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The report released by UNESCO highlights that over 250 million children, adolescents, and youth were out of school in 2018 due to diverse reasons (Deloumeaux, 2019). The 2020 Global Education Monitoring Report published by UNESCO points out that less than 10% of countries have laws that guarantee full inclusion in education. The report further identifies the key factors responsible for learners’ exclusion in education systems worldwide, including gender, poverty, disability, ethnicity, migration, and sexual orientation (UNESCO, 2020). Evidently, educational divide remains a significant and global challenge for many governments, schools, and other educational stakeholders. Since its inception, generative AI has revolutionized the educational field, fundamentally altering the landscape of teaching and learning (Chen et al., 2022). The key question is whether generative AI will deepen existing inequalities or enhance inclusivity and equity (see a discussion in Yang et al., 2024). On the one hand, generative AI as the potential to bridge educational divide by providing educational resources and personalized learning experiences to students who may lack access to traditional educational opportunities. This allows students to learn in a way that is most effective for them, closing the gaps in learning outcomes that may exist between different groups of students. In addition, this can expand access to quality education, particularly for students in remote or underserved areas who may not have access to a diverse range of educational resources (OECD, 2023). On the other hand, generative AI tools, like many advanced technologies, may not be equally accessible to all. Schools and individuals in developing countries or regions with limited resources may lack the infrastructure, funding, or expertise to integrate these tools into their educational systems (UNESCO, 2023a). Effective use of generative AI requires a certain level of digital literacy. This includes understanding how to operate the technology, interpret its outputs, and integrate it into learning processes (Jones & Hafner, 2021). Individuals or communities with limited digital literacy skills may struggle to capitalize on the benefits of these tools, which may exacerbate educational equity (UNESCO, 2023b). Thus, how can educators, teachers, and researchers harness generative AI to provide individualized learning experiences and help bridge potential educational divide? This is an essential but underexplored area of research (Hwang et al., 2020). Bridging educational divide, with inclusivity and diversity as key principles, has been a core goal of Computers and Education: Artificial Intelligence since its inception. Keeping these principles in mind, this special issue aims to tap into this unknown territory by advancing our limited understanding in that regard. We are looking for submissions that present original research, practical applications, or thought-provoking perspectives on innovative and effective ways to address educational divide caused by generative AI. We welcome submissions on a broad range of topics, including but not limited to: Systematic reviews, meta-analysis, theories, and trends on the applications of generative AI for bridging educational divide Case studies and teaching practices in using generative AI for bridging educational divide for disadvantaged learners Technical discussions of developing generative AI for bridging educational divide Ethical, cultural, and social considerations of using AI for bridging educational divide Perceptions held by various educational stakeholders towards using generative AI for bridging educational divide, including learners, teachers, parents, and administrators Learning experiences of disadvantaged groups in using generative AI to protect and uphold their educational and scholarly rights
The omnipresence of artificial intelligence (AI) in modern education presents unprecedented opportunities and challenges. Regardless of whether educators formally adopt AI, students are increasingly utilizing these tools, prompting a significant shift in traditional educational paradigms. This evolution raises critical questions about the nature of assessment, the skills that should be nurtured and evaluated, and the ethical implications of AI in education. Noteworthy is the potential of low-cost AI to provide accommodations for differently-abled learners, democratizing access to education. This scenario necessitates a re-evaluation of conventional assessment methods, urging educators to consider how AI can enhance educational equity, foster diverse skill sets, and redefine the metrics of academic success. The integration of AI in assessment alters how we evaluate learning and challenges our understanding of what constitutes valuable knowledge and competencies in the digital age. This research aims to investigate how artificial intelligence (AI) can improve both formative and summative assessment practices in education and what shifts in pedagogy and assessment methodology are required to realize these improvements. The focus is on critically examining the transformative influence of AI on traditional assessment approaches, exploring how it can broaden and enhance the evaluation of learner abilities and knowledge. This entails thoroughly exploring AI's role in creating more dynamic, inclusive, and effective assessment strategies suitable for diverse learning environments. Additionally, the research will address the ethical implications and challenges associated with integrating AI into educational assessments, including issues of academic integrity and potential biases in AI algorithms. Particular attention will be given to developing AI tools that cater to the needs of differently-abled learners, thereby advancing accessibility in education. The goal is to provide actionable insights and recommendations for educators and policymakers in higher education to harness AI's potential in formative and summative assessments, ultimately leading to a significant shift in educational practices, and thus a more adaptive, fair, and comprehensive evaluation system. The proposed research topic aims to delve into the dynamic landscape of educational evaluation in the context of the rapidly evolving field of Artificial Intelligence (AI). As AI technologies continue to permeate various aspects of education, understanding their impact on evaluation practices becomes crucial for ensuring effective and meaningful assessments. In line with this, the following themes are envisioned: - Enhancement of assessment practices; - Dynamic and inclusive assessment strategies; - Ethical implications and challenges; - Best practices: Actionable insights and recommendations.
The opposition between uniqueness and universality in rural science, technology, engineering, mathematics, and medicine (STEMM) education research is an enduring feature of the field. Theories and methods developed to be universally applicable are constantly adopted or reimaged in studying and understanding certain unique STEMM education phenomena or issues within and across rural contexts, partly due to the vastness and variety that exists in what is labeled as rural and/or STEMM education. Research ideas and findings focused on a unique rural population or setting often can have universal implications for other rural and non-rural populations or settings, though not explicitly articulated in many publications. Striving to be both unique and universal is a fundamental challenge, yet has the potential to advance knowledge and practice in the field of rural STEMM education. The overall goal of this Research Topic is to introduce and explore the ideas of rural-focused and rural-reimaged approaches in potentially bridging the gaps between uniqueness and universality in STEMM education research. Rural-focused theories and constructs (e.g., place-based education, rural identity) are centered around populations and issues in rural settings, whereas rural-reimaged theories and constructs (e.g., urban-rural spatial inequality, social capital, expectancy-value beliefs) are traditional theories and constructs that are reconceptualized to include rural perspectives in the studies. This Research Topic seeks articles that examine both the uniqueness and universality of rural STEMM education and educational research utilizing rural-focused and/or rural-reimaged lens or approaches. We particularly welcome articles that address unique assets, challenges, needs, opportunities, and/or lessons learned of rural STEMM education while being situated in a broader research discipline, as well as articles that explore the commonalities and connections across study cases, policies/programs/practices, or contexts of rural STEMM education. This Research Topic invites theoretical, methodological, and empirical contributions addressing, but not limiting to the following key topics: Rural-focused topics: • Defining rurality in STEMM education • Defining STEMM in rural areas • Place-based STEMM teaching, learning, etc. • Rural STEMM identity, belonging, etc. • STEMM education in rural-serving postsecondary institutions • STEMM education for local workforce development Rural-reimaged topics: • Urban-rural spatial inequality in rural STEMM education • Community cultural wealth in rural STEMM education • STEMM funds of knowledge of rural learners • Underrepresentation of rural students in STEMM education • Intersectionality in rural STEMM education • Critical policy analysis in rural STEMM education • Communities of practice in rural STEMM education • Research-practice partnerships for rural STEMM education Articles need to define rurality for interpretation by international readers and describe the uniqueness and universality of the research topics, theories, methods, findings, and/or implications in the context of rural STEMM education.
In a recent reflection on the field of language teacher motivation, Kubanyiova (2019) suggested a need for a broader and necessarily transdisciplinary scoping of research across applied linguistics and beyond, as a way of articulating this domain's purposes and expanding its theoretical and methodological repertoires. The current socio-political picture is that of an ‘uneven world’ (Pennycook, 2022) of racial, gender, and socioeconomic inequalities. Recent debates in applied linguistics have insisted on the need for the language teacher education research to respond to these wider social and political concerns across diverse national and local settings in which the lives of language teachers and their students are located (Crozet & Díaz, 2020; De Costa & Ustuk, 2024; Heidt, forthcoming; Kramsch & Zhang, 2018; Kubanyiova & Crookes, 2016; Motha, Jain, & Tecle, 2012; Sharma et al., 2022; Si’ilata, 2019). In the same vein, this special issue pushes language teacher motivation scholarship to look beyond the dominant psychological paradigms and considers more encompassing metaphors for critically conscious, ethically responsible and practice-oriented agendas for this strand of research. We invite contributions which reflect on the significance of understanding teacher motivation in an unequal world, are firmly embedded in their socio-political settings and which link concerns with language teachers’ motivation (broadly conceived) with social consequences in their workplaces, in their communities and, crucially, in their students’ lives. This special issue is particularly concerned with language teacher motivation research that is located in diverse, unrepresented and underserved linguistic, geographical and socio-political settings is underpinned by practice-oriented methodologies and analytical approaches that connect questions of teacher motivation to social and educational consequences for students (e.g. ethnographic, discursive, participatory, collaborative, arts-based) makes space for new voices and demonstrates commitment to responsible scholarship (Charity Hudley & Flores, 2023; Holmes et al., 2022; Motha, 2020) engages in productive dialogue with other domains of applied linguistics and beyond. Language teacher motivation and the surrounding concepts have seen a surge of research interest in recent years. Recent prominent works have considered L2 teacher motivation from various theoretical frameworks (such as Hiver et al, 2018; Kimura et al, 2014; Kubanyiova, 2009; Rahmati & Sadeghi, 2021; Yuan, et al, 2017) or have explored its links with factors contributing to or mitigating motivation, including motivation and self-concept (Kumazawa, 2013), motivation and autonomy (Kimura et al, 2022), motivation and vision (Rahmati, et al. 2018; Kubanyiova, 2014) motivation and burnout (Sato, et al, 2022), among others.
In today’s rapidly evolving educational landscape, emerging learning technologies are paving the way for a new realm of research. These advancements are particularly significant in the context of global challenges such as human rights violations, inequality, and poverty, which hinder peace and sustainability. Recognizing these issues, UNESCO emphasizes the importance of global citizenship education as a means to mitigate these problems (UNESCO GCED, 2023). It is essential for learners of all ages to engage actively in creating societies that are peaceful, tolerant, inclusive, secure, and sustainable. UNESCO’s Global Citizenship Education framework (UNESCO Global Citizenship Education, 2023) outlines three key educational goals: • Cognitive: Developing knowledge and critical thinking skills to navigate the complexities of the world. • Socio-emotional: Cultivating values, attitudes, and social skills that foster emotional, psychosocial, and physical development, enabling respectful and peaceful coexistence. • Behavioral: Encouraging conduct, practical application, and active engagement in societal issues. The Sustainable Development Goals (UN Sustainable Development Goals, 2023) underscore the aim to equip all learners with knowledge and skills for sustainable development, including education in sustainable living, human rights, gender equality, peace, non-violence, global citizenship, and cultural diversity’s role in sustainability. Technology’s role in promoting global citizenship is increasingly recognized as crucial. In this vision of future education, global, national, and international collaboration is vital. In our interconnected and technologically advanced society, personal and professional growth is largely influenced by information technology, which sets the standards for knowledge creation. Lifelong learning enhancement, incorporating the values of global citizenship, and the transmission of universal values are key factors. Altinay et al. (2020) stress the importance of active participation in education at all levels and emphasize the significance of inclusivity and accessibility. The United Nations and UNESCO Sustainability Goals (UN Sustainable Development Goals, 2023) highlight the necessity of education for all, encompassing lifelong learning that includes social justice and global citizenship in diverse contexts. Fleming’s study (2019) focuses on diversity, exploring the dynamics of ethnicity and inequality at policy, school, and individual levels, and their impact on the education of ethnic minorities in their host communities.
Religious education policy and practice in many countries is not only determined by the state or the school but by or in response to an intermediate context. This special issue of the Journal of Beliefs and Values seeks to explore how religions and worldview education is (or has previously) been determined/shaped and adapted in relation to locality or region. The call is timely at it is roughly a century since the publication of the first locally agreed syllabuses in England, the West Riding of Yorkshire in 1922, then Cambridgeshire in 1924. Indeed, locally agreed syllabuses from 1944 became the statutory mechanism for determining the religious education curriculum in England (Fancourt 2022), thus becoming the vehicle for the subject’s definition and content historically and over time (Parker & Freathy 2011; 2012). Moreover, in response to wider cultural and educational change this legal, locally negotiated framework became the locus for, and facilitated, new developments in the subject, such as the introduction of ‘world religions’ and Humanist perspectives (Watson 2010). Likewise, other countries have regional structures for the subject. For instance, the different Länder in Germany each determine its own form of the subject, and respond differently to particular local differences (Euchner 2018). The region of Alsace-Lorraine in France, which maintains a confessional selective model, unlike the laic model of the rest of France (Demissy 2009), is both a historical anomaly, but also a policy alternative. In Indonesia, the contexts of different islands and regions are relevant, so that Islamic education can be different in predominantly Hindu Bali to the rest of the islands (Saihu & Sarnoto 2020). Further, confessional models of religious education are often organised regionally, e.g., through church dioceses. These variations in the nature of religious education at a local level around the globe raise theoretical questions, about framing of the subject at the micro, meso and macro- levels (e.g., Berglund et al. 2016), and about the relationship between central government and local need. In the English context, it begs questions about the necessity of a central determinacy of the subject, recently recommended by the Commission on Religious Education. Comparisons across national jurisdictions through the lens of the local e.g., Franken’s (2020) study of Flanders in Belgium and Quebec in Canada have the potential to reveal interesting things about the dynamics of curriculum formation, amongst other things.