Scott Jarvis is the Stoller-Grabe Endowed Distinguished Chair in Applied Linguistics at Northern Arizona University, and he currently serves as Editor-in-Chief of Language Learning. His main areas of research are crosslinguistic influence, lexical diversity, and forensic linguistics, and across these areas he has played a leading role in shaping several new strands of inquiry. He is one of the principal architects of the study of conceptual transfer—crosslinguistic influence arising from language-specific concepts and patterns of conceptualization—which he developed across a body of work beginning with his 1998 book Conceptual Transfer in the Interlingual Lexicon and his 2008 volume Crosslinguistic Influence in Language and Cognition (with Aneta Pavlenko), and continuing through subsequent work clarifying the construct’s scope and theoretical foundations. He has likewise been instrumental in establishing text-analytic and detection-based approaches to the study of language transfer—including native language identification and text classification, as presented in his 2012 edited volume Approaching Language Transfer through Text Classification—and in advancing the modeling and measurement of lexical diversity as a multidimensional construct grounded in human judgments. His recent research has, inter alia, investigated conceptual transfer and the comprehension and comprehensibility of legal language, particularly non-native speakers’ understanding of their Miranda rights. Professor Jarvis has authored or edited six books and edited volumes and published more than seventy journal articles, book chapters, and reviews. Alongside his current editorship of Language Learning, he has served the journal as Executive Director, and has held leadership roles in the field, including Treasurer of the American Association for Applied Linguistics (AAAL) and co-convener of the AILA Research Network on Crosslinguistic Influence. Additionally, he has served on numerous editorial boards. His contributions have earned recognition including the 2021 AAAL Research Article Award—for his co-authored study of native and non-native speakers’ understanding of their Miranda rights—and an honorary doctorate from the University of Jyväskylä, Finland.

This pilot study adopts an exploratory mixed-methods design to examine the interpretive challenges posed by English analytical terms for learners of English as a Foreign Language (EFL), with particular emphasis on semantic transparency and opacity. Integrating descriptive quantitative assessment with qualitative inquiry, the study explores how lexical phenomena such as polysemy, synonymy, and homonymy affect learners’ comprehension of domain-specific terminology in the field of migration and asylum. A sample of fifteen ­B2-level EFL learners completed a contextualized test of analytical terms and participated in semi-structured interviews designed to elicit their interpretive strategies. Given the exploratory nature of the study and its limited sample size, the findings are not intended for broad generalization but rather to inform future large-scale research. The results indicate that semantic opacity significantly impedes accurate interpretation, with participants demonstrating a marked reliance on literal, compositional processing rather than context-driven inferencing. Furthermore, learners reported a need for enhanced contextual support when engaging with specialized terminology. The findings suggest important pedagogical implications, particularly regarding the integration of AI-assisted tools, such as corpus-based resources and terminology management systems, to support vocabulary acquisition in specialized domains. Although the effectiveness of such tools was not empirically evaluated in this study, the research offers an initial contribution to understanding the multidimensional nature of terminological competence in EFL contexts and outlines potential directions for future investigation, including the role of AI-driven technologies in specialized vocabulary instruction.

Using a mixed-method approach, this study investigates the potential impact of the introduction of Artificial Intelligence (AI) tools on the self-efficacy beliefs of pre-service teachers. Over a 30-week period of instruction, quantitative data from the Teacher Sense of Efficacy Scale (TSES) revealed a statistically significant increase in participants’ sense of self-efficacy. Qualitative data from interviews highlighted benefits such as enhanced instructional confidence, expanded pedagogical repertoires, improved feedback practices, and the fostering of reflective practices. However, there also emerged a number of challenges, including the risk of over-reliance on AI, potentially undermining critical engagement, constraining originality, and creating identity-related tensions. The findings suggest that while the integration of AI tools demonstrates huge potential, teacher education programs must prioritise critical engagement with AI outputs and design-based learning to ensure teachers retain agency and promote responsible AI use in education.

The book is renowned for its novel approach combining psychology, applied linguistics, and cognitive science as well as for its extensive examination of the state of individual differences research. Beyond a basic field review, every chapter explores the theoretical and empirical limits of modern methods. This volume confirms the significance of personal variance in L2 learning. The four main sections of the book, each of which concentrates on a different set of cognitive variables, are age, intelligence, aptitude, and affect (Part I); memory, attention, and noticing (Part II); learning strategies, metacognition, and self-regulation (Part III); L2 skills, learning challenges, and anxiety (Part IV).