Knowledge of Connectors as Cohesion in Text: A Comparative Study of Native English and ESL (English as a Second Language) Speakers

Abstract

Knowledge of connectors as linguistic devices for establishing intersentential coherence was examined in three experiments. Native English and English-as-a-Second-Language (ESL) speakers completed a rational close task in which they chose among instances of four types of connectors: additives, causal, adversative, and sequential responses. Verbal explanations of the correct responses indicated that both native English and ESL students were aware of prescriptive usage rules and the differences in function and meaning among the four types of connectors. Analyses of the incorrect responses indicated a general tendency to overuse causal, and to a lesser extent, additive connectors. Verbal response justifications for incorrect answers indicated that the majority of errors were due either to inaccurate processing of the test or to an inability to choose the connector that fit an inappropriately inferred relation. The results are discussed in terms of the processing demands of the various types of connectors and the influence of everyday usage of casual and additive connectors on how individuals use and understand such terms. Implications for improving the design of content domain texts are provided and instructional strategies for use with ESL students are suggested.

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Document Details

Document Type
Technical Report
Publication Date
Aug 18, 1989
Accession Number
ADA213269

Entities

People

  • J. Murray
  • Susan R. Goldman

Organizations

  • University of California, Santa Barbara

Tags

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • California
  • Classification
  • Cognition
  • Cognitive Science
  • Computer Science
  • Education
  • Engineering
  • English Language
  • Language
  • Linguistics
  • Military Research
  • Naval Training
  • New York
  • Psychology
  • Social Sciences
  • Students

Fields of Study

  • Linguistics

Readers

  • Computational Linguistics
  • Educational Psychology
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Translation