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The Dalai Lama has represented Buddhism as a religion of non-violence, compassion, and world peace, but this does not reflect how monks learn their vocation. This book shows how monasteries use harsh methods to make monks of men, and how this tradition is changing as modernist reformers—like the Dalai Lama—adopt liberal and democratic ideals, such as natural rights and individual autonomy. In the first in-depth account of disciplinary practices at a Tibetan monastery in India, Michael Lempert looks closely at everyday education rites—from debate to reprimand and corporal punishment. His analysis explores how the idioms of violence inscribed in these socialization rites help produce educated, moral persons but in ways that trouble Tibetans who aspire to modernity. Bringing the study of language and social interaction to our understanding of Buddhism for the first time, Lempert shows and why liberal ideals are being acted out by monks in India, offering a provocative alternative view of liberalism as a globalizing discourse.

This book presents a wide range of methodological perspectives on researching what teachers think and do in language teaching. It contains chapters by the editors and a leading expert in teacher cognition, as well as eight case studies by new researchers, accompanied by commentaries by internationally known researchers.

In Language Online, David Barton and Carmen Lee investigate the impact of the online world on the study of language. The effects of language use in the digital world can be seen in every aspect of language study, and new ways of researching the field are needed. In this book the authors look at language online from a variety of perspectives, providing a solid theoretical grounding, an outline of key concepts, and practical guidance on doing research. Chapters cover topical issues including the relation between online language and multilingualism, identity, education and multimodality, then conclude by looking at how to carry out research into online language use. Throughout the book many examples are given, from a variety of digital platforms, and a number of different languages, including Chinese and English. Written in a clear and accessible style, this is a vital read for anyone new to studying online language and an essential textbook for undergraduates and postgraduates working in the areas of new media, literacy and multimodality within language and linguistics courses.

The question of how generative AI tools, such as large language models and chatbots, can be leveraged ethically and effectively in education is ongoing. Given the critical role that writing plays in learning and assessment within educational institutions, it is of growing importance for educators to make thoughtful and informed decisions as to how and in what capacity generative AI tools should be leveraged to assist in the development of students’ writing skills. This paper reports on two longitudinal studies. Study 1 examined learning outcomes of 48 university English as a new language (ENL) learners in a six-week long repeated measures quasi experimental design where the experimental group received writing feedback generated from ChatGPT (GPT-4) and the control group received feedback from their human tutor. Study 2 analyzed the perceptions of a different group of 43 ENLs who received feedback from both ChatGPT and their tutor. Results of study 1 showed no difference in learning outcomes between the two groups. Study 2 results revealed a near even split in preference for AI-generated or human-generated feedback, with clear advantages to both forms of feedback apparent from the data. The main implication of these studies is that the use of AI-generated feedback can likely be incorporated into ENL essay evaluation without affecting learning outcomes, although we recommend a blended approach that utilizes the strengths of both forms of feedback. The main contribution of this paper is in addressing generative AI as an automatic essay evaluator while incorporating learner perspectives.

This volume represents the first collection of empirical studies focusing on peer interaction for L2 learning. These studies aim to unveil the impact of mediating variables such as task type, mode of interaction, and social relationships on learners' interactional behaviors and language development in this unique and pedagogically powerful learning context. To examine these issues, contributors employed quantitative, qualitative, and mixed-methods designs as well as cognitive, social, and sociocognitive theoretical frameworks. The majority of the studies are classroom based and were conducted in a rich array of settings covering five continents and encompassing a wide range of learner L1s and target languages. These settings include second and foreign language classrooms from primary to university level, content-based programs, online contexts, and after-school programs. To span the divide between research and practice, each study includes a section suggesting pedagogical implications.

Chatbot usage is evolving rapidly in various fields, including higher education. The present study’s purpose is to discuss the effect of a virtual teaching assistant (chatbot) that automatically responds to a student’s question. A pretest–posttest design was implemented, with the 68 participating undergraduate students being randomly allocated to scenarios representing a 2 × 2 design (experimental and control cohorts). Data was garnered utilizing an academic achievement test and focus groups, which allowed more in depth analysis of the students’ experience with the chatbot. The results of the study demonstrated that the students who interacted with the chatbot performed better academically comparing to those who interacted with the course instructor. Besides, the focus group data garnered from the experimental cohort illustrated that they were confident about the chatbot’s integration into the course. The present study essentially focused on the learning of the experimental cohort and their view regarding interaction with the chatbot. This study contributes the emerging artificial intelligence (AI) chatbot literature to improve student academic performance. To our knowledge, this is the first study in Ghana to integrate a chatbot to engage undergraduate students. This study provides critical information on the use and development of virtual teaching assistants using a zero-coding technique, which is the most suitable approach for organizations with limited financial and human resources.

One of the biggest challenges for EFL (English as Foreign Language) students to learn English is the lack of practicing environments. Although language researchers have attempted to conduct flipped classrooms to increase the practicing time in class, EFL students generally have difficulties interacting with peers and teachers in English in class. The advancement of Artificial Intelligence (AI) provides an opportunity to address this problem. With AI technologies, computer systems, in particular in the form of AI chatbots, are able to identify the meanings of users' statements and make responses accordingly. In the research design, AI-based chatbots were employed in the in-class and out-of-class activities for facilitating the students' speaking performance and interactions during the learning process in a university flipped English speaking classroom. The experimental results show that the mind map-guided AI chatbot approach (MM-AI) promoted the students' English speaking performances more than did the conventional AI chatbot approach (C-AI). Moreover, the MM-AI also promoted the students' learning performance and organized the interaction between the robots and humans more than the C-AI did. The findings could be a valuable reference for language educators and researchers who intend to conduct AI-supported flipped classrooms in language learning.

This study examined development of academic, language, and social skills among 4-year-olds in publicly supported prekindergarten (pre-K) programs in relation to 3 methods of measuring pre-K quality, which are as follows: (a) adherence to 9 standards of quality related to program infrastructure and design, (b) observations of the overall quality of classroom environments, and (c) observations of teachers' emotional and instructional interactions with children in classrooms. Participants were 2,439 children enrolled in 671 pre-K classrooms in 11 states. Adjusting for prior skill levels, child and family characteristics, program characteristics, and state, teachers' instructional interactions predicted academic and language skills and teachers' emotional interactions predicted teacher-reported social skills. Findings suggest that policies, program development, and professional development efforts that improve teacher — child interactions can facilitate children's school readiness.

The volume provides new multidisciplinary insights and updated empirical data on the process through which cultures, identities, and knowledge are brought into being through the everyday dialogues that animate children's life at home and school.

How workers experience and express status loss in organizations has received little scholarly attention. I conducted a qualitative study of a French high-tech company that had instituted English as a lingua franca, or common language, as a context for examining this question. Results indicate that nonnative English-speaking employees experienced status loss regardless of their English fluency level. Yet variability in their self-assessed fluency—an achieved status marker—was associated with differences in language performance anxiety and job insecurity in a nonlinear fashion: those who believed they had medium-level fluency were the most anxious compared with their low- and high-fluency coworkers. In almost all cases where fluency ratings differed, self-assessed rather than objective fluency determined how speakers explained their feelings and actions. Although nonnative speakers shared a common attitude of resentment and distrust toward their native English-speaking coworkers, their behavioral responses—assertion, inhibition, or learning—to encounters with native speakers differed based on their self-perceived fluencies. No status differences materialized among nonnative speakers as a function of diverse linguistic and national backgrounds. I discuss the theoretical and practical implications of these findings for status, achieved characteristics, and language in organizations.