Research trends in task-based language teaching: A bibliometric analysis from 1985 to 2020

This study offers a bibliometric analysis of research trends in task-based language teaching (TBLT) from 1985 to 2020. The analysis covers research questions related to the publication trends, venues for publication, productive authors, highly cited articles and references and, more importantly, the most frequently explored TBLT-related topics and their developmental patterns across the past 35 years. Results showed that TBLT was still mostly approached from the traditional cognitive-interactionist and psycholinguistic perspectives with a focus on tasks, individuals (i.e., learners and teachers), task-related variables (e.g., task complexity and task repetition), task performance, and the resultant linguistic forms. While this field of research has witnessed a growing interest in learners’ individual differences and computer-mediated, technologies-assisted learning, a decreasing trend has been observed in topics related to error and recast. Implications for task-based research, pedagogy, and research methodologies are discussed.This study offers a bibliometric analysis of research trends in task-based language teaching (TBLT) from 1985 to 2020. The analysis covers research questions related to the publication trends, venues for publication, productive authors, highly cited articles and references and, more importantly, the most frequently explored TBLT-related topics and their developmental patterns across the past 35 years. Results showed that TBLT was still mostly approached from the traditional cognitive-interactionist and psycholinguistic perspectives with a focus on tasks, individuals (i.e., learners and teachers), task-related variables (e.g., task complexity and task repetition), task performance, and the resultant linguistic forms. While this field of research has witnessed a growing interest in learners’ individual differences and computer-mediated, technologies-assisted learning, a decreasing trend has been observed in topics related to error and recast. Implications for task-based research, pedagogy, and research methodologies are discussed

Between Political Tendentiousness and Mass Media: Popularizing Propaganda under Party Politics (1927-1937) ---A Case Study of Shenbao Free Talk

Through the study of Shenbao Free Talk, this dissertation showcases an urban underground left-wing propaganda during party politics of 1927-1937 that flowed between literature and journalism and between intellectual literary debates and writing experimentation on mass media. This study purposefully challenges the view of a static top-down propaganda mechanism that attached full agency to the CCP. As my project will show, the CCP had since its early phase in the 1920s and 1930s actively sought commercial media as a means to strengthen its appeal to the urban audiences. Such propaganda work in cities featured a gradual and indirect infiltration into the literate urban readers and was decidedly different from the straight-forward strategies of propagating didactic messages that were employed towards the rural peasants. My study of Free Talk 自由谈, literary column/supplement of the most long-lasting Chinese commercial newspaper Shenbao 申报, has demonstrated how an anti-GMD (Guomindang 国民党, or the Nationalist Party) public discourse developed and disseminated on mass media as an outcome of left-wing literary debates within and outside of China. The product of literary sarcasm based on news materials constituted a collective resistant discourse against the GMD as the newspaper readers entertained themselves by reading the sharp witty literary scoffing at the government-controlled news, which they encountered on daily basis. The resistant discourse emerged and matured through theoretical discussions and literary practice from the most talented Chinese left-wing writers, who certainly found their talent more fully employed in left-wing propaganda among urban readers than in the Party-directed propaganda to the rural peasants. To paraphrase in the words of Xi Jinping, what Free Talk had achieved was to conjure a “spiritual nourishment” to “organically integrate ideology, artistry and enjoyability” to the media for urban readers, who, like those in the contemporary age, were not to be easily won over with outright didacticism. In the 1930s Shanghai, it was first of all the witty metropolitan satires with renewed literary forms tinted with Western vanguardism, instead of political messages, that sailed into the hearts of the urban readers. In analyzing how the low-key left-wing propaganda had channeled through urban mass media much to the favor of the CCP, the dissertation examines three key elements of the process: Shenbao Free Talk, Chinese and international left-wing community, and the new rhetorical of the left-wing propaganda – zawen. Part I of the dissertation traces the institutional history of Free Talk – instead of seeing the newspaper as developing a Habermasian public sphere or cultivating the collective imagination of national modernity, as demonstrated in many secondary studies of early modern newspapers, I see Shenbao’s role as deepening the public involvement in political and social affairs through analysis of the paper’s editorial development. Part II studies the important bond of mass media and the CCP, a.k.a., the left-wing writers. By tracing literary theories/debates on the relation between journalism and literature and between politics and writing that travelled from Europe via Japan to China, I depict a cultural movement that aims to bridge Communist political act and literature featuring involvement of the entire international left-wing community at the same period – from mid 1920s to the 1930s. Part III examines zawen, the Chinese mass media counterpart of the international literary reportage and the signature Shenbao Free Talk rhetoric. I follow the seminal line of Lu Xun – the initiator of the genre – to demonstrate left-wing intellectuals’ creative efforts in packaging the political discourse to not only avoid censorship but also appeal to the urban public into political participation

Research on the Improvement of Calculation Method for the Interference Assembly of Locomotive Traction Gear

The interference assembly is the main method for the connection between the traction gear and the shaft. The selection of the interference plays a critical role in the design of the traction gear. The traditional method of the calculation of the interference of the traction gear oversimply the mathematical model. The error goes out of the acceptable range so that the old method is not suitable for the design of the web structure. In this paper we propose an improved algorithm for solving the interference of the traction gear by combining the classical elastic mechanics theory and the finite element segmentation technique. The results from our improved algorithm is compared with that from the traditional method and the finite element simulation data is compared with the experimental results. Both comparisons verified the rationality and the feasibility of our algorithm. Our research provides the theoretical reference significance and practical guiding value for the selection of the range of interference

A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects

Tracking humans that are interacting with the other subjects or environment remains unsolved in visual tracking, because the visibility of the human of interests in videos is unknown and might vary over time. In particular, it is still difficult for state-of-the-art human trackers to recover complete human trajectories in crowded scenes with frequent human interactions. In this work, we consider the visibility status of a subject as a fluent variable, whose change is mostly attributed to the subject's interaction with the surrounding, e.g., crossing behind another object, entering a building, or getting into a vehicle, etc. We introduce a Causal And-Or Graph (C-AOG) to represent the causal-effect relations between an object's visibility fluent and its activities, and develop a probabilistic graph model to jointly reason the visibility fluent change (e.g., from visible to invisible) and track humans in videos. We formulate this joint task as an iterative search of a feasible causal graph structure that enables fast search algorithm, e.g., dynamic programming method. We apply the proposed method on challenging video sequences to evaluate its capabilities of estimating visibility fluent changes of subjects and tracking subjects of interests over time. Results with comparisons demonstrate that our method outperforms the alternative trackers and can recover complete trajectories of humans in complicated scenarios with frequent human interactions.Comment: accepted by CVPR 201

Direction-aware Spatial Context Features for Shadow Detection

Shadow detection is a fundamental and challenging task, since it requires an understanding of global image semantics and there are various backgrounds around shadows. This paper presents a novel network for shadow detection by analyzing image context in a direction-aware manner. To achieve this, we first formulate the direction-aware attention mechanism in a spatial recurrent neural network (RNN) by introducing attention weights when aggregating spatial context features in the RNN. By learning these weights through training, we can recover direction-aware spatial context (DSC) for detecting shadows. This design is developed into the DSC module and embedded in a CNN to learn DSC features at different levels. Moreover, a weighted cross entropy loss is designed to make the training more effective. We employ two common shadow detection benchmark datasets and perform various experiments to evaluate our network. Experimental results show that our network outperforms state-of-the-art methods and achieves 97% accuracy and 38% reduction on balance error rate.Comment: Accepted for oral presentation in CVPR 2018. The journal version of this paper is arXiv:1805.0463