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Effectiveness of force dynamic explanations of English causative verbs and the role of imagery

Bibliographic Data

ID12197456
AuthorsC Mueller (0000-0002-3369-9124, Fuji Women's University, corresponding author), Charles M Mueller (Fuji Women's University), Yasuhiro Tsushima (Fuji Women's University)
Year2019
Volume30
Issue3
Pages439-466
Publication date2019-06-25
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCognitive Linguistics (JOURNAL)
Journal identifiersISSN: 0936-5907 • E-ISSN: 1613-3641
PublisherDe Gruyter Mouton (PUBLISHER • DE)
DOI10.1515/cog-2017-0093
OpenAlexW2954278173
LanguageEN
Citations received2
References cited28

The current study examines the effectiveness of a CL-based force dynamic (FD) lesson relative to a more conventional approach that seeks to convey the target semantics through corresponding L1 forms. Exp. 1 ( N =67) examined Japanese EFL students’ acquisition of the English verbs force, get, have, help, let, make , and prevent , comparing the effectiveness of force dynamic explanations with dynamic diagrams and a translation-based approach. Both groups showed significant learning on both the posttest and delayed posttest, but the FD group’s greater gains over the conventional instruction on both the posttest and delayed posttest did not reach significance. Exp. 2 ( N =97) replicated most of the Exp. 1 conditions but with a slightly altered instructional format to ensure participant’s focus on force dynamic relationships. The FD group’s greater gains on a posttest given three weeks following instruction fell short of statistical significance. Exp. 3 ( N =54) compared the effectiveness of a FD lesson using dynamic images with a lesson without such images and found no significant differences between the groups. The three experiments demonstrate that CL-based instruction on force dynamics provides a viable alternative to conventional instruction in which target semantics are conveyed through translation

Force dynamics · Linguistics · Mathematics education · Semantics (computer science · Translation (biology · Chemistry · Computer Science · Language, Metaphor, and Cognition · Mathematics · Psychology · Second Language Acquisition and Learning · Visual and Cognitive Learning Processes

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Unique citing works2
Citations per year0.4
Citation span2021 - 2024 (4)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 2

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