Transfer of Perceptual Expertise: The Case of Simplified and …epa.psy.ntu.edu.tw/documents/2016/Liu_Chuk_Yeh_Hsiao... · 2017-07-13 · marked by reduced holistic (i.e., increased

Cognitive Science (2016) 1–28Copyright © 2016 Cognitive Science Society, Inc. All rights reserved.ISSN: 0364-0213 print / 1551-6709 onlineDOI: 10.1111/cogs.12307

Transfer of Perceptual Expertise: The Case of Simplifiedand Traditional Chinese Character Recognition

Tianyin Liu,a Tin Yim Chuk,a Su-Ling Yeh,b Janet H. Hsiaoa

aDepartment of Psychology, University of Hong KongbDepartment of Psychology, National Taiwan University

Received 10 June 2014; received in revised form 23 July 2015; accepted 3 August 2015

Abstract

Expertise in Chinese character recognition is marked by reduced holistic processing (HP),

which depends mainly on writing rather than reading experience. Here we show that, while simpli-

fied and traditional Chinese readers demonstrated a similar level of HP when processing characters

shared between the simplified and traditional scripts, simplified Chinese readers were less holistic

than traditional Chinese readers in perceiving simplified characters; this effect depended mainly

on their writing rather than reading performance. However, the two groups did not differ in HP of

traditional characters, regardless of their difference in reading and writing performances. Our

image analysis showed high visual similarity between the two character types, with a larger vari-

ance among simplified characters; this may allow simplified Chinese readers to interpolate and

generalize their skills to traditional characters. Thus, transfer of perceptual expertise may be con-

strained by both the similarity in feature and the difference in exemplar variance between the cate-

gories.

Keywords: Holistic processing; Chinese character recognition; Reading; Writing

1. Introduction

Holistic processing (i.e., gluing features together into a Gestalt) has been found to be a

behavioral visual expertise marker for the recognition of faces (Tanaka & Farah, 1993)

and many other nonface objects, such as cars (Gauthier, Curran, Curby, & Collins, 2003),

fingerprints (Busey & Vanderkolk, 2005), and greebles (a kind of artificial stimuli; Gau-

thier & Tarr, 1997). In experts’ eyes, the parts of these stimuli are integrated and recog-

nized as a whole instead of various parts (Gauthier & Tanaka, 2002), and thus experts’

flexibility to access the information of individual parts is reduced (Maurer, Le Grand, &

Correspondence should be sent to Janet Hsiao, Department of Psychology, University of Hong Kong,

PokFulam Road, Hong Kong. E-mail: [email protected]

Mondloch, 2002). In the literature, holistic processing is commonly assessed through the

composite paradigm. Taking the composite face effect as an example, a composite face is

made by combining the top half of one face and the bottom half of another face together.

In the original composite face study done by Young, Hellawell, and Hay (1987), partici-

pants found it difficult to recognize the top of a celebrity’s face when it was aligned with

the bottom of another celebrity’s face. Later, Hole (1994) also demonstrated the compos-

ite face effect using unfamiliar faces. He asked participants to perform same/different

judgments about the top halves of two composite faces while ignoring the other face

halves, and the results showed that participants reported two identical top halves to look

different when they were aligned with two different bottom halves. Presumably, holistic

processing binds the two halves of the faces together and people get interference from

the irrelevant halves in the same/different judgment of the attended halves, and conse-

quently they perceive two identical top halves of faces as different when the top halves

are paired with different bottom halves. Thus, holistic processing assessed through the

composite paradigm can be understood as obligatory attention to all parts of an object,

which leads to failure of selective attention to parts (Richler, Tanaka, Brown, & Gauthier,

2008).

Chinese characters are the basic writing units in Chinese orthography. They consist of

strokes packed into a relatively constant square-shaped configuration, in contrast to words

in most alphabetic languages, which are linear combinations of letters. It has been sug-

gested that Chinese character recognition shares some similarities with face recognition

(McCleery et al., 2008). For example, both faces and Chinese characters have a homoge-

nous shape, are recognized at the individual level, and are learned in an upright orienta-

tion. Yet in contrast to face recognition, expertise in recognizing Chinese characters is

marked by reduced holistic (i.e., increased analytic) processing assessed using the com-

posite paradigm (Hsiao & Cottrell, 2009).1 This effect may be due to expert Chinese

readers’ orthographic knowledge about Chinese characters, and consequently they have a

better ability to selectively attend to different parts of a Chinese character than novices.

More specifically, Chinese characters are composed of strokes, which combine to form

over 200 different basic stroke patterns in Chinese orthography (Hsiao & Shillcock,

2006), and these basic stroke patterns are the smallest functional units in Chinese charac-

ter recognition (Chen, Allport, & Marshall, 1996). For expert Chinese readers, when rec-

ognizing Chinese characters, they may be more sensitive to the internal constituent

components/stroke patterns and have better ability to ignore some unimportant configural

information for recognition, such as exact distances between features (Ge, Wang,

McCleery, & Lee, 2006), as compared with novices (Ho, Ng, & Ng, 2003; Hsiao & Cot-

trell, 2009). Consequently, expert readers may process Chinese characters less holistically

than novices. This phenomenon suggests that holistic processing effects, as an expertise

marker in visual object recognition, depend on the characteristics of the stimuli and the

perceivers’ learning experience with the stimuli (Hsiao & Cottrell, 2009; see also Tso,

Au, & Hsiao, 2014). It is possible that holistic processing effects can also be influenced

by the perceivers’ prior experiences with similar object types. Nevertheless, it remains

unclear what factors may influence the transfer of holistic processing effects.

2 T. Liu et al. / Cognitive Science (2016)

There are currently two Chinese writing systems in use in Chinese speaking regions,

namely simplified and traditional Chinese. The simplification movement of Chinese char-

acters first emerged in the early 1900s, and the simplified script widely implemented

today was the version created during the writing reform initiated by the central govern-

ment of the People’s Republic of China in 1956 for easing the learning process in both

recognition (reading) and production (writing) (Zhao & Baldauf, 2011). Today the major-

ity of Chinese speaking regions, including Mainland China, Singapore, and Malaysia, use

the simplified script, while Hong Kong and Taiwan continue to use the traditional script.

Three basic emphases of the simplification process were (a) to simplify common radicals

of characters and apply in contexts where they occur (e.g., radical “言” was simplified as

“讠,” and applied to characters containing this radical, “討” to “讨,” “話” to “话,” etc.);

(b) to remove elements within characters (e.g., “愛” to “爱” and “髮” to “发”); and (c) to

combine some homophones and eliminate redundant characters (e.g., “範” and “范” were

combined into the latter, and the former was eliminated; McBride-Chang, Chow, Zhong,

Burgess, & Hayward, 2005). The simplification process did not apply to all characters;

among the most frequently used 3,500 characters, around 40% of them were simplified

and have approximately 22.5% fewer strokes than the traditional counterparts (Gao &

Kao, 2002); the other 60% remained the same, or in other words, are shared between the

two scripts. The contrast between simplified and traditional Chinese characters thus pro-

vides us a unique opportunity to examine factors that may influence transfer effects of

holistic processing across similar object types.

The effect of simplifying the script has been a subject of dispute over the last two dec-

ades. For instance, while simplified characters were designed to ease the learning process,

many researchers (e.g., Chen, 1999; Seybolt & Chiang, 1979) believe that pure reduction

in strokes or elimination of characters without standardization of principles was an artifi-

cial control of the natural direction of language evolution (Hodge and Louie, 1998), and

it may make the simplified characters harder to learn in the long term: On one hand,

reducing the number of strokes may make the characters easier to write for beginners as

they are visually less complex; on the other hand, because the simplification process did

not preserve all phonetic and semantic information of the characters, up to a certain point,

characters may become hard to learn due to violation of orthographic rules as readers’

lexicon size expands (Chen, 1999). Zhao and Baldauf (2011) also argued that the charac-

ters in the simplified script were “simplified individually, but complicated systematically”

(p. 171), indicating that fewer strokes did not necessarily make the characters easier to

learn and memorize given their inconsistency with the orthographic rules. In a nutshell,

simplicity does not guarantee efficiency.

Meanwhile, some recent studies suggest that learning simplified Chinese characters

may be beneficial. For example, McBride-Chang et al. (2005) found that visual skills of

children who learned simplified characters were significantly better than those of Hong

Kong children who learned the traditional script, especially visual discrimination skills.

They argued that because simplified Chinese characters have fewer visual features for dis-

crimination than their traditional counterparts, simplified Chinese readers need to develop

better visual discrimination skills in order to tell characters apart. Consistent with this

T. Liu et al. / Cognitive Science (2016) 3

finding, Peng, Minett, and Wang’s (2010) ERP data suggested that adult simplified char-

acter readers have developed a better ability to discriminate characters that are identical

in the simplified and traditional scripts (i.e., shared characters) from noncharacters that

were constructed by adding or removing one stroke from the characters, as compared

with traditional character readers. This result suggests that simplified character readers

may have developed better analytic visual discrimination skills than traditional character

readers. These findings thus suggest that reading simplified characters may require more

analytic (i.e., less holistic) processing than reading traditional characters.

Tso et al. (2014) recently showed how writing experience influences holistic process-

ing in Chinese character recognition (see also Tso, Au, & Hsiao, 2011, 2012, 2013). They

recruited proficient Chinese readers who were skilled in both reading and writing Chinese

characters (Writers), those who had proficient reading ability but limited writing experi-

ence in Chinese (Limited-Writers), and non-Chinese readers (Novices). They found that

compared with Novices, Limited-Writers perceived Chinese characters more holistically,

whereas Writers perceived Chinese characters less holistically. This result reflects an

inverted U-shape pattern of holistic processing with increased Chinese character exper-

tise: Perceptual experience alone increases holistic processing, whereas sensorimotor

experience reduces holistic processing. Thus, the reduced holistic processing effect

observed in expert Chinese readers may depend on writing rather than reading perfor-

mance. Although simplified Chinese readers may be able to read traditional characters

through their similarity with simplified characters or context information, they generally

do not know how to write them (and similarly for traditional Chinese readers to read and

write simplified characters). Thus, similar to Limited-Writers, they may perceive charac-

ters in their unfamiliar script more holistically, and this effect may depend on their writ-

ing rather than reading performance.

Here, we aim to examine whether native simplified Chinese readers process Chinese

characters more analytically (less holistically) than traditional Chinese readers due to the

differences in their scripts. In addition, we examine how simplified and traditional Chi-

nese readers process Chinese characters in the script they are not familiar with. We first

examine their perception of characters that are shared in the two scripts (i.e., shared char-

acters); according to the previous findings about simplified Chinese readers’ superior

visual discrimination skills to traditional Chinese readers (McBride-Chang et al., 2005;

Peng et al., 2010), simplified Chinese readers may exhibit stronger analytic processing

(weaker holistic processing) in processing shared characters. We then examine partici-

pants’ perception of Chinese characters in the simplified and the traditional forms. We

predict that simplified Chinese readers will perceive simplified characters less holistically

than traditional readers due to their expertise with the simplified script, and vice versa in

the perception of traditional characters; these holistic processing effects may be related to

their writing ability, that is, the ability to recall and write down the characters (Tso et al.,

2013). On the other hand, it is also possible that Chinese readers are able to transfer their

analytic processing skills to process characters in the script they are not familiar with due

to the similarity between the two Chinese scripts; in this case, the two groups may not dif-

fer in holistic processing in perceiving either the traditional or the simplified characters.


This investigation thus enables us to examine transfer of analytic character processing in

readers with different character reading experiences in order to understand the factors that

may influence transfer effects of perceptual expertise.

2. Experiment 1

2.1. Methods

2.1.1. ParticipantsTwenty-four native readers of simplified Chinese from Mainland China and 24 native

readers of traditional Chinese from Hong Kong participated in the study. They were all

skilled writers in their own script: All Mainland China participants had passed the Chinese

test of National Entrance Examination to college, and all Hong Kong participants had

passed the Chinese test of Hong Kong Advanced Level Examination. They were all stu-

dents at University of Hong Kong; all simplified Chinese readers had resided in Hong

Kong for less than 1 year (average length of stay was 9.35 months) at the time they were

recruited. To ensure the two reader groups had limited exposure to the other script at the

time they were recruited, a questionnaire was designed to collect information about their

language background and exposure. Participants of both groups reported having no formal

education about the other script, and being exposed to the script they were less familiar

with for less than 10% of the text they encountered daily on average. Note that the official

written languages used in Hong Kong are English and traditional Chinese and the official

language for instruction at University of Hong Kong is English. All Hong Kong traditional

Chinese readers were born and raised in Hong Kong, and their experience with traditional

Chinese characters (calculated as years of education) was 15 years on average, signifi-

cantly more than Mainland China simplified Chinese readers’ exposure to traditional Chi-

nese since they arrived in Hong Kong (F(1, 46) = 1,194.95, p < .001). Note also that with

increasing interaction between Mainland China and Hong Kong, publications in simplified

Chinese characters are accessible in Hong Kong, and classes teaching simplified Chinese

characters have been included in some primary and high schools’ in recent years.

In addition, the two groups had similar education background (average years of educa-

tion, Mainland China = 15.79, SE = .38; Hong Kong = 15.29, SE = .42) and similar age

(Mainland China average = 22.71, SE = .70; Hong Kong average = 22.21, SE = .73). All

of them had normal or corrected-to-normal vision and were right-handed as measured by

the Edinburgh Handedness Inventory (Oldfield, 1971).

2.1.2. Holistic processingThe complete composite paradigm was used to examine holistic processing effects

(Gauthier & Bukach, 2007). The experiment procedure was adopted from Hsiao and Cot-

trell (2009). In each trial, participants were presented with a pair of Chinese characters

simultaneously and told to attend to only half of each character and judge whether they

were the same or different. There were in total four types of trials depending on congru-


ency and response (see Fig. 1a): same in congruent trials, different in congruent trials,same in incongruent trials, and different in incongruent trials. In congruent trials, the

attended and irrelevant halves of the characters led to the same response (i.e., both were

the same or different); in incongruent trials, they led to different responses. The level of

holistic processing was assessed by the performance difference between the congruent

and incongruent trials.

Note that in contrast to the partial design where holistic processing is assessed by an

alignment effect (i.e., the performance difference between aligned and misaligned trials;

e.g., Young et al., 1987; Hole, 1994), in the complete design it is assessed by a congru-

ency effect (i.e., the performance difference between congruent and incongruent trials)

without a misalignment condition (Hsiao & Cottrell, 2009). Hsiao and Cottrell (2009)

showed that misalignment is able to reduce holistic processing observed in Chinese char-

acter processing, consistent with the literature on face and object recognition (e.g., Rich-

ler et al., 2008).

2.1.2.1. Materials: The materials consisted of 480 pairs of Chinese characters in Ming

font (the most common font used in print), divided equally into three script types: 160

pairs were unique simplified characters; 160 pairs were the corresponding traditional ver-

sion of the simplified characters, that is, having same meaning and pronunciation but dif-

fering in orthography; the remaining 160 pairs were characters shared between the two

scripts, that is, shared characters (see Table 1 for an illustration). The frequency of the

characters in the materials ranged from 2 per million to 250 per million based on single

character appearance in 80/90’s text (Ho & Kwan, 2001; the frequency of the characters

in the dataset ranged from 1 per million to 3,679 per million, with the median being 25

per million). Characters of different script types were matched in relative character fre-

quency, and the traditional characters were significantly more complex (complexity of

characters was measured by number of strokes throughout this paper) than the simplified

A B

Fig. 1. Illustration of stimulus pairs in the complete composite paradigm (a) and trial sequences (b). Stimulus

contrast was lowered to avoid ceiling effects. In (a), the attended components are the bottom halves, while

the top halves shaded in gray (not shown in the experiment) are irrelevant.


ones (t(159) = 6.17, p < .01). In each script type, half of the characters had a top–bottom(TB) configuration, the other half were left–right (LR) structured (see Fig. 2, for exam-

ples), and the TB and LR characters were matched in complexity (F(1, 959) = 2.03,

p = .21) and frequency (F(1, 959) = .67, p = .50). We used both TB and LR characters

to counterbalance possible influence from character structure (Yeh & Li, 2002); the LR

structure is the most dominant structure in Chinese orthography, followed by the TB

structure (see, e.g., Hsiao & Shillcock, 2006).

The 80 character pairs in each script type and character configuration combination were

further divided into the four conditions in the complete composite paradigm, with 20 pairs

in each condition (shown in Fig. 1a). Each character was then divided into two compo-

nents, horizontally for TB and vertically for LR configured characters. In either character

configuration condition, the attended halves were the same across congruent and incongru-

ent trials (see Fig. 1a, for an illustration), and character frequency and visual complexity

were matched across congruent and incongruent trials (character frequency: t(239) = 0.82,

p = 0.51; visual complexity: t(239) = 1.2, p = 0.21). Summary of the descriptive proper-

ties of the stimuli used for the holistic processing task are presented in Table 2.

Fig. 2. Examples of top–bottom (TB) and left–right (LR) structured shared, simplified, and traditional coun-

terparts of simplified Chinese characters (the red line separates the top from the bottom, and the left from the

right components).

Table 1

Examples of test stimuli of the complete composite paradigm


Table

2

Summaryofthedescriptiveproperties

ofthestim

uliusedin

thecomplete

composite

paradigm

CharacterType

Shared

Sim

plified

Traditional

Congruency

Congruent

Incongruent

Congruent

Incongruent

Congruent

Incongruent

CorrectResponse

Sam

eDifferent

Sam

eDifferent

Sam

eDifferent

Sam

eDifferent

Sam

eDifferent

Sam

eDifferent

Number

ofpairs

TB

20

20

20

20

20

20

20

20

20

20

20

20

LR

20

20

20

20

20

20

20

20

20

20

20

20

Meancomplexity(number

ofstrokes)

TB

11.4

9.8

11

10.9

9.6

9.1

9.5

9.7

15.5

15.3

15.5

16.4

LR

9.5

8.9

9.7

9.0

9.1

8.4

8.6

8.6

14.2

14.1

14.6

15.2

Meanfrequency

(per

million)

TB

18

30

14

52

35

28

67

32

40

26

76

35

LR

47

36

22

20

20

28

29

29

20

26

25

25


2.1.2.2. Design: The design had three within-subject variables: congruency (congruent

vs. incongruent), character configuration (TB vs. LR), and script type (simplified vs. tradi-

tional vs. shared); and a between-subject variable: group (simplified vs. traditional Chi-

nese readers). The dependent variable was discrimination sensitivity measured by A0,which is calculated by the following equation:

A0 ¼ :5þ signðH � FÞ ðH � FÞ2 þ jH � Fj4maxðH;FÞ � 4HF

" #

H and F present the hit rate and false alarm rate, respectively, and better performance is

indicated by a higher A0. Here we used A0 instead of D0 because A0 is a bias-free nonpara-

metric measure of sensitivity according to signal detection theory (Stanislaw & Todorov,

1999), and it can be calculated when the hit rate or the false-alarm rate is 1 or 0, which

was present in the data we collected.

2.1.2.3. Procedure: All characters were shown in low contrast (Michelson contrast = .2)

to avoid ceiling effects. In each trial, participants were presented with a central fixation

cross for 1,000 ms, followed by a symbol indicating which half of the character (top or

bottom for TB characters; left or right for LR characters) they should attend to. They

were then presented with a pair of characters above and below the initial fixation, respec-

tively, for 500 ms, followed by a mask with alternating black and white pixels (Fig. 1b).

Both characters were about 2.5 degrees of visual angle away from the center, and each

character was approximately 1.5 9 1.5 cm in size with a viewing distance of 50 cm,

occupying around 1.7 degrees of visual angle. Participants judged whether the attended

halves of the two characters were the same or different as quickly and accurately as pos-

sible with a serial response box; their accuracy was collected and no feedback was given.

There were six blocks of test; each block had 80 trials; characters with different configu-

rations or in different script types were presented in different blocks. The sequence of

blocks was counterbalanced across participants while the four different types of trials

were randomized in each block. A practice session with characters not used in the materi-

als was given before the test. Participants were given ample time to rest between blocks,

and they started a new block on their own when they were ready. On average, the holistic

processing task took 40–45 min to finish.

2.1.3. Reading and writing performanceTasks assessing participants’ reading and writing abilities were adopted from Tso et al.

(2011, 2013) to examine whether the differences in holistic processing, if any, can be

attributed to these factors. Participants’ reading ability was assessed by a character nam-

ing task, in which they named the characters in their mother tongue (i.e., Mandarin for

Mainland China participants and Cantonese for Hong Kong participants). Their writing

ability was assessed by a character copying and a word dictation task. Summary of the

descriptive properties of the stimuli used in examining reading and writing performances


are presented in Table 3. All reading and writing assessment tasks were carried out after

the completion of the holistic processing task; breaks were given between tasks, and on

average it took 30–40 min to finish the reading and writing tasks (and hence less than

90 min to complete the entire study).

2.1.3.1. Character naming: The materials consisted of 120 Chinese characters, half with a

TB structure and the other half with a LR configuration. In either configuration, 20 charac-

ters were simplified characters, 20 were the corresponding traditional version of the simpli-

fied characters, and the remaining 20 were shared characters; these characters were not

used in the complete composite (holistic processing) task. All characters selected for the

naming task were of medium to high frequency (ranging from 28 per million to 1,316 per

million; Ho & Kwan, 2001) to mimic the day to day experience in speaking and reading in

Chinese; they were matched in relative frequency across the script types (F(2,117) = 1.69, p = .19). The traditional characters had significantly more strokes than the

simplified ones, (t(39) = 10.92, p < .01); in other words, they were more visually com-

plex. In each trial, after a 500 ms central fixation, participants were presented with a char-

acter occupying approximately 1.5 degrees of visual angle at the center of the screen, and

they were asked to read it out in front of a microphone. The onset of their pronunciation

was detected by a microphone attached to a serial response box. Their response time was

recorded as the duration between the onset of the character presentation and the onset of

the pronunciation. Upon their response, the screen turned blank and the experimenter

pressed buttons on a response box to record the accuracy and initiate the next trial.

2.1.3.2. Character copying: Participants copied 60 characters (20 shared, 20 simplified,

and 20 traditional) as quickly and as accurately as possible. The characters were

Table 3

Summary of the descriptive properties of the stimuli used in the character naming, copying, and dictation

tasks

Shared Simplified Traditional

TB LR TB LR TB LR

Character naming

Number 20 20 20 20 20 20

Mean complexity 9.9 7.7 7.6 7.5 13 14

Mean frequency (per million) 216 249 240 128 216 125

Character copying

Number 10 10 10 10 10 10

Mean complexity 14.7 19.1 14 9.2 20.7 19.6

Mean frequency (per million) 2.8 8.9 7.1 6 4.2 3

Word dictation

Number 10 10 10 10 10 10

Mean complexity (of target character) 9 9.4 8.7 9.1 17.9 19.8

Word frequency (per million) 273 385 167 197 189 211

Note TB, top–bottom; LR, left–right.


randomly selected from those used in the character naming task; half of them had a TB

structure, whereas the other half had a LR configuration. All characters were of low to

medium frequency (ranging from 2 per million to 26 per million) and were matched

in relative frequency across script types (F(2, 57) = 2.05, p = .14). High-frequency

characters were not used in the copying task to reduce the chance of ceiling effects.

The traditional characters had significantly more strokes than their simplified counterparts

(t(19) = 8.26, p < .01). In each trial, after a 500 ms central fixation, participants were

shown a stimulus at the center of the screen, occupying around 1.5 degrees of visual

angle, and were asked to copy it as quickly and as accurately as possible. After they fin-

ished copying, they pressed a button on a serial response box to signal completion and

the screen turned blank. Then the experimenter pressed buttons on a serial response box

to record the accuracy and to initiate the next trial. The 60 stimuli were presented in a

random order in one block.

2.1.3.3. Word dictation task: Forty characters (20 shared and 20 traditional/simplified)

were selected from the character naming task. Each character was concatenated with a

second character to compose a two-character word, and these words were used here.

Words instead of characters were used to avoid ambiguity, because a single Chinese char-

acter has around 11 homophones on average (Tan & Perfetti, 1998). All words were of

medium to high frequency (from 162 per million to 1,037 per million) to mimic the daily

experience of writing in Chinese (Taiwan Ministry of Education, 1997) and were matched

in relative word frequency across different script types (F(2, 57) = 2.77, p = .11). Partici-

pants listened to the words presented in a female voice in their native language, that is,

Cantonese for Hong Kong participants and Mandarin for Mainland China participants.

The audio recordings of the words were presented by a computer in a random order. Par-

ticipants wrote down each word in their own script first and then in the other script, even

if they thought the characters were the same in the two scripts. If they did not know how

to write a character, they indicated it by putting a cross on the space. In each trial, after

the words “get ready” were presented on the screen for 500 ms, participants were pre-

sented with a stimulus; they then pressed a button on a serial response box to indicate

whether they knew how to write it or not. After writing the word in both scripts, they

pressed a button to indicate completion and start of the next trial. Their accuracy of writ-

ing the first character of each word was assessed (to match the character naming task).

2.2. Results

In the A0 measure, repeated-measures ANOVA revealed main effects of congruency (F(1,46) = 68.89, p < .01, g2

p = .61) and character configuration (F(1, 46) = 26.08, p < .01,

g2p = .37). Participants did better in congruent (M = .98, SE < .01) than incongruent tri-

als (M = .94, SE = .01), and in processing LR (M = .97, SE = .02) than TB (M = .95,

SE = .02) characters. There was also a significant interaction between configuration and

congruency (F(1, 46) = 35.28, p < .01, g2p = .44). Participants were more holistic in

processing TB characters than LR characters; yet this effect did not interact with group


(F(1, 46) = .02, p = .89). In addition, there was a marginal three-way interaction between

script, congruency, and group (F(2, 92) = 2.94, p = .058, g2p = .06), suggesting that the

interaction between congruency and group might be different across the three script types.

Meanwhile, there was no main effect of group (F(1, 46) = 2.64, p = .11, g2p = .03). To

investigate how the two groups differed in processing different script types, we first com-

pared their behavior in processing shared characters, and then contrasted their perfor-

mance in perceiving simplified and traditional characters.

2.2.1. Shared charactersA main effect of congruency was found (F(1, 46) = 52.34, p < .01, g2

p = .53), but

there was no interaction between congruency and group (F(1, 46) = 2.05, p = .16,

g2p = .10), nor main effect of group (F(1, 46) = 2.01, p = .16, g2

p = .04; Fig. 3a), and

both groups demonstrated a similar level of holistic processing. This result suggests that

the two groups do not differ in holistic processing of shared Chinese characters because

they are both experts in reading shared characters.2

2.2.2. Simplified versus traditional charactersHere we contrasted the processing of simplified and traditional characters using

repeated-measures ANOVA with script type (simplified vs. traditional character), congru-

ency, character configuration, and group as the independent variables. The results

revealed main effects of congruency (F(1, 46) = 59.08, p < .01, g2p = .57) and character

configuration (F(1, 46) = 26.53, p < .01, g2p = .37). There was a marginal interaction

between congruency and group (F(1, 46) = 3.92, p = .054, g2p = .08): Simplified Chinese

readers tended to perceive the characters less holistically overall. There was also a three-

way interaction between script type, congruency, and group (F(1, 46) = 4.93, p < .05,

g2p = .10), suggesting the interaction between congruency and group was different

between the two scripts. No main effect of group was found (F(1, 46) = 2.19, p = .15,

g2p = .05). We then examined their performance in processing the two scripts separately.

A B C

Fig. 3. Performance of Mainland China and Hong Kong Chinese readers in the complete composite paradigm

with (a) shared Chinese characters, (b) simplified Chinese characters, and (c) traditional Chinese characters.


In processing simplified characters, as predicted, there was a main effect of congruency

(F(1, 46) = 36.35, p < .01, g2p = .44; Fig. 3b) and the interaction between congruency

and group (F(1, 46) = 6.51, p < .05, g2p = .12): Simplified Chinese readers processed

simplified characters less holistically than traditional Chinese readers, possibly due to

their expertise with simplified characters.

To examine whether the difference in holistic processing of simplified characters was

dependent on their reading and writing performance measures3 (Table 4), separate ANCO-

VAs were conducted with reading and writing task performances as covariates. We found

that the interaction between congruency and group was still significant when putting their

simplified character naming accuracy or RT as covariate (reading accuracy: F(1,46) = 4.76, p < .05, g2

p = .10; reading RT: F(1, 46) = 4.60, p < .05, g2p = .10). After

controlling for simplified character copying accuracy, the interaction between congruency

and group became marginal (F(1, 46) = 4.08, p = .05, g2p = .08). Only when we put sim-

plified character dictation accuracy as a covariate did the interaction become not signifi-

cant (F(1, 46) = .42, p = .52, g2p = .01). These results are consistent with Tso et al.’s

(2013) finding that the reduced holistic processing effect in expert Chinese character pro-

cessing may depend more on writing rather than reading or copying performance.

In contrast to the results with simplified Chinese characters, in processing traditional

characters, there was only a main effect of congruency (F(1, 46) = 50.48, p < .01,

g2p = .53), but no interaction between group and congruency (F(1, 46) = 0.20, p = .66;

Fig. 3c). This showed that the two groups processed traditional characters with a similar

level of holistic processing, regardless of their performance difference in reading and

writing traditional characters (Table 4). This result suggests that, while traditional Chi-

nese readers processed simplified characters more holistically than simplified Chinese

readers, possibly due to the lack of experience in reading and especially in writing sim-

plified characters, simplified Chinese readers were able to transfer their analytic process-

ing (reduced holistic processing) skills to the processing of traditional characters, even

Table 4

Mainland China and Hong Kong participants’ reading and writing performance in shared, simplified, and tra-

ditional Chinese characters

Task Script Type

Mainland China (Simplified

Chinese Readers)

Hong Kong (Traditional

Chinese Readers)

Accuracy RT (ms) Accuracy RT(ms)

Naming Shared 1.00 (0.00) 284.85 (16.97) 0.99 (0.00) 329.38 (12.30)

Simplified 0.99 (0.00) 280.74 (16.50) 0.97 (0.01) 354.10 (11.48)

Traditional 0.97 (0.01) 329.24 (14.91) 0.99 (0.00) 328.40 (13.20)

Copying Shared 0.96 (0.00) 0.96 (0.00)

Simplified 0.98 (0.00) 0.94 (0.00)

Traditional 0.65 (0.02) 0.94 (0.00)

Dictation Shared 0.99 (0.00) 0.98 (0.00)

Simplified 0.99 (0.00) 0.66 (0.05)

Traditional 0.21 (0.04) 0.99 (0.00)


though they particularly had difficulty in writing traditional characters, as reflected in

their copying and dictation performances.

3. Experiment 2

In Experiment 1, we compared holistic processing of Chinese characters in simplified

Chinese readers from Mainland China and traditional Chinese readers from Hong Kong.

Nevertheless, there are several noticeable differences in Chinese teaching methods

adopted in Mainland China and Hong Kong. For example, in Hong Kong, children learn

to read and write Chinese mainly through rote repetition and memorization (Cheung &

Ng, 2003), whereas in Mainland China, children are taught explicitly about character

components and rules of combination. As a result, simplified Chinese readers in the

Mainland may be generally more sensitive to the internal constituent components of char-

acters than traditional Chinese readers in Hong Kong (McBride-Chang et al., 2005). In

addition, Cantonese is the spoken language in Hong Kong, and Mandarin is spoken by

Mainland Chinese; the two spoken languages differ in various ways. For example, Can-

tonese has 19 onsets (initial consonants) and nine tones (six working), while Mandarin

has 21 onsets and four tones. Thus, their character reading performance may differ due to

the differences in the acoustic properties between the two spoken languages. In addition,

while Cantonese is the spoken language, the written Chinese is still based on Mandarin

words and grammar, which gives rise to the disparity between the oral and written lan-

guage in Hong Kong (Cheung & Ng, 2003). To rule out the influence from the teaching

methods and spoken languages in accounting for the current results, in Experiment 2 we

recruited traditional Chinese readers in Taiwan, where children are also taught about

character components explicitly and speak Mandarin, and compared their character pro-

cessing with the simplified Chinese readers’ behavior in Experiment 1.

3.1. Methods

Twenty-four native traditional Chinese readers from Taiwan participated in the study,

and their performance was compared with the Mainland Chinese participants recruited in

Experiment 1. All Taiwanese participants had passed the Chinese subtest of General

Scholastic Ability Test, which insured their proficiency level in traditional Chinese, and

they were recruited from National Taiwan University. The same questionnaire used in

Experiment 1 was adopted for participants to report their language background and expo-

sure; none of the participants had formal education about the other Chinese script, and

they reported being exposed to the other script for less than 10% of the text they encoun-

tered daily on average. Note that with increasing communication between Taiwan and

Mainland China, books published by Mainland China publishers in simplified Chinese

can be found in bookstores in Taiwan. In addition, the development and flourishing of

the Internet and social media platforms, such as Weibo (Mainland China’s equivalence to

twitter), have attracted users from Mainland China and Taiwan, and both simplified and


traditional Chinese characters are supported by these platforms, exposing users to both

scripts. In our experiment, simplified Chinese readers’ length of stay in Hong Kong was

significantly shorter than Taiwan participants’ years of education (F(1, 46) = 1204.13,

p < .001). Both Mainland China and Taiwan participant groups had a similar education

background (average years of education, Mainland China = 15.79, SE = .38; Tai-

wan = 15.79, SE = .35) and similar age (Mainland China = 22.71, SE = .70; Tai-

wan = 22.04, SE = .66). All of them had normal or corrected-to-normal vision and were

right-handed as measured by the Edinburgh Handedness Inventory (Oldfield, 1971). The

materials, design, and procedure used in Experiment 2 were identical to those used in

Experiment 1.

3.2. Results

ANOVA was used to analyze the data. There were three within-subject variables: congru-

ency, character configuration, and script type; and a between-subject variable: group. In

A0, repeated-measures ANOVA revealed main effects of congruency (F(1, 46) = 106.54,

p < .01, g2p = .70) and character configuration (F(1, 46) = 36.48, p < .01, g2

p = .45).

Participants did better in congruent (M = .97, SE = .01) than incongruent trials

(M = .93, SE = .01), and in processing LR (M = .96, SE = .01) than TB (M = .94,

SE = .01) characters. Similar to Experiment 1, there was a significant interaction between

configuration and congruency (F(1, 46) = 53.25, p < .01, g2p = .54), and it did not inter-

act with group (F(1, 46) = 1.53, p = .22, g2p = .03). There was also a significant three-

way interaction between script, congruency, and group (F(2, 92) = 3.74, p < .05,

g2p = .08), suggesting that the interaction between congruency and group was different

across the three script types. Similar to the results in Experiment 1, no significant main

effect of group was found, although it was marginal (F(1, 46) = 3.16, p = .09, g2p = .06).

To investigate how the two groups differed in processing different script types, we

first compared their behavior in processing shared characters, and then contrasted

their performance in processing simplified versus traditional characters as performed in

Experiment 1.

3.2.1. Shared charactersA main effect of congruency was found (F(1, 46) = 50.67, p < .01, g2

p = .52), but

there was no interaction between congruency and group (F(1, 46) = .82, p = .37,

g2p = .02), nor main effect of group (F(1, 46) = .78, p = .38, g2

p = .02; Fig. 4a). The

results echoed the findings in Experiment 1: Both groups demonstrated a similar level of

holistic processing because they are both experts in reading shared characters (Table 5).4

3.2.2. Simplified versus traditional charactersRepeated-measures ANOVA revealed main effects of congruency (F(1, 46) = 75.50,

p < .01, g2p = .63) and character configuration (F(1, 46) = 27.64, p < .01, g2

p = .38),

but no significant main effect of group, although it was marginal (F(1, 46) = 3.42,

p = .08, g2p = .08). There was also a significant interaction between congruency and


group (F(1, 46) = 4.63, p < .05, g2p = .10): Mainland China simplified Chinese readers

tended to perceive both characters less holistically overall; and a three-way interaction

between script type, congruency, and group (F(1, 46) = 7.25, p < .05, g2p = .14), suggest-

ing that the interaction between congruency and group was different between the two

scripts. Below we examined their performance in processing the two scripts separately.

In processing simplified characters, as predicted, there was a main effect of congruency

(F(1, 46) = 45.55, p < .01, g2p = .50; Fig. 4b), and the interaction between congruency

and group was significant (F(1, 46) = 8.95, p < .01, g2p = .16): Simplified Chinese read-

ers processed simplified characters less holistically than traditional Chinese readers, possi-

bly due to their expertise with simplified characters.

Again the two groups differed in some reading and writing performance measures in

processing simplified characters5 (Table 5); to examine whether the difference in holistic

processing of simplified characters was dependent on these measures, we put them as

A B C

Fig. 4. Performance of Mainland China and Taiwan Chinese readers in the complete composite paradigm

with (a) shared Chinese characters, (b) simplified Chinese characters, and (c) traditional Chinese characters.

Table 5

Mainland China and Taiwan participants’ reading and writing performance in shared, simplified, and tradi-

tional Chinese characters

Task Script Type

Mainland China (Simplified

Chinese Readers)

Taiwan (Traditional Chinese

Readers)

Accuracy RT(ms) Accuracy RT(ms)

Naming Shared 1.00 (0.00) 284.85 (16.97) 0.99 (0.00) 358.95 (9.86)

Simplified 0.99 (0.00) 280.74 (16.50) 0.93 (0.01) 406.10 (10.78)

Traditional 0.97 (0.01) 329.24 (14.91) 0.98 (0.00) 373.10 (9.00)

Copying Shared 0.96 (0.00) 0.98 (0.01)

Simplified 0.98 (0.00) 0.89 (0.02)

Traditional 0.65 (0.02) 0.98 (0.01)

Dictation Shared 0.99 (0.00) 1.00 (0.01)

Simplified 0.99 (0.00) 0.32 (0.03)

Traditional 0.21 (0.04) 0.99 (0.00)


covariates in separate ANCOVA tests. We found that the interaction between congruency

and group was still significant when putting either their simplified character naming RT

(F(1, 46) = 5.07, p < .05, g2p = .10) or simplified character copying accuracy (F(1,

46) = 4.60, p < .05, g2p = .10) as covariates. The interaction between congruency and

group became not significant after controlling for their simplified character naming accu-

racy (F(1, 46) = 2.01, p = .11, g2p = .05), suggesting reading accuracy of simplified Chi-

nese characters might play a role in explaining the difference in holistic processing of

simplified Chinese characters between Mainland China and Taiwan participants. This phe-

nomenon was in contrast to the results of Hong Kong participants, in which the interac-

tion between congruency and group remained significant after controlling for their

simplified character naming accuracy. This difference between Hong Kong and Taiwan

participants may be due to a larger difference in reading accuracy of simplified Chinese

characters between Mainland China and Taiwan participants (.99 vs. .93) than between

Mainland China and Hong Kong participants (.99 vs. .97). In addition, after controlling

for their simplified character dictation accuracy, the interaction effect became not signifi-

cant (F(1, 46) = 1.91, p = .23, g2p = .07). This result was consistent with what we found

in Mainland China and Hong Kong participants, and it is also consistent with Tso et al.’s

(2013) finding that the reduced holistic processing effect in expert Chinese character

processing may depend on writing (dictating) performance.

In contrast, in processing traditional characters, there was only a main effect of con-

gruency (F(1, 46) = 50.92, p < .01, g2p = .53), but no interaction between group and con-

gruency (F(1, 46) = 0.10, p = .99; Fig. 4c). This suggests that the two groups processed

traditional characters with a similar level of holistic processing, regardless of their perfor-

mance difference in reading and writing traditional characters. These findings were con-

sistent with what we found between Mainland China and Hong Kong participants,

suggesting that simplified Chinese readers were more capable of transferring their analytic

processing skill to the processing of the characters in the script unfamiliar to them.

4. Discussion

4.1. Behavioral findings

Experiments 1 and 2 examined whether simplified and traditional Chinese readers pro-

cessed Chinese characters differently in terms of holistic processing, and whether they

were able to transfer their analytic (reduced holistic) processing skills to the script unfa-

miliar to them. The results showed that, first, when processing characters that are identi-

cal in the two scripts (shared characters), simplified Chinese readers and traditional

Chinese readers did not differ in holistic processing, most likely because they were both

experts in reading shared characters. In other words, simplified Chinese readers do not

seem to process shared characters more analytically than traditional Chinese readers due

to their experience in reading simplified Chinese characters, as assessed through the com-

plete composite paradigm. This result is in contrast to Peng et al.’s (2010) finding, which


suggests that simplified Chinese readers may be more analytic in processing shared char-

acters than traditional Chinese readers. More specifically, Peng et al. (2010) showed that

in simplified Chinese readers, shared characters elicited larger ERP P300 amplitude than

noncharacters that differed from the shared characters by one stroke; in contrast, such

effect was not observed in traditional Chinese readers. Perhaps the difference in analytic

processing of shared characters between simplified and traditional Chinese readers is at

the stroke level, and thus the composite paradigm, which examines selective attention to

parts/components, is not sensitive to such difference.

Second, we found that when processing simplified characters, simplified Chinese read-

ers from Mainland China were less holistic than traditional Chinese readers from Hong

Kong and Taiwan, and the difference seemed to be more dependent on their word dicta-

tion performance than naming or copying performances. This finding is consistent with

Tso et al.’s (2011, 2013) studies, which showed a close relationship between writing

experience and reduced holistic processing in Chinese character recognition. More specifi-

cally, they showed that compared with novices, proficient Chinese readers who had lim-

ited writing experience showed increased holistic character processing, whereas proficient

Chinese readers who were also proficient in writing characters showed reduced holistic

processing. Thus, writing, or more specifically dictation, the ability to recall and write

Chinese characters from memory, seems to enhance analytic (reduce holistic) character

processing. This finding suggests a close relationship between perceptual and sensorimo-

tor processing in visual word recognition (see, e.g., James & Atwood, 2009).

Third, although simplified Chinese readers performed worse in writing (dictating) tradi-

tional characters than traditional Chinese readers, their performance in holistic processing

of traditional characters did not differ from traditional Chinese readers. This effect sug-

gests that writing experience might not be the only attribution to reduced holistic process-

ing in Chinese characters. The data reveal that simplified Chinese readers are able to

transfer the analytic processing skills acquired in learning to read and write simplified

characters to the processing of traditional characters, indicating that holistic processing

can be influenced by transfer effect in addition to writing experiences. However, the

transfer is asymmetrical; while simplified Chinese readers can transfer the analytic pro-

cessing skills to the processing of traditional Chinese characters, traditional Chinese read-

ers could not do so in perceiving simplified Chinese characters. This finding is consistent

with the results of McBride-Chang et al.’s (2005) study, which showed that children who

learned to read simplified Chinese characters had better visual skills in matching line

drawings or geometric forms (including Visual Closure, Visual Discrimination, and

Visual Spatial Relationships subtests from Gardner, 1996) than those who learned to read

traditional Chinese characters. Taken together, these findings seem to suggest that simpli-

fied Chinese readers are more able to transfer their analytic processing skills acquired

from reading and writing simplified Chinese characters to unfamiliar/novel stimuli, such

as traditional Chinese characters, or line drawings/geometric forms. Thus, transfer of per-

ceptual expertise effects between two categories is not always symmetrical; it may

depend on the perceptual representation developed as the result of one’s learning experi-

ence of a category. We explore this possibility below.


4.2. Visual similarity analysis of the characters in the two scripts

Since writing experience could not account for the asymmetrical transfer effect, this

asymmetric transfer effect may be related to the differences in visual forms between sim-

plified and traditional characters. As discussed in the Introduction, Chen (1999) pointed

out that there are fewer strokes in simplified characters than their traditional counterparts,

and this could make them visually more distinct from each other as compared with tradi-

tional Chinese characters. Zhao and Baldauf (2011) also suggested that simplification of

some of the original traditional script with variations in rules might increase the variance

among the simplified script.

To examine whether the visual form representation of simplified characters indeed has

a larger variance than that of traditional characters, we conducted a visual similarity anal-

ysis on a set of most frequently used characters (Ho & Kwan, 2001). From the set, we

identified 1,492 simplified characters and 3,131 shared characters; then we included the

corresponding 1,492 traditional characters into the set. The set therefore contained the

most frequently used simplified, traditional, and shared characters, forming a representa-

tive Chinese character space; in total there were 6,115 characters. We generated an image

for each character in Ming font (the most common font in print); each image was

40 9 40 pixels in size. To obtain an estimated mental representation of the characters at

an early perceptual stage, we used overlapping 2D Gabor filters to filter the images,

because Gabor filter responses were found to be a good approximation of the neural

responses in the human primary visual cortex V1 (Sanger, 1989). At each pixel there

were Gabor filters of five frequency scales and eight orientations; the five scales corre-

sponded to 2–32 (21–25) cycles per character (see, e.g., Hsiao & Lam, 2013; Hsiao,

Shieh, & Cottrell, 2008). After obtaining the Gabor representation of each character

image, principal component analysis (PCA) was then conducted on this set of images.

PCA is a generic, biologically plausible linear compression technique for dimensionality

reduction (Sanger, 1989), and it has been commonly used to simulate possible informa-

tion extraction processes in the brain in computational models of human cognition (e.g.,

Hsiao & Lam, 2013; Hsiao et al., 2008; Tong, Joyce, & Cottrell, 2008). Fig. 5 shows the

representations of the traditional and simplified characters based on the first two principal

components. (The shared characters were not plotted in order to better illustrate the

difference between the traditional and the simplified characters.)

The PCA plot showed that the representations of the traditional and simplified charac-

ters overlapped with each other, suggesting a high visual similarity between the two. In

addition, characters in the traditional character set (including both traditional and shared

characters) were less spread out than those in the simplified character set (including both

simplified and shared characters): The traditional character set had a smaller variance

(0.0080) as compared with the simplified character set (0.0084); similar results were

obtained when we changed the font from Ming font (the most frequently used font in

print) to Kai (less frequently used in print) (traditional character set: 0.0077; simplified

character set: 0.0081) or Feng fonts (not commonly used in print) (traditional character

set: 0.0082; simplified character st: 0.0083). To quantitatively test the difference between


the two sets in the spread of distribution, for each character in a set, we calculated the

average distance between this character and all the other characters from the same set.

Thus, in total we had 4,623 observations (one for each character) from the traditional set

and 4,623 observations from the simplified set. We then compared these distances in the

two character sets using paired t-test. The comparisons were done on Ming, Kai, and

Feng font characters separately. Table 6 summarizes the results. The results showed that

across all three font types, the average distance from each character to all the other char-

acters in the character set was significantly larger in the simplified Chinese character set

than in the traditional Chinese character set. This result was consistent with the PCA plot

(Fig. 5), indicating that the representation of the traditional characters was more con-

densed (i.e., had a smaller variance), whereas that of the simplified characters was more

spread out (i.e., had a larger variance).

To quantify the proportion of the distributions that were overlapped with each other,

for the distribution of each character set, we estimated a Gaussian distribution from the

Table 6

The average distance between each character and all the other characters in the same character set, separately

for the simplified and traditional character set. In all character sets with different font types, the simplified

character set had a significantly larger average distance among characters as compared with the traditional

character set (Paired t-test, MING: t(4622) = 56.85, d = 0.52, CI [.0029, .0031], p < .001; FENG: t(4622) = 27.93, d = 0.69, CI [.0011, .0012], p < .001; KAI: t(4622) = 65.86, d = 0.25, CI [.0032, .0034],

p < .001)

Simplified Chinese Traditional Chinese pMing Font .13 .12 <.001Kai Font .13 .12 <.001Feng Font .13 .12 <.001

Fig. 5. Results of the PCA of 1,175 simplified and 1,175 traditional Chinese characters in Ming font, the

most common font used in prints. The two dimensions represent the first two principal components (i.e., with

the highest eigenvalues, or in other words, the dimensions with the largest variance). The red dots represent

simplified Chinese characters, and the blue dots represent traditional Chinese characters.


data, and measured the percentage of overlap between the two Gaussian distributions in

the area within two standard deviations from the mean. More specifically, for the area

within two standard deviations from the mean in the two Gaussian distributions, we cal-

culated the percentage of overlap as the intersection of the two distributions divided by

the union of the two distributions. The union represented the area occupied by either tra-

ditional or simplified character distributions, whereas the intersection represented the area

occupied by both traditional and simplified character distributions. Using this method, we

found that the proportion of overlap between the two distributions was 0.79. Thus, the

two distributions were highly overlapped, with the distribution of traditional characters

having a smaller variance than that of simplified characters.

Fig. 6 shows a similar PCA plot with only the characters used in the current study. It

can be seen that the distributions of the used characters resembled those of the whole

character sets: The two distributions were largely overlapped, with the distribution of the

simplified characters being more spread out than that of the traditional characters.

Thus, due to the overlap between the representations of the simplified and traditional

characters (which suggests high similarity in feature), and a larger variance in the repre-

sentation of the simplified characters, simplified Chinese readers may be more able to

interpolate and generalize their analytic skills developed in reading and writing simplified

characters to reading traditional characters, as compared with traditional Chinese readers

in reading simplified characters (cf. Tong et al., 2008). The results of our visual similarity

analysis supported the speculation that simplification of Chinese characters made them

physically more distinctive than their traditional forms (Chen, 1999). The advantage of

having a visually more distinctive (or in other words, with a larger variance) set of char-

acters in one’s mental lexicon seems to be in the ease of transferring analytic processing

skills to unfamiliar characters with similar structures, as reflected in the generalization

abilities observed in simplified Chinese readers.

Fig. 6. Results of the PCA of 160 simplified and 160 traditional Chinese characters used in the current study.

The red dots represent simplified Chinese characters, and the blue dots represent traditional Chinese characters.


Tanaka, Curran, and Sheinberg (2005) trained participants to recognize different types of

birds and showed that training at the subordinate (species) level better facilitates perceptual

expertise transfer to novel exemplars and novel categories than training at the categorical

(family) level. Through computational modeling, Tong et al. (2008) further showed that the

advantage of training at the subordinate level in perceptual expertise transfer lies in the

magnification of differences between exemplars within a category (i.e., a larger variance) in

one’s perceptual representation as the result of the subordinate-level training, making it

easier to discriminate novel exemplars or exemplars in novel categories. Although in Tong

et al.’s (2008) simulation, the difference in variance of perceptual representation was

observed at the hidden layer level of a neural network (i.e., an intermediate perceptual rep-

resentation), whereas in the current study, our analysis was performed at an earlier percep-

tual level based on Gabor filter responses; both cases demonstrate the advantage of a more

spread-out perceptual representation in the transfer of perceptual expertise. This effect sug-

gests that in perceptual expertise acquisition, different learning experiences, such as learn-

ing to recognize objects at the subordinate level versus the categorical level, or learning to

read simplified versus traditional Chinese characters, can lead to different transfer effects

due to differences in the perceptual representation developed as the result of one’s learning

experience; the type of learning experience that enhances exemplar variance in the presenta-

tion seems to facilitate transfer of perceptual expertise effects.

4.3. Other possible explanations of the transfer effect

Recent research has suggested an advantage of training with simpler forms, as opposed

to complex forms, in the transfer effect to new situations in relational learning. This find-

ing might also be related to the asymmetric generalization effect observed in the process-

ing of simplified and traditional Chinese characters. For example, research done in

mathematics and science has revealed that training with simple instances yields better

transfer effects to new situations than training with more complex exemplars (e.g., Gold-

stone & Sakamoto, 2003; Goldstone & Son, 2005; Kaminski, Sloutsky, & Heckler, 2008).

This might be because simple exemplars enable selective attention to the right informa-

tion essential for generalization of knowledge rather than to the irrelevant details in the

complex exemplars. As discussed in the Introduction, the simplification process of Chi-

nese characters involved trimming down some strokes in the components or removing

some components within characters, aiming to ease the recognition and production of the

characters. This simplification process may have implicitly preserved parts of the tradi-

tional characters that are essential for recognition/discrimination while removing less

informative parts. In addition, since simplified characters typically preserve part of their

traditional counterparts, when a simplified Chinese reader attempts to read a traditional

character, a common strategy may be to look for familiar components or parts of the

components within the traditional characters. This strategy may encourage the engage-

ment of local attention, leading to a similar level of analytic processing as traditional Chi-

nese readers. In contrast, when a traditional Chinese reader reads a simplified character,

he or she may take the holistic pattern of the simplified character and try to see whether


it matches part of a traditional character, leading to an increased holistic processing effect

as compared with simplified Chinese readers. This asymmetric generalization effect of

reduced holistic processing between traditional and simplified Chinese readers is consis-

tent with a recent finding by Thai and Son (2013). They found that training novices with

simplified Chinese characters produced better generalization to the recognition of the cor-

responding characters in the other script than training with traditional characters. The

ways that simplified characters were created might be related to this asymmetrical gener-

alization effect. Future work will examine this possibility.

In a recent study, McBride-Chang et al. (2011) found that literacy experiences may

influence visual spatial skills, and that literacy experiences with different orthographies

may shape different aspects of visual spatial skills. This finding is consistent with the cur-

rent results, which showed that simplified and traditional Chinese readers had different

transfer effects in holistic/analytic processing of characters in the two Chinese written

systems due to the difference in their experience with the orthographies. McBride-Chang

et al. (2011) also suggested a bidirectional association between visual-spatial skills and

the process of learning to read (see also Zhou, McBride-Chang, & Wong, 2014). Accord-

ingly, it is possible that a better ability to transfer analytic processing of characters in a

script to a new script with similar character structures can facilitate learning to read in

the new script. This possibility requires further investigation.

In conclusion, here we show that reduced holistic processing of Chinese characters can

be influenced by transfer effect, in addition to sensorimotor experience as reported previ-

ously (Tso et al., 2014). Expertise in reading and writing simplified Chinese characters

seems to facilitate readers to transfer their analytic processing skills to the processing of

traditional Chinese characters, as compared with traditional Chinese readers in processing

simplified characters. This asymmetric transfer effect between the two groups of readers

may be related to a larger variance in the visual forms of simplified characters than those

of traditional characters. This finding suggests that transfer of perceptual expertise effects

in visual recognition may be constrained by both the similarity in feature and the differ-

ence in exemplar variance between visual categories. It also has important implications

for teaching and learning in perceptual expertise acquisition. For example, a learning pro-

gram that implicitly enhances exemplar variance in one’s perceptual representation, such

as the subordinate-level training used in Tanaka et al. (2005), or with explicit instructions

to direct learners’ attention to largest variations among exemplars, may facilitate transfer

of perceptual expertise effects to novel exemplars or stimuli with similar features in a

novel category.

Acknowledgments

We are grateful to the Research Grant Council of Hong Kong (project #HKU 745210H

and #HKU 758412H to J.H. Hsiao). We thank Nick Wang for his suggestions about com-

paring simplified and traditional Chinese reading. We thank the Editor and three anony-

mous reviewers for helpful comments.


Notes

1. Wong et al. (2012) showed that Chinese readers (experts) had a stronger holistic

processing effect in processing real Chinese characters than noncharacters (i.e.,

nonexisting characters consisting of real Chinese character components in illegal

positions), whereas non-Chinese readers (novices) did not show this effect; this

suggests that holistic processing in Chinese character recognition may also be influ-

enced by familiarity with the component positions.

2. The two groups of readers did not differ significantly in accuracy in naming

(F(1, 46) = 3.61, p = .07), copying (F(1, 46) = .11, p = .74), or dictating the

shared Chinese characters (F(1, 46) = 3.29, p = .08). However, Mainland China

simplified Chinese readers were faster than Hong Kong traditional Chinese readers

in naming the shared characters (F(1, 46) = 4.83, p < .05). This difference may be

due to the pronunciation differences between Cantonese (spoken by Hong Kong

participants) and Mandarin (spoken by Mainland China participants). It may also

be related to greater confusion in pronunciation in Hong Kong participants due to

their knowledge of both Cantonese and Mandarin pronunciations of the characters

as Mandarin has become more popular in Hong Kong than before. Note that two

shared characters were removed from analysis based on the item analysis of partici-

pants’ reading accuracy of each character, since the average accuracy of the two

characters were below 2 standard deviations from the mean accuracy of Mainland

China and Hong Kong participants’ performance (0.99).

3. When we compared the two groups, Mainland China participants were more accu-

rate (F(1, 46) = 18.76, p < .001) and faster (F(1, 46) = 13.77, p < .01) in naming

simplified Chinese (one outlier was removed from the analysis according to the item

analysis of participants’ reading accuracy of each character), whereas Hong Kong

participants were more accurate (F(1, 46) = 11,31, p < .01), but not significantly

faster (F(1, 46) =.73, p = .40) in naming traditional Chinese characters. Note, how-

ever, this effect was due to a main effect of group in naming RT of all three types of

characters (F(1, 46) = 6.22, p < .05): Mainland China participants in general had

shorter naming RT than Hong Kong participants (see note 2, for reference). When

we examined their naming performance within each participant group, Mainland

China simplified Chinese readers were more accurate (t(23) = 4.04, p < .01) and

faster (t(23) = 3.57, p < .01) in naming simplified than traditional Chinese charac-

ters, whereas Hong Kong participants were faster (t(23) = 4.25, p < .001) and more

accurate (t(23) = 4.93, p < .001) in naming traditional than simplified Chinese char-

acters. Thus, both groups of participants were more proficient in reading the script

they are more familiar with. In the writing tasks, Mainland China participants were

more accurate in copying (F(1, 46) = 12.83, p < .01) and dictating (F(1,46) = 37.09, p < .001) simplified Chinese characters than Hong Kong participants,

while Hong Kong participants were more accurate in copying (F(1, 46) = 91.75,

p < .001) and dictating (F(1, 46) = 442.29, p < .001) traditional Chinese characters


than Mainland China participants. Thus, both groups of participants were more profi-

cient in writing the script they are more familiar with.

4. Mainland China simplified Chinese readers and Taiwan traditional Chinese readers

did not differ in accuracy in naming (F(1, 46) = 3.85, p = .06) or dictating shared

characters (F(1, 46) = 3.43, p = .07). However, in the copying task, Taiwan partic-

ipants performed slightly but significantly better than Mainland China participants

(F(1, 46) = 6.05, p < .05; mean accuracy: Mainland China = 96%, Tai-

wan = 98%). Similar to the results in Experiment 1, Mainland China simplified

Chinese reader were faster than Taiwan traditional Chinese readers in naming

shared Chinese characters (F(1, 46) = 13.13, p < .01). This effect might be attribu-

ted to the widely used Minnan dialect in Taiwan in addition to Mandarin, which

may lead to greater confusion in pronunciation in Taiwan participants because of

their knowledge of both the Minnan and Mandarin pronunciations of the characters.

Note that three shared characters were removed from the analysis based on the item

analysis of participants’ reading accuracy of each character, since the average accu-

racy of the three characters was below two standard deviations from the mean

accuracy of Mainland China and Taiwan participants’ naming performance (0.99).

5. In between group comparisons, Mainland China participants were more accurate (F(1,46) = 34.24, p < .001) and faster (F(1, 46) = 42.84, p < .001) than Taiwan partici-

pants in naming simplified Chinese characters. In contrast Taiwan participants were

more accurate (F(1, 46) = 4.92, p < .05), but slower (F(1, 46) = 42.84, p < .001) in

naming traditional Chinese characters (two characters were identified as outliers and

removed from the analysis according to the item analysis of participants’ reading

accuracy of each character). Note, however, that there was a main effect of group in

naming RT of all three types of characters (F(1, 46) = 13.65, p < .01): Mainland

China participants in general named characters faster than Taiwan participants (see

note 10 for reference). When we examined their naming RT within each group sepa-

rately, Mainland China participants named simplified characters more accurately (t(23) = 4.16, p < .001) and faster (t(23) = 3.61, p < .01) than traditional charac-

ters, and Taiwan participants were more accurate (t(23) = 4.79, p < .001) and faster

(t(23) = 3.60, p < .01) in naming traditional than simplified characters. In the writing

tasks, Mainland China participants were more accurate in copying (F(1, 46) = 21.44,

p < .001) and dictating (F(1, 46) = 421.34, p < .001) simplified Chinese characters

than Taiwan participants, while Taiwan participants were more accurate in copying

(F(1, 46) = 133.62, p < .001) and dictating (F(1, 46) = 443.29, p < .001) traditional

Chinese characters than Mainland China participants. Thus, both groups of partici-

pants were more proficient in writing the script they are more familiar with.

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