university students likely to exhibit the same problems in developing digital literacy as other university student groups (such as uneven digital skills and limited independent learning), as revealed by previous research (Eshet, 2004). Indeed, in Mainland China, the development of pre-service teachers' literacy has also been criticized to be inadequate (Yang et al., 2022). On the other hand, they are prospective teachers tasked with disseminating digital literacy to future students (List et al., 2020). Consequently, their digital literacy is related to the future development and implementation of digitization of education.

Despite its importance, exploring the influential factors in advancing pre-service teacher digital literacy remains an underexplored area, and no model currently exists that explicates the relationships between these potential influential factors. Identifying these key factors, including societal, university and student perspectives, is essential for improving the cultivation of pre-service teacher digital literacy. Therefore, this study aims to identify the influential factors to address the research questions: What factors influence the development of pre-service teachers' digital literacy?
 
Model and Hypothesis Development

Concerning the planned behavior theory and previous research in pre-service teacher digital literacy, five key potential, influential factors were identified for this study, i.e. Technology Use in Class, Behavioral Intention to Use, Technology Operation, and Personal Innovativeness in ICT, Perceived Ease of Use. According to the literature review, this study designed an influential factors model to examine their relationship. Survey data collected from students in initial teacher education programmes at three universities in China will be employed to test this model using a Structural Equation Modeling (SEM) method. The eleven hypotheses proposed in this study are as follows:

H1: Technology Use in Class positively affects Pre-service Teacher Digital Literacy.
H2: Behavioral Intention to Use positively affects Pre-service Teacher Digital Literacy.
H3: Technology Operation has a positive effect on Pre-service Teacher Digital Literacy.
H4: Personal Innovativeness in ICT positively affects Pre-service Teacher Digital Literacy.
H5: Technology Use in Class positively affects Behavioral Intention to Use.
H6: Personal Innovativeness in ICT positively affects Behavioral Intention to Use.
H7: Perceived Ease of Use positively affects Behavioral Intention to Use.
H8: Perceived Ease of Use positively affects Technology Operation.
H9: Behavioral Intention to use acts as a mediator between Technology Use in Class and Pre-service Teacher Digital Literacy.
H10: Behavioral Intention to use acts as a mediator between Personal Innovativeness in ICT and Pre-service Teacher Digital Literacy.
H11: Technology Operation acts as a mediator between Perceived Ease of Use and Pre-service Teacher Digital Literacy.

Research Method

Participants

Non-probability convenience sampling will be employed in this study without a formal sampling frame due to an unknown sampling size before data collection (Teddlie & Yu, 2007). This study plans to sample in three Normal universities located in different regions in China (East, North and Central China).

To ensure that all participants had been involved in at least one year of study on campus, the first-year students who enrolled for less than one year were excluded from this study. Thus, the targeted participants in the data collection will focus on sophomore, junior, senior and postgraduate-level students in initial teacher education programmes at these three universities. The estimated sample size is more than 300 pre-service teachers.

 
Data collection

The data will be collected via an online questionnaire from early September 2024. The questionnaire consists of two sections: demographic questions (5 items) and main scales of influential factors (6 scales with 25 items). All the students will participate voluntarily and be informed of the critical information and data processing of this study at a preliminary stage. All the questionnaire responses will be held confidentially and reported anonymously.

Data analysis

The data analysis will involve a two-step procedure, Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM), which were recommended by Hair et al. (2010). CFA will first be conducted on the raw data using IBM SPSS AMOS version 29.0 to examine the construct validity of the measurement instrument. Following that, an SEM using IBM SPSS Statistics version 29.0 will be employed to discover the relationship among the constructs.

Contributions

First, this study supports that pre-service and in-service teachers’ digital literacy has different focuses and practical situations. Therefore, this study adopted an adapted conceptual framework to assess the digital literacy level of pre-service teachers rather than using a framework for in-service teachers, as some previous research has done. This can provide a reference for future research in initial teacher education.

A majority of previous research focuses on developing students’ digital literacy at a micro level, such as individual influential factors (Spante et al., 2018). This study's model also encompasses university and societal perspectives, such as policies and technology support from the university. This facilitates illuminating how digital policies and infrastructure support shaped the development of university students' digital literacy, especially in China's context with a highly centralized system, which tends to be disregarded in previous research (Yang et al., 2007).

Finally, this study will envision how to incorporate sufficient and effective digital literacy training into initial teacher education programmes and how pre-service teachers' digital literacy can be improved on campus to help them better embrace this digital society. This may provide implications and directions for future research in China and internationally.

Authors

• YIYUN ZHANG, Univeristy of Brisol

• Jingyi Ma, University of Bristol, UK