19 International Symposium on Theoretical and Applied Linguistics ...

G E N E R A L S E S S I O N
as thinking opportunities provided for students in the classroom, including recall and recognition,
comparison, abstract reasoning, analysis etc. Intellectual demand cannot be observed directly. It is
mediated through language use in teacher-student interaction in the classroom. A level of intellectual
demand too far below the intellectual capacity of students in their L1 is considered a barrier to L2
development.
The pilot study explored the issue of intellectual demand from a cross-lingual perspective. This
perspective was taken because empirical evidence has proved that literacy skills in the L1 and L2 are
strongly related, and are manifestations of a common underlying proficiency (Cummins & Schecter,
2003). Cross-lingual transfer is likely to occur in developing academic language proficiency, which is
of prime concern in the study context. Cross-lingual transfer occurs between languages of the same
family, and between remotely-related languages such as English and Chinese (see Geva & Wang,
2001). While there is continued need for high English proficiency personnel in the high-tech economy
in Hong Kong, the transferable proficiency possessed by students in their L1 such as higher order
thinking skills etc. did not seem to be taken into consideration in English curriculums or classroom
practice, which was a major impetus of the study. A question, therefore, arose – can Hong Kong’s
English language instruction take advantage of students’ conceptual maturity in Chinese and use it for
the benefit of their second language learning?
To undertake such a cross-lingual investigation, we used detailed classroom interaction data as a
window to observe intellectual demand. Corpus approach (a computer-assisted database) was chosen
to carry out the study because of its capacity in processing large amounts of data and also the
acknowledged inadequacy of available observational schemes (Allwright & Bailey, 2002). A corpus
with two small sub-corpora (one in English and the other in Chinese) was compiled for the pilot. The
Chinese language sub-corpus was used as a benchmark for reference.
In this paper we report the results, dilemmas and challenges encountered in the pilot corpus study.
Issues such as determination of levels of intellectual demands and using L1 reference data are raised.
Audience feedback will be valuable to the on-going research process.
Chinese word inferiority effect: a test of Kao's model
1 Chih-Wei Hue, 2 Yu-Hsiang Tseng, 3 Ching-Ching Lu,
4 Chien-Hui Kao, 5 Yu-Fu Chen & 6 Yin-Wen Kou
1,2,4,5&6 National Taiwan University & 3 National Hsinchu University of Education
1 hue@ntu.edu.tw, 2 r95227102@ntu.edu.tw, 3 cclu@mail.nhcue.edu.tw,
4 d92227011@ntu.edu.tw, 5 r93227103@ntu.edu.tw & 6 93702032@nccu.edu.tw
Character is the writing unit of Chinese, which is usually composed of a semantic and a phonological
radical. A Chinese word usually consists of two syllables, or two characters. The characters in a text
can be printed from left-to-right, right-to-left, or top-to-bottom.
Chinese word inferiority effect (WIE) refers to the phenomena that the probability that a reader fails
to detect a pair of position transposed characters (PTCs) embedded in text is higher, when the
targeting characters are a word than not a word (Hue, <strong>19</strong>89). Different from the parafoveal-processing
hypothesis Healy proposed to account for the English WIE (Hadley & Healy, <strong>19</strong>91), Kao, Hue, Tseng
and Lo (in press) argued that Chinese WIE occurs because of two reasons. First, when two PTCs are
in parafovea, the visual information extracted from them is not sufficient to make detection because
word is not reading unit of Chinese. Secondly, while the two PTCs are in fovea, their means can be
integrated with that of their preceding characters before their visual information is fully processed.
The purpose of the present research is to test further Kao et al.’s idea. Experiment 1 was a
normative study. From news papers, 120 sentences were selected. Each sentence is composed of 27
to 31 characters, and is written in two phrases. A key two-character word (noun) was selected from
the second phrase of a sentence. A cloze test was developed using them, with the key words
substituted by blank spaces. From the responses of 20 participants, the probability of response (or
predictability) of the key word of a sentence was computed.
In Experiment 2, the fore mentioned sentences were used as the stimuli of a detection task, only
that for some of the high and some of the low predictable target words, the positions of their
constituent characters were transposed. In the experiment, the sentences were presented one at a
time. When a sentence was presented, the participants were asked to detect a certain target item in it.
There were two variables manipulated: type of target (a character containing of a particular radical VS.
a pair of PTCs) and type of key word that embeds target (high VS. low predictability). The results
<strong>19</strong> th ISTAL <strong>19</strong>