ETR&D

Generative Artificial Intelligence (GAI) has received widespread attention recently, influencing teacher education in various ways. However, there is little discussion on pre-service teachers’ behavioral intention towards GAI. Therefore, this study employs subjective norm, AI self-efficacy, facilitating conditions, and trust to expand the Technology Acceptance Model, understanding pre-service teachers’ adoption of GAI. The study involves 486 undergraduates from a university in Jiangsu Province, China. The Partial Least Squares Structural Equation Model is used to test the research model. Research model proved to be both reliable and valid, confirming nine out of ten hypotheses. The findings indicate that: (1) AI self-efficacy strongly predicts perceived ease of use; (2) The most direct and strongest impact on perceived usefulness is perceived ease of use, followed by facilitating conditions; (3) Perceived ease of use doesn’t directly affect attitude towards use, but perceived usefulness and trust significantly influence this attitude; (4) Attitude towards use greatly predicts behavioral intention, followed by perceived usefulness and subjective norm. This research helps in advancing policy development in educational institutions and the integration of GAI and teacher education.

Computational thinking (CT) skills have become increasingly important in modern education, as they equip students with critical problem-solving skills applicable across various domains. Given the growing emphasis on digital literacy, it is essential to investigate grade- and gender-level differences in CT skills among students to support targeted interventions and to ensure that all students have equal opportunities to succeed in the digital age. This study examined CT skill development among primary school students, taking both grade- and gender-level disparities into account. Using quantitative data from a diverse sample of 517 primary school students, we conducted a comprehensive analysis of their CT scores. The results revealed no significant gender differences in CT scores among primary school students. However, notable age-related disparities emerged, with CT scores rising as students progressed through higher grades. This finding underscores the importance of considering developmental factors in CT education and highlights the need for age-appropriate CT curricula. By investigating both grade- and gender-level differences, this study aims to support educators and policymakers in developing more inclusive and effective strategies for cultivating CT skills among young learners, thereby preparing them for the challenges of the digital age.

Many universities utilized a reactive, piecemeal approach to adapt and rapidly reopen schools at the onset of the COVID-19 pandemic. Although schools were able to resume classes online relatively quickly, there was limited time to explore best practices for an optimal online learning environment. The pandemic exposed significant issues in the technological infrastructure at universities that impacted revenue, enrollment, and the overall learning environment. The technological infrastructure encompasses online teaching/learning, virtual engagement, and billing practices for distance education. While billing for distance education is not commonly included as a part of a university’s digital framework, we contend that it is a pivotal issue that could impact operational efficiencies. Tuition/fee rates and enrollment numbers for online vs. face-to-face courses in 50 US schools are explored. A review of the literature, anecdotal evidence, paired t-tests, and descriptive statistics reveal similar trends; for most universities, if tuition/fee rates for students that have the same residency status are compared, there are significant differences in the cost for online and face-to-face courses. The impact of these billing disparities, within the context of a university’s digital infrastructure, is also explored. Ultimately, this research paper highlights challenges and strategies to improve faculty preparation, technology, internet access, assessments, exam proctoring/supervision, IT support, learning management systems, and billing in a virtual learning/teaching environment.

The potential of immersive virtual reality (IVR) to deliver engaging occupational safety training has been established by previous research; however, to date, there have not been any pedagogical models to guide its implementation. This study’s objective was to conceptualize a pedagogical model for IVR safety training by combining a multidisciplinary theoretical framework with safety trainers’ contextual and pedagogical expertise. The research questions were (1) what kind of pedagogical practices do trainers apply in safety training, and (2) how do the trainers’ pedagogical practices inform the sociocultural contextualization of the pedagogical model for IVR safety training? Eighteen safety trainers were interviewed across two work organizations. An inductive approach was used in the interview data analysis. Three main categories of pedagogical practices were identified: (1) matching pedagogy to training goals, (2) guiding social interaction in training situations, and (3) utilizing organizational resources for training development. The findings extended our understanding of the sociocultural training context and provided insight into the pedagogical practices used in safety training. Based on the findings, pre- and post-training activities were added to the pedagogical model, and the descriptions of trainers’ actions during the facilitated introduction and debriefing phases were modified to support the training’s relevance to the learners, trainers, and organizations. This study illustrates a pragmatic approach to developing safety training in the context of advanced learning technology in design-based research. The pedagogical model will be applicable by training and education providers in IVR safety training across industries and in practice-based learning.

The measurable effects of music in online learning remains a topic of extensive debate, largely due to inconsistent findings within existing literature. Many of these inconclusive results stem from research methodologies that focus on singular perspectives, often overlooking a balance between cognitive challenges and emotional benefits of background music. Consequently, educators and instructional designers frequently overlook the potential of music to enhance learning experiences and offer new resources to explore emotion regulation. This perspective article offers a comprehensive and balanced examination of leveraging music’s benefits in online education. In this article, we synthesize recent theories across music cognition, educational psychology, instructional technology, empirical studies, and documented applications of music within online instructional contexts. Based on this analysis, we present three evidence-based propositions: (1) a refined theoretical framework elucidating music’s influence on behavior and learning outcomes, (2) four strategies to harness music for enhancing learner motivation, engagement, and comprehension, (3) guidelines and reflections for effectively integrating music into instructional design. The manuscript concludes with suggestions for mobilizing the four propositions and leveraging generative AI to enhance the role of music in learning, and the further steps that researchers and practitioners can take to implement music in online learning.

This case study investigates how a designed learning environment cultivates a “sense of promisingness”—an ability to discern what may work in uncertain conditions, essential for creative expertise. The study focused on 32 in-service teachers enrolled in a Master’s program in Taiwan, who engaged in mutually-supportive development of their thesis proposals over 18 weeks using the Knowledge Forum (KF) online tool. To evaluate the development of a sense of promisingness, we analyzed online discussion content where participants expressed their understanding of “what may work, how, and why” for improving their thesis proposals. We particularly examined three types of discourse moves—sharing-, argument-, and integration-oriented—to identify conditions fostering this ability. Key findings revealed that (1) sharing-oriented discourse was necessary but not sufficient for promoting the sense of promisingness, and (2) increased effort in integration-oriented discourse moves correlated with a higher likelihood of developing this ability. The study demonstrates that the course activity, designed based on knowledge-building principles in KF, serves as an effective instructional intervention for cultivating a sense of promisingness among graduate students. This research addresses a gap in the literature regarding methods to develop such knowledge-creating sense and the role of different discourse moves in sustaining knowledge advancement in online learning environments. The paper concludes with design implications for similar educational contexts.