The Application of Task-based Language Learning in English Teaching

Task-based Language Teaching(TBLT) proved to be an influential teaching approach in second language acquisition recent years. Yet, TBLT came into being with certain culture background, it can't be applied randomly and mechanically. This paper precisely introduces the task-based language learning and reviews the literature on the basic pedagogical theories of TBLT,then briefly introduces the framework of Willis for TBLT, and takes a small size group of middle school students as an example.It mainly aims to discuss the application of Task-based language learning in the classroom and through analyzing the disadvantages of task-based language teaching to find out a successful approach to implement TBLT.

Autonomous and Incidental Learning of Vocabulary Through Task-based Language Teaching

This study mainly discussed the effects of three tasks of translating authentic business report on L2 vocabulary learning.160 students were chosen from different majors by a pre-task proficiency test.The findings revealed that task 3 was the optimum task in vo-cabulary gain and direct vocabulary learning had a more facilitated power than incidental vocabulary learning in this translation task forthe learners with the lowest level of vocabulary.This study also suggested that the caution of need and evaluation needed to be adjustedand paid for the learners with the lowest vocabulary level.

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.

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.

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.

Experienced Language Learners' Perceptions of Task-based Language Teaching-A Case Study of Guangdong University of Foreign Studies in China

The aim of this dissertation was to investigate the attitudes and opinions from experienced language learners towards task-based language teaching(TBLT), a popular and widely adopted teaching approach, in the context of Guangdong University of Foreign Studies(GDUFS) in China and provide suggestion for making improvements in language teaching.

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.

Meta-cognitive Strategy Training and the Development of Learners＇ Autonomy in Language Learning

As the ultimate goal of education, autonomy in language learning has aroused a lot of attention from scholars at home and abroad. While in universities of China, students do not have strong autonomy in English language learning. The author tries to adopt specific meta-cognitive strategies to facilitate students＇ autonomy in learning by improving learners＇ capacities in study planning or management, monitoring and evaluating in learning to raise their consciousness and ability in autonomy, and lay a foundation for life-long learning.

混合方法中的有声思维与刺激性回忆——基于Language Learning外刊文献中的口头报告数据

有声思维和刺激性回忆作为数据采集方式和数据分析对象已被融入应用语言学混合研究当中,其在混合设计中作为质化分析对象的情况仍然占有较大的比重。虽然我们可以像分析语篇那样对口头报告的内容进行质化分析,但其可被量化的特征也尤为突出。在混合设计中,同步报告与量化分析、追溯报告与质化分析之间具有较强的关联性,而其在实验方法中,作为质化分析数据的情况更多。在口头报告仅用于质化分析的文献中,口头报告体现出了更强的传统内省数据的特征,并多被设计为混合研究中唯一或核心的质化分析对象。在口头报告仅用于量化分析的文献中,口头报告是两种或多种量化数据采集方式之中的一种。在口头报告用于混合设计时,质化分析往往只起到了解释或补充的作用,而口头报告构成的是核心或重要的量化数据来源,更多地体现出其在量化数据采集和分析中的作用。

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.

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.

On the Application of Task-based Language Teaching Approach to English Phonetic Teaching

Task-based language teaching approach(TBLTA), which lays stress on "learning by doing", gained increasing popularity in English teaching in recent years. The design of phonetic teaching calls for more emphasis from English educators since it is one of the basic rounds of English teaching. This paper made a trial on the utilization of TBLTA in the English phonetic teaching context and designed a TBLTA model for English phonetic teaching based on discussions about model and merits of TBLTA.

Task-Based Approach in Language Teaching

During recent years,some notions about tasks have been considered as the major part of analysis in different teaching approaches and teachers are being more interested in the use of taskbased approach both in foreign and in second language teaching.The main goal of this article is to introduce and discuss some major principles of task-based language teaching and indicates how teachers can apply them in their curriculum.

Language teachers should develop students' vocabulary learning skills

It is self-evident that vocabulary work is the most essential and necessary task in foreign language accepition. English language teachers should develop students’ vocabulary learning skills.

On the Role of Noticing in Second Language Acquisition and Learning

Apparent discrepancy exists between Schmidt's Noticing Hypothesis and Krashen's Input Hypothesis. Whilst Krashen highlights the importance of comprehensible input and asserts that language is acquired unconciously, the notion of conscious learning has gained wide support from Schmidt and other researchers. They argue that noticing enhances second language development as one crucial level of consciousness. By reviewing the theoretical constructs that underlie the role of noticing, this paper aims to justify the role of noticing as one crucial level of consciousness in enhancing second language learning.

Language Awareness and Second Language Learning:A Critical Review

Beginning with the history,definition and levels of Language Awareness,this paper reviewed and analyzed two views:1) Language awareness is one necessary condition in language learning,or 2) Language learning can be achieved without Language Awareness.It pointed out the problems existing in these studies:1) Limitations in sample choice,concerning the adult beginning learners instead of the learners in different learning stages;2) Limitations in methodology,preferring cross-sectional researches to longitudinal case studies;and 3) Limitations in material choice,focusing on "word" level rather than other levels or aspects of language learning.This paper argued that language awareness is dynamic in the whole process of language learning.

Mental Image and Its Application in Language Learning

Mental image has often been believed to play a very large, even pivotal, role in both memory and motivation. However, with the lateralization of the brain, the treasure of mental image, a function dominated by the right hemisphere of the brain, is often neglected in the realm of language learning, a function dominated by the left-brain. Thus, educational systems have largely, if not exclusively, catered to the logic, analytical left-brain, and unwisely phase out the imagery elements of the right brain. In this paper, therefore, the author argues that mental image should not be a property confined to children, who have more imagination. This kind of human treasure should be appropriately deployed through the process of language teaching and learning, for it can provide a strong impetus for language learning, thus making language-learning process more enjoyable and beneficial.

A Review of Language Learning Strategy

This paper presents definitions of language learning strategies,discusses four classifications of language learning strategies,focuseson research on language learning strategies,and it aimsto provide areview oflanguage learning strategy.

Review on Learner Belief about Second Language Learning

Learner belief is attracting growing attention since it is regarded as one element of individual difference which account for learners' different achievements in second language learning. This article gives a review o studies of learner belief about second language learning concerning its properties, classifications, and majo approaches to investigation. Based on the review, the importance of the research in the field is emphasized.