Multiple Intelligences as Predictors of Foreign Language Pragmatic Knowledge: The Case of Five Frequent English Speech Acts

Authors

1 University of Sistan and Baluchestan, Zahedan, Iran

2 Imam Khomeini International University, Qazvin, Iran

10.22132/tel.2020.107876

Abstract

Because of the important role of multiple intelligences (MIs) in learning a second/foreign langue (L2) as supported by the existing second language acquisition (SLA) literature, some pragmatic scholars have asked for studying their contribution to pragmatic competence (e.g., Taguchi & Roever, 2017). Accordingly, the present investigation has attempted to examine the relationship between L2 learners’ multiple intelligences and their speech-act pragmatic performance. A sample of 124 EFL students who were selected from an initial sample of 206 learners at two Iranian state universities based on their scores on the Michigan Test of English Language Proficiency (MTELP) took part in this study. The data collection procedure was done in two subsequent phases. First, McKenzie's (1999) multiple intelligences (MI) survey including 90 items was filled out by the participants. Then, a validated 50-item multiple-choice discourse completion test (MDCT) including five frequent English speech acts (requests, apologies, refusals, complaints, and compliments/compliment responses) was administered. Data analysis using multiple regression revealed that four of the intelligence including logical, interpersonal, verbal, and intrapersonal intelligences were significant predictors of L2 learners' speech-act pragmatic knowledge. Among these four intelligences, verbal intelligence was the strongest followed by interpersonal, intrapersonal, and logical intelligences. However, five other intelligences (i.e., naturalistic, musical, existential, visual, & kinesthetic intelligences were not significant predictors of L2 pragmatic performance). These findings can have some pedagogical implications for EFL teachers in helping their learners develop their speech-act pragmatic knowledge based on their MIs.   

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