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Alexa’s integration in rural primary schools has improved the pedagogy and has created an engaging and objective learning environment. This study investigates the integration, with a specific focus on exploring its various aspects. The impact of Alexa’s on students' English vocabulary, comprehension and public speaking are examined. This study aims to provide insights the teachers and highlight the potential of artificial intelligence (AI) in rural education.

This content analysis study explores the use of Alexa in primary education in rural areas of India. The study focuses on the types of the questions asked by the students and examines the pedagogical implications of these interactions. By analyzing the use of Alexa in rural educational settings, this study aims to contribute to our understanding of how voice assistants are utilized as educational tools in underprivileged areas.

Alexa significantly improved students' English vocabulary, comprehension and public speaking confidence. Alexa increased school enrollment and retention. Virtual voice assistants like Alexa may improve pedagogy and help India’s rural education. This study shows AI improves rural education.

The study only covers rural India. Self-reported data and observations may bias the study. The small sample size may underrepresent rural educational institutions in India.

Alexa is used to study rural India’s primary education. Voice assistants in rural education are understudied. The study examines Alexa’s classroom use, student questions, and policy and teacher education implications. AI’s education transformation potential addresses UNESCO’s teacher shortage. This novel study examines how AI can improve rural education outcomes and access.

A number of recent artificial intelligence (AI)-enabled technologies, including summarisers, paraphrasers and the cutting-edge chatbots not only have outstanding potentials in modern educational systems but also could lead to a dramatic paradigm shift in the whole education process. This study aims to explore the factors that shape the academic community’s desire and intention to use AI conversational chatbot technology, with a particular focus on the leading ChatGPT.

This study uses a mixed method approach to explore the educators’ adoption of chatbots through an empirically validated model. The model, known as the “Educators’ Adoption of ChatGPT”, was developed by integrating the theoretical foundations of both the Unified Theory of Acceptance and Use of Technology and Status Quo Bias (SQB) frameworks, as well as insights gathered from interviews. The relationships within this model were then tested using a quantitative approach. The partial least squares-structural equation modelling method was used to analyse 243 valid survey responses.

The outcomes of the analysis indicated that perceived educators’ effort expectancy, educators’ autonomous motivation, perceived learners’ AI competency, perceived educators’ competency, innovative behaviour towards technological agility and perceived students’ engagement are significant determinants of educators’ intention to use chatbots. In contrast, perceived unfair evaluation of students, perceived students’ overreliance and perceived bias/inaccuracies were shown to have significant impacts on the resistance to use the technology, which typically implies a negatively significant influence on the educators’ use intention. Interestingly, perceived fraudulent use of ChatGPT was proven insignificant on the resistance to use chatbots.

This study makes a significant contribution to the field of educational technology by filling the gap in research on the use and acceptance of AI-enabled assistants in education. It proposes an original, empirically validated model of educator adoption, which identifies the factors that influence educators’ willingness to use chatbots in higher education and offers valuable insights for practical implementation.

The current synthesis study was conducted to locate comprehensive perspectives about the transformation of higher education institutions from being the only places where formal education programs are offered into settings where lifelong learning can be integrated. This demands an inquiry through not only instance investigation but also a more comprehensive evidence upsurge which has great importance in obtaining lessons and drawing conclusions from existing facts to show how higher education institutions can be places where lifelong learning is promoted for the good of both individuals and societal advancement.

Using a meta-synthesis methodology, a comprehensive overview of the current state of knowledge in the area of higher education institutions' role in promoting lifelong learning was synthesized.

The study identified wide-ranging lifelong learning conceptualizations, potential beneficiaries, learning contents and ways of delivery that can be applied in higher education institutions. Furthermore, the practical challenges, partnership and coordination concerns and policy and reform issues towards promoting lifelong learning were addressed.

This meta-synthesis provides crucial evidence for higher education policymakers and practitioners seeking to guide the transformation of their institutions into settings where lifelong learning is integrated with other forms of educational programs, thereby optimizing individual's professional development and societal progress.

The purpose of this study is to examine effects of classroom-level and student-level factors on student engagement in the context of a higher education system vertically differentiated into research, applied and comprehensive university types.

The study used a cross-sectional multilevel design to explain student engagement based on class and student variables. Specifically, the study collects data from 656 students and 61 randomly selected teachers at both levels and uses multilevel modeling to explain relationship patterns.

The results show that institutions vary significantly in student engagement scores. In addition, while a significant variation is found at the student and classroom level, the effects of academic achievement, instructional quality, teaching experience and teacher qualifications on student engagement vary across classrooms in institutions. However, the interaction effect of classroom and student-level variables on student engagement remains non-significant.

The main contribution of this lies in the explanation of student engagement using classroom and student level factors in a vertically differentiated higher education system using multilevel modeling. Student engagement varied in classrooms research universities applied and comprehensive universities.

Given the importance of teacher leadership in influencing, motivating and inspiring student learning engagement and associated learning outcomes, a robust instrument to assess this construct is critical. Although there are some teacher leadership instruments available in existing literature, efforts to adapt robust psychometric instruments to measure teachers' leadership practices in Ethiopian higher education institutions have been limited. Therefore, this study attempted to address this gap by adapting the Teacher Leadership Scale (TLS) based on the Multifactor Leadership Questionnaire (MLQ-5X) and validating its psychometric properties for use in higher education settings.

Using a cross-sectional design, the study involved 409 undergraduate university students who were randomly selected from public universities. Factor analytic methodologies, including exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), were used to analyze the data collected.

The result confirmed a set of 36 items arranged in nine factors, which have a theoretically supported factor structure, excellent model fit and robust evidence for validity, and reliability and measurement invariance. These results demonstrate that the scale is a strong psychometric tool for measuring the leadership profile and practice of higher education teachers.

It can be concluded that the TLS can assist stakeholders in several ways. Researchers can benefit from the scale to measure teachers' leadership practices and predict their influence on student learning outcomes. In addition, the scale can help practitioners and policymakers collect relevant data to rethink teacher professional development initiatives, leadership training programs and other practices aimed at improving teacher leadership effectiveness.

How can a qualitative life course approach inform the analysis of the impact of disability policy on individual lives? This contribution puts forward the concept of policy reception in an effort to apply the key principles of a life course perspective to the study of policy impact, a perspective which is of particular relevance in the case of disability policy. Drawing on a broader qualitative study of the reception of disability policy in France, the paper, focusing on the in-depth analysis of two life stories, makes two main contributions. The first is theoretical, putting forward the concept of policy reception to address the missing link between “the state and the life course,” as pointed out by Mayer and Schoepflin (1989). The second is methodological, detailing how biographical interviews, following this life course approach, can be used to operationalize this concept of policy reception. These contributions are illustrated by study results focusing on the reception of disability-related educational policies.

Mexico is a large, culturally and linguistically diverse country. More than half of its population lives below the poverty line, a fifth is of indigenous origin, and 5% have a disability. This chapter offers a brief description of the general characteristics of the country and the legislative changes toward inclusion and presents the status and progress toward the 2030 Agenda educational goals toward inclusive education. Although efforts have been made to improve the quality of education and inclusion, the country's complexities: poverty, cultural diversity, and political adjustments, among others, have held back progress, as will be explained in this chapter.

This study evaluated the impact of a faculty training program on student assessment using the Kirkpatrick model.

A self-reported survey assessed 111 Saudi and non-Saudi participants' satisfaction. Subjective and objective measures (self-reported measures, assessment literacy inventory and performance-based assessment tasks) gauged participants' learning level. Pre- and post-training data were collected from 2020 to 2022.

A highly significant effect on satisfaction (>80%) and learning levels was observed, as manifested by workplace practices of student assessment (>70%, the cut-off score). Pre- and post-training comparisons of participants' satisfaction and assessment literacy scores showed significant improvements following training. Multiple regression analyses showed no significant effects for gender and educational attainment but a substantial impact of academic cluster on participants' student assessment skills.

Long-term effects of training faculty on assessment practices and student achievement will be studied at the institutional level in future research.

The current study contributes to human capital investment via faculty training on student assessment, helping them comply with assessment best practices. This assures the quality, fairness and consistency of assessment processes across disciplines in higher education institutions, enhances assessment validity and trust in educational services and may support institutional accreditation.

This study provides opportunities for sharing best practices and helps establish a community of practice. It enhances learning outcomes achievement and empowers higher education graduates with attributes necessary to succeed in the labor market. The human capital investment may have a long-term impact on overall higher education quality.

This study contributes to the scarce literature investigating the impact of training faculty from different clusters on student assessment using subjective and objective measures. It provides developing and evaluating a long-term student assessment program following the Kirkpatrick model.

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.