2 0 1 44 6 2 2 5 1 - 2 7 0

DOI10.6251/BEP.20140402

151

10% 20~30% 15%

5900

CDE

Rayner & Pollatsek, 1989

1. hue@ntu.edu.tw

2. NSC100-2410-H-002-056-MY2

252

1 123paragraph4

contextCunningham, 1976Carver, 1994

Lo, Hue, & Tsai, 2007

1999200212345

19991955

1000 472 1140

1919

1993 10 554,478 4,261 1932193012,687 207,246 2 12 36 303,941 5,364

1word character

word character word

253

1 3799

541558654793622 631 1955 24 2546

200197 700-800 1500-1800 2200-2700 3500-4500

2012

1

20012

2002 120 34 10 5998 200

1

Lo 20072

254

Tsai, Lee, Lin, Tzeng, & Hung, 2006

1231955 10 2004

151

10928 14

4937 65 12.65 5.65

12319 23 4 8

12 1. 12 2. 12 3. 12 4. 12 2 4

1 3

255

LimeSurvey 2.0Schmitz, 2012

1 / 5.602.43 5.912.33 5.822.86 6.102.53 6.052.15 6.072.50 7.641.75 7.302.27 7.472.07 8.051.32 7.951.47 7.731.39 4.142.21 4.522.37 4.412.06 5.502.04 5.212.46 5.871.81 3.552.20 3.782.70 3.182.13 4.351.93 3.681.86 4.301.93 5.522.17 6.222.09 5.712.26 5.702.23 6.682.00 5.872.36 4.122.32 4.222.26 3.411.87 3.701.89 3.842.03 3.732.21 5.192.96 3.962.57 5.412.90 2.852.41 3.892.85 3.873.33 5.362.48 5.222.56 5.242.54 5.402.41 4.582.32 4.001.68 3.882.20 3.871.94 4.352.03 3.352.23 3.111.88 3.572.31

256

1

Lord1953the numbers do not know where they are from 1 9 1 2 9

M = 7.48

SD = 1.72b = 0.06t149= 0.85p = .40

M = 5.89SD = 2.43b = -0.09t149= 0.89p = .37M = 4.89SD = 2.23b = 0.34t149= 3.67p < .001M = 3.81SD = 2.15b = 0.13t149= 1.45p = .15

M = 5.89SD = 2.19b = 0.09t149= 0.93p = .35M = 3.89SD = 2.13b = -0.09t149= 0.93p = .35

M = 4.96SD = 2.35 b = -0.24t149= -2.43p = .02M = 4.29SD = 2.97 b = -0.27t149= -2.19p = .03M = 3.70SD = 2.13 b = -0.11t149= -1.22p = .22

4 t

257

M = -0.18SD = 1.10

t18= -0.73p = .47M = 0.18SD = 0.51t18= 1.59p = .13

M = 0.06SD = 0.93t16= 0.26p > .10

2 /

-2.131.23*** -2.390.93*** -1.741.02*** -1.770.62*** -1.660.85*** -1.451.18***

-2.200.96*** -2.240.98*** -1.880.84*** -1.801.02*** -1.530.86*** -1.531.17***

-1.581.07*** -1.671.26*** -1.210.97*** -1.421.02*** -1.211.06*** -1.481.06***

-1.231.08*** -1.331.12*** -1.090.81*** -1.230.87*** -1.260.79*** -1.371.07***

-1.880.92*** -2.000.80*** -1.561.12*** -1.351.09*** -1.471.14*** -1.651.25***

-1.141.01*** -1.111.04*** -1.030.74*** -0.950.93*** -0.920.87*** -1.071.02***

-1.360.99*** -1.611.21*** -1.150.91*** -0.651.20*** -0.181.10*** -0.400.99***

-0.691.01*** -0.780.99*** -0.710.90*** -0.470.94*** -0.180.51*** -0.420.64***

-0.180.63*** -0.330.72*** -0.060.93*** -0.350.78*** -0.080.58*** -0.500.63***

-0.360.66*** -0.390.69*** -0.060.90*** -0.450.72*** -0.080.58*** -0.480.69***

-0.570.63*** -0.650.96*** -0.180.98*** -0.650.69*** -0.080.58*** -0.550.66****p < .05**p < .01***p < .001

12

2001 5900

258

C-CATLo & Hue, 2008; Lo, Hue, & Tseng, 2012

123

2

102 12 36 475 209,445 character tokens 3,390 character types2002

265 354 53 76 1500 10

3

/ A B C AB

BC

AC

ABC

ABC

290 1,756

302 1,393

276 1,262

158 2,411

148 2,002

140 2,227

104 2,908

526 4,411

731 7,291

784 7,147

744 6,376

500 13,018

504 12,169

506 12,455

414 17,942

1,163 20,814

1,212 17,529

1,275 16,611

1,250 16,235

916 32,133

914 30,941

894 31,944

783 46,304

1,796 50,375

1,667 30,813

2,001 31,771

1,727 29,732

1,379 60,073

1,397 59,027

1,300 58,428

1,182 87,138

2,501 92,316

2,160 49,137

2,517 52,388

2,194 49,232

1,830 98,855

1,882 99,153

1,748 96,170

1,616 145,243

3,027 150,757

2,520 68,979

2,847 72,376

2,589 68,090

2,187 138,755

2,229 137,875

2,123 134,815

1,973 203,791

3,390 209,445

21 5900

9 2123

http://crl.psy.ntu.edu.tw/characAnalysis

259

526 104 526 78 1500 212 10 2,52068,9792,84772,376 2,58968,090 10% 36 1,973 60%

6.671.545.341.404.341.393.261.312.321.31 1.721.25 17%

15% 33% 30%

9.703.9611.284.4112.654.3212.654.3212.714.50 12.904.5532% 35% 50% 49% 30% 33% 39% 37%

0.260.170.120.080.08 0.07

260

2

261

3

12

Carver, 1994Hu & Nation, 2000; Mohammadi & Keshavarz, 20092-5%

ABC 36 A 158 B 159 C 158

3 1r = -.29

262

2

.80 .90

3

475 4

children-centereddifficultyeconomyCDE CDE CDE

CDE 1 0 z

z z z CDE CDE

1 7.485.894.294.962z CDE 5.655CDE CDE

4 1.00 0.92 1.00 0.87 0.90 1.00 0.87 0.83 0.76 1.00 -0.27 -0.26 -0.24 -0.24 1.00 0.22 0.23 0.20 0.24 -0.29 1.00

CDE

.99 .99 .99CDEABC CDE 21.877.3719.106.8621.445.6512.504.8813.235.5012.833.787.113.476.093.996.763.931.485.27-1.132.720.133.71-5.184.83-6.855.17-3.654.40-7.194.47-10.464.59-9.873.45 CDE

CDE

CDE

263

1 CDE confidence band CDE 2 CDE CDE

CDE CDE

12 CDE quartileinter quartile rangeIQR 12 CDE CDE 12 CDE inter quartile rangeIQR CDE CDE

C 3 CDE 14.36 12 CDE 4.226.578.21 IQR 3.99 CDE 6.57 + 3.99 = 10.56 1320 462 5 659 183 8 CDE A 1 CDE-8.42 12 CDE 2.846.246.85IQR = 4.00 CDE 6.24 4.00 = 2.24 31 12 18 38 26 17

ABC 3321 23 CDE 1598 181215

264

4 CDE CDE CDE

265

19281930

10% 20~30%

15%

CDE CDE readability

CDE

Yang, Fan, Di, Havlin, & Wu, 2013

266

1955[Ai, W. (1955). Issues in Chinese characters learning.

Taipei, Taiwan: Chung Hwa.]

1930[Wang, W. H. (1930). Study of Chinese Characters

taught in different elementary school grades. Shanghai, China: Ming Chi.]

2012569-70[Ho, Y. H. (2012). Misconceptions

concerning materials used in elementary school textbooks. New Taipei City Education, 5, 69-70.]

20011423-32[Lin, K.

L. (2001). A brief history of National Institute for Compilation and Translation in editing

elementary school Chinese textbooks. National Institute for Compilation and Translation News

Bulletin, 14, 23-32.]

2001 ROCLING

[Ma, W. Y., Hsieh, Y. M., Yang, C. H., & Chen, K. C.

(2001). Construction of Chinese corpus and design of its management system. Proceedings of

Research on Computational Linguistics Conference 2001. Tainan, Taiwan. ]

2002[National Languages

Committee (2002). Characters and words used by elementary school students. Taipei, Taiwan:

Ministry of Education. ]

1928[Chen, H. C. (1928). Vocabularies in vernacular

Chinese. Shanghai, China: Commercial Press.]

2004

27193-115[Yeh, S. L., Lin, Y. H., & Li, C. L. (2004). Role of character

structure in judgments of visual similarity of Chinese characters for children in elementary school.

Journal of Education & Psychology, 27(1), 93-115.]

1932[Yeh, S. T. (1932). Kai-Ming elementary Chinese

textbook. Shanghai, China: Kai-Ming. ]

2002

33345-377[Yeh, S. H. (2002). Research on the teaching materials of the characters learning

for the examined first volume of the Chinese textbooks adopted in the nine-years top-to-down

curriculum implementation. Journal of Taipei Municipal Teachers College, 33, 345-377.]

1999[Tai, R. C., Tse, S. K., & Hao,

C. J. (1999). Teaching and learning of Chinese characters. Shangtung, China: Shangtung Education.]

267

1993[Tai, B. Y. (1993). Language education in

elementary school. Zhejiang, China: Zhejiang Education Publishing House.]

2002[Tse, S. K. (2002). Comprehensive and

effective teaching and learning of Chinese characters. Hong Kong, Hong Kong: Greenfield

Enterprise Ltd.]

Carver, R. P. (1994). Percentage of unknown vocabulary words in text as a function of the relative

difficulty of the text: Implications for instruction. Journal of Literacy Research, 26, 413-437.

Cunningham, J. W. (1976). Metaphor and reading comprehension. Journal of Literacy Research, 8,

363-368.

Hu, M., & Nation, I. S. P. (2000). Unknown vocabulary density and reading comprehension. Reading in a

Foreign Language, 13, 403-430.

Lo, M., & Hue, C. W. (2008). C-CAT: A computer software to analyze and select Chinese characters and

character components for psychological research. Behavior Research Methods, 40, 1098-1105.

Lo, M., Hue, C. W., & Tseng, Y. H. (2012). C-CAT2: A computer software used to analyze traditional and

simplified Chinese characters, character components and neighbors. Chinese Journal of

Psychology, 54, 243-252.

Lo, M., Hue, C. W., & Tsai, F. C. (2007). Chinese readers knowledge of how Chinese orthography

represents phonology. Chinese Journal of Psychology, 49, 315-334.

Lord, F. M. (1953). On the statistical treatment of football numbers. American Psychologist, 8, 750-751.

LimeSurvey: An open source survey tool (Version 2.0) [Computer Software]. Hamburg, German:

LimeSurvey Projeot.

Mohammadi, V., & Keshavarz, M. H. (2009). The effect of unknown vocabulary density on EFL learners

reading comprehension of nonfiction general English texts. Journal of English Language Studies,

1, 1-22.

Rayner, K., & Pollatsek, A. (1989). The psychology of reading. Hillsdale, NJ: Lawrence Erlbaum

Associates.

Tsai, J. L., Lee, C. Y., Lin, Y. C., Tzeng, O. J., & Hung, D. L. (2006). Neighborhood size effects of

Chinese words in lexical decision and reading. Language and Linguistics, 7, 659-675.

Yan, X., Fan, Y., Di, Z., Havlin, S., & Wu, J. (2013). Efficient learning strategy of Chinese characters

based on network approach. PLoS ONE, 8(8), e69745.

268

2014 02 21

2014 03 11

2014 04 01

2014 04 02

269

Bulletin of Educational Psychology, 2014, 46(2), 251-270

National Taiwan Normal University, Taipei, Taiwan, R.O.C.

Examining the Appropriateness of Teaching Sequence of Chinese Characters in Chinese Elementary School

Textbooks

Yu-Hsiang Tseng Chih-Wei Hue Ming Lo Department of Psychology

National Taiwan University

Meg Lu Ching-Ching Lu

Department of Education Graduate Institute of Taiwan Languages

and Language Education

National University of Tainan National Hsinchu University of Education

An elementary school student in Taiwan is expected to learn 2500~2900 different Chinese characters from Chinese textbooks.

The purpose of the present research is to evaluate the appropriateness of the arrangement of character sequences in textbooks.

One hundred and fifty one experienced elementary school teachers of Chinese descent participated in Study 1. They were

asked to evaluate the relative importance of 9 properties of Chinese characters, including character usage in writing, features

of character orthography, and complexity of character phonology and semantics, when selecting characters to teach. The

participants indicated that properties such as frequency of use in childrens books and number of words included as

morpheme are important and should be considered in every grade. They also found that, number of character strokes is

important for grade 1 and 2, and frequency of use in childrens own writing should be considered in grade 5 and 6. Based

on the findings of Study 1, Study 2 evaluated how the potential characters to be learned were arranged in Chinese textbooks

published by three publishers. The results showed that although the characters in the textbooks published by the same

publisher were selected and arranged in accordance with the sequence indicated by character properties, there was much

variation regarding the selection and learning sequence arrangement of the characters among the publishers. For example,

between two publishers, there could be 20~30% difference on the characters to be learned included in the textbooks. All

together, the potential characters to be learned in about 15% of the articles were misplaced in the teaching sequence.

Moreover, a database containing about 5900 different characters and their properties has been built, and a computer program

utilizing the database to analyze the characters in an article has also been designed. The database and program will be

available on the internet.

270

KEY WORDS: CDE index, character properties, Chinese characters, Chinese textbooks, teaching sequence