Systematizing Teacher Development:A Review of Foreign Language Teacher Learning

Foreign language teaching practice is developing rapidly,but research on foreign language teacher learning is currently relatively fragmented and unstructured.The book Foreign Language Teacher Learning,written by Professor Kang Yan from Capital Normal University,published in September 2022,makes a systematic introduction to foreign language teacher learning,which to some extent makes up for this shortcoming.Her book presents the lineage of foreign language teacher learning research at home and abroad,analyzes both theoretical and practical aspects,reviews the cuttingedge research results,and foresees the future development trend,painting a complete research picture for researchers in the field of foreign language teaching and teacher education as well as front-line teachers interested in foreign language teacher learning.This is an important inspiration for conducting foreign language teacher learning research in the future.And this paper makes a review of the book from aspects such as its content,major characteristics,contributions and limitations.

Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements.Researchers are exploring machine learning to predict software bugs,but a more precise and general approach is needed.Accurate bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning methods.However,these studies are not generalized and efficient when extended to other datasets.Therefore,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems.The methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a model.Four National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were combined.It reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

Recent Advances on Deep Learning for Sign Language Recognition

Sign language,a visual-gestural language used by the deaf and hard-of-hearing community,plays a crucial role in facilitating communication and promoting inclusivity.Sign language recognition(SLR),the process of automatically recognizing and interpreting sign language gestures,has gained significant attention in recent years due to its potential to bridge the communication gap between the hearing impaired and the hearing world.The emergence and continuous development of deep learning techniques have provided inspiration and momentum for advancing SLR.This paper presents a comprehensive and up-to-date analysis of the advancements,challenges,and opportunities in deep learning-based sign language recognition,focusing on the past five years of research.We explore various aspects of SLR,including sign data acquisition technologies,sign language datasets,evaluation methods,and different types of neural networks.Convolutional Neural Networks(CNN)and Recurrent Neural Networks(RNN)have shown promising results in fingerspelling and isolated sign recognition.However,the continuous nature of sign language poses challenges,leading to the exploration of advanced neural network models such as the Transformer model for continuous sign language recognition(CSLR).Despite significant advancements,several challenges remain in the field of SLR.These challenges include expanding sign language datasets,achieving user independence in recognition systems,exploring different input modalities,effectively fusing features,modeling co-articulation,and improving semantic and syntactic understanding.Additionally,developing lightweight network architectures for mobile applications is crucial for practical implementation.By addressing these challenges,we can further advance the field of deep learning for sign language recognition and improve communication for the hearing-impaired community.

Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiveness of the models. The research findings reveal that RNN surpasses CNN in Urdu sentiment analysis,gaining a significantly higher accuracy rate of 91%. This result accentuates the exceptional performance of RNN,solidifying its status as a compelling option for conducting sentiment analysis tasks in the Urdu language.

Let’s Talk LGBTQIA+:Strategies and Activities for Teaching Diversity and Inclusion in the Foreign Language Classroom at the College Level

In this presentation,the author explores strategies and activities that create a welcoming and nurturing environment for LGBTQIA+foreign language students at the college level in the United States.Indeed,as it is commonly stated,there is a clear lack of visibility,acceptance/tolerance,and inclusion of LGBTQIA+voices(active and proactive)in foreign language teaching and learning(pedagogical material as well as in-class attitudes and delivery).The reasons for this deficiency are diverse since they cover not only outward discrimination against and/or indifference(passive-aggressive behavior)toward the LGBTQIA+community and its plight,but they also illustrate the sheer,physical inexistence of quality material that can be used to create,present,and foster a welcoming and all-encompassing classroom environment that addresses the diverse spectrum of the LGBTQIA+community while its members try to learn a foreign language and(positively)negotiate how to express their very identity in their new language of choice.Moreover,the scant material that is available in the United States as well as in other Western countries where the LGBTQIA+community by and large is accepted-at least from the legal point of view-hardly represents and covers the subject matter in a satisfactory way.To address this gap,the author will provide some examples in European Portuguese(EP)and Italian(IT),followed by a courtesy translation in English,to illustrate some positive activities and strategies for including LGBTQIA+-related subject matter in the foreign language classroom at the college level.It is his desire that instructors of other foreign languages duplicate in their respective vernaculars the strategies and activities herein presented in order to create a welcoming and safe classroom environment that embraces the LGBTQIA+community as it goes through the enjoyable journey of learning a new language and culture.

An Empirical Study on Students’Evaluation of Moral Education in Foreign Language Education in China

Students’evaluation of moral education is of great significance for improving the quality of teaching.Through a survey of 2715 undergraduates majoring in foreign languages,this paper analyzes their evaluation of the moral education.Findings show that students speak highly of teachers’competence in moral education,teaching methods and the integration of moral education in the textbooks,but not in the course assessment and the overall effect of moral education.Suggestions were proposed accordingly to improve moral education of foreign language education in China.

The impact of ChatGPT on foreign language teaching and learning: Opportunities in education and research

The revolutionary online application ChatGPT has brought immense concerns to the education field.Foreign language teachers being some of those most reliant on writing assessments were among the most anxious,exacerbated by the extensive media coverage about the much-fantasized functionality of the chatbot.Hence,the article starts by elucidating the mechanisms,functions and common misconceptions about ChatGPT.Issues and risks associated with its usage are discussed,followed by an in-depth discussion of how the chatbot can be harnessed by learners and teachers.It is argued that ChatGPT offers major opportunities for teachers and education institutes to improve second/foreign language teaching and assessments,which similarly provided researchers with an array of research opportunities,especially towards a more personalized learning experience.

Research Nexus and Implications of Learner Identity in Foreign Language Education

One of the most obvious markers of an individual’s identity is their language.However,in some ways,the relationship between identity and language acquisition seems to be missed.In fact,a lot of studies have shown that identity may influence the reasons behind language acquisition,especially in bilingual or multilingual societies.Learning English can provide EFL(English as a Foreign Language)students with a good sense of identity and encourage them to practice their agency,which can improve learning efficiency and effectiveness.This paper examines how the efficacy and results of language learning are influenced by the learner’s identity.

Research on Foreign Language Talent Cultivation Mode Based on the Concept of Language Security

Language security is an important part of national security,and in the current complex international environment,the issue of language security is becoming more and more prominent and has become an unignorable part of national security strategy.As the bridge and link of international communication,foreign language talents’language skills and the level of national security awareness directly affect our country’s international image and the effect of international communication.Therefore,the establishment of a foreign language talent cultivation mode based on the concept of language security is not only an important way to improve the quality of foreign language education but also a realistic need to safeguard national security and promote international exchanges.Starting from the influence of the language security concept on foreign language talent cultivation,this paper analyzes the foreign language talent cultivation mode based on the language security concept,with a view to providing new ideas and methods for the development of foreign language education.

Research on the Status Quo and Improvement Needs of Foreign Language Teachers’ Teaching Competence in Curriculum-Based Ideological Education in Xinjiang Colleges and Universities

This study investigated the status quo and further improvement needs of foreign language teachers’teaching competence in curriculum-based ideological education(CIE)in Xinjiang colleges and universities.The results show that the teachers’teaching competence in CIE is generally good,with the“cultivating quality”being the highest and the“scientific research quality”the lowest;there still exist several problems,such as teachers’lack of theoretical knowledge in CIE,lack of teaching resources,and insufficient abilities in teaching design and research.It is hoped that with the support and efforts from university administrations,teachers can improve their teaching competence in CIE through various approaches adopted and multiple measures taken,thus optimizing their teaching effectiveness,promoting the construction of CIE in Xinjiang colleges and universities in the new era,and contributing to Xinjiang’s high-quality development.

Positive effects of native language in the foreign language learning and teaching

Native language has been rejected for a long time in the foreign language class, which results from a misunderstanding to native language transfer by most teachers. Actually, it is an effective learning strategy to complete the communication task under the help of native language, which should be acknowledged. Using native language to explain specific words or grammar rules can take advantage of the limited class-time efficiently and increase the class efficiency; using native language to discuss teaching method and solve the problems for the students can promote their enthusiasm. In these specific teaching processes, native language is an important teaching resource. Instances identify that native language has positive effects in the foreign language learning and teaching and it should have its own standpoint.

Is There an Optimum Age For Foreign Language Learning?

Age is one of the factors which influnce foreign language learning, but not the most important one. Comparision on the effect of foreign language learning between adults and children cannot rely merely on age. So the question of an optimum age for foreign language learning is not a simple one which is only related to age. There are different optimum ages for different aims and demands of learning foreign language.

Autonomy and Foreign Language Learning

Independent language learning is one aspect of what the research literature calls learner autonomy, in other words, the ability and willingness of learners to study foreign languages on their own. This article illustrates the strategies I used to design, carry out and sustain my independent language learning project.

Analysis of the Current Situation of Spoken Foreign Language Teaching and Learning in Ethnic Regions

With the enhancement of friendship between different nations, foreign language learning has become more and more important. In particular, spoken language is playing a vital role in foreign language learning and practice. In order to improve foreign language teaching and learning proficiency in ethnic regions, the author analyses the current situation of spoken foreign language teaching and learning in ethnic regions and suggests some ways to solve the existing problems.

A Study on Left-behind Junior Students'Foreign Language Learning Anxiety

Since the 1960s, foreign language educators and researchers home and abroad have started to pay attention to the influence of the affective variables including language learning anxiety on foreign language learning. This thesis tried to find out the factors that may influence the foreign language learning anxiety level of left-behind students and put forward ways to help lower down the foreign language learning anxiety level of the left-behind junior middle school students.

Researches on Foreign Language Learning Anxiety

Foreign language anxiety is one of the factors of affecting foreign language achievement. It is negatively associated with language skill learning. This article will show some researches on foreign language anxiety from certain aspects.

Causes of Gender Differences in Foreign Language Learning

This essay,in light of recent studies in foreign language teaching and learning by gender,try to explore the causes why boys are underachieved in language learning from a world-wide perspective and accordingly identify what clues for good practice already exist and to offer some tentative suggestions to help the"failing boys".

A Research on the Influence of Motivation And Attitude on Foreign Language Learning

There are various affective factors which have a profound influence on foreign language learning,such as aptitude,social-psychological factors and emotion,etc,among which the social-psychological factors,namely,motivation and attitude,are the focus ofthis thesis.This thesis aims to analyze the role played by motivation and attitude in foreign language learning.

Cultivation of Autonomous Learning Ability and Intercultural Communication Competence in Foreign Language Teaching

Learner Autonomy has been a hot topic in foreign language learning and teaching since 1960s,especially in relation to life-long skills.As the globalization develops,intercultural communication becomes more and more significant for college students.This essay attempts to explore main approaches to cultivate and improve students' autonomous learning ability and intercultural communication competence in foreign language teaching.

A Light-Weight Deep Learning-Based Architecture for Sign Language Classification

With advancements in computing powers and the overall quality of images captured on everyday cameras,a much wider range of possibilities has opened in various scenarios.This fact has several implications for deaf and dumb people as they have a chance to communicate with a greater number of people much easier.More than ever before,there is a plethora of info about sign language usage in the real world.Sign languages,and by extension the datasets available,are of two forms,isolated sign language and continuous sign language.The main difference between the two types is that in isolated sign language,the hand signs cover individual letters of the alphabet.In continuous sign language,entire words’hand signs are used.This paper will explore a novel deep learning architecture that will use recently published large pre-trained image models to quickly and accurately recognize the alphabets in the American Sign Language(ASL).The study will focus on isolated sign language to demonstrate that it is possible to achieve a high level of classification accuracy on the data,thereby showing that interpreters can be implemented in the real world.The newly proposed Mobile-NetV2 architecture serves as the backbone of this study.It is designed to run on end devices like mobile phones and infer signals(what does it infer)from images in a relatively short amount of time.With the proposed architecture in this paper,the classification accuracy of 98.77%in the Indian Sign Language(ISL)and American Sign Language(ASL)is achieved,outperforming the existing state-of-the-art systems.