scholarly journals A Social Network Analysis of Knowledge Infrastructure in the Second Language Acquisition Domain

2017 ◽  
Vol 34 (null) ◽  
pp. 125-160
Author(s):  
Jang Hye Zin ◽  
Gohar Feroz Khan ◽  
WOODJACOB GRAEME
Keyword(s):  
Second Language ◽  
Social Network ◽  
Social Network Analysis ◽  
Second Language Acquisition ◽  
Language Acquisition ◽  
Network Analysis ◽  
Knowledge Infrastructure ◽  
Analysis Of Knowledge

Recent Contributions of Data Mining to Language Learning Research

2019 ◽  
Vol 39 ◽  
pp. 93-112 ◽  
Author(s):  
Mark Warschauer ◽  
Soobin Yim ◽  
Hansol Lee ◽  
Binbin Zheng
Keyword(s):  
Data Mining ◽  
Second Language ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Text Mining ◽  
Language Learning ◽  
Second Language Learning ◽  
Empirical Support ◽  
Learning Research

AbstractThis paper will review the role of data mining in research on second language learning. Following a general introduction to the topic, three areas of data mining research will be summarized—clustering techniques, text-mining, and social network analysis—with examples from both the broader field and studies conducted by the authors. The application of data mining in second language learning research is relatively new, and more theoretical and empirical support is needed in the appropriate collection, use, and interpretation of data for specific research and pedagogical objectives. The three examples that we introduce illustrate how new data sources accessible in online environments can be analyzed to better understand the optimal instructional context for corpus-based vocabulary learning (clustering technique), characteristics and patterns of collaborative written interaction using Google Docs (text mining and visualizations), and issues of access and community in computer-mediated discussion (social network analysis). Implications of these new techniques for L2 research will be discussed.

Use and Methods of Social Network Analysis in Knowledge Management

2011 ◽  
pp. 565-574 ◽  
Author(s):  
Tobias Müller-Prothmann
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Theoretical Analysis ◽  
Knowledge Flows ◽  
Knowledge Networks ◽  
Personal Networks ◽  
Informal Communities ◽  
Analysis Of Knowledge

Whilst the primary importance of informal communities of practice and knowledge networks in innovation and knowledge management is widely accepted (see Armbrecht et al., 2001; Brown & Duguid, 1991; Collinson & Gregson, 2003; Jain & Triandis, 1990; Lesser, 2001; Liyanage, Greenfied & Don, 1999; Nahapiet & Ghoshal, 1998; Nohria & Eccles, 1992; Wenger, 1999; Zanfei, 2000), there is less agreement on the most appropriate method for their empirical study and theoretical analysis. In this article it is argued that social network analysis (SNA) is a highly effective tool for the analysis of knowledge networks, as well as for the identification and implementation of practical methods in knowledge management and innovation. Social network analysis is a sociological method to undertake empirical analysis of the structural patterns of social relationships in networks (see, e.g., Scott, 1991; Wasserman & Faust, 1994; Wellman & Berkowitz, 1988). This article aims at demonstrating how it can be used to identify, visualize, and analyze the informal personal networks that exist within and between organizations according to structure, content, and context of knowledge flows. It will explore the benefits of social network analysis as a strategic tool on the example of expert localization and knowledge transfer, and also point to the limits of the method.

Use and Methods of Social Network Analysis in Knowledge Management

2011 ◽  
pp. 1096-1106 ◽  
Author(s):  
Tobias Muller-Prothmann
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Theoretical Analysis ◽  
Knowledge Flows ◽  
Knowledge Networks ◽  
Personal Networks ◽  
Informal Communities ◽  
Analysis Of Knowledge

Whilst the primary importance of informal communities of practice and knowledge networks in innovation and knowledge management is widely accepted (see Armbrecht et al., 2001; Brown & Duguid, 1991; Collinson & Gregson, 2003; Jain & Triandis, 1990; Lesser, 2001; Liyanage, Greenfied & Don, 1999; Nahapiet & Ghoshal, 1998; Nohria & Eccles, 1992; Wenger, 1999; Zanfei, 2000), there is less agreement on the most appropriate method for their empirical study and theoretical analysis. In this article it is argued that social network analysis (SNA) is a highly effective tool for the analysis of knowledge networks, as well as for the identification and implementation of practical methods in knowledge management and innovation. Social network analysis is a sociological method to undertake empirical analysis of the structural patterns of social relationships in networks (see, e.g., Scott, 1991; Wasserman & Faust, 1994; Wellman & Berkowitz, 1988). This article aims at demonstrating how it can be used to identify, visualize, and analyze the informal personal networks that exist within and between organizations according to structure, content, and context of knowledge flows. It will explore the benefits of social network analysis as a strategic tool on the example of expert localization and knowledge transfer, and also point to the limits of the method.

Analysis and Control in the Development of Second Language Proficiency

1994 ◽  
Vol 16 (2) ◽  
pp. 157-168 ◽  
Author(s):  
Ellen Bialystok
Keyword(s):  
Second Language ◽  
Second Language Acquisition ◽  
Language Acquisition ◽  
Language Learning ◽  
Cognitive Processing ◽  
Language Proficiency ◽  
Cognitive Framework ◽  
Starting Point ◽  
And Control ◽  
Analysis Of Knowledge

This paper describes a cognitive framework for explaining the acquisition and use of a second language. The framework is based on the identification of two cognitive processing components, called analysis of knowledge and control of processing, that jointly function to develop proficiency in the language. The framework is explained briefly and then applied to five issues in second language acquisition: the similarity of first and second language learning, the starting point for second language acquisition, consciousness, variability, and instruction.

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