Theories of reading have seldom been examined across orthographies. In the
present study, Dual Coding Theory (DCT), a general theory of cognition applied to
literacy, was applied to Chinese sentences to investigate the effects of language
concreteness and abstractness on immediate recall. Forty Chinese-English bilinguals
read and recalled five concrete sentences and five matched abstract sentences. Of the ten
sentences, five were English, and five were Chinese. Due to the characteristics of
Chinese orthography, Chinese script may have a direct and more efficient access to
meaning; hence, it is possible that concrete sentences in Chinese would not have the
typical advantage over abstract sentences in recall found in other languages. However,
the results showed that concrete Chinese sentences were recalled better than abstract
Chinese sentences. A 2 (languages: Chinese vs. English) x 2 (sentence concreteness:
concrete vs. abstract) analysis of variance with proportion of recall as the dependent
variable showed that significant main effects were found for languages, F (1, 76) =11.68, p = .001, n2 = .13, and for concreteness, F (1, 76) = 38.12, p < .001, n2 = 33. That is,
Chinese was overall recalled significantly better than English, and concrete sentences
were overall recalled significantly better than abstract sentences. There was no
significant interaction. Concrete Chinese sentences were recalled 1.32 times as much as
abstract Chinese sentences, thus confirming the concreteness effects in Chinese. The
results of the study are consistent with those of previous studies on DCT in alphabetic
languages, and they also provide evidence of concreteness effects across orthographies.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-08-8322 |
| Date | 2010 August 1900 |
| Creators | Chen, Tsuei-Fen |
| Contributors | Sadoski, Mark |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | application/pdf |
Page generated in 0.0023 seconds