This book focuses on the dynamic relationships among individual difference (ID) variables (i.e., willingness to communicate, motivation, language anxiety and boredom) in learning English as a foreign language in the virtual world Second Life. The theoretical part provides an overview of selected issues related to the four ID factors in question (e.g., definitions, models, sources, types, empirical investigations). The empirical part reports the findings of a research project which aimed to examine the changing nature of WTC, motivation, boredom and language anxiety experienced by six English majors during their visits to the said virtual world, the main contributors to the changes in the levels of the constructs under investigation, as well as their relationships. The book closes with the discussion of directions for further research as well as pedagogical implications.

The last few decades have seen extensive research focusing of the relative effectiveness of different instructional options that can be employed in teaching grammar structures (e.g., deduction and induction, different types of corrective feedback, input-based vs. output-based practice). However, the contribution of such pedagogical intervention and the resulting knowledge of target language grammar are mediated by a number of factors related to a specific context, the properties of the features being taught and, most importantly, individual learner profiles. Nonetheless, research into the moderating role of individual difference variables has been scant, limited to only several factors, and seldom taking into account complex interactions between variables. The book seeks to fill this evident gap by investigating the mediating effect of selected cognitive and affective factors on explicit and implicit (or highly automatized) knowledge of the English passive voice. In doing so, the study sheds the so-much-needed light on the predictors of second language grammar knowledge but also, to some extent, on the usefulness of instructional techniques used to develop it.

This edited book brings together ten empirical papers reporting original studies investigating different facets of individual variation second language learning and teaching. The individual difference factors covered include, among others, motivation, self, anxiety, emotions, willingness to communicate, beliefs, age, and language learning strategies. What is especially important, some of the contributions to the volume offer insights into intricate interplays of these factors while others attempt to relate them to learning specific target language subsystems or concrete instructional options. All the chapters also include tangible implications for language pedagogy. The book is of interest to both researchers examining the role of individual variation in second language learning and teaching, teacher trainers, graduate and doctoral students in foreign languages departments, as well as practitioners wishing to enhance the effectiveness of second language instruction in their classrooms.

This book syntheses cutting-edge research on the role of individual differences (IDs) in the field of SLA and in computer assisted language learning. It also outlines the theoretical and methodological issues at the heart of this research, presents empirical findings and charts future directions of this research. Pawlak and Kruk provide an overview of the latest theoretical developments in research on IDs in SLA as well as methodological considerations that are crucial when researching individual variation, with special emphasis on data-collection procedures that are most prominent in CALL. The book goes on to summarize and explore a body of empirical evidence concerning the role of individual difference factors in CALL, singling out existing gaps, methodological problems, and areas in need of further investigation. Finally, the authors provide a guide on how empirical investigations of individual difference factors in CALL can be improved by incorporating latest developments from the broader field of SLA. This book will be of great interest to postgraduates and scholars in the domain of applied linguistics and second language education who are interested in CALL, as well as those studying and undertaking research in second language learning and teaching.

This book argues that, in line with the tenets of positive psychology in SLA and the rhetorical/relational goal theory, positive teacher-student interpersonal relationships are deemed to be of great significance for empowering students to accomplish favorable academic outcomes and to successfully learn a second/foreign language (L2), whether at its affective, behavioral, or cognitive levels. Therefore, understanding the role of teacher interpersonal behaviors and their effect on students' learning gains in the domain of SLA is of utmost importance, particularly as this line of research is at its nascent stage of development, and, as a result, available empirical evidence is still inconclusive. To address this issue, drawing on the mixed methods design, this book mainly aims to, first, empirically scrutinize the role of “5Cs” positive teacher interpersonal variables (i.e., care, clarity, closeness, confirmation, and credibility) in L2 students' affective, behavioral, and cognitive learning outcomes through the mediation of student-perceived learner empowerment in the L2 context of Iran. Second, it is intended to show how L2 teacher educators, teachers, and materials developers, among other key educational stakeholders, can facilitate the provision of interpersonally rich language learning environments with the ultimate goal of enhancing students' L2 learning.

Online learning has become more and more common globally, whether for comfort, adapting to work hours or just having the freedom to study from anywhere. And now under the coronavirus pandemic, as people are having to stay at home, it has become more important than ever. Although the popularity of wireless network and portable smart device makes it possible for people to acquire and learn knowledge anytime and anywhere, it does not necessarily mean an increased learning performance. Relevant research in cognitive science has revealed possible limitations in online learning. For example, the knowledge acquired through online learning tends to be fragmented and lacks guidance for integrated thinking among different subjects, which makes it difficult for learners to form a systematic knowledge structure. Learners may experience cognitive overload, metacognitive illusion and low learning efficiency in self-regulated learning. It follows that, in the post COVID-19 era, online learning puts forward new requirements and challenges to the contemporary students, not only to their learning strategies but positive character traits in learning. Most of the current learning theories were developed in the early 20th century and may not fit in well with the current situation, then possibly leading to inefficient learning and increased learning burden. Therefore, it is necessary and important to reexplore the influencing factors and mechanisms that affect the learning efficiency of students at all levels nowadays, based on which we could construct a theoretical model of efficient learning model.

Technological advancements have enhanced all functions of society and revolutionized the healthcare field. Smart healthcare applications and practices have grown within the past decade, strengthening overall care. Biomedical signals observe physiological activities, which provide essential information to healthcare professionals. Biomedical signal processing can be optimized through artificial intelligence (AI) and machine learning (ML), presenting the next step towards smart healthcare. AI-Enabled Smart Healthcare Using Biomedical Signals will not only cover the mathematical description of the AI- and ML-based methods, but also analyze and demonstrate the usability of different AI methods for a range of biomedical signals. The book covers all types of biomedical signals helpful for smart healthcare applications. Covering topics such as automated diagnosis, emotion identification, and frequency discrimination techniques, this premier reference source is an excellent resource for healthcare administration, biomedical engineers, medical laboratory technicians, medical technology assistants, computer scientists, libraries, students and faculty of higher education, researchers, and academicians.