Jill Jegerski · 2024
This handbook chapter provides an overview of research on input processing (IP) that has employed online (i.e., real time) methods, including self-paced reading, eye-tracking, event-related potentials (ERPs), and neuroimaging. Although online techniques are relatively new in research on IP, VanPatten’s theories have long emphasized the importance of investigative techniques that record data in real time. This overview includes the discussion of three issues that are currently prominent in this area: empirical indicators of learning during IP, strategies and pitfalls that characterize the processing of language learners, and the effects of instruction on online processing. Basic information regarding the four main research methods is also provided and the chapter concludes with some recommendations for practice and possible directions for future research on IP using online methods.
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Maha Abdelhaq (735574), Raed Alsaqour (735575), Shawkat Abdelhaq (735576) · Figshare · 2015
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Greenwich Academic Literature Archive (University of Greenwich) · 2013
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Alessandro Benati, Luciana Pedrazzini · Greenwich Academic Literature Archive (University of Greenwich) · 2013
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Alessandro Benati · Greenwich Academic Literature Archive (University of Greenwich) · 2012
Prof. Benati is an academic scholar in the area of Applied Linguistics and Second Language Studies. His research focuses on how second language learners process incoming linguistic information at input level. He has worked extensively with James Lee (University of New South Wales, Australia) on classroombased research measuring primary and secondary effects of processing instruction. Their most recent collaboration is Processing Instruction and Discourse (Continuum Publishing, 2010). He has also collaborated with Bill VanPatten (Michigan State University, USA) on a book on second language acquisition (Key Terms in Second Language Acquisition, Continuum Publishing, 2010).
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Yang, Han · ScienceDB · 2025
It contains the MCNP5 input file for the annular reactor and the data processing file for the neutron flux density distribution.
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Bilingual processing and acquisition · 2021
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Michael J. Leeser, Gregory D. Keating, Wynne Wong · Studies in bilingualism · 2020
Abstract In this chapter, we highlight Bill VanPatten’s numerous contributions to the fields of second language acquisition (SLA) and instructed second language acquisition (ISLA), and to the language teaching profession. We begin with an overview of his major professional achievements, followed by an exploration of his early work and the origins of his model of input processing. We underscore the significant contribution that his model of input processing makes to theory building in SLA and subsequently discuss his pioneering instructional innovation, processing instruction, along with the prolific body of research it has inspired. After briefly noting the importance of his work on acquisition and processing more broadly, we conclude with an overview of the individual chapters included in the volume.
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Подолкова, Світлана Віталіївна, Подолкова, Светлана Витальевна, Podolkova, Svitlana Vitaliivna et al. · Electronic Sumy State University Institutional Repository (Sumy State University) · 2008
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Кисельова, А.Г., Кисельов, Г.Д., Сергеєв, А.А. et al. · The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy · 2011
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Vance, M, Rosen, S, Coleman, M · UCL Discovery (University College London)
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BILL VANPATTEN · Multilingual Matters eBooks · 2008
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Vojtěch Vorel · Lecture notes in computer science · 2016
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Georg Northoff · Elsevier eBooks · 2024
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David Margulies, Galina Melman, Clifford E. Felder et al. · Journal of the American Chemical Society · 2004
We describe the design and function of a molecular logic system, by which a combinatorial recognition of the input signals is utilized to efficiently process chemically encoded information. Each chemical input can target simultaneously multiple domains on the same molecular platform, resulting in a unique combination of chemical states, each with its characteristic fluorescence output. Simple alteration of the input reagents changes the emitted logic pattern and enables it to perform different algebraic operations between two bits, solely in the fluorescence mode. This system exhibits parallelism in both its chemical inputs and light outputs.
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David Margulies (167855), Galina Melman (2055382), Clifford E. Felder (2509849) et al. · Figshare · 2016
We describe the design and function of a molecular logic system, by which a combinatorial recognition of the input signals is utilized to efficiently process chemically encoded information. Each chemical input can target simultaneously multiple domains on the same molecular platform, resulting in a unique combination of chemical states, each with its characteristic fluorescence output. Simple alteration of the input reagents changes the emitted logic pattern and enables it to perform different algebraic operations between two bits, solely in the fluorescence mode. This system exhibits parallelism in both its chemical inputs and light outputs.
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Alfonso Morales-Front, Joe Barcroft · 2024
Neurally inspired and gradient in nature, usage-based (UB) approaches to language acquistion in their different historical varieties—functionalism, connectionism, and emergentism as applied to language, the competition model, cognitive linguistics, and complexity theory as applied to language, among others—are well equipped to develop theory and conduct research on the role of input processing (IP) in language acquisition. This chaper focuses on what applications of UB perspectives have done and can do to advance our understanding of IP. The chapter reviews IP’s functional and connectionist roots, considers the extent to which research on IP is informed by UB perspectives, and highlights examples of areas in which research on IP and UB approaches are mutually informative. The chapter concludes by addressing instructional issues and potential future directions in this area of research.
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Yoshua Bengio, Paolo Frasconi · IEEE Transactions on Neural Networks · 1996
We consider problems of sequence processing and propose a solution based on a discrete-state model in order to represent past context. We introduce a recurrent connectionist architecture having a modular structure that associates a subnetwork to each state. The model has a statistical interpretation we call input-output hidden Markov model (IOHMM). It can be trained by the estimation-maximization (EM) or generalized EM (GEM) algorithms, considering state trajectories as missing data, which decouples temporal credit assignment and actual parameter estimation. The model presents similarities to hidden Markov models (HMMs), but allows us to map input sequences to output sequences, using the same processing style as recurrent neural networks. IOHMMs are trained using a more discriminant learning paradigm than HMMs, while potentially taking advantage of the EM algorithm. We demonstrate that IOHMMs are well suited for solving grammatical inference problems on a benchmark problem. Experimental results are presented for the seven Tomita grammars, showing that these adaptive models can attain excellent generalization.
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S. Mina, B. Prazak, A. Hochgatterer · 2008
In the field of assistive technology is a significant variety of special input devices are available. There are dozens of different switches on the market but in some cases none of them are an appropriate solution either for the user or for the care
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Bill VanPatten · 2003
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