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Seyed Mohammad Hosseini

Seyed Mohammad Hosseini

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0003-3144-6593
Education: PhD.
ScopusId: 57930611200
Faculty: Literature and Languages
Address: Arak University
Phone:

Research

Title
The Effect of Teaching Conditional Sentences (Type II), Active and Passive Voice, and Past Perfect Tense on Iranian EFL Learners Using Langacker's Cognitive Grammar
Type
Thesis
Keywords
Cognitive grammar, Traditional grammar teaching, grammar teaching, cognitive linguistics, conditional sentences, passive voice, past perfect tense
Year
2021
Researchers Majid Amerian(PrimaryAdvisor)، Seyed Mohammad Hosseini(Advisor)

Abstract

Due to its internal complexity, mastering grammar rules and explanations in the traditional approaches has represented a great challenge for EFL learners. The aim of this thesis is to address some of the existing problems of presenting grammar to EFL learners in the traditional approaches toward grammar by introducing and investigating the applicability of the Cognitive Grammar (CG) approach. This quasi-experimental study uses Langacker’s Cognitive Grammar as the basis of grammar instruction and uses the assumptions and insights of CG (e.g. meaningfulness of every grammatical unit, use of visual representation for grammatical explanations, etc.) to employ in pedagogical situations. This study compares the effects of CG instructions to those taught by traditional grammar rules in two groups. The results indicate the relatively high effectiveness of both instructional options in reinforcing the use of target structures (conditional sentences, passive structures, and past perfect tense) in both groups with CG instruction being more successful than the traditional instructions on all three target structures. However, the differences between the two groups only showed a statistically significant difference in results in the case of past perfect tense and only showed a subtle better performance of CG group on other grammatical items, a possible explanation for achieving such results can be that CG insights need more modifications and adjustments to fit in educational situations.