Skip to content
naulon
Not checkedNot checked for notices yet.

Big-C-Culture and Little-c-culture Genres: The Effect of Input Flooding on Speaking Accuracy

Zari Saeedi Talab, Sara Salehabadi

Teaching English Language · 2019

doi:10.22132/tel.2019.86928 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Learners have been required to be in the know about some target language cultural knowledge to improve their communicative ability that is a subject in stereotypical perspective towards different cultures named psychological phenomenon which affects the supranational communication. This study targets to investigate the impact of input flooding (extensive reading) on Iranian EFL learners' speaking accuracy. In this mixed-method study, 48, Iranian advanced-level participants studying English as a foreign language at Azadi English institute with a well-equipped library were chosen based on the Oxford Placement Test (2013). According to their test scores, they were randomly divided into two experimental groups, one receiving a ten-session literature-oriented (Big-C culture genre) input flooding treatment; while the other received a ten-session culture-oriented (Little-c culture genre) input flooding treatment using the story books of graded readers. The speaking test of IELTS, Cambridge ESOL, (2013) was run twice to see the effect of the program on their speaking. The result of the T-test measures reveals the significant effect of input flooding through literature and culture-oriented texts on the EFL learners' speaking structural accuracy. The findings bear some clear implications for those teachers who intend to add more meaning to the learning process of their students, for those involved in language policy planning, course design, and material development as well as researchers and learners.

Abstract licence: CC BY-NC

References26

    26 more references, whose wording the paper’s licence keeps private.

    Reads

    Read by people on this page

    None yet.

    Checked or read by AI through naulon

    None yet.

    A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

    Are you an author?

    Is this your paper?

    Claim it to add your note and be paid when agents cite it. Free.