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The concluding chapter, with a humanistic perspective on learning and technology, emphasizes the unique human aspects that AI cannot replicate, such as factuality, creativity, and humanity.
An investigation of how AI can be applied within specific subjects and disciplines, including TPACK, subject didactic opportunities and problems, and a focus on search criticism and source awareness.
A panoramic view of the digital era and how AI affects today's teaching, introducing the opportunities and simultaneous challenges that technology brings.
An introduction to AI, including an overview of essential technologies such as machine learning and deep learning, and a discussion on generative AI and its potential limitations. The chapter includes an exploration of AI's history, including its relationship to cybernetics, its role as a codebreaker, periods of optimism and “AI winters,” and today's global development with generative AI. Chapter 1 also include an analysis of AI's role in the international and national context, focusing on potential conflicts of goals and threats that can arise from technology.
The chapter highlights the importance of AI literacy. Opportunities and challenges that AI creates in the educational context, such as strategies for technology use, and what AI tools like ChatGPT can enable and hinder in the learning process.
This scoping review directs attention to artificial intelligence–mediated informal language learning (AI-ILL), defined as autonomous, self-directed, out-of-class second and foreign language (L2) learning practices involving AI tools. Through analysis of 65 empirical studies published up to mid-April 2025, it maps the landscape of this emerging field and identifies the key antecedents and outcomes. Findings revealed a nascent field characterized by exponential growth following ChatGPT’s release, geographical concentration in East Asia, methodological dominance of cross-sectional designs, and limited theoretical foundations. Analysis also demonstrated that learners’ AI-mediated informal learning practices are influenced by cognitive, affective, and sociocontextual factors, while producing significant benefits across linguistic, affective, and cognitive dimensions, particularly enhanced speaking proficiency and reduced communication anxiety. This review situates AI-ILL as an evolving subfield within intelligent CALL and suggests important directions for future research to understand the potential of constantly emerging AI technologies in supporting autonomous L2 development beyond the classroom.
Artificial Intelligence (AI) has reached memory studies in earnest. This partly reflects the hype around recent developments in generative AI (genAI), machine learning, and large language models (LLMs). But how can memory studies scholars handle this hype? Focusing on genAI applications, in particular so-called ‘chatbots’ (transformer-based instruction-tuned text generators), this commentary highlights five areas of critique that can help memory scholars to critically interrogate AI’s implications for their field. These are: (1) historical critiques that complicate AI’s common historical narrative and historicize genAI; (2) technical critiques that highlight how genAI applications are designed and function; (3) praxis critiques that centre on how people use genAI; (4) geopolitical critiques that recognize how international power dynamics shape the uneven global distribution of genAI and its consequences; and (5) environmental critiques that foreground genAI’s ecological impact. For each area, we highlight debates and themes that we argue should be central to the ongoing study of genAI and memory. We do this from an interdisciplinary perspective that combines our knowledge of digital sociology, media studies, literary and cultural studies, cognitive psychology, and communication and computer science. We conclude with a methodological provocation and by reflecting on our own role in the hype we are seeking to dispel.
This article argues that the environmental contexts of memory are vulnerable to Artificial Intelligence (AI)-generated distortions. By addressing the broader ecological implications for AI’s integration into society, this article looks beyond a sociotechnical dimension to explore the potential for AI to complicate environmental memory and its role in shaping human–environment relations. First, I address how the manipulation and falsification of memory risks undermining intergenerational transmission of environmental knowledge. Second, I examine how AI-generated blurring of boundaries between real and unreal can lead to collective inaction on environmental challenges. By identifying memory’s central role in addressing environmental crisis, this article places emerging debates on memory in the AI era in direct conversation with environmental discourse and scholarship.
Artificial Intelligence technologies have impacted our world in ways we could not have imagined a decade ago. Generative AI (GenAI), a powerful, complex and general use subset of AI has become available to the public in recent years. GenAI's effect on education, research, and academic practice is far-reaching and exciting, yet also deeply concerning. While GenAI has the potential to offer transformation in the practice of educational research, there are few resources which clarify why, when, and how these tools might be used ethically and sensitively. This Element introduces key areas of consideration for education researchers seeking to use GenAI, including examining the existing research, critically evaluating the benefits and risks of GenAI in educational research, and providing example use-cases of good and bad practice.
This chapter summarizes the complex nature of bilingual academic communication, highlighting the gradual and non-binary process of language acquisition. It emphasizes the importance of academic language, which is structured with regular patterns that facilitate learning in subjects like math, history, and science. It advocates for a deeper understanding of how academic language proficiency is developed through the systematic practice of lexis, syntax, and discourse.
In an era of globalization, multilingualism is vital for social mobility and equity. Educational institutions must adapt to the multilingual reality of today’s classrooms, where proficiency in a global language can open doors to social rights and international participation. The chapter stresses that multilingualism should be seen as an asset, not a transitional quirk, and highlights the benefits of bilingual education in fostering cognitive flexibility and critical thinking. Finally, it explores the need for proper resources, including qualified bilingual teachers, to make bilingual education effective and accessible to all students.
This chapter delves into the role of discourse in language development, extending beyond simple grammar to encompass social context and effective communication. It examines how cognitive structures, linguistic principles, and text genres – narrative, descriptive, expository, and argumentative – interact to shape discourse. Special focus is placed on cognitive discourse functions (CDFs), which guide thought and communication, alongside the importance of cohesion and coherence in constructing meaning.
While discourse is often overshadowed by syntax and lexis, research uncovers developmental patterns in both monolinguals and bilinguals. As learners advance, they refine cohesion strategies, transition from narrative to expository texts, and better integrate CDFs. Tools like Coh-Metrix and TAACO aid in discourse analysis, though much is still to be explored.
L1 and L2 discourse development follows similar paths, though L2 growth may lag due to syntactic proficiency thresholds. This chapter highlights the interplay of cognition, language exposure, and academic demands in shaping discourse mastery, reinforcing the need to support multilingual proficiency in education.
This chapter uncovers the power of academic language in bilingual education. Unlike casual speech, academic language is structured, dense, and cognitively demanding – challenging L2 learners. Success requires ‘L2 instructional competence’, blending language proficiency with advanced cognitive functions.
We explore key theories like the threshold hypothesis, which suggests a minimum language level for learning, and the interdependence hypothesis, which highlights skill transfer between languages. Classroom models categorize tasks by cognitive demand, illustrating structured speaking patterns and the need for rediscursification – language adjustments that enhance comprehension.
Academic language is crucial for professional and societal success, from writing essays to understanding abstract concepts. Biliteracy is a continuous process, supported by bilingual programmes such as CLIL and EMI. By linking cognitive insights with multilingual education, this chapter sets the foundation for quality bilingual instruction in a multilingual world.