The architecture of the mental lexicon and the selection of lexical nodes
Main Article Content
Abstract
This study presents the architecture of the mental lexicon of third language learners by focusing on three representation levels: letter, word and language. In particular, this analysis attempts to examine the extent of the influence of the first and second languages known by bilingual learners of English. The study is guided by Dijkstra’s (2003) Multilingual Interactive Activation (MIA) model, and the hypothesis of the language selective or language nonselective access of third language learners is tested. The method involved in this analysis is the word translation task as a tool for investigating the organization of the mental lexicon. The results obtained as a result of the translation task claim that trilingual speakers can operate with three languages during the process of learning.
Keywords: multilingual processing, mental lexicon, language typology.
Downloads
Article Details
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
References
Bertalanffy, L., (1968).General system theory : Foundations, Development, Applications, NY.
Brewer, Gene A., (2010), Public service motivation and performance. In Walker R.M.,Boyne,G. Brewer, G. A., Public management and performance. Cambridge University Press, pp. 152-177
Dubnick, M. (2005).Accountability and the promise of performance : In Search of the Mechanisms. Public Performance & Management Review 28(3) , pp 376-417.
Final Report of Invalsi 2011-12 http://www.invalsi.it/snv2012/documenti/Rapporti/Rapporto_rilevazione_apprendimenti_2012.pdf
Gupta, B.B. ,Agrawal, P.K. , Joshi, R.C., Misra, M., (2011).Estimating Strength of a DDoS Attack Using Multiple Regression Analysis. Springer, 33:280-289.
Hair, J. F., Rolph E.Anderson, Tatham, R. L., Black W. C., (1995). Multivariate Data Analysis ,(4th ed.) Upper Saddle River, NJ: Prentice Hall.
Horn, J.L.,( 1965).A rationale and test for the number of factors in factor analysis , Psychometrika, 30:179–185.
Jensen G. E. (1954).The school as a social system.Educational Research Bulletin. Taylor & Francis ,33( 2), pp. 38-46
Jolliffe, I.T.( 2002). Principal Component Analysis.Second Edition, Springer,
Kaiser, H. F., (1960),The application of electronic computers to factor analysis, Educational and Psychological Measurement, 20:141-151.
Kim,S. (2005). Individual-Level Factors and Organizational Performance in Government Organizations. Journal of Public Administration Research and Theory, . 15( 2),pp245–261,
T. Parsons, The Social System, New York, Free Press,( 1951), p. 107
Van Dooren, W., Bouckaert G. and Halligan J. Performance management in the public sector (2015), Routledge
Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41, 321-327