2,075 research outputs found

    Knowledge Tracing in Sequential Learning of Inflected Vocabulary

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    Topic Modeling and Text Analysis for Qualitative Policy Research

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    This paper contributes to a critical methodological discussion that has direct ramifications for policy studies: how computational methods can be concretely incorporated into existing processes of textual analysis and interpretation without compromising scientific integrity. We focus on the computational method of topic modeling and investigate how it interacts with two larger families of qualitative methods: content and classification methods characterized by interest in words as communication units and discourse and representation methods characterized by interest in the meaning of communicative acts. Based on analysis of recent academic publications that have used topic modeling for textual analysis, our findings show that different mixed‐method research designs are appropriate when combining topic modeling with the two groups of methods. Our main concluding argument is that topic modeling enables scholars to apply policy theories and concepts to much larger sets of data. That said, the use of computational methods requires genuine understanding of these techniques to obtain substantially meaningful results. We encourage policy scholars to reflect carefully on methodological issues, and offer a simple heuristic to help identify and address critical points when designing a study using topic modeling.Peer reviewe

    Computational Intelligence and Human- Computer Interaction: Modern Methods and Applications

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    The present book contains all of the articles that were accepted and published in the Special Issue of MDPI’s journal Mathematics titled "Computational Intelligence and Human–Computer Interaction: Modern Methods and Applications". This Special Issue covered a wide range of topics connected to the theory and application of different computational intelligence techniques to the domain of human–computer interaction, such as automatic speech recognition, speech processing and analysis, virtual reality, emotion-aware applications, digital storytelling, natural language processing, smart cars and devices, and online learning. We hope that this book will be interesting and useful for those working in various areas of artificial intelligence, human–computer interaction, and software engineering as well as for those who are interested in how these domains are connected in real-life situations

    Linguistic development and education

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    Classifying hand configurations in Nederlandse Gebarentaal (Sign Language of the Netherlands)

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    This study investigates the morphological and morphosyntactic characteristics of hand configurations in signs, particularly in Nederlandse Gebarentaal (NGT). The literature on sign languages in general acknowledges that hand configurations can function as morphemes, more specifically as classifiers , in a subset of signs: verbs expressing the motion, location, and existence of referents (VELMs). These verbs are considered the output of productive sign formation processes. In contrast, other signs in which similar hand configurations appear ( iconic or motivated signs) have been considered to be lexicalized signs, not involving productive processes. This research report shows that meaningful hand configurations have (at least) two very different functions in the grammar of NGT (and presumably in other sign languages, too). First, they are agreement markers on VELMs, and hence are functional elements. Second, they are roots in motivated signs, and thus lexical elements. The latter signs are analysed as root compounds and are formed from various roots by productive processes. The similarities in surface form and differences in morphosyntactic characteristics observed in comparison of VELMs and root compounds are attributed to their different structures and to the sign language interface between grammar and phonetic for

    An Experimental Study of the Effect of Specialized Reading Treatment on the Reading Achievement of Second Grade Students

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    Many pupils do not achieve success in reading by the traditional instruction. A few can be helped by remedial classes offering individual children help for specific difficulties. In this study a method was explored that suggests a plan that can be used in a regular classroom to benefit all low-achieving students

    Black English and Culture Meet the Mainstream Classroom

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    Learning English can often be a critical factor in people’s lives, and the choice to disengage from learning out of sheer frustration can have devastating psychological and social effects for people who need to acquire English in order to be able to fulfill academic, personal and professional goals. While I was not able to find statistics on a global level, it is easy to believe that English language learners do disengage frequently. This is most obvious in the United States where the Standard English (SE) model of teaching black children has resulted in a high level of disengagement with learning and a nationally disproportionate low level of academic success among people in black communities where there is a difference between the dialect of their spoken language and the SE dialect they encounter in school. In this paper, I attempt to show how the development of the black English (BE) language, and the issue of black literacy in America, reflects how culture and language are forged by real life experience. Learning a second language is similarly a real life experience. An awareness of this dynamic should be used to inform language teaching methods, if we are to make best use of learner’s time, money and effort, in learning a second language. By focusing on the development of BE, and the subsequent literacy issues, I hope to illuminate how language teaching methods and practices benefit from using a learner’s culture and language

    Recent Trends in Computational Intelligence

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    Traditional models struggle to cope with complexity, noise, and the existence of a changing environment, while Computational Intelligence (CI) offers solutions to complicated problems as well as reverse problems. The main feature of CI is adaptability, spanning the fields of machine learning and computational neuroscience. CI also comprises biologically-inspired technologies such as the intellect of swarm as part of evolutionary computation and encompassing wider areas such as image processing, data collection, and natural language processing. This book aims to discuss the usage of CI for optimal solving of various applications proving its wide reach and relevance. Bounding of optimization methods and data mining strategies make a strong and reliable prediction tool for handling real-life applications

    The adult basic skills ESOL curriculum. Draft

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