Top Research Papers on Language Learning

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Abstract Background The use of chatbots as learning assistants is receiving increasing attention in language learning due to their ability to converse with students using natural language. Previous reviews mainly focused on only one or two narrow aspects of chatbot use in language learning. This review goes beyond merely reporting the specific types of chatbot employed in past empirical studies and examines the usefulness of chatbots in language learning, including first language learning, second language learning, and foreign language learning. Aims The primary purpose of this review is to di...

The digital competencies teachers and learners require to use this chatbot ethically and effectively to support language learning are presented.

Vocabulary is now well recognized as an important focus in language teaching and learning. Now in its third edition, this book provides an engaging, authoritative guide to the teaching and learning of vocabulary in another language. It contains descriptions of numerous vocabulary learning strategies, which are supported by reference to experimental research, case studies, and teaching experience. It also describes what vocabulary learners need to know to be effective language users. This new edition has been updated to incorporate the wealth of research that has come out of the past decade. It...

A brief review of the infant statistical language learning literature is presented, and broader questions concerning why infants are sensitive to statistical regularities are raised.

This work proposes a method that addresses the problem of visual question answering by introducing counterfactuals in the training, and shows that simulating plausible alternative training data through this process results in better generalization.

It is suggested that the most recent generation of Large Language Models (LLMs) might finally provide the computational tools to determine empirically how much of the human language ability can be acquired from linguistic experience.

A data-driven exploration of children's early language learning across different languages, providing an empirical reference and a new theoretical framework. This book examines variability and consistency in children's language learning across different languages and cultures, drawing on Wordbank, an open database with data from more than 75,000 children and twenty-nine languages or dialects. This big data approach makes the book the most comprehensive cross-linguistic analysis to date of early language learning. Moreover, its data-driven picture of which aspects of language learning are consi...

The CorefBERT model is presented, a novel language representation model designed to capture the relations between noun phrases that co-refer to each other, and has made significant progress on several downstream NLP tasks that require coreferential reasoning.

Now in its second edition, this reader-friendly text offers a comprehensive treatment of concepts and knowledge related to teaching second language (L2) listening, with a particular emphasis on metacognition. This book advocates a learner-oriented approach to teaching listening that focuses on the process of learning to listen. It applies theories of metacognition and language comprehension to offer sound and reliable pedagogical models for developing learner listening inside and outside the classroom. To bridge theory and practice, the book provides teachers with many examples of research-inf...

The state of the art of RL methods for their possible use for different problems of NLP, focusing primarily on conversational systems, is reviewed, mainly due to their growing relevance.

This study modeled viral escape with machine learning algorithms originally developed for human natural language, and identified escape mutations as those that preserve viral infectivity but cause a virus to look different to the immune system, akin to word changes that preserve a sentence’s grammaticality but change its meaning.

"Innovations and Challenges in Language Learning Motivation provides a cutting-edge perspective on the latest challenges and innovations in language learning motivation, incorporating numerous examples and cases in mainstream psychology and in the field of second language acquisition. Drawing on over three decades of research experience as well as an extensive review of the latest psychological and SLA literature, Dörnyei provides an accessible overview of these cutting-edge areas and covers novel topics that have not yet been addressed in L2 motivation research, such as: fundamental theoreti...

Context Optimization (CoOp) is proposed, a simple approach specifically for adapting CLIP-like vision-language models for downstream image recognition that achieves superb domain generalization performance compared with the zero-shot model using hand-crafted prompts.

By reviewing the trainset in a crossed way, this work is able to distinguish easy examples from difficult ones, and arrange a curriculum for language models, and obtains significant and universal performance improvements on a wide range of NLU tasks.

A blueprint for the brain network underlying social L2 learning is provided, enabling the integration of neurocognitive bases with social cognition of second language while combining theories of language and memory with practical implications for the learning and teaching of a new language in adulthood.

The author revealed that teachers had had limited preparation experiences at both the TFLAS and ESL levels, where teachers had struggled with the intensity of the anxiety levels and the complexity of the material.

This paper proposes a multi-modal neural network that applies BI-GRU (Bidirectional Gated Recurrent Unit) to English word segmentation, and uses the CRF (Conditional Random Field) model to annotate sentences in sequence, effectively solving the long-distance dependency of text semantics, shortening network training and predicted time.

This work proposes a federated learning framework to obtain various types of image representations from different tasks, which are then fused together to form fine-grained image representations that are much more powerful than the original representations alone in individual tasks.

The year 2020 marked the 25th year since Bonny Norton published her influential TESOL Quarterly article, ‘Social identity, investment, and language learning’ (Norton Peirce, 1995) and the fifth year since we, Darvin and Norton (2015), co-authored ‘Identity and a model of investment in applied linguistics’ in the Annual Review of Applied Linguistics. From the time Norton's 1995 piece was published, investment and motivation have been conceptually imbricated and often collocated, as they hold up two different lenses to investigate the same reality: why learners choose to learn an additional lang...