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TitleMotor experience modulates perceptual representation ofobjects: the case of Chinese characterrecognition

Author(s) Tso, Van-yip, Ricky.;ù •im

.

Citation

Issued Date 2012

URL http://hdl.handle.net/10722/173880

RightsThe author retains all proprietary rights, (such as patent rights)and the right to use in future works.

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Motor Experience Modulates Perceptual Representation of Objects: The Case of

Chinese Character Recognition

By

Ricky Van-yip Tso

BSocSc (HKU)

A thesis submitted in partial fulfillment of the requirements for

the degree of Master of Philosophy

at the University of Hong Kong

September 2012

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Abstract of thesis entitled

“Motor Experience Modulates Perceptual Representation of Objects: The Case of

Chinese Character Recognition” 

Submitted by

Ricky Van-yip Tso

For the degree of Master of Philosophy

at the University of Hong Kong

in September 2012

Holistic processing and left-side bias are both behavioral markers of expert face

recognition. In contrast, expertise in Chinese character recognition involves left-side bias but

reduced holistic processing (Hsiao & Cottrell, 2009). Here I hypothesized that this reduction

in holistic processing may be related to writing rather than reading experience. In

Experiment 1, I tested Chinese literates who could read and write Chinese characters

fluently (Writers), and Chinese literates who had limited writing practices and thus had

reading performance far exceeding their writing ability (Limited-writers). I found that

Writers perceived Chinese characters less holistically than Limited-writers. In contrast to

what previous research suggested, reduction in holistic processing in Chinese readers

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depended on writing experience instead of reading performance. In addition, reading

 performance was affected by font familiarity and context for Limited-writers but not Writers.

Writing experience seems to enhance analytic processing and awareness of orthographic

components of Chinese characters, which may in turn facilitate reading in unfamiliar fonts.

By contrast, both Writers and Limited-writers showed a similar level of left-side bias in

 processing symmetric Chinese characters, suggesting that left-side bias is a consistent

expertise marker for orthographic processing uninfluenced by writing experience.

In Experiment 2, I investigate the developmental trend of holistic processing in

Chinese character recognition and its relationship with reading and writing abilities by

testing Chinese children who were learning Chinese at a public elementary school in Hong

Kong on these abilities. I found that the holistic processing effect of Chinese characters in

children was reduced as they reached higher grades; this reduction was driven by enhanced

Chinese literacy rather than age. In addition, I found that writing performance predicts

reading performance through reduced holistic processing as a mediator. Overall, the results

of this study suggest that writing hones analytic processing, which is essential for expert

Chinese character recognition, and in turn facilitates learning to read in Chinese. This study

is also the first to identify Limited-writers as a window onto basic processes of reading.

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Motor Experience Modulates Perceptual Representation of Objects: The Case of

Chinese Character Recognition

By

Ricky Van-yip Tso

BSocSc (HKU)

A thesis submitted in partial fulfillment of the requirements for

the degree of Master of Philosophy

at the University of Hong Kong

September 2012

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Declaration

I declare that this thesis represents my own work, except where due

acknowledgement is made, and that it has not been previously included in a thesis,

dissertation or report submitted to this University or to any other institution for a

degree, diploma or other qualifications.

Signed  ………………………………………………… 

Ricky Van-yip Tso

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Acknowledgements

I must express my deepest gratitude to my advisor, Dr. Janet Hsiao. Janet has been guiding

me through my ups and downs with the greatest warmth, patience and encouragement one

could ever imagine. She has become more like a friend to me. Being her student is the most

fortunately thing that have happened to me throughout my postgraduate years. I must also

thank Prof. Terry Au for co-supervising my project, and for her continuous guidance and

supports. I am extremely grateful to have such wonderful supervisors and to have the

opportunity to learn from their expertise and wisdom.

I thank my fellow labmates, Kloser Cheung, Fanny Lam, Tianyin Liu and Yetta Wong.

Their unconditional supports through tough times have brightened every moment of my days.

I must also express deep gratitude to all the helpers and friends who gave me a helping hand

for my intensive school data collection. I must not forget to thank all the participants, parents

and schools that took part in this study. Without them this project would never have been

feasible.

I would like to express my greatest gratitude to my family who genuinely loved me and

cared for me. Last but not least, I would like to thank Amy Chen for her love and support.

She has always accepted me and supported me in every single moment. Her infinite

encouragement has given me the sunshine I need to get my work done.

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Author Note

Ricky Van-yip TSO, Department of Psychology, University of Hong Kong.

In this thesis, experiments reported in Chapter 2 were presented in the 33rd annual meeting of

the Cognitive Science Society, Boston, Massachusetts, USA, and was included in the

Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Experiment 1

in Chapter 3 was presented in the 34th annual meeting of the Cognitive Science Society,

Sapporo, Japan, and was included in the Proceedings of the 34th Annual Conference of the

Cognitive Science Society

Correspondence concerning this thesis should be addressed to Ricky Van-yip Tso,

Department of Psychology, University of Hong Kong, Pokfulam, Hong Kong.

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Contents

Declaration .................................................................................................................................. i 

Acknowledgements .................................................................................................................... ii 

Author Note .............................................................................................................................. iii 

Contents .................................................................................................................................... iv 

List of abbreviations ................................................................................................................. vi 

List of Figures .......................................................................................................................... vii 

List of Tables .............................................................................................................................. x 

Chapter 1 Introduction............................................................................................................... 1 

1.1. Chinese Character Perception ......................................................................................... 3 

1.2. Writing and reading in Chinese....................................................................................... 6 

Chapter 2 Study 1: The Effect of Writing Experience on Chinese Character Perception ......... 9 

2.1. Participants .................................................................................................................... 11 

2.2. Materials and Procedures .............................................................................................. 13 

2.2.1. Reading and writing performances ......................................................................... 13 

2.2.2. Holistic processing ................................................................................................. 16 

2.2.3. Left-side bias .......................................................................................................... 19 

2.3. Results ........................................................................................................................... 21 

2.3.1. Chinese reading and writing proficiency................................................................ 21 

2.3.2. Holistic Processing ................................................................................................. 23 

2.3.3. Copying Task .......................................................................................................... 25 

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2.3.4. Left-side bias .......................................................................................................... 26 

2.3.5. Effects of word-embedment and font familiarity on character-naming performance

................................................................................................................................ 28 

2.4. Discussion ..................................................................................................................... 29 

Chapter 3 Study 2: The Effect of Learning to Read and Write in Chinese on Chinese

Character perception —  A Developmental Investigation .......................................................... 32 

3.1. Experiment 1: Test for holistic processing of Chinese characters in Chinese speaking

children ................................................................................................................................ 34 

3.1.1. Participants ............................................................................................................. 34 

3.1.2. Materials and Procedures ....................................................................................... 34 

3.1.3. Results .................................................................................................................... 38 

3.2. Experiment 2: Test for holistic processing of Chinese characters in non-Chinese

speaking children ................................................................................................................. 46 

3.2.1. Participants ............................................................................................................. 47 

3.2.2. Materials and Procedures ....................................................................................... 47 

3.2.3. Results .................................................................................................................... 47 

3.3. Discussion ..................................................................................................................... 49 

Chapter 4 General Discussions and Conclusions .................................................................... 52 

4.1. General Discussions ...................................................................................................... 52 

4.1.1. Holistic Processing ................................................................................................. 52 

4.1.2. Left-side bias .......................................................................................................... 57 

4.2. Conclusions ................................................................................................................... 61 

References ................................................................................................................................ 63 

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List of abbreviations

ANOVA

fMRI

LH

RH

 NCS

Analysis of Variance

Functional Magnetic Resonance Imaging

Left Hemisphere

Right Hemisphere

 Non-Chinese Speaking

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List of Figures 

Figure 1. Examples of chimeric face stimuli (adopted from Hsiao & Cottrell, 2009). Two left

halves of an original face (middle) were combined to form the left chimeric face

(left), and the two right halves formed the right chimeric face (right). ..................... 3 

Figure 2. An example of a Ming font (a) and a Feng font (b) character. ................................. 14 

Figure 3. Illustration of stimulus pairs in the complete composite paradigm and trial

sequences. In (a), it shows the four conditions used in the paradigm; the attended

components are shaded in grey. In (b), a 1,000 ms central fixation cross precedes

each trial, followed by a cue either below or above the cross to indicate which

halves (top or bottom) of the characters participants should attend to in the

following display. .................................................................................................... 17 

Figure 4. Examples of the stimuli used and the test sequence in the left-side bias experiment.

In (a), two left halves of an original character (middle) were combined to form the

left chimeric character (left), and the two right halves formed the right chimeric

character (right; note that the chimeric characters are still legal Chinese characters).

In (b), participants were presented with an original character either on the left or

right of the screen in each trial (shown on the left of the screen here) and were

instructed to judge which of the right or left chimeric characters (above and below

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the arrow) looked more similar to the original image. ............................................ 20 

Figure 5. Accuracy rate of Limited-writers and Writers for the dictation and word naming

task (***p < 0.001). ................................................................................................. 22 

Figure 6. Response time (a) and A’(b) of Limited-writers and Writers in congruent and

incongruent trials of the holistic processing task (**p < 0.01). .............................. 25 

Figure 7. Copying response time for real Chinese characters, real Korean characters, and

 pseudo-Chinese characters for Limited-writers and Writers (** p < 0.01). ............ 26 

Figure 8. Preference for left chimeric characters in Writers and Limited-writers in Ming and

Feng fonts. ............................................................................................................... 27 

Figure 9. Response time for naming characters and words in Ming and Feng fonts for Writers

(a) and Limited-writers (b) (* p < 0.05; ** p < 0.01). ............................................. 29 

Figure 10. Predicted mediation effect of reduced holistic processing between Chinese writing

and reading performance. ........................................................................................ 33 

Figure 11. Examples of Chinese characters with left-right configuration (left) and top-bottom

configuration (right). ............................................................................................... 37 

Figure 12. A'  of congruent and incongruent trials for first, third and fifth graders in the

holistic processing task (* p < 0.05; ** p < 0.01; *** p < 0.001). ............................. 41 

Figure 13. Partial mediation effect of reduced holistic processing on dictation and word

naming performances (* p 

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Figure 14. A'  of congruent and incongruent trials for non-Chinese speaking first, third and

fifth graders in the holistic processing task ............................................................. 47 

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List of Tables

Table 1. Means of reading, writing and copying performance in first, third and fifth

graders……………………………………………………………………..………39

Table 2. Correlations Among Age, Rapid-naming speed, Character naming accuracy,

Character naming response time, Word naming accuracy, Word naming response

time, Copying response time, Dictation accuracy, and Holistic A'………………...42 

Table 3. Hierarchical regression analysis among holistic processing and reading, dictation and

copying performance…………………………………………………………….…43 

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Chapter 1

 Introduction

Holistic processing is the tendency to process separate features of an object as a single

whole unit (Richler, Wong, & Gauthier, 2011), and it is shown to be a behavioral marker of

face recognition expertise. One common paradigm to test for holistic processing in face

recognition is the Complete Composite Paradigm (see Richler, Wong, & Gauthier, 2011).

In each trial, participants are instructed to judge whether two corresponding halves of two

stimuli are the same or different. The irrelevant halves will give the same responses in

congruent trials, while the giving different responses in incongruent trials. Holistic

 processing is measured by the performance difference between congruent and incongruent

trials. Another paradigm to test for holistic processing is the part-whole paradigm (see

Joseph & Tanaka, 2002; Tanaka & Farah, 1993; Tanaka et al ., 1998). In this design,

 participants were first presented with a face sample; immediately after this presentation,

 participants were tested either in the whole-face condition or the isolated-part condition. In

the whole-face condition, participants were presented with the sample face and a novel

face that differ from the sample face by only one feature (e.g. nose), and were asked to

 judge which face appeared in the previous trial. Alternatively in the isolated-part

condition, participants were presented with an isolated feature from the sample face (e.g.

mouth) and a novel feature and were asked to judge which feature appeared in the sample

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face. Participants would perform better in the whole-face condition if they processed faces

holistically. Some have speculated that holistic processing applies to other types of expert-

level object recognition because it facilitates within-category object discrimination by

incorporating featural and configural information beyond individual parts (Bukach,

Gauthier, & Tarr, 2006; Gauthier & Bukach, 2007; Wong, Palmeri, & Gauthier, 2009; but

for a contrasting view, see McKone, Kanwisher, & Duchaine, 2007). For example, training

 participants to recognize novel artificial symmetric objects (“Greebles”), Gauthier and

colleagues (1998) found a positive correlation between holistic processing and expertise in

within-category object recognition. Consistently, Wong, Palmeri and Gauthier (2009)

showed that participants had an increase in holistic processing when trained to

individualize an artificial object type (“Ziggerins”). 

Left-side bias is another phenomenon consistently reported in face perception; it

refers to the effect that a chimeric face made from two left half-faces is usually judged

more similar to the original face compared with one made from two right half-faces from

the viewer’s perspective (Brady, Campbell, & Flaherty, 2005; Gilbert & Bakan, 1973;

Figure 1). Consistent with this perceptual bias effect, in eye movement studies, viewers

also have a tendency to look at the left side of the face more often than the right side when

 processing faces (Leonards & Scott-Samuel, 2005; Mertens, Siegmund, & Crusser, 1993).

The left-side bias effect may well be due to the involvement of the right hemisphere (RH)

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in face recognition (Hsiao, Shieh, & Cottrell, 2008; Burt & Perrett, 1997).

Figure 1. Examples of chimeric face stimuli (adopted from Hsiao & Cottrell,

2009). Two left halves of an original face (middle) were combined to form the

left chimeric face (left), and the two right halves formed the right chimeric face

(right).

1.1. Chinese Character Perception

Chinese characters, with their many shared visual properties with faces, were

hypothesized to induce a similar processing effect in expert readers (Hsiao & Cottrell,

2009; McCleery et al ., 2008). More specifically, the Chinese writing system is

logographic; while words in most alphabetic languages are linear in structure and consist

of letter series of varying lengths, Chinese characters have a more homogenous, square

configuration, and each character is a grapheme that maps onto a morpheme (Shu, 2003;

Wong & Gauthier, 2006). The basic units of a Chinese character are strokes, which

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combine to form more than a thousand different stroke patterns in the Chinese writing

system (Hsiao & Shillock, 2006); these stroke patterns in turn form the characters. A

typical literate recognizes 3,000 to 4,000 characters. In addition, Chinese characters are

generally recognized regardless of variations in font and handwriting style, similar to face

recognition regardless of differences in facial expressions (Hsiao & Cottrell, 2009), and

experts recognize Chinese characters individually like faces (Wong & Gauthier, 2006).

Indeed, as in the case of expertise in face recognition, Hsiao and Cottrell (2009)

showed that expert Chinese readers demonstrated left-side bias when viewing mirror-

symmetric Chinese characters, whereas novices did not. They found that expert Chinese

readers significantly chose the left-chimeric image of a Chinese character to be more

similar to the original image, and had an overall tendency to look at the left side of

characters. Hsiao and Cottrell’s (2009) finding suggests that left-side bias is an expertise

marker for Chinese character recognition and was consistent with research suggesting a

RH involvement in Chinese orthographic processing (e.g., Tzeng, Hung, Cotton, & Wang,

1979; Yang & Cheng, 1999). This is also consistent with ERP studies that showed more

RH lateralized or bilateral processing in the occipitotemporal region (Liu & Perfetti, 2003;

Hsiao, Shillcock, & Lee, 2007), in contrast to the LH lateralization classically observed in

English and alphabetic word processing (see Dahaene & Cohen, 2011). Similar findings

were shown in fMRI studies (e.g. Tan et al ., 2000; Tan et al., 2001; see also Tan, Laird, Li,

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& Fox, 2005).

However, unlike face perception, the expertise marker for Chinese character

recognition turned out to be reduced holistic processing (Hsiao & Cottrell, 2009). Using

the Complete Composite Paradigm, Hsiao and Cottrell (2009) showed that experienced

Chinese readers engaged in less holistic processing than novices in perceiving Chinese

characters. Perhaps experienced Chinese readers are more sensitive to the constituent

components of Chinese characters and can more readily ignore some configural

information unimportant for character recognition, such as exact distances between

features (Ge, Wang, McGleery, & Lee, 2006). Such constituent components may not look

easily separable to novices, probably because novices are less able to distinguish

individual features and components in Chinese characters (Chen, Allport, & Marshall,

1996; Ho, Ng, & Ng, 2003; Hsiao & Cottrell, 2009). Hsiao and Cottrell (2009) have

therefore suggested that holistic processing is not a general expertise marker for object

 processing; it depends on the features of the stimuli and the tasks typically performed on

the stimuli (see also Wong et al ., 2009).

 Note however that the experience with learning to read Chinese characters is different

from typical face recognition in one apparent way — while a typical Chinese reader can

read and write characters proficiently, one is not expected to draw out all the familiar faces

seen every day. Thus, it is possible that the reduced holistic processing effect in expert

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Chinese character processing, in contrast to expert face processing, is related to expert

readers’ writing rather than reading experience. Unlike writing alphabetic words, which

only requires recalling a few dozens of letters in an alphabet together with the specific

combinations corresponding to their sounds, writing Chinese characters requires retrieving

more than a thousand pieces of script information from long term memory. One may have

to attend analytically to detailed stroke patterns of individual Chinese characters in order

to memorize and write them. Perhaps expert Chinese readers in Hsiao and Cottrell’s

(2009) study had reduced holistic processing because they were concurrently experienced

character writers. Consistent with our speculation on the relationship between

writing/motor experience and holistic processing in expert Chinese character recognition,

Zhou, Cheng, Zhang, and Wong (2012) recently found that artists with face drawing

experiences had reduced holistic face processing compared with ordinary observers.

 Never theless, Hsiao and Cottrell’s (2009) study offered a window on holistic processing

and left side bias in relation to expertise of complex object recognition by showing that

holistic processing may not be a general expertise marker and that it does not always

concur with RH lateralization.

1.2. Writing and reading in Chinese

In Hong Kong, although the internal structures of Chinese characters are not explicitly

emphasized in formal lessons, Chinese children acquire better orthographic awareness as

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they progress to higher grades (Ho et al ., 2003). One explanation has to do with motor

 programming through extensive copying and reading at school (Guan, Liu, Chan, Ye, &

Perfetti, 2011; Tan, Spinks, Eden, Perfetti, & Siok, 2005). Copying performance

significantly predicts reading ability (Chan, Ho, Tsang, Lee, & Chung, 2006; McBride-

Chang, Chung, & Tong, 2011; Tan, et al ., 2005), and dictation performance is correlated

with reading performance (McBride-Chang, Chung, et al ., 2011; Tse, Kwan, & Ho, 2010).

It has been proposed that writing performance can predict reading performance because

children may consolidate knowledge of orthographic structures of characters with

graphomotor memory of strokes as they copy the stroke sequences (Tan et al., 2005; Tse et

al., 2010). Consistent with this speculation, learning to write seems to strengthen Chinese

character recognition (Guan et al., 2011). Other research also suggested that writing

experience plays an important role in shaping the neural representation specialized for

reading (e.g. James & Atwood, 2009; Longcamp, Anton, Roth, & Velay, 2003). A neural

 pathway linking the Broca’s area and the supplemental motor area was activated during

silent reading of Chinese pinyin (Romanized transcription of Mandarin pronunciation) in

an fMRI study (He et al., 2003). The left middle frontal gyrus, an area just anterior to the

 premotor area, was activated in normal but not dyslexic Chinese readers when reading

(Siok, Perfetti, Jin, & Tan, 2004). These results consistently suggest a close relationship

 between increasing sensory-motor integration through writing practice and the

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development of reading skills.

This thesis aims at investigating the effect of enhanced Chinese literacy, particularly

writing experiences, on our perceptual representation of Chinese characters. In Chapter 2, I

will present a study that examines perceptual differences of Chinese characters between

Chinese readers who can read and write fluently and Chinese readers who can read

fluently but have limited writing performances (I will discuss this phenomenon in details

in the next chapter). I will then present my findings on the effect of enhanced Chinese

literacy on Chinese character perception in children in Chapter 3. Chapter 4 will discuss

the significance of the findings in this research and its educational implications.

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Chapter 2

Study 1: The Effect of Writing Experience on Chinese Character Perception 

Typically, fluent readers of a language can also write fluently; however, there exist some

Chinese readers who have high reading proficiency but far poorer writing ability –  whom I

will call “Limited-writers”. They are usually students or graduates of international schools

who have learned to “write” in Chinese using computer software that converts input in a

 phonic alphabet (e.g., the Pinyin system) into Chinese characters, expatriates living in

Chinese speaking countries, or overseas Chinese immigrants who learned to read in

Chinese from environmental prints including Chinese mass media. Writing Chinese

characters requires retrieving more than a thousand pieces of script information from long

term memory. Because writing in Chinese orthography is more complex and resource-

intensive than writing in an alphabetic language (Chan et al ., 2006; Chung & Ho, 2010;

Tse et al ., 2010), marked discrepancy between reading and writing performance in Chinese

is possible. With limited writing practice but plenty of reading experience, Limited-writers

may recognize the holistic structures of characters similarly to face recognition, with

limited analysis of the constituent structures. Thus, the cognitive processes involved in

Chinese reading for Limited-writers may be different from readers who have received

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intensive character writing training (Writers). To date, virtually no research has recognized

such a Chinese community can be a window onto basic processes in reading.

In Study 1, I aim to examine whether these rather proficient Chinese readers who have

limited experience in writing Chinese characters (i.e., Limited-writers) process Chinese

characters differently from those who can both write by hand and read proficiently (i.e.,

Writers). I first investigate reading and writing performance differences between Writers

and Limited-writers. I then examine whether Writers perceive characters less holistically

than Limited-writers, and whether the reduced holistic processing effect is related to their

reading and writing performance. Since writing practice may enhance orthographic

awareness of characters and de-emphasize configural information in character recognition,

I predict that Writers will perceive characters less holistically than Limited-writers, and

this effect will be related to their difference in writing rather than reading performance  –  

contrary to what the research literature suggests. The ability to perceive characters

analytically (less holistically) may be the underlying mechanism for how writing

experience enhances Chinese character recognition.

We also examine whether Limited-writers as well as Writers have a similar left-side

 bias effect in Chinese character perception. Brady et al . (2005) showed that the left-side

 bias effect in face perception was stronger when viewing familiar faces compared with

unfamiliar faces; this phenomenon suggests that the left-side bias effect may be related to

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familiarity with the stimuli. Since both Writers and Limited-writers are proficient readers

and thus are familiar with Chinese characters, I predict that Writers and Limited-writers

will have a similar degree of left-side bias in perceiving Chinese characters.

We also investigate the effect of word embedment of a character on its naming speed

and accuracy. Experienced Chinese readers can name characters embedded in a high

frequency word faster than when the characters were presented alone (e.g., Cheng, 1981,

Chu & Leung, 2005; Zhang & Peng, 1992). If Limited-writers indeed acquire Chinese

characters from the context where characters are seldom read alone, this word embedment

effect should be more prominent in Limited-writers than Writers who have extensively

 practiced writing individual characters. In addition, I explore whether differences in

writing experience between these two groups would lead to performance differences in

reading different fonts. Limited-writers are usually exposed to printed rather than

handwritten Chinese characters and often find reading hand-written characters difficult.

Writers, by contrast, are more experienced in deciphering different handwritings and

 perhaps as a result are less affected by font variations in reading printed Chinese words.

Thus, here I also examine the effect of font familiarity on character and word naming

speed.

2.1. Participants

40 Cantonese native-speaking Chinese readers (17 males and 23 females) in Hong Kong

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 participated in our study. They had similar college-level education background. Half of

them had always attended conventional local schools and reported to have fluent reading

and writing proficiency (i.e., Writers), whereas the other half had either studied overseas or

at international schools and had not received formal Chinese lessons that prepared students

for the local public Chinese examinations (i.e., Limited-writers). All Limited-writers

reported having studied either at international schools or overseas and had little Chinese

writing experiences. They all reported having fluent reading ability. Writers’ and Limited-

writers’ reading and writing abilities were further tested by a word -naming task and a

dictation task respectively (which will be described in 2.2.1.). We differentiated our

Limited-writers from Writers by their performances in the word-naming and dictation task,

i.e., Limited-writers were expected to have the same performance level in the word-

naming task as Writers, but have poorer performance in the dictation task (see 2.3.1.). The

average age of Limited-writers was 21.45 (S.E. = .57) and Writers was 21.47 (SE = .50).

The two groups did not differ in age, F(1, 38) = .001, n.s. They all had normal or

corrected-to-normal vision.

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2.2. Materials and Procedures

2.2.1. Reading and writing performances

Four tests were administered to test for reading and writing performances: 1. Character

naming task, 2. Word naming task, 3. Character copying task, and 4. Word dictation task.

Tasks 1 and 2 assessed participant’s reading ability, while Tasks 3 and 4 assessed their

copying and word recalling/writing ability respectively. Tasks 2 and 4 were compared to

examine the discrepancy between word naming and word recalling/writing performances.

1. Character naming task:

Participants were presented with 84 medium to high frequency Chinese characters of

similar visual complexity one at a time and asked to read aloud as quickly and as

accurately as possible. The characters had an average frequency of 443.3 per 663,424

characters (SE = 45.4) and stroke number of 10.9 (SE = .16; Ho & Kwan, 2001). Half of

the stimuli were presented in Ming font (a common font in print) and the other half were

 presented in Feng font (an unfamiliar font that simulates handwriting; Figure 2). Each

character was approximately 1.5 x 1.5 cm2  in size and each participant had a viewing

distance of 55 cm. Each character spanned about 1.6 degree of visual angle. Each trial

started with a central fixation cross for 500 ms, followed by the character presentation.

After a participant had responded, the screen would turn blank and the experimenter would

 press a button to record the accuracy and to start the next trial. The response time was

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measured as the time difference between the stimulus onset and the onset of the

 pronunciation, detected by a microphone.

Figure 2. An example of a Ming font (a) and a Feng font (b) character.

2. Word naming task:

Participants read aloud 40 medium to high frequency two-character words (average

frequency = 194.7 per 530,452 words, SE = 19.6; Taiwan Ministry of Education, 1997) as

quickly and accurately as possible. Half of the stimuli were presented in Ming font and the

other half in Feng font. Each word was approximately 1.5 x 3.0 cm2  in size and each

 participant had a viewing distance of 55 cm. Each word spanned about 3.1 degree of visual

angle. The procedure was the same as that of Task 1. The response time was measured as

the time difference between the stimulus onset and the onset of the pronunciation of the

first character.

3. Character copying task:

Participants copied 60 characters (20 real characters, 20 pseudo-characters, and 20 Korean

characters) as quickly and as accurately as possible. The Chinese characters were high

frequency characters that were randomly selected from the characters used in Task 1 with

an average stroke number of 10.7 (SE = .48). The pseudo-characters were orthographically

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legal but non-sense characters. Each trial started with a central fixation cross for 500 ms,

followed by the character presentation. Each character was approximately 1.5 x 1.5 cm 2 in

size and each participant had a viewing distance of 55 cm. Each character spanned about

1.6 degree of visual angle. I used Korean and pseudo-characters to see whether

 participants’ performance in copying Chinese characters can be generalized to copying

novel but configurally similar characters (e.g., top-bottom, left-right, top heavy, bottom

heavy). After copying a character, a participant would press a button to make the screen

turn blank and start the next trial. The response time was recorded.

4. Word dictation task:

Participants wrote down 40 two-character words as quickly and as accurately as possible

when they heard from a computer each word read aloud by a female native-speaker of

Cantonese (Words instead of single characters were used here to reduce ambiguity due to

the many homophonic characters in the Chinese lexicon). The words were the same as

those used in Task 2. Each trial started with the words “Get ready” on the screen for

500ms. After hearing the word, participants pressed corresponding buttons to indicate

whether they could recall the word or not, before they started writing. After they finished

writing, the experimenter would press a button to record accuracy and to reveal the next

word.

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2.2.2. Holistic processing

To examine holistic processing effects, procedures were adopted from Hsiao and Cottrell

(2009). 80 pairs of medium to high frequency Chinese characters in Ming font with a top-

 bottom configuration as adopted by Hsiao and Cottrell (2009) were chosen. Participants

were asked to attend to only half (either top or bottom) of each character in a pair on each

trial and make a same-different judgment. Twenty pairs were presented in each of the four

conditions (Figure 3a):  same in congruent trials, different in congruent trials, same in

incongruent trials, and different in congruent trials. A complete composite paradigm

(Gauthier & Bukach, 2007) was adopted; in congruent trials, the attended and irrelevant

halves of the characters led to the same response (i.e., both were the same or different),

while in incongruent trials, the attended and irrelevant halves led to different responses 1. If

a stimulus was processed holistically, there should be interference from the irrelevant

halves in matching the attended halves in incongruent trials; holistic processing thus could

 be assessed as the performance difference between incongruent and congruent trials. I

adopted this design to avoid influence from response biases that may occur in the partial

composite design, in which the irrelevant halves are always different (see Gauthier &

Bukach, 2007; Robbins & McKone, 2007). In addition, holistic face processing measured

1 Unlike the partial composite paradigm, in which a misaligned condition must be administered (i.e. the top

halves and bottom halves of the stimuli are misaligned from each other; e.g., Hole, 1994; Robbins &

McKone, 2007), holistic processing can be indicated by the performance difference between the congruent

and incongruent trials using the complete composite design without a misaligned condition (Gauthier &

Bukach, 2007; Hsiao & Cottrell, 2009).

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with the complete composite paradigm was positively correlated with face recognition

 performance; in contrast, this relationship was obscured when using the partial composite

design (Richler, Wong, & Gauthier, 2011; see also Konar, Bennett, & Sekuler, 2010).

Figure 3. Illustration of stimulus pairs in the complete composite paradigm and

trial sequences. In (a), it shows the four conditions used in the paradigm; the

attended components are shaded in grey. In (b), a 1,000 ms central fixation

cross precedes each trial, followed by a cue either below or above the cross to

indicate which halves (top or bottom) of the characters participants should

attend to in the following display.

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Each character was approximately 1.5 cm x 1.5 cm in size and each participant had a

viewing distance of 55 cm. Each character spanned about 1.6 degree of visual angle.

During the experiment, the stimuli presented on the screen were of relatively low contrasts

to avoid ceiling effects. In each trial, after 1,000 ms of central fixation, participants were

cued with a symbol that indicated which half (top or bottom) of each character they should

attend to. The pair of characters was then presented, with one above and one below the

initial fixation, 5.7 degree of visual angle away from each other. During the 500 ms

 presentation time, participants looked at each character once and responded as quickly and

accurately as possible, pressing corresponding buttons to judge if the character parts were

the same or different (Figure 3b). Accuracy and reaction time were collected. I measured

 participants’ discrimination sensitivity A'  as:

 

 

Where H  and F  are the hit and false alarm rate, respectively. A' is a bias-free

nonparametric measure of sensitivity; d'  was not used here because response biases may

affect its measurement when assumptions of normality and homogeneity of variance are

not met (Stanislaw & Todorov, 1999). The A’ or response time difference between

incongruent and congruent trials measures holistic processing — a larger difference

indicates stronger holistic processing.

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2.2.3. Left-side bias

To compare the left-side bias effect between Writers and Limited-writers, I adopted the

 procedure from Hsiao and Cottrell (2009). 80 Chinese mirror-symmetric characters of high

frequency were selected (average frequency = 385.0 per 530,452 words, SE = 67.8; Ho &

Kwan, 2001). There were a total of 160 trials with each character presented twice in Ming

font and Feng font respectively. For characters presented in each font, mirror images were

used in half of the trials. If a character was presented in Ming font, then the mirror image

of the original character was presented in Feng font, and vice versa; this was to

counterbalance any differences between the two sides of each character. For each character

image, one chimeric character was created from two left halves (left chimeric character)

and another one from two right halves of the character (right chimeric character; Figure

4a), similar to chimeric faces. 

Each character was approximately 6 x 6 cm2  in size and each participant had a

viewing distance of 55 cm, under this viewing distance, each character spanned about 6.7

degree of visual angle. In each trial, after 1,000 ms of a central fixation, the original

character was presented randomly either on the left or the right side of the computer

screen, at about 7.2 degree of visual angle away from the center. The left and right

chimeric characters were presented along with the original image, with one above and one

 below an arrow at the center; the arrow directed the location of the original character at

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which participants were told to look first. Each character was about 3 degree of visual

angle away from the center. The stimuli stayed on the screen until participants made a

response. Participants judged which of the two chimeric characters looked more similar to

the original one by pressing the corresponding buttons (Figure 4b). I measured the left-side

 bias effect as the percentage of trials in which the left chimeric character was selected.

These experiments were all conducted using E-prime v2.0 (Psychology Software

Tools, Pittsburgh, PA).

Figure 4. Examples of the stimuli used and the test sequence in the left-side bias

experiment. In (a), two left halves of an original character (middle) were

combined to form the left chimeric character (left), and the two right halves

formed the right chimeric character (right; note that the chimeric characters are

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still legal Chinese characters). In (b), participants were presented with an

original character either on the left or right of the screen in each trial (shown on

the left of the screen here) and were instructed to judge which of the right or left

chimeric characters (above and below the arrow) looked more similar to the

original image.

2.3. Results

2.3.1. Chinese reading and writing proficiency

ANOVA was used for the analyses. For the reading performance, the variables were font

(Ming vs. Feng fonts) and group (Writers vs. Limited-writers). The results showed that

Writers and Limited-writers did not differ in word naming accuracy,  F (1, 38) = .471, n.s.,

η p 2 = .02 ( M = .98, SE = .006, and M = .98, SE = .007 respectively), suggesting that both

groups had high reading proficiency for high frequency words. Nevertheless, Writers had

significantly shorter response times in word naming ( M = 450 ms, SE = 13) than Limited-

writers ( M = 593 ms, SE = 36), F (1, 38) = 12.365, p < .01, η p 2 = .26. In character naming,

Writers outperformed Limited-writers in both accuracy,  F (1, 38) = 4.806,  p = .05, η p  2 =

.097 ( M = .98, SE = .004, and  M = .97, SE = .007 respectively), and response time,  F (1,

38) = 14.45,  p  < 0.01, η p  2  = .315 ( M = 478 ms, SE = 16, and  M = 682 ms, SE = 32

respectively. I will report the font effects in reading performance in a later section). As for

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writing performance, Writers had shorter response times overall in character copying ( M =

3881 ms, SE = 173) than Limited-writers ( M = 5601 ms, SE = 350), F (1, 38) = 15.39, p <

.01, η p 2 = .347. In the dictation task, Writers were significantly more accurate ( M = .86,

SE = .01) than Limited-writers ( M = .35, SE = .04), F (1, 38) = 140.53, p < .001, η p 2 = 604.

Figure 5 contrasts the discrepancy between dictation (word writing) and word naming

accuracy in Writers and Limited-writers (i.e., they had similar word reading accuracy but

differed in dictation/writing accuracy)2.

Figure 5. Accuracy rate of Limited-writers and Writers for the dictation and

word naming task (***p < 0.001).

2 We did not report accuracy for the copying task as it required additional inter-rating efforts to judge

objectively the accuracy of the stimuli copied by the adults. We also did not report the response time for

the dictation task as it is difficult to consider both the recalling time and writing time of the words.

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2.3.2. Holistic Processing

Repeated-measures ANOVA was used to investigate holistic processing effects

(condition: congruent vs. incongruent trials x group: Writers vs. Limited-writers). For

response time, I found a main effect of condition,  F (1, 38) = 26.14,  p < .001, η p 2 = .408,

and an interaction between condition and group,  F (1, 38) = 15.6,  p < .001, η p 2 = = .291,

 but no main effect of group, F (1, 38) = 1.20, n.s., η p 2 = .031. Limited-writers responded

significantly more slowly in incongruent trials than in congruent trials, t (19) = 5.489, p <

.001, d  = 1.30, while Writers recorded similar response times in congruent and incongruent

trials, t (19) = 0.875, n.s. , d  = .21. Similarly, on A’, I found a main effect of condition,  F (1,

38) = 10.66, p < .01, η p 2 = .219, and an interaction between condition and group, F (1, 38)

= 8.02,  p < .01, η p  2 = .174, but no main effect of group,  F (39) = .434, n.s., η p

  2 = .011.

Limited-writers had a significantly smaller A’ in incongruent trials than in congruent trials

t (19) = 3.592, p < .01,, d = .84, while this difference was not significant for Writers, t (19)

= 0.390, n.s., d  = .08. These results suggest that Writers perceived Chinese characters less

holistically than Limited-writers3 (Figure 6).

Since Writers and Limited Writers differed in some reading performance measures in

3  Since our two participant groups were all typically developed adults in similar ages, their performance

difference in the incongruent trials was unlikely to be due to difference in inhibition control. In addition,

Hsiao and Cottrell (2009) showed that the holistic processing effect observed in Chinese character

processing disappeared when character halves were misaligned, suggesting that the effect was due to

inability to selectively attend to character halves when they were aligned.

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addition to their difference in writing experience, to examine whether their difference in

holistic processing was due to their difference in writing or reading abilities, I analyzed the

holistic processing effect in response time with their reading and writing performance

measures put as covariates (ANCOVA). The difference in holistic processing between

Writers and Limited Writers was still significant even when character naming response

time, F (1, 38) = 6.978, p 

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Figure 6. Response time (a) and A’(b) of Limited-writers and Writers in

congruent and incongruent trials of the holistic processing task (**p < 0.01).

2.3.3. Copying Task  

Repeated-measures ANOVA was used for the analysis on copying RT (group x

character type: real Chinese vs. real Korean vs. pseudo-Chinese). I found a main effect of

character type, F (2, 37) = 79.68, p < .001, η p 2 = .172, and a main effect of group,  F (1, 38)

= 19.73,  p < .001, η p  2 = .342, but no interaction between group and character type,  F (2,

37) = 1.94, n.s. Real characters were copied faster than Korean characters, t (39) = 9.736, p 

< .001, d = 1.53, and pseudo-characters, t (39) = 11.985, p < .001, d = .45, while pseudo-

characters were copied faster than Korean characters, t (39) = 2.827,  p  < .01, d = 1.89.

When I investigated copying performance for different character types separately, Writers

copied significantly faster than Limited-writers for Chinese characters,  F (1, 38) = 15.39, p 

= .003,  η p  2  = .359, Korean characters,  F (1, 38) = 10.257,  p  = .003,  η p

  2  = .289, and

 pseudo-characters,  F (1, 38) = 14.706,  p = .001,  η p  2  = .332 (Figure 7). These results

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suggest that writers are able to generalize their Chinese character copying ability to

copying novel characters that have similar structures.

Figure 7. Copying response time for real Chinese characters, real Korean

characters, and pseudo-Chinese characters for Limited-writers and Writers (** p

< 0.01).

2.3.4. Left-side bias

Repeated-measures ANOVA (font x group) was used for the analysis on the left-side bias

effect. I found a significant main effect of font,  F (1, 38) = 11.558,  p < .01, η p  2 = .233:

 participants had a stronger preference for left chimeric characters when the characters

were presented in Ming font than when they were presented in Feng font. There was no

main effect of group, F (1, 38) = .470, n.s., or an interaction between group and font,  F (1,

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38) = .024, n.s.,. This showed that both Writers and Limited-writers had a similar degree

of left-side bias in perceiving Chinese characters in either font.

To further understand this phenomenon, I conducted post-hoc t-tests for Writers and

Limited-writers separately. I found a significant preference for left chimeric characters in

Ming font in both Writers (.54), t (19) = 2.378, p < .05, d  = .53, and Limited-writers (.56),

t (19) = 2.271, p < .05, d  = .51, whereas the preference for left chimeric characters in Feng

font was not significant in either Writers (.48, n.s.,) or Limited-writers (.49, n.s.) This

result suggested that participants exhibited left-side bias for Chinese characters only in a

familiar font (Ming) but not in an unfamiliar font (Feng; Figure 8).

Figure 8. Preference for left chimeric characters in Writers and Limited-writers

in Ming and Feng fonts.

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2.3.5. Effects of word-embedment and font familiarity on character-naming performance

Repeated-measures ANOVA (font x word-embedment: word vs. character x group)

was used for the analysis on naming response time. I found a main effect of font,  F (1, 18)

= 37, p < .001, η p 2 = .242, a main effect of group,  F (1, 38) = 18.79, p < .001, η p

 2 = .323,

and a main effect of word-embedment, F  (1, 38) = 4.486, p < .05, η p 2 = .106. I also found

an interaction between font and group,  F (1, 38) = 6.072, p < .05, η p 2 = .139, between font

and word-embedment,  F (1, 38) = 5.933,  p  < .05,  η p  2  = .135, and among font, word-

embedment, and group,  F (1, 38) = 4.293,  p  = .05, η p  2  = .093. These effects were not

observed in the accuracy data. To further understand these interactions, I analyzed data for

Writers and Limited-writers separately.

For Limited-writers, the results revealed a main effect of font, F (1, 19) = 8.686, p <

.01,  η p  2  = .341. Although no main effect was found for word-embedment (word vs.

character),  F (1, 19) = 1.484, n.s., an interaction between font and word-embedment was

found, F  (1, 19) = 4.962,  p < .05, η p 2 = .211. Post-doc t-tests found that Limited-writers

named words faster than characters in Ming font, t (19) = 3.802,  p < .05, d  = .87, but this

difference was not found in Feng font, t (19) = .664, n.s. Limited-writers named Ming font

words faster than Feng font words, t (19) = 2.684, p < .05, d  = .60, but their naming speed

 between Ming font and Feng font characters did not differ, t (19) = .437, n.s.. For Writers,

the results revealed neither an interaction between word-embedment and font,  F (1, 19) =

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1.174,  n.s., nor a main effect of font,  F (1, 19) = 2.574, n.s., although a main effect of

word-embedment was found, F (1, 19) = 12.846, p < .01, η p 2 = .212. Post-doc t-tests found

that Writers named words faster than characters regardless of whether words were in Ming

font, t (19) = 3.427, p < .01, d  = .53, or Feng font, t (19) = 2.460, p < .05, d  = .45. As shown

in Figure 9, these data suggest that Limited Writers’ character recognition depends on

familiarity with both font and context (word-embedment), whereas Writers can generalize

their recognition ability to unfamiliar fonts.

Figure 9. Response time for naming characters and words in Ming and Feng

fonts for Writers (a) and Limited-writers (b) (* p < 0.05; ** p < 0.01).

2.4. Discussion 

The results from Study 1 suggest that Limited-writers processed Chinese characters more

holistically than Writers. ANCOVA showed that this effect could be strongly accounted for

 by their performance difference in the dictation (word writing) task, but importantly could

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not be as strongly accounted for by their differences in any of the reading performance

measures, including character and word naming accuracy and response times. These

results suggest that the holistic processing effect in Chinese character recognition depends

mainly on writing experience, or more specifically, the ability to recall and write down

Chinese characters rather than reading performance. Perhaps writing experience enhances

the ability to analyze the orthographic structures and components of Chinese characters,

which leads to reduced holistic processing. Complementing Hsiao and Cottrell’s (2009)

study, here I showed that the reduced holistic processing effect observed in expert Chinese

readers uniquely depended on writing experiences, or more specifically, the ability to

recall and write Chinese characters.

Both Writers and Limited writers had similar accuracy in the word naming task.

Though the dictation task and the word-naming task used the same words, Writers

outperformed Limited in the dictation task. In addition, Writers also outperformed

Limited-writers in the copying task that involved Korean characters (Hangul), each of

which typically consists of several phonetic symbols arranged in configurations

commonly found in Chinese characters. The Writers' ability to analyze Chinese characters

may have generalized to Korean characters, thereby facilitating Korean character copying.

Study 1 also showed that Limited-writers recognized a character embedded in a word

of Ming font faster than when it is alone or of Feng font, while Writers named two-

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character words faster than single characters regardless of font type (Figure 7). It suggests

 both context (word-embedment) and font familiarity helps Limited-writers recognize

Chinese characters.

Consistent with Hsiao and Cottrell’s (2009) findings, our experiment on left-side

 bias in Chinese characters showed that both Writers and Limited-writers —  both are expert

Chinese readers — have a similar preference for left chimeric characters. This left-side bias

was only found for characters in Ming font but not Feng font. It seems that left-side bias is

a consistent expertise marker for Chinese character recognition and is uninfluenced by

writing experience. 

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Chapter 3

Study 2: The Effect of Learning to Read and Write in Chinese on Chinese

Character perception —  A Developmental Investigation

Although previous studies have suggested a close relationship between Chinese writing

and reading performance in children, the underlying mechanism remains unclear (e.g.

Guan et al ., 2011; McBride-Chang et al ., 2011)5. Study 1 suggests that writing experience

reduces HP of Chinese characters, which marks expert-level character recognition; here I

hypothesize that writing experience enhances character recognition performance by

modulating the perceptual system, allowing readers to identify Chinese characters more

analytically. The modulating effect of writing experience on our perception of Chinese

characters has never been studied before in Children who are learning to read and write

Chinese characters. Thus, I investigate whether children in upper grades perceived

characters less holistically than children in lower grades in an elementary school where the

Chinese language is taught. I also examined their Chinese reading and writing

 performance to see what can predict Children’s reduced HP of Chinese characters.  I

 predict that upper-grade children (who should have better Chinese literacy than lower-

grade children) will process Chinese characters more analytically (i.e., less holistically)

5 Although some studies have proposed that writing enhances graphomotor memory of Chinese characters,

which in turn facilitates reading (see e.g. Tan et al ., 2005; Tse et al ., 2010). Yet, this hypothesis has not been

statistically tested.

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than children in lower grades. I hypothesize that children’s reduction in HP can be

 predicted by writing performances across grades. Since writing performance also strongly

correlates with reading abilities in Chinese (Guan et al ., 2011; McBride-Chang et al .,

2011; Tan et al ., 2005), I hypothesize that HP mediates between Chinese reading and

writing abilities in children. More specifically, I predict that writing experience leads to

reduced holistic processing in Chinese characters, which in turn enhances reading abilities

in Chinese (Figure 10).

Figure 10. Predicted mediation effect of reduced holistic processing between

Chinese writing and reading performance.

The results from Study 1 also suggest that writing experience may facilitate reading

Chinese characters in an unfamiliar font, as Limited-writers had difficulty reading words

in the Feng font (a font that mimics handwriting and was unfamiliar to the participants)

whereas this effect in Writers was minimal. Hence here I also examine the possible effect

of enhanced Chinese writing proficiency on naming characters and words in familiar and

unfamiliar fonts.

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3.1. Experiment 1: Test for holistic processing of Chinese characters in

Chinese speaking children

Experiment 1 tested for HP and left-side bias of Chinese characters in children from first,

third, and fifth grades. They were all learning to read and write in Chinese at school and

were all tested for reading and writing performances in Chinese. This experiment aims at

testing the effect of enhanced Chinese literacy on HP and left-side bias of Chinese

characters as children progress to higher grades.

3.1.1. Participants

56 first grade (mean age = 5.88 years, SE = .051), 73 third grade (mean age = 7.90, SE =

.056), and 88 fifth grade (mean age = 9.89, SE = .047) Chinese children from an

elementary in Hong Kong participated in our study. They were all Cantonese native-

speaking and were all receiving regular Chinese language curriculum at school. All of

them had normal or corrected-to-normal vision.

3.1.2. Materials and Procedures

3.1.2.1. Reading and writing performances

Four tests were administered: 1. Character naming task, 2. Word naming task, 3. Character

copying task, and 4. Word dictation task. Tasks 1 and 2 assessed participant’s reading

ability, while Tasks 3 and 4 assessed their copying and word recalling/writing ability

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respectively6.

1. Character naming task:

Children were presented with 60 Chinese characters one at a time. Half of the stimuli were

 presented in Ming font and the other half were presented in Feng font. The fonts used for

each character were counterbalanced across participants. They were instructed to read

aloud the characters as quickly and as accurately as possible. The characters had an

average stroke number of 9.08 (SE = .10) and were arranged from high to low frequency

(frequency information for primary students was obtained from Leung & Lee, 2001). The

trials stopped after 5 consecutive errors made7. The procedures and paradigm were

identical to the character naming task in Study 1.

2. Word naming task:

Children read aloud 30 two-character words arranged from high to low frequency

(frequency information for primary students was obtained from Leung & Lee, 2001) as

quickly and accurately as possible. Half of the stimuli were presented in Ming font and the

other half were presented in Feng font. The fonts used for each word were

counterbalanced across participants. The procedures and paradigm were identical to the

word naming task in Study 1.

3. Character copying task:

6 Because of the literacy level difference between adults and children, stimuli used for testing Chinese

proficiency in Study 1 and Study 2 were obtained from different corpuses.7 Similar experimental procedures have been used in Yeung and colleagues, 2011

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Children copied 30 characters (10 real characters, 10 pseudo-characters, and 10 Korean

characters) as quickly and as accurately as possible. The Chinese characters were

randomly selected from the characters used in task 1. The procedures and paradigm were

identical to the character copying task in Study 1

4. Word dictation task:

Children wrote down 30 two-character words (the same words used in task 2) as quickly

and as accurately as possible when they heard each word said in a female voice presented

 by a computer. The procedures and paradigm were identical to the word dictation task in

Study 1.

3.1.2.2. Test for rapid automatized naming

Because general symbol processing speed is related to reading ability in children (Ho &

Lai, 1999; Wolf & Bowers, 1999), we adopted a computerized rapid automatized naming

(RAN) task to measure this component in children (see Denckla & Rudel, 1976). The

digits 1, 2, 3, 4, 5, 6, 7, 8, and 9 were presented one at a time for 4 times on the computer

screen. Each trial started with a central fixation cross for 500ms, followed by the digit

 presentation. The screen turned blank after a child had responded and the experimenter

 pressed a button to record the accuracy and to start the next trial. Their response time was

measured as the time difference between the stimulus onset and the onset of the

 pronunciation, detected by a microphone.

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3.1.2.3. Test for holistic processing

To test for HP effects, I adopted the same procedures from Study 1. Here 160 pairs of

medium to high frequency Chinese characters in Ming font were chosen; 80 pairs had a

top-bottom configuration and 80 pairs had a left-right configuration (Figure 11). The

frequency information of the Chinese characters was obtained from Ho and Kwan (2001).

The top-down and left-right characters were matched in stroke number and frequency. In

each trial, children were presented with two characters and instructed to attend to only half

(either top or bottom for top-bottom characters, or left or right for left-right characters) of

each character and judge whether they were the same or different. Forty pairs were

 presented in each of the four conditions (Figure 3a): same in congruent trials, different in

congruent trials, same in incongruent trials, and different in incongruent trials.

Figure 11. Examples of Chinese characters with left-right configuration (left) and

top-bottom configuration (right).

3.1.2.4. Left-side bias

We adopted the same procedures from Study 1 to compare the left-side bias effect of

Chinese characters between children from first, third and fifth grades. Here 40 Chinese

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mirror-symmetric characters of high frequency were selected (average frequency = 385.0

 per 530,452 words, SE = 67.8; Ho & Kwan, 2001). There were a total of 80 trials with

each character presented twice in Ming font and Feng font respectively.

These experiments were all conducted using E-prime v2.0 (Psychology Software

Tools, Pittsburgh, PA).

3.1.3. Results

3.1.3.1. Chinese reading and writing proficiency

Pearson’s correlation regression analysis showed a positive correlation between grade and

character-naming accuracy (r2 = .602, p < .001), word-naming accuracy (r2 = .512, p <

.001) and dictation accuracy (r2 = .707, p < .001); and a negative correlation between

grade and character-naming response time (r2 = .269, p < .001), word-naming response

time (r2 = .347, p < .001) and character-copying response time (r2 = .620, p < .001). These

results suggest that children had better Chinese reading and writing proficiency as they

reached higher grades. Table 1 summarizes the means of different Chinese proficiency

measures in each grade.

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Table 1. Means of reading, writing and copying performance in first, third and fifth

graders

Grade 1 Grade 3 Grade 5Mean (SD)

Character-naming

accuracy

.38 (.23) .80 (.18) .93 (.06)

Character-naming

Response Time (ms)

1237 (506) 850 (271) 714 (217)

Word-naming

accuracy

.43 (.29) .87 (.16) .96 (.06

Word-naming

Response Time (ms)

1101 (429) 720 (162) 603 (129)

Copying RT (ms) 12162 (2289) 6618 (1481) 5727 (1189)

Dictation Accuracy .11 (.07) .42 (.20) .72 (.17)

3.1.3.2 Holistic Processing

Repeated-measures ANOVA was used to investigate HP effects (congruency: congruent

vs. incongruent trials x grade: Grade 1 vs. Grade 3 vs. Grade 5). I found a significant

effect of grade, F(2, 213) = 25.090, p < 0.001, η p 2 = .2, a significant effect of congruency,

F(1, 213) = 268.319, p < 0.001, η p  2 = .56, and an interaction between congruency and

grade F(1, 213) = 11.376, p < 0.001, η p  2 = .10. The main effect of congruency suggests

that across grades, children process Chinese characters holistically. While the main effect

of grade showed that the performance level increased with grade, the interaction between

grade and congruency suggests that children processed Chinese characters with varying

levels of congruency effect across grades (Figure 12).

Pairwise post-hoc t-tests showed that A' in congruent trials was larger than in

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incongruent trials in first, t(55) = 12.01, p < .001, d  = 1.60, third, t(72) = 7.838, p < .001,

d  = .92, and fifth graders t(86) = 8.439, p < .001, d  = .91. In congruent trials, first graders

had a smaller A' than third, t(127) = 3.226, p < .01, d  = .57, and fifth graders, t(141) =

4.576, p < .001, d   = .77, while third and fifth graders did not differ statistically in A',

t(158) = .994, n.s. In incongruent trials, first graders had a smaller A' than third, t(127) =

3.991, p < .001, d  = .71, and fifth graders, t(141) = 7.878, p < .001, d  = 1.33, and third

graders had a smaller A' than fifth graders, t(158) = 2.450, p < .05, d   = .40. I also

conducted pairwise post-hoc t-tests on the A' difference between incongruent and

congruent trials (i.e., Holistic A') between children in the 3 grades. I found that first

graders had a larger Holistic A' than third graders, t(127) = 2.334, p

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Figure 12. A'  of congruent and incongruent trials for first, third and fifth graders in

the holistic processing task (* p < 0.05; ** p < 0.01; *** p < 0.001).

3.1.3.3. Pearson’s Correlation Analysis

Table 2 presents the correlations among age, rapid-naming speed, literacy measure, and

Holistic A'. Most of the correlations among the variables were statistically significant,

except for that between rapid-naming speed and Holistic A'. This shows that the

developmental change in HP of Chinese characters is least likely related to a general

improvement in orthography recognition.

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Table 2. Correlations Among Age, Rapid-naming speed, Character naming

accuracy, Character naming response time, Word naming accuracy, Word naming

response time, Copying response time, Dictation accuracy, and Holistic A'

3.1.3.3. Hierarchical Regression Analysis

We investigated how HP could be uniquely predicted by literacy level by partialing out the

variance due to age. As summarized in Table 3, HP was predicted uniquely by reading and

writing performance and vice versa. The variance of HP can be significantly explained by

reading and dictation performances, but not copying performance, when partialing out the

variance due to age.

Table 3. Hierarchical regression analysis among holistic processing and reading,

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dictation and copying performance

Predicted Variable: Holistic A'

Age vs. Character Naming (Response Time & Accuracy)Steps Variables  Δr 

2  

1 Age .110***

2 Character Naming .037*

1 Character Naming .141***

2 Age .005

Age vs. Word Naming (Response Time & Accuracy) 

1 Age .099***

2 Word Naming .056**

1 Word Naming .147***

2 Age .008Age vs. Copying (Response Time)

1 Age .104***

2 Copying .001

1 Copying .067***

2 Age .038**

Age vs. Dictation (Accuracy)

1 Age .155***

2 Dictation .014

1 Dictation .118***

2 Age .0111  p < 0.1 * p 

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 between dictation accuracy and word naming accuracy (z = 2.403, p < .05). The mediator

effect of Holistic A' was partial as the direct effect of dictation accuracy and word naming

accuracy remained statistically significant, β = .635, p < .001 (Figure 13)8.

Sobel’s β  = .635***

Figure 13. Partial mediation effect of reduced holistic processing on dictation and

word naming performances (* p 

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This showed that first, third and fifth graders had a similar degree of left-side bias in

 perceiving Chinese characters in either font.

To examine whether the children had a left-side bias effect in the perception of

characters, I conducted one-sample t-tests again the chance level (i.e., 50% left chimeric

character preference) for Ming and Feng Chinese characters. I did not find a preference for

left chimeric characters in Ming font (.51), t (214) = .957, n.s., nor Feng font in children

(.50), t (214) = .554, n.s. This result suggested that children had not developed left-side

 bias for Chinese characters in either a familiar font (Ming) or an unfamiliar font.

3.1.3.6. Effects of font familiarity on character- and word-naming performances

Repeated-measures ANOVA (font: Ming vs. Feng x grade) was used for the analysis on

character-naming response time. I found a main effect of font, F(1, 181) = 16.9, p < .001,

η p 2 = .085, and a main effect of grade, F(2, 181) = 37.01, p

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d  = .37, and fifth graders, t(117) = 2.192, p < .05, d  = .41, while third and fifth graders did

not differ statistically, t(128) = .135, n.s., d  = .02. These results suggest that word-naming

 performances depended greatly on font familiarity in lower grades than in upper grades.

This font-grade interaction was not found in character-naming.

3.2. Experiment 2: Test for holistic processing of Chinese characters in

non-Chinese speaking children

Since I could not totally rule out the effect of inhibitory control differences due to age on

HP in Experiment 1, Experiment 2 aimed to test HP of Chinese characters in non-Chinese

speaking (NCS) children that do not receive the local Chinese curriculum as a control

group. In Hong Kong, there are designated local schools that admit NCS students. They

learn under the same curriculum as typical local Chinese children except for reading and

writing Chinese, and their language of instruction is English because their native language

is not Chinese and their Chinese reading and writing proficiency is far below the levels of

children from mainstream schools that were teaching Chinese as a native language. Their

school adopted a school-based curriculum in which NCS children may only be taught

simple Chinese speaking skills and simple Chinese vocabulary. If reduction in HP is

mainly contributed by enhanced Chinese literacy, I predict that the HP of Chinese

characters of NCS children will remain the same as they progress to higher grades, since

their Chinese literacy level should be homogenous across grades.

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3.2.1. Participants

30 first grade (mean age = 7.00 years, SE = .079), 30 third grade (mean age = 9.33, SE =

.151), and 22 fifth grade (mean age = 11.47, SE = .198) NCS children from an elementary

in Hong Kong participated in our study. They were all receiving the same curriculum as

typical Chinese children but were not receiving regular Chinese language curriculum at

school, and the language of instruction at school was English. All of them had normal or

corrected-to-normal vision.

3.2.2. Materials and Procedures

To test for HP effects, I adopted identical procedures and materials from Experiment 1.

3.2.3. Results

Figure 14. A'  of congruent and incongruent trials for non-Chinese speaking first,

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third and fifth graders in the holistic processing task

Repeated-measures ANOVA was used to investigate HP effects (congruency: congruent

vs. incongruent trials x grade: Grade 1 vs. Grade 3 vs. Grade 5). I found a significant

effect of grade, F(2, 79) = 15.496,  p  < 0.001,  η p  2  = . 282, a significant effect of

congruency, F(1, 79) = 66.244,  p  < 0.001, η p  2  = . 456. However, I did not find an

interaction between congruency and grade, F(2, 79) = 0.780,  p = .462,. The main effect of

congruency suggests that across grades, NCS children also process Chinese characters

holistically. The main effect of grade showed that the performance level increased with

grade. The absence of interaction between grade and congruency suggests that children

 processed Chinese characters with the same level of congruency effect across grades

(Figure 14).

3.2.3.1. Comparing with Experiment 1

To further understand the HP difference between Chinese and NSC children in each grade,

I defined holistic A’ as the A’ difference between congruent and incongruent trials and ran

a two-way ANOVA with group (Chinese vs. NCS children) and grade (grade 1 vs. grade 3

vs. grade 5) as the between-subject variables to test for effects in holistic A'. I found a

main effect of grade, F(2, 292) = 4.790, p < .01, η p 2 = .032, but no main effect of group,

F(1,292) = 1.112, n.s. I also found a marginal interaction between group and grade,

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F(2,292) = 2.333, p = .099, η p 2 = .0169.

To further understand this marginal interaction effect, I ran post-hoc t-tests to

compare the HP effect (i.e., holistic A’) between Chinese and NCS children in each grade

(Levene’s test showed homogeneity of variance across groups). I found that Chinese

children were more holistic than NCS children in Grade 1, t(52) = 2.261, p < .05, d  = 0.62.

However, both Chinese children and NCS children had similar HP in Chinese characters in

Grade 3, t(65) = .277, n.s, and Grade 5, t(28) = .240, n.s. These effects suggested that the

reduction in holistic processing observed in Chinese speaking children as they progressed

to higher grades was mainly due to a stronger holistic processing effect in grade 1

compared with NCS children10.

3.3. Discussion

Experiment 1 showed that as children who learned the Chinese language in a mainstream

school progress to higher grades, they processed Chinese characters less holistically.

Hierarchical regression analysis suggests that this reduction in HP could not be solely be

9 Note that in this two-way ANOVA, Levene’s test showed homogeneity of variance across groups, although

the analysis involved unequal sample sizes. In a separate analysis, I conducted a mixed ANOVA with group

and grade as the between-subject variable and congruency (congruent vs. incongruent) as the within-

subject variable,  and Levene’s test failed to support the homogeneity of variance assumption; thus this

mixed ANOVA analysis was not reliable and not reported here.10

 In grade 1, Chinese speaking and NCS children differed significantly in performance in congruent trials (t-

test with Welch’s correction for unequal variances t(42) = 3.223, p < .01) but did not differ in incongruent

trials (t(55) = 1.232, n.s.). Their performance in incongruent trials was also significantly above the chance

level (A’ = 0.5; t(85) = 4.334, p < .001;). Thus the weaker HP effect in NCS children was unlikely to be due to

a floor effect in the incongruent trials.

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accounted for by age, but by an overall improvement in Chinese reading and writing

 performance.

The mediation analysis showed that HP partially mediates the effect of dictation

accuracy and word naming accuracy (Figure 13). This is consistent with our hypothesis

that writing performance (i.e., the ability to recall and write down Chinese characters)

 predicts the HP effect in Chinese character processing, which in turn predicts word

reading performance (Figure 10). Writing experience can perhaps enhance the ability to

analyze character components (i.e., reduced HP), which facilitates character recognition.

My control study in Experiment 2 suggests that without learning to read and writing

Chinese characters extensively, children do not have a reduction in HP as they reached

higher grades. Unlike in Experiment 1 where children learning the Chinese language at

school showed a reduction in HP as they progressed to higher grades, the NCS children in

Experiment 2 were shown to process Chinese characters with the same level of HP across

all 3 grades. Since the NCS children were not learning the typical Chinese curriculum,

reduction in HP of Chinese characters in higher grades in Chinese-speaking children was

likely a result of enhanced Chinese literacy but not age.

Post-hoc t-tests showed that first graders who are learning the Chinese language in a

mainstream school processed Chinese characters more holistically than NCS first graders.

The Chinese proficiency of the Chinese first graders in the current study was much higher