Purpose – The purpose of this study is to assess the efficiency of the technology acceptance model (TAM) to explain pre-service teachers' intention to use technology in Turkey. Design/methodology/approach – A total of 197 pre-service teachers from a Turkish university completed a survey questionnaire measuring their responses to four constructs which explain their intention to use technology: attitude towards computer use, perceived usefulness, and perceived ease of use. A structural equation modeling (SEM) approach was employed for modeling and data analysis. Findings – Results revealed that the TAM is an efficient model to explain the intention to use technology of Turkish pre-service teachers. The proportion of variance explained in pre-service teachers' intention to use technology by its antecedents was 51 percent. In addition, four out of five hypotheses were supported in this study. Overall, the data in this study provided support that the TAM is a fairly efficient model with a potential to help in understanding technology acceptance pre-service teachers in Turkey. Originality/value – The TAM is a well-tested and validated model to explain the intention to use technology. However, information on its cross-cultural validity is limited. This study validated the TAM on a sample of pre-service teachers in Turkey and the results provided initial support for the cross-cultural validity of the TAM.

Technology acceptance studies are interesting because they are practical and theoretically helpful in explaining the adoption and intention to use a particular technology. There is a large amount of research on e-learning and other technologies in the literature, but there is limited evidence to explain why secondary school students’ intention to use e-learning. This study explains secondary school students’ intentions to use e-learning with an extended Technology Acceptance Model (TAM). TAM is a useful theory to explain how people adopt new technologies in different fields. Data were collected from 2739 secondary school students in Turkey (Mage = 11.95). Confirmatory factor analysis (CFA) and structural equation modelling (SEM) were used to test the conceptual model. The results are consistent with the original TAM model. The most critical variable affecting secondary school students’ intention to use e-learning technologies is enjoyment. The results show that there may be differences in the intention to use e-learning technologies for secondary school students in different cultures and contexts.

The purpose of this study is to explore the factors influencing individuals’ intentions to adopt generative AI, particularly within the context of digital literacy. It examines the impact of human capabilities and the relationship with technology from a transhumanist perspective. The study utilises an integrated framework combining the Unified Theory of Acceptance and Use of Technology (UTAUT) and the information quality dimension of the Information Acceptance Model (IAM). The moderating effect of attitudes towards AI is also analysed. Survey data from 362 participants in Turkey were collected and analysed using partial least squares structural equation modelling (PLS-SEM), supported by multi-group analysis based on digital literacy levels determined through clustering. The findings indicate that information quality, performance expectancy, social influence and attitudes towards AI significantly influence AI adoption intention. However, effort expectancy does not have a significant effect. Multi-group analysis reveals that higher digital literacy strengthens the impact of attitudes towards AI on adoption, and the effect of social influence on attitudes towards AI. Conversely, lower digital literacy strengthens the effect of information quality on adoption intention. This research contributes to the understanding of the role of digital literacy in generative AI acceptance. It provides insights for improving digital competence to facilitate AI adoption, especially in the context of diverse digital literacy levels, highlighting that the moderating role of digital literacy varies across different predictor–outcome relationships, which has not been extensively explored in existing literature.

This study reports on a survey of 4-8th grade students’ (N=10139) playing game tendencies and digital game preferences based on gender. Descriptive statistics were used to determine the children’ playing game tendencies and digital game preferences. And also, frequent pattern mining was used to discover which digital games are played frequently and together by children. The findings showed that children have an increase time spent playing games on weekend and boys tend to playing game more than girls. On the other hand, action games stood out as the most common choice among the children both girls and boys. In terms of game language, Turkish and English games were preferred almost equally. In addition, children mostly preferred digital games that can be played online, offering in-app purchases, and played on mobile devices. According to the frequency of playing, it was found that the children mostly preferred to play Minecraft, followed by Subway Surfers and Hay Day, respectively. In terms of gender, it was concluded that girls mostly preferred Subway Surfers, while boys played Hay Day. When the games were considered according to the frequency of playing together, Temple Run and Subway Surfers games among girls, and FIFA and Piano Tiles games among boys can be played together. The research reveals more detailed information about children’ game preferences in terms of gender.

Eye-tracking methods have become a valuable tool for reading research, as they provide significant evidence on the behavioral and cognitive performance of developing readers. They also help identify reading behavior patterns among children with neurodevelopmental conditions, such as reading difficulties (RD) or attention-deficit hyperactivity disorder (ADHD). In this paper, we reviewed relevant literature (73 empirical studies) from 2008 to 2023 (15 years). We documented how reading performance was measured through eye-tracking methodology among typical and atypical readers across various languages. To ensure a rigorous and transparent review, we adhered to the PRISMA framework, defined keywords, established inclusion and exclusion criteria, conducted data extraction, and employed a multi-phase selection process. We focused on research samples, stimulus designs, independent variables, eye-tracking systems, and metrics. The results indicated that research involving typically developing children mainly included participants from primary school and employed various eye-tracking methods, with English being the most studied language. Studies on children with RD and ADHD varied significantly in participants’ sample sizes, languages, and experimental designs. The discussion emphasizes the need for standardized data-collection procedures to enhance the reliability and comparability of findings, thereby supporting the development of effective interventions and instructional methods for reading difficulties.

This chapter provides an in-depth examination of assistive technologies designed to address the challenges faced by individuals with hearing impairments. Section 1 highlights the communication barriers and social interactions. Sect. 2 explores the effectiveness of these assistive technologies through bibliometric analysis, revealing how technological advancements are shaping trends in this field. The aim of this chapter is to elucidate how technological aids developed for individuals with hearing impairments support equal opportunities in every aspect, from education to professional life.