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Educational podcasts have become an increasingly prevalent media used to disseminate profession‐specific information through easily accessible means. Despite the potential of educational podcasts as convenient and effective medium, there is a dearth of literature dedicated to the topic. Thus, using the Uses and Gratification framework, the psychometric properties of the Educational Podcasts Motivation Scale were examined, as well as the motivational factors that influence intention to listen to educational podcasts and recommend podcasts to others were explored. A sample of individuals in the field of education (n = 606), such as in‐service K‐12 teachers and higher education professors, were recruited for this study. This sample were randomly divided, and an exploratory factor analysis (EFA) was conducted with the first set (n = 312) to identify underlying constructs, and confirmatory factor analysis (CFA) and structural equation modelling (SEM) were employed with the second set (n = 294). The scale demonstrated strong psychometric properties and five distinct motivational factors were identified: Information Gathering, Flexibility in Use, Social Interaction, Entertainment, and Professional Encouragement. Several motivational factors had significant associations with the constructs of "intention" and "word‐of‐mouth". This paper demonstrates both the unique motivational factors related to listening to educational podcasts and the motivational factors that overlap with other forms of media. Further examination of the underlying motivations to listen to educational podcasts is warranted. Practitioner notesWhat is already known about this topic Educational podcasts have become an increasingly prevalent media used to disseminate information to specific professions and fields that provide current practices and research information through easily accessible means.Educational podcasts have been found to be an effective tool to improve self‐efficacy and knowledge around topics with educators and college students, as well as a means to develop communities of practice where educators share knowledge and experiences.Results of studies using the uses and gratifications framework to examine the gratifications for listening to podcasts have found an array of overlapping, and sometimes conflicting, gratifications from the use of podcasts. Those most often identified include entertainment, multitasking and convenience, social interaction, escapism and educational purposes.What this paper adds This paper outlined the development of the Educational Podcasts Motivation Scale and used an exploratory factor analysis, confirmatory factor analysis and structural equation modelling to demonstrate its strong psychometric properties.Five distinct motivational factors for why educators engage with educational podcasts were identified: (a) Information Gathering, (b) Flexibility in Use, (c) Social Interaction, (d) Entertainment and (e) Professional Encouragement.This paper identifies that educators are often most motivated to listen to educational podcasts due to constructs such as social interaction, flexibility in use and information gathering.Implications for practice and/or policy The findings in this paper demonstrate the perceived benefits and uses of educational podcasts as a learning tool, further establishing educational podcasts as a useful tool that should be incorporated into learning environments.The findings in this paper indicate that those embedding educational podcasts within learning activities and professional development should consider how to emphasise the flexibility, social interactions and learning aspects of these tools to promote the attractive features of this tool.Although this study sheds light on the reasons those in the field of education use this medium, additional research is needed to explore how and why these individuals engage with educational podcasts. [ABSTRACT FROM AUTHOR]

Many technology acceptance models used in education were originally designed for general technologies and later adopted by education researchers. This study extends Davis' technology acceptance model to specifically evaluate educational technologies in higher education, focusing on virtual classrooms. Prior research informed the construction of the model, which contains perceived usefulness, perceived ease of use, behavioural intent, access and convenience, system attributes and self‐efficacy. Education‐specific constructs include cognitive engagement, feedback, instructor practice and class interaction and communication. Additionally, a new construct called comfort and well‐being is introduced. A total of 427 valid responses on a 5‐point Likert scale were received from university students. Exploratory factor analysis, confirmatory factor analysis and structural equation modelling were used to analyse the data. The model accounted for 78% of variance of behavioural intent, with comfort and well‐being demonstrating the strongest influence. Cognitive engagement, access and convenience influenced perceived usefulness, and system attributes and self‐efficacy influenced perceived ease of use. Feedback, instructor practice and class interaction and communication were not significant as educational constructs for this cohort. Based on this analysis, a final extended educational technology acceptance model (EETAM) is proposed for further use and testing.Practitioner notesWhat is already known about this topicMost technology acceptance models used in education were made for general technologies, or do not include factors specific to learning and pedagogy.Most students prefer face‐to‐face learning experiences and active class engagement.Qualitative research shows that instructional attributes and student comfort and well‐being are known to be important for students.What this paper addsA novel extended educational technology acceptance model, informed by prior empirical research, is presented.Confirmation of the importance of including student comfort and well‐being in technology acceptance models used in education.The model revealed the heterogeneous nature of the student learning experience.Implications for practice and researchTechnology acceptance models used in educational settings should include factors specific for education and learning, and student comfort and well‐being.We encourage use of the presented model in educational settings to further test the model. [ABSTRACT FROM AUTHOR]

As teachers are purveyors of digital citizenship and their perspectives influence classroom practice, it is important to understand teachers' views on digital citizenship. This study establishes the Teachers' Perceptions of Digital Citizenship Scale (T‐PODS) as a survey instrument for scholars to investigate educators' views on digital citizenship for their students. Drawing upon existing research, a theorized model of digital citizenship was developed and validated via a confirmatory factor analysis (CFA), resulting in a 14‐item four‐factor model. Factor constructs include digital ethics, participation and engagement, informed citizens and civic know‐how. As teachers' views can shift over time, particularly with the emergence of new technologies, scholars can utilize T‐PODS as they investigate educators' perceptions of digital citizenship across time and context.Practitioner notesWhat is already known about this topicDigital citizenship is crucial for modern society and involves becoming a well‐informed and responsible participant in digital spaces.A few instruments exist for measuring digital citizenship, which have focused on the behaviours and perceptions of young people, including children and university students.Teachers play an important role in helping children develop their digital citizenship skills.What this paper addsThis study presents a new validated model that conceptualizes four key constructs of digital citizenship: digital ethics, participation and engagement, informed citizen and civic know‐how.It also demonstrates the relationship between these constructs and their connections to the literature.This article also establishes the Teachers' Perceptions of Digital Citizenship Scale (T‐PODS), a 14‐item survey instrument that measures teachers' perceptions of these four constructs.Implications for practice and/or policyResearchers and educators can use T‐PODS to understand teachers' perceptions of digital citizenship across time, locations and contexts.Drawing upon the four key constructs, teachers can identify and address constructs, skills and processes that are most applicable to their students and educational goals.Policymakers and curriculum developers can utilize these four constructs to develop both targeted and well‐rounded digital citizenship educational experiences. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) literacy is at the top of the agenda for education today in developing learners' AI knowledge, skills, attitudes and values in the 21st century. However, there are few validated research instruments for educators to examine how secondary students develop and perceive their learning outcomes. After reviewing the literature on AI literacy questionnaires, we categorized the identified competencies in four dimensions: (1) affective learning (intrinsic motivation and self‐efficacy/confidence), (2) behavioural learning (behavioural commitment and collaboration), (3) cognitive learning (know and understand; apply, evaluate and create) and (4) ethical learning. Then, a 32‐item self‐reported questionnaire on AI literacy (AILQ) was developed and validated to measure students' literacy development in the four dimensions. The design and validation of AILQ were examined through theoretical review, expert judgement, interview, pilot study and first‐ and second‐order confirmatory factor analysis. This article reports the findings of a pilot study using a preliminary version of the AILQ among 363 secondary school students in Hong Kong to analyse the psychometric properties of the instrument. Results indicated a four‐factor structure of the AILQ and revealed good reliability and validity. The AILQ is recommended as a reliable measurement scale for assessing how secondary students foster their AI literacy and inform better instructional design based on the proposed affective, behavioural, cognitive and ethical (ABCE) learning framework. Practitioner notesWhat is already known about this topic AI literacy has drawn increasing attention in recent years and has been identified as an important digital literacy.Schools and universities around the world started to incorporate AI into their curriculum to foster young learners' AI literacy.Some studies have worked to design suitable measurement tools, especially questionnaires, to examine students' learning outcomes in AI learning programmes.What this paper adds Develops an AI literacy questionnaire (AILQ) to evaluate students' literacy development in terms of affective, behavioural, cognitive and ethical (ABCE) dimensions.Proposes a parsimonious model based on the ABCE framework and addresses a skill set of AI literacy.Implications for practice and/or policy Researchers are able to use the AILQ as a guide to measure students' AI literacy.Practitioners are able to use the AILQ to assess students' AI literacy development. [ABSTRACT FROM AUTHOR]

The number of studies providing empirical evidence on e‐learning in the field of special education is limited. From this point of view, the aim of this study is to examine whether the factors influencing the e‐learning adoption of university students with disability differ according to the type of disability and gender. The participants of the study consist of 809 university students with a single disability (orthopaedic, visual or hearing). Confirmatory factor analysis and two‐way ANOVA were used in the analysis of the study. The factor analysis showed that validity and reliability of the measurement tool was established and the model fit was good. The results revealed that for all dependent variables (social influence, self‐efficacy, compatibility and facilitating conditions), students with orthopaedic disability and visual impairment had higher scores than students with hearing impairment. On the other hand, contrary to expectations, there was no difference between students with orthopaedic disability and students with visual impairment in any of the factors according to the type of disability. In addition, none of the factors differed by gender. The findings provide empirical evidence that can contribute to the planning of online education processes of students with disability by revealing the similarities and differences in the use of e‐learning systems according to the type of disability. Practitioner notesWhat is already known about this topic The field of special education deals with the special needs of individuals and frequently uses technology to provide the support they need.It is observed that educational processes have been moved to online environments due to the COVID‐19 pandemic, which has affected the field of education nowadays and e‐learning systems in online environments have become indispensable for students with special needs.With their flexible structure, e‐learning systems create universal and inclusive learning environments for all students.Accessibility and special education adaptations are needed for individuals with special needs to use e‐learning systems effectively. For this, first of all, the effects of the disabilities of these individuals in using e‐learning systems should be determined.What this paper adds The results showed that social influence, self‐efficacy, compatibility, and facilitating conditions all differed significantly by type of disability.The research findings revealed that all factors differed significantly in terms of orthopaedic and visual impairment versus hearing impairment.The main contribution of the study can be summarized as investigating the relationships between technology adoption and types of disability with empirical evidence and the fact that the implications and inferences made for theory and practice have the potential to make critical contributions to technology acceptance and use of individuals with special needs.It can be stated that the tool adapted in this study offers a valid and reliable tool for future studies with university students with special needs.Implications for practice and/or policy There is a need for considering the individual differences of participants and adaptations for hearing in the adoption of e‐learning systems.Individual differences should be taken into account in the designs of e‐learning systems, and user‐oriented designs should be given priority.It can be mentioned that providing subtitle support for live lessons and recorded videos for the hearing impairment and adding sign and text support to the audio stimuli, providing screen readers for the visual impairment in the e‐learning system can make valuable contributions to improving the quality of education. [ABSTRACT FROM AUTHOR]