Needs analysis is a technique in collecting and accessing information relevant to course design. In the needs analysis, the interview is one of the methods and it involves asking in-depth questions using a structured or semi-structured guide to better understand the individual’s points of view. A pilot test for an interview is an important and useful process in conducting qualitative research. Its findings might indicate that some improvements for the major study are needed. This article will explore the advantages of the pilot study, how it was undertaken and the experiences and findings throughout the study. The pilot test was conducted by interviewing two nursing lecturers using Google Meet. This pilot test was conducted with three stages of an interview process such as a pre-interview, peri-interview and post-interview. There were no serious modifications were needed after data analysis of the pilot study was done. It indicates that the research instruments, semi-structured questions can be considered as valid and reliable and can be used for the real study. At the same time, the researcher recognized that the MOOC course and communication at risk module need details explanation because they are new for the participants and to make clear distinction between risk communication and therapeutic communication. This study gives the researchers valuable experiences in applying the three stages of the interview session. The most important, the findings of this study can be applied in the real study

Effectively incorporating technology into teaching and learning can be accomplished through the application of information and communication technology (ICT). Nonetheless, the extent to which ICT is employed in educational environments is heavily impacted by numerous factors. Teachers' ICT integration in China was investigated with the aim of identifying the specific factors that influence it. The research sample consists of 680 educators, and it highlights three primary elements that affect their adoption of ICT: attitudes, self-efficacy, and digital competence. Employing a partial least squares structural equation modeling (PLS-SEM) method, the results indicate that all three elements play a significant role in the effective integration of ICT by educators. The study also indicated the mediating effect of attitudes and digital competence. Furthermore, the research identified no substantial disparities in the factors based on sex or age, except for the correlation between self-efficacy and attitudes. By providing useful insights for the development of successful instructional designs that integrate ICT, this study contributed to the advancement and impact of educational technology.

Technology invention and implementation have resulted in long-term educational progress. This study aimed to identify the innovative strategies in determining the factors influencing in-service teachers’ technology integration in China, focusing on the information and communication technology (ICT) integration. The sample consists of 685 in-service teachers. Four factors are found to influence in-service teachers’ ICT integration: attitudes, self-efficacy, digital competence, and digital tools use. The results of the study utilizing the PLS-SEM approach demonstrated that all four factors have a substantial impact on in-service teachers’ ICT integration and interact with each other. Meanwhile, attitudes, digital competence, and digital tools use have a mediating effect in this research. In addition, the study discussed the effects of gender, age, and teaching experience on influencing factors and ICT integration. This research provided beneficial insights for a successful design of instruction with ICT and contributed to innovative strategies for educational technology.

The integration of Information and Communication Technology (ICT) can significantly improve teaching and learning outcomes, but various factors determine the degree to which ICT is integrated into educational practices. This study used quantitative methodology to examine four key factors that impact in-service teachers’ ICT integration and how they interact with each other. Data was collected through snowball sampling from 685 in-service teachers in Henan Province, China. Using partial least squares structural equation modeling (PLS-SEM), the study analyzed four factors from the Technology Acceptance Model 3 (TAM 3) and the Will-Skill-Tool model (WST model): attitudes (AT), self-efficacy (SE), digital competence (DC), and digital tools utilization (DTU). The findings revealed that all four elements exerted a noteworthy influence on the integration of ICT by in-service instructors. Meanwhile, attitudes, digital competence, and digital tools utilization have a mediating effect in this research. Additionally, the study examined how gender, age, and teaching experience influence these factors and ICT integration. The findings revealed that females exhibit higher levels of positive attitudes and digital competence than males, while teachers aged 31–35 years have stronger digital abilities, digital tool use, and ICT integration compared to younger or older teachers. Furthermore, teachers with less than three years of teaching experience exhibit significantly stronger attitudes, self-efficacy, digital competence, and ICT integration than those with more than ten years of experience. The implication of the study provides valuable insights for designing effective ICT-based instruction and developing teacher education and educational technology programs aimed at promoting ICT integration in the classroom.

This dataset describes two main variables, technological pedagogical and content knowledge (TPACK) and Beliefs on ICT, which may affect pre-service teachers' (PSTs) use of ICT (UICT) during teaching practices. TPACK assumes that PSTs should actively combine some domains of knowledge to design good quality of ICT-integrated courses lessons. Beliefs on ICT in this study consist of a mix of behavioral, normative, and control beliefs on ICT integration in education. In addition, UICT is defined as ICT used by PSTs during teaching practices. Three approaches were applied for the purification of the dataset; development of instruments, survey, and exploratory factor analysis (EFA). The dataset consists of demographic information, TPACK, Beliefs on ICT, and UICT. The dataset is beneficial to teacher educators in designing effective programs that best nurture PSTs' UICT during teaching practices. Researchers sharing similar sample characteristics in developing countries may adapt this dataset for more rigorous statistical analyses.