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The journal Historia y Memoria de la Educación, HME, is calling for papers on the theme of transnationality and transculturality in the history of education. The concept of transnational history refers to a research approach that examines the different degrees of interaction, connection, circulation, intersection and intertwining that reach beyond the nation state. The idea of cultural transfer is based on an understanding of culture that rejects the concept of homogenous identities and closed national cultures and argues for a broad multicultural definition that reflects the construction of reference points in particular historical and territorial spaces. Based on this central axis, the following themes are proposed: 1) Centres and peripheries: cultural and pedagogical movements and the formation of transnational and transcultural networks. 2) The image of other cultures in national and international pedagogical discourses. 3) Migrants and migrations in the history of education. 4) The reflection of transnationality and transculturality in the material culture of the school. 5) History of environmental education, development education and education for sustainable development goals.
Over the past two decades, there has been a growing interest in examining language teachers’ professional identity (Derakhshan & Nazari, 2022a; Yazan, 2023). Teacher professional identity is generally a dynamic, multilayered, and evolving construct, playing a vital role in teachers’ professional success (Pennington & Richards, 2016; Yazan, 2018). That is, how teachers perceive their profession and their professional responsibilities directly affect their performance in instructional environments (Borg 2019). Most language professionals agree upon the fact that language teachers’ perceptions of the teaching profession and their role as language teachers originate from their ongoing interpretations of professional experiences (Derakhshan & Nazari, 2022b; Derakhshan et al., 2023; Tajeddin & Adeh, 2016; Yazan, 2023). In fact, they assume that the pleasant and unpleasant emotions teachers experience in response to classroom climate, administrators’ and colleagues’ behaviors, and students’ learning outcomes can shape their professional identity. Taking this assumption into consideration, several language scholars to date have explored the role of emotions in language teachers’ identity formation. However, a short glance at the available literature reveals that the research on the role of emotions in constructing and reconstructing English teachers’ professional identity is still in its infancy. In fact, little is known about the interaction between English teachers’ emotions and their professional identity. To bridge this gap and shed more light on the function of emotions in constructing English teachers’ professional identity, the present special issue seeks to bring together studies assessing the potential influences of positive and negative emotions on EFL and ESL teachers’ identity formation. This special issue particularly welcomes original research, intervention-based studies, critical reports, synthetic reviews, and meta-analyses. Regarding the design of studies in this area, they can be longitudinal, qualitative exploration of a few cases in detail, experimental, large-scale quantitative exploration of correlational or cause-effect relationships, or mixed methods research studies. Studies that go beyond self-reported data by using observations and narrative inquiry are highly welcomed in this special issue. Finally, to ensure the interplay between emotions and professional identity formation, this special issue suggests that scholars use robust statistical methods such as multiple regression, confirmatory factor analysis, and structural equation modeling. Potential keywords include but are not limited to the following: EFL and ESL Teachers, Teacher Professional Identity, Identity Formation, Professional Experiences, Pleasant Emotions, Unpleasant Emotions, Aggression, Anger, Boredom, Dissatisfaction, Frustration, Stress, Autonomy, Agency, Classroom Climate, Enthusiasm for Teaching, Growth Mindset, Job Satisfaction, Organizational Commitment, Passion, Self- and collective efficacy, Teaching Enjoyment, Perceived Colleague Support, Principal Behavior
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.
Teleneuropsychology (TeleNP) can be defined as the application of audiovisual technologies to enable remote consultations with patients to conduct neuropsychological assessment and/or treatment. Over the last fifteen years, TeleNP began to demonstrate its potential as a viable therapeutic option for neuropsychologists. At this stage, it is beyond debate that the COVID-19 pandemic made telemedical options urgent and essential, leading to the widespread use in both clinical and research settings. However, the absence of prior norms, practice guidelines, and a full understanding of the methodological complexities has revealed a critical gap in the field. Prior to the pandemic, APA and the Joint Task Force for the Development of Telepsychology Guidelines for Psychologists (2013) published useful guidelines for the delivery of remote psychological services. However, due to the unprecedented nature of the challenges the entire healthcare system was facing, an advocacy team was established by the Interorganizational Practice Committee (Bilder et al., 2020) to propose a framework for future formal TeleNP guidelines. These were important fundamental steps, but to date a lot of work still remains to be done.
Artificial Intelligence (AI) in Higher Education: Impacts on Learning, Teaching, Assessment, and Educational Development Artificial Intelligence (AI) has emerged as a transformative force across various domains, and education is no exception. In the context of higher education, both teachers and students are already using AI tools for different purposes such as enhancing learning, improving teaching efficiency, generating learning materials, facilitating writing tasks, providing feedback, and assessing students’ tasks (Banihashem et al., 2024; Cotton et al., 2024; Farrokhnia et al., 2024). Although the utilization of AI tools in higher education is experiencing rapid growth, our comprehension of how these tools should be effectively integrated remains limited and their impact is still unknown. This shortfall in understanding poses inherent risks to their implementation in higher education. For instance, evidence suggests that both teachers and students may over-rely on AI (Darvishi et al., 2023), potentially jeopardizing the development of essential skills like self-regulation and critical thinking (Oca et al., 2023). Given the potential risks posed by AI tools for learning, teaching, assessment, and educational development, it is crucial to advocate for empirical research to grasp the appropriate roles AI tools can play in these domains. In this special issue, we seek to compile and disseminate cutting-edge research exploring appropriate AI roles for learning, teaching, assessment, and educational development within the context of higher education. This special issue call is hosted by “Innovations in Education and Teaching International” (IETI) journal which welcomes strong empirical contributions that are focused on promoting innovation and best evidence-based educational practices in higher education. In line with the scope of IETI journal, which highlights AI as a significant recent innovation in education, we invite empirical studies that shed light on the effective utilization of AI tools for learning, teaching, assessment, and educational development within higher education contexts. Conceptual papers will also be welcomed where appropriate. Building upon this, the special issue invites contributions that explore, but are not limited to, the following themes: Pedagogical implications of AI for enhancing learning in higher education Pedagogical implications of AI for improving teaching in higher education Evidence-based educational practices and developments with AI in higher education Design, development, and evaluation of AI-based educational tools in higher education Adaptive and personalized learning using AI in higher education Analysis of teaching and learning of AI in higher education Intelligent tutoring and learning systems using AI in higher education AI and development of learning design and materials in higher education Ethical, policy, and privacy challenges of AI-generated content in higher education AI for assessment of, assessment for, and assessment as learning in higher education Social and cultural aspects of designing AI learning environments in higher education Pedagogical challenges for designing and implementing AI in higher education Integration of AI in the curriculum development and educational design in higher education
The advent of Generative Artificial Intelligence (GAI) technologies, including large language models like ChatGPT® by OpenAI® and Gemini® by Google Deepmind®, has unveiled considerable potential to revolutionize various facets of science education—ranging from learning goals and curriculum materials to assessment practices and learning outcomes—thereby fostering a more equitable science learning environment. These innovations hold the promise of empowering learners and educators to realize their maximum potential, equipping them with essential tools and scientific acumen crucial for future professional success (Herdiska & Zhai, in press). By customizing educational experiences and aligning them with individual learners' needs, GAI applications facilitate not only the acquisition of specific scientific knowledge and skills but also bolster critical thinking, problem-solving, data literacy, and decision-making capabilities. Furthermore, GAI's potential to automate routine educational tasks—such as grading, assessment, and record management—portents a paradigm shift in educational processes. This automation can significantly enhance the efficiency and preciseness of these tasks, thereby alleviating the administrative burden on educators (Zhai et al., 2022; Zhai & Nehm, 2023) as well as reducing the time commitment and work load of educators. As a result, educators are afforded greater capacity to engage in complex, high-impact activities such as mentorship, discussion facilitation, and personalized feedback provision, all of which are pivotal for effective and equitable science education. The integration of GAI applications into educational settings demands a reevaluation and redesign of educational materials to make them more equitable, interactive, engaging, and tailored to cater to the diverse learning needs and preferences of students. This approach has the potential to elevate the quality of educational content, making it more accessible, adaptable, and engaging thereby enriching the overall science learning experience. Commensurately, large language models offer new tools for the analysis of textual data which has the potential to provide educators with rich insights into both learners’ performance and understanding of science content and processes (Tai et al., 2024). Large longitudinal educational survey studies have contributed to the understanding of educational equity, but these studies do not offer solutions (Tai, 2022). The influence of GAI on science teaching is particularly significant, as it allows educators to adopt novel teaching strategies assisted by GAI that are precisely aligned with the specific needs and preferences of learners. GAI applications can provide educators with actionable, data-driven insights into students' learning patterns and preferences via natural language processing (Latif & Zhai, 2023) or computer vision (Lee & Zhai, 2023), enabling the adoption of more effective, engaging, and relevant multimodal methods (Lee et al., 2023). Moreover, GAI applications can enhance educational outcomes by improving both the quality and equity of learning, thereby augmenting learners’ ability to fulfill their science educational objectives and increasing their likelihood to succeed in subsequent STEM-related career pursuits. In conclusion, the integration of GAI applications in science education holds the potential to fundamentally transform our approach to learning goals, processes, materials, pedagogy, and outcomes. This transformation advocates for a more personalized and equitable learning model, tailored to meet the unique requirements and preferences of individual learners. To realize this ambition, interdisciplinary collaborations between researchers in science education and AI are indispensable to propel research and practical implementation. Additionally, a thorough exploration of the challenges (e.g., bias, gender disparities) (Wilson et al., 2023) and opportunities associated with the deployment of GAI applications in science education is crucial to anticipate and ensure equitable educational experiences.