主题：【原创】浅谈汉字与拼音文字的比较 （上） -- 人间树

打死你我也不认楼主有漏洞

我自己，那漏洞是大把大把的，整个一漏勺

说到头发颜色，现在的很多南欧（例如意大利）和西南欧（例如法国南部，西班牙）人的头发也是黑的。不过却不算黄种人。

埃及人、苏美尔人是啥人种其实很好解决。埃及的木乃伊很多，古苏美尔人和古罗马人也是有遗骨的，是啥人种，验个DNA就清楚了。比纠缠头发的颜色，鼻子的高低要准确。要注意的是验证的取样范围要广。这几个地区历史上有过多次入侵，不同时代的人种未必相同。

不过，就算验出是黄种人也证明不了你的理论。盖埃及、苏美尔文明都比中国早。反而可以作为中国文明西来的证据。

至于希腊的战车，这个其实早有解释。古希腊人的来源很杂，主体一般认为是前2000年左右从巴尔干半岛迁入的数支不同民族融合后构成的。希腊的地形虽然不适合车战，但不代表迁入之前的民族没有战车。另外，希腊神话、史诗中的车战大多是武将战斗。所以很可能战车只在小范围做指挥、传令、斥候等用途。最后，神话和史诗的最终成型是亚历山大之后的希腊化时期，最终整理定稿要到文艺复兴直至十九世纪。是否窜入了后代的也未可知。

这一点，其实在印度神话中也能找到例证。例如印度教现在一般禁食牛肉。但早期印度神话中却没有牛崇拜或牛肉禁忌。这其实反映了入侵的雅利安人从游牧民族向农耕民族转化的过程。人种没变，传说仍在，风俗文化却因为实际环境的变化而改变了。

前段时间我专门在网上查过资料 (多谢Dracula的核对)

1) 同样内容,中文字数大约是英文单词数的1.5倍,(可以查证翻译论坛和一篇英国论文,明日枯荷包 指出 翻译公司给出的比例是1.6,但要考虑翻译是按照中文字数收钱的)

2) 美国人的平均阅读速度是250~300word/min, 1000word/min的速度很少有人能够达到 (google 或者 wikipedia)

3) 教育部新出台的《义务教育阶段语文课程标准》和语文教学大纲明确规定: 初中生每分钟500字. 考虑到九年制义务教育,每分钟500字的速度可以作为平均速度的下线

4) 网上可以找到中文的阅读速度测试, 看完一段文字后回答几个问题,只要正确率达到80%就算测试通过. 相信在做的各位很容易达到每分钟1500字(如果是小说爱好者),而对应的1000word/min在美国很少见,美国教授也只有600~800word/min(参见google book的一篇文章).

综上所述, 中国初中生的每分钟500字至少相当于英文333word/min,这已经超过美国人的平均阅读速度.从哲学上,事情都有两面性,中文和英文没有绝对的优劣. 中文需要更多的时间学习,一但学会,就提供高得多的阅读速度.

另) 关于中英文阅读速度比较,除了首都师范大学的文章外,还有英国一大学出的论文和书.

• 汉语说难也难，说不难也不难

顺带宝推——这是我第二次宝推啊

而且，付出总是应该得到回报的

好像你还得到了4个铢钱，不错了

不过没几个人加我好友，不知道多少人能看到……

怎么和你引得数据不一样呢？

“The average American adult reads prose text at 250 to 300 words per minute. While proofreading materials, people are able to read at 200 wpm on paper, and 180 wpm on a monitor.[7]

Comprehension speeds have been assessed at 400 wpm for full comprehension, and research has shown that speed reading at 600 wpm can achieve about 70% comprehension and 50% comprehension at 1000 wpm”

我不太清楚同语文教学大纲中提到的”每分钟500字”比较应该使用250-300，还是400，还是600。但是英语阅读速度肯定比你使用的数字高。

关于“同样内容,中文字数大约是英文单词数的1.5倍”你能不能提供一个链接。我用托尔斯泰的《战争与和平》作了个实验，用网上的英文译本和中文译本，随便挑了几章，统计了一下字数和单词数。中文字数大致是英文单词数的一倍。

你说中文阅读速度很容易达到一分钟1500字，也就是说1小时9万字。大致是100页。我对这个数字有点怀疑。有什么依据呢？

http://www.scientrans.com/service-word-account.html

所以我觉得可以以1.65:1来算

http://www.informaworld.com/smpp/content~db=all~content=a918928855

只有摘要，全文是要买的。摘要说，同样的阅读材料，中文对英文的阅读时间为24.7分对26.6分。文章认为，这个区别是显著的。

只从摘要上说，试验结果，中文英文阅读速度的区别是statistically significant（p-value是多少，摘要上没列出），但是24.7对26.6，7%的差别很难说是economically significant。

第二，TOEFL和HSK的难度完全一样吗？这8篇汉语文章和8篇英语文章难度完全一样吗？如果考虑到这些因素，真正的标准差应该比文章报告的要大。由于不知道p-value是多少，不清楚考虑这些因素后，结果还是不是statistically significant。

第三，摘要里提到with reading comprehension being held constant，但是我还是想读一下他们具体是怎么处理这个问题的。我的感觉，这个问题不是把reading comprehension加到回归方程右边那么简单。

不过，根据这项研究的摘要，我的印象是汉语、英语阅读速度没有什么大的差别。汉语、英语优劣的争论上，阅读速度不是一个重要因素。

AUTHOR: Xuehong Lü; Jie Zhang

TITLE: Reading efficiency: A comparative study of English and Chinese orthographies

SOURCE: Reading Research and Instruction 38 no4 301-17 Summ 1999

The magazine publisher is the copyright holder of this article and it is reproduced with permission. Further reproduction of this article in violation of the copyright is prohibited.

ABSTRACT

This project studies variation in reading speed between languages of different orthographies. Modern Chinese with logographic characters and English with alphabetic written systems are the two languages under study. It is hypothesized that native Chinese readers read faster than native English readers on the same reading comprehension test. College freshmen (126 from Capital Normal University in China and 111 from Brigham Young University in the USA) were asked to read 16 passages selected from standardized foreign language tests (8 from TOEFL and 8 from HSK) and answer multiple choice questions (60 in total) that follow each of the passages. Findings indicate that the Chinese readers (24.7 minutes) are faster than the English readers (26.6 minutes) by about 2 minutes on the same reading material. The difference is significant even with reading comprehension being held constant. Results have implications on teaching Chinese as foreign language and the Chinese written language reform.

Reading is a comprehensive process originating from the orthographic script of the language. Learning to read Arabic is different from learning to read German or English, and all three are different from learning to read Chinese. Since reading involves decoding of the script, and languages in the world are written with different systems, reading efficiency should vary from one system to another.

According to Perfetti (1985), the critical difference among writing systems is how the units of the writing system, the script, code the units of the language. At one extreme is the system that clearly codes the sound of the language, such as most Indo-European languages including English and the man-made Esperanto. At the other extreme is a writing system that directly codes meaning. Early picture writing offers the earliest examples of such a system, and today's abstract representations or ideographs are also common in meaning-based writing systems. In fact, Chinese remains the most widely used meaning-based writing system in which ideographs and pictographs are prominent (Perfetti, 1985).

English alphabetic and Chinese logographic systems are typical of the orthographical differences. Because of the "radical compound" nature of Chinese characters, reading Chinese may not necessarily involve the decoding of the script as English readers have to do. In other words, a Chinese native reader may not have to transform the script into pronunciation before fully understanding the meaning of the word (Au, 1992; Rozin et al., 1971). Additionally, for the same amount of information, written Chinese takes less space than written English, so that less eye fixation should be required in reading Chinese. Therefore, the Chinese reading process for a native reader can be less time consuming than reading English for an English native reader.

An exhaustive review of literature has located a very limited number of studies comparing reading efficiencies in English and Chinese. The only studies that directly address reading speed in English and Chinese have been done by Gray (1956) and Just, Carpenter, and Wu (1983). However, these two studies contain some flaws in sampling, instrumentation, and measurement, caused possibly by lack of funding as well as lack of the researchers' knowledge of the Chinese language. Thus, neither study was able to test the hypothesis proposed in this current research. Therefore, a more straightforward measure of reading efficiency is needed.

This research issue is significant both in teaching Chinese as a foreign language and in the Chinese written language reform. The contemporary history of Chinese language has witnessed several reforms or attempted reforms in its writing system. Beyond the simplification of Chinese characters, the radical reformists have advocated romanization of the Chinese writing system. The essential purpose of the language is communication, and efficiency is a measure of the merits of a language. Results from this research project may provide scientific evidence to support or oppose the language reform proposals in both simplification and romanization.

A REVIEW OF RELEVANT LITERATURE

English orthography looks better than the Chinese orthography in terms of relating the script to speech. Written Chinese is different from that of English in that the former is a logographic system. In the Chinese logograph, each character is a pronunciation unit. Some researchers (e.g., Au, 1992; Rozin et al., 1971) proposed that reading Chinese characters does not involve the processing of phonological recoding. That is to say, phonological information is not involved, or at least not as important as reading an alphabet such as English.

This statement has been criticized in the past few decades (Leong, 1973). Critics argue that about 85% of all Chinese characters used today belong to a category called "radical compound" (Wang, 1973, 1981). A radical compound is composed of two parts: a "radical" and a "phonetic." The radical presents the semantic or categorical information (e.g., an object made of metal; a person ... etc.); and the phonetic provides the phonological information.

Previous studies on reading efficiency have focused on the measure of eye fixations (pauses made by a reader's eyes along the lines of print). Just and Carpenter (1980) has used an aggregate measure (gaze duration) that sums all fixations beyond some minimum. It is more typical in eye movement research not to summate over fixations. According to Kliegl, Olson, and Davidson (1982), the procedure of Just and Carpenter (1980) produces misreadings of fixation time that cause problems for theoretical modeling.

To examine fluency in reading English and Chinese texts, Just, Carpenter, and Wu (1983) conducted experiments in their laboratory. College students were asked to read short scientific texts and the eye-fixation was monitored by computer. The English version of the texts was particularly revealing about word decoding and processes that translate written symbols into mental concepts. The Chinese version of the experiment also focused on word encoding processes because these processes were most likely to be influenced by the properties of a particular orthography.

The experiments examined the eye-fixation of 13 native Chinese speakers as they read Chinese translations of the 15 scientific texts. The Chinese readers had received their college undergraduate education in Hong Kong or Taiwan. Their reading ability was compared with their American counterparts, although the two groups of readers differed in several ways. For example, the Chinese students were bilingual and generally had more undergraduate or graduate education than the American students.

The texts used in this study were translations of the scientific passages excerpted from Newsweek and Time magazines, presenting generally unfamiliar information on scientific or technological topics. The translations into Chinese were made by a native Chinese speaker who was also fluent in English. Every attempt was made to produce Chinese texts comparable in style and difficulty to the English versions, by translating the texts sentence by sentence and by using comparable vocabulary.

The researchers found that, in English, native readers spent more time on long words than on short words, and in Chinese, the gaze duration on Chinese words increased with the number of characters in a word. The interpretation given to this finding in the English readers is that encoding processes operate on letters or letter groups and that the letters or letter groups are processed once at a time. As a result, longer words take longer time to encode. The word-length effect in Chinese cannot be identical because of the difference between the two orthographies.

In another important study, Gray (1956) compared the eye fixations and reading speed of a group of 78 adult readers of 14 different languages, including Arabic, English, Hebrew, and Chinese. Most of the readers were university graduate students and native speakers of their original language. They were currently living in the United States but had received all or most of their elementary and secondary education in their native country.

The readers were presented two texts that had been translated into their native languages. The translated versions varied from language to language in the number of words and lines of print. For example, in English, each of the two experimental passages contained approximately 150 words and covered 13 lines of print. In Chinese, each took approximately 140 words, 5 lines, and covered a much smaller space. These differences reflected variation in space (e.g. number of lines) that was considered to express the same concept in different languages. Nevertheless, the differences were also indicative of the large variation among the orthographies.

Controversially, Gray concluded that orthography had little effect on the nature of the eye fixation of the readers, although there was some slight variation in the average number of eye fixations and their average duration. For example, the average number of fixations was 1.6 words/fixation for English, 2.5 words/fixation for Chinese, and 1.3 words/fixation for Hebrew. Gray explained these differences with accidental differences among the various samples of readers rather than with the orthography. In conclusion, the general finding of Gray's study was that at a very general level, fluent reading was similar across different languages and orthographies. In other words, orthography had little effect on the nature of the eye fixation of the readers, although he found some slight variation in the average number of eye fixation and their average duration. Gray attributed the differences to (1) the fact that the linguistic unit of words varies from language to language, and (2) accidental differences among the various samples of readers rather than to the orthography itself.

As the study by Just, Carpenter, and Wu (1983), Gray's study was flawed in at least the following five ways. First, his sample consisted of only international graduate students studying in the USA who spoke their native languages as well as English as their second language. The subjects' proficiency in English varied, and their proficiency in their native languages may also vary since they left their native country at different ages. Second, the sample size of only 78 subjects was small. The 78 subjects represented 14 different languages, with an average of 5-6 readers attending each language. Third, there was no control of educational levels. It was claimed that the readers had received all or most of their elementary and secondary education in their native language, but their native language reading proficiency should vary contingent upon the amount of education they received before they left for the USA. Fourth, reading speed was not objectively and straightforward measured. There is no doubt that eye fixation is a measure of reading speed, but a more straightforward and efficient measure of reading speed should involve subjects' reading long passages for which time is monitored and comprehension is checked. Fifth, in Gray's study, subjects' decision of how carefully and quickly to read was not controlled for. The variation in eye fixation could be a consequence of the differences in the readers' attention rather than those in orthography.

Previous researchers have tried to investigate linguistic factors that affect reading speed, but without much success. Mann (1986) and Willows (1974) used developmental data in their studies of the effect of phonemic awareness on children's later reading skills. They found that phonemic awareness was a good prediction of children's later reading skills. In English, there is little doubt about the importance of phonological information in the process of word perception. In other words, English language allows its readers to process the information from phonological script to comprehension in an easy way, as long as the reader is able to identify the phonemes.

On the other hand, phonological recoding was thought to be unnecessary in reading Chinese characters. Some researchers have intuitively thought that reading Chinese may not require any phonological information (Tzeng, 1994). By definition, it is "possible" to get the meaning onto a logograph without the mediating of phonological information anyway.

Studying the differences in various orthographies and factors that influence reading efficiency, previous researchers have made significant contributions to our understanding of the issues. Some empirical studies (e.g. Just, Carpenter, & Wu, 1983; Mann 1986, 1988, 1989; and Willows, 1974) have supported the hypothesis that reading efficiency differs from language to language in accordance with the type of orthography, while some others (e.g. Gray, 1956) have not been able to make the connection. However, previous research on the effect of type of orthographies on reading efficiency has at least three weaknesses: (1) reading efficiency (or speed) was not straightforwardly measured, (2) extraneous variables (such as the subjects' educational level and their proficiency in the examined language) were not adequately controlled for, and (3) the sample sizes were not big enough for reasonable generalizations.

To study the reading efficiency without the above-mentioned problems, an attempt was made by Everson (1988) to investigate the variation in reading speed and comprehension from logographic and alphabetic orthographies. Everson selected 60 first year Chinese learners from the United States Air Force Academy to read a same passage printed in either in pinyin (romanization) or characters. Results of the study indicated that the learners of Chinese as a second language read the romanized form of Chinese faster and with better comprehension than they read the passage in the form of characters.

Explanations by the researcher for the finding are in the difference between romanization and the character. Different from the characters, the romanized form of Chinese denotes the four tones, which are distinguishable phonemes, capitalizes the first letter of a proper noun, and writes syllables of one word together. Results of the research might have told us that romanization is more efficient for reading than characters. The research might have provided supporting evidence for the Chinese language reform. However, the finding might also be a function of the subjects' first language, English, which is an alphabetic orthography. People tend to be more used to the script they were more familiar with. Second, the finding might also be a function of instruction in which pinyin was taught more than the characters. Further, subjects of the research were all first year students of the language, and more studies with higher level Chinese learners might be needed to investigate the variation in reading efficiency between romanized and characterized scripts.

Some similar research was conducted for the Japanese language. Researchers compared subjects' response speeds to Kanji (logographs, Chinese characters) and Kana (phonetic graphs) among Japanese readers of various levels, and found that the subjects' response to Kanji was three times faster than that to Kana. Those researchers argued that three steps have to be involved in reading an alphabetic script like Kana: graph, sound, and then meaning, but in reading a logographic script, only two of the three steps are needed: from the graph to the meaning (Xu, 1996). This partially explains why reading Chinese is usually faster than reading English.

Eventually, only by comparing native readers of different orthographies can we find the reliable and valid variances in reading efficiency as a function of the orthography. The current research project is designed to exclude all the previously documented extraneous variables so as to conduct a more systematic study of the effects of orthography on reading efficiency.

This project is intended to use a more scientific design with large samples to investigate the reading efficiency in English and Chinese. Based on what we know about the orthography theories and previous studies, it is hypothesized that:

1. Native Chinese reading is generally faster than native English reading;

2. on a speed reading test, native Chinese readers score higher than native English readers in comprehension rates for the same reading contents;

3. when reading efficiency is calculated by comprehension score (number of questions answered correctly) divided by speed (number of minutes used to finish the reading), native Chinese reading is more efficient than native English reading;

4. with comprehension rates being controlled for, native Chinese reading is generally faster than native English reading; and

5. with speed being controlled for, the comprehension rate in native Chinese reading is higher than that in native English reading.

RESEARCH DESIGN

In order to make sure that the reading speed and reading comprehension rate are the function of orthography, extraneous variables should be strictly controlled for during the test. To do this, an experimental design was called for. A survey design using large random samples was incorporated with the experimental tests to make the findings more reliable and valid.

SUBJECTS

College freshman students were randomly selected from Capital Normal University in China and Brigham Young University in Utah to represent respectively native Chinese readers and native English readers. The sample size for each language group was about 140, with approximately equal numbers of males and females from various areas of study. College freshmen were chosen as research subjects out of the following three reasons:

1. with the same educational level, they should be comparable in reading ability,

2. college students are generally more careful and conscientious readers than non-student populations, and

3 in the higher education environment, the procedure of random sampling is easier than in others.

Capital Normal University and Brigham Young University were selected as the sampling frames from the two populations because they are believed to be comparative in their freshmen students' reading abilities.

MATERIALS

Eight English passages were selected from the Test of English as a Foreign Language (TOEFL), and eight from the Chinese Standard Test (HSK: Hanyu Shuiping Kaoshi). Each of the sixteen passages is followed by two or more multiple-choice questions measuring reading comprehension. The English passages and questions were translated into Chinese, and the Chinese ones into English. In order to keep translation errors to a minimum, back translation techniques were used with the help of several bilingual scholars. Thus, each of the two groups was tested on sixteen passages in their specific form. The total number of questions for the sixteen passages is 60. The contents of all the passages are either of popular science in nature or basic social issues. As a principle of TOEFL and HSK, all the passages are neutral in terms of points of view and unbiased against any group of people.

In order to reduce the influence of extraneous variables during the test, each of the 16 passages is printed on a separate page, with its corresponding questions on the back of the same page. Respondents were instructed not to re-read the passage once they had finished reading it.

In the test for both languages, the first passage is originally from the Test of English as a Foreign Language (TOEFL), and the second is from the Chinese Standard Test (HSK: Hanyu Shuiping Kaoshi). All eight English and Chinese passages are alternatively ordered so that the results will not be biased to readers of any language, even if a subject turns in an incomplete test.

The English version of the test was printed in WordPerfect default font size, and the Chinese version was printed in Nan Ji Star default size. Both sizes are comparable and regular and are not supposed to create difficulties or advantages to a reader of any version. The English and Chinese versions of the test are available for inspection upon request from interested readers.

MEASUREMENTS

The major independent variable in the study is orthography. This is a dummy variable varying from English to Chinese.

Reading speed and comprehension rate are two major dependent variables. Reading speed is measured by the number of minutes in which a subject finishes reading all 16 passages and completing all 60 multiple choice questions. Comprehension rate is measured by the number of questions answered correctly by a subject.

A third dependent variable measuring reading efficiency is actually an index of reading speed and comprehension rate. Efficiency is a ratio of comprehension (number of questions answered correctly) to the speed (number of minutes used to finish the test):

Efficiency = Correct Items / Minutes Used

A high efficiency rate indicates either more "correct items" or less "minutes used" or both. For our test material, the value of "correct items" should vary from 0 to 60, and the value of "minutes used" should theoretically vary from 1 to infinity. However, the test was designed for a normal native reader of either English or Chinese to finish with adequate comprehension within 30 minutes. Pilot studies conducted in both English and Chinese languages indicated that the majority of readers could finish the whole thing within about 40 minutes. Subjects of the study were asked to read the passages in one of the two language forms (English and Chinese) and then answered multiple-choice questions measuring their reading comprehension. All subjects were required to treat the reading as a timed test and encouraged to finish it as quickly and correctly as possible. The test administrators supervised the test and recorded the time (minutes) used by each subject to finish the test. The comprehension scores (number of questions answered correctly) would be recorded after the tests were collected.

ANALYSES AND FINDINGS

Subjects for the research project are from Capital Normal University in Beijing, China and Brigham Young University in Provo, Utah, USA. They are representing two different languages under study: Chinese and English. The two institutions were selected both for comparability and for convenience. They are of similar level in terms of quality of students in each country.

For each sample, the test was administered to about 130 students. Since we prefer to study only freshmen students, some non-freshmen cases were deleted from the samples. After removing the cases that were far from complete, we have 126 subjects for the Chinese sample, and 111 for the English sample. The demographic characteristics of the two samples are shown in Table 1.

For the current data, reliability tests were performed on mean scores of all the 16 passages. Three scales were tested for the instrument's reliability: (1) for all the 16 passages, (2) for the 8 odd-numbered passages, and (3) for 5 randomly selected passages. Table 2 presents the alpha value and other information for each scale tested. As we can see from the table, the more items involved in the reliability test, the higher the alpha tends to be. Generally, the instrument is adequately reliable as a test for reading comprehension.

Table 2 also presents the results of reliability tests for each of the two samples. Comparing the alpha values between the English and Chinese versions of the instrument, we find that the English version is more reliable than the Chinese version for the scales with 8 items and 5 items, but not for the scale with all 16 items. Generally, the versions are not different in their reliability levels.

As standard foreign language tests, both TOEFL and HSK have endured long-time examinations and refinements for their reliability and validity. For a validity test, we are looking at the degree to which the tests are measuring what they are supposed to measure. Both tests are aimed at a valid test of an examinee's proficiency of a foreign language. In the reading comprehension sections from which passages were selected for the current project's use, both TOEFL and HSK were designed to test an examinee's reading speed and comprehension. Reading speed and comprehension are what we are testing our subjects on. The only difference between the original purpose of the TOEFL/HSK and the purpose in the current project lies in the subjects: their examinees are foreign language readers, but ours are native readers of the language. For native readers, the passages should be much easier, and they can finish reading the whole thing in a shorter time than non-native readers. Therefore, 16 passages were put together to form an adequately long test so that variance in reading speed and comprehension can be detected for native readers.

The hypotheses specified in the research have been tested one after another. As a result, the data supported all the five hypotheses.

Hypothesis #1: Native Chinese reading is generally faster than native English reading. To compare the difference in reading speed between the English native readers and Chinese native readers, a one-way Analysis of Variance (ANOVA) was performed with the number of minutes used to finish the whole reading as the dependent variable and the group (with two values: English and Chinese) as the dependent variable. The mean number of minutes used by Chinese readers to finish the test was 24.7 (S.D. = 4.7), while that by English readers was 26.6 (S.D. = 5.1), with df=1, F=8.6, and significant level=.004. Chinese read about 2 minutes faster and with a smaller standard deviation than the English readers do on the test.

Hypothesis #2: On the reading test, native Chinese readers score higher than native English readers in comprehension rates for the same reading contents. When reading comprehension is measured by the number of questions answered by subjects correctly, we can see which group understands the same material with more comprehension of the texts. The mean score for the Chinese group is 50.1 (S.D.=6.0), and the mean score for the English group is 43.9 (S.D. = 6.8), with df=1, F=54.7, and significant level=.000. On average, the Chinese readers can answer 6 more questions correctly than the English readers on a 60-question test.

Hypothesis #3: When reading efficiency is calculated by comprehension score (number of questions answered correctly) divided by speed (number of minutes used to finish the reading), native Chinese reading is more efficient than native English reading. A fast reader may not have a good comprehension score, and inversely, a reader who has scored high on comprehension may have done so at the expense of time. The new variable of efficiency was created to balance out the discrepancies. As we already know, the efficiency score is obtained by the number of correct answers divided by the number of minutes used to finish the test. The mean efficiency score for the Chinese readers is 2.10 (S.D.=.45) and for the English readers, 1.70 (S.D.=.39), with df=1, F=50.6, and significant level=.000.

Hypothesis #4: With comprehension rates being controlled for, native Chinese reading is generally faster than native English reading. As discussed earlier, a fast reader may not score high on the comprehension test, and a reader who has a high comprehension score may do so at expense of the time. A correlation test for the two variables was performed to address the concern. The result is that the correlation coefficient is .002 and the probability level is .97. There is almost no relationship between the number of minutes used and the number of questions answered correctly; a person who has spent more time on the reading does not necessarily score high on the comprehension test.

To further address the concern, a multiple regression model is designed:

Speed = a + b[sub1](Orthography) + b[sub2](Comprehension)

where the "speed" (number of minutes used to finish the test) is determined by "a" (an intercept or constant value for the model) and "b[sub1]" (the slope provided by the model for the variable of orthography) times the value of orthography, and additionally "b[sub2]" times the comprehension score. In this model, the speed is predicted with orthography (English or Chinese) or comprehension held constant. In other words, when we determine a subject's reading speed with a known orthography value, the comprehension is held constant, and when we determine his reading speed with a known comprehension score, the orthography is held constant.

As can be seen from Table 3, the Y intercept (constant) is 23.39. This is about the average speed for everyone in the samples to finish the test. However, the actual speed of a certain reader is predicted by his/her orthography (English or Chinese) and comprehension score as follows:

Speed = 23.39 + (-2.32)(Orthography) + (.07)(Comprehension).

Since the variable "orthography" (or sample) is recoded as 0 = English and 1 = Chinese, a negative slope value for orthography for the model indicates that the time value is always lower for the Chinese reader than for an English reader. In this case, the speed of reading for the Chinese is always faster than that for the English readers by 2.32 minutes. The comprehension slope value in the table tells us that with every point made in comprehension (every question answered right), the time is increased by .07 minutes. However, the relation is too weak to be significant at the .05 probability level. With the strong predicting power from the orthography, the multiple regression model has an F value of 5.36 and is significant at .005 level.

Hypothesis #5: With speed being controlled for, the comprehension rate in native Chinese reading is higher than that in native English reading. Table 3 also has the information of the multiple regression model that predicts comprehension with a known value of orthography and speed. The second model has comprehension as its dependent variable:

Comprehension = a + b[sub1](Orthography) + b[sub2](Speed)

Again, in this model the comprehension value is predicted with orthography (English or Chinese) or speed held constant. In other words, when we determine a subject's comprehension score with a known orthography value, the speed is held constant, and when we determine his comprehension with a known speed, the orthography is held constant.

For the model, the Y intercept of 40.68 as shown in Table 3 indicates that the minimum comprehension mean score is about 40.68. The actual score of comprehension can be predicted by orthography and speed as follows:

Comprehension = 40.68 + (6.39)(Orthography) + (.12)(Speed).

Since English has been coded as 0 and Chinese as 1, this multiple regression model tells us that a Chinese reader always scores at least 6.39 more than a English reader the comprehension. With orthography being held constant, every one minute used in the test will help an average subject increase his/her comprehension score by .12, although the relationship is not significant at .05 level. Again, with the strong predicting power from the orthography, the multiple regression model has an F value of 28.55 and a probability level lower than .0001.

Both models with either speed or comprehension as dependent variable have supported the general hypothesis of the study that the orthography (English or Chinese) makes difference in reading speed and comprehension. Chinese readers read faster than the English readers, and Chinese readers read the passages with less comprehension errors than their English counterparts

DISCUSSION AND CONCLUSION

The current research project with a survey design and refined instruments has come to the conclusion that reading Chinese is faster than reading English. An important implication of the findings lies in teaching Chinese as a foreign language. When students and instructors are convinced that being able to read Chinese characters is more profitable than previously believed, there should be more motivation and enthusiasm in teaching and learning the most difficult part of the language.

Another important implication of the finding is in the Chinese language reform. The ultimate goal of the radical reformers of the Chinese language is to romanize the Chinese written system. Obviously, the findings of the current research suggest that a transfer of written Chinese from logographs to phonetic graphs may not necessarily benefit its readers in terms of reading speed and comprehension rate.

The Chinese characters are notoriously known as hard to learn, hard to remember, and hard to write, and, additionally, numerous in amount of words to know for being literate (Taylor & Taylor, 1995, p.117). A Chinese child usually spends about two more years than an English-speaking child to learn to read and write to the degree of basic functioning. Language reform has been vehemently called for since beginning of the century, especially after the May 4th Movement in 1991. Chinese intellectuals such as Chen Duxiu and Hu Shi all advocated the Chinese language reform by abolishing the Chinese characters (Yan, 1996). They attributed the failure in science and technology early this century in China compared to western civilization to the difficulty in the written language. They further argued that if the characters were replaced by some form of alphabets, Chinese students would be able to spend more time on science and technology learning (He, 1996). This idea was later supported by the communists after 1949, when Mao Zedong claimed Chinese should "take the romanization road."

Because of historical reasons, the romanization of the Chinese language has never been realized in China. However, the delay of the Chinese romanization is not necessarily regret. Koreans and Japanese who alphabetized their written forms earlier have now shown some signs of Chinese characters coming back. Obviously, the Chinese characters are considered by more and more people to be indispensable in Korean and Japanese (Taylor & Taylor, 1995). Experiences in language reforms in Korea and Japan may have implied something for the Chinese language reformers.

The original motivation for alphabetizing or romanizing Chinese characters was from the facts that the Chinese characters are hard to learn, hard to remember, and hard to write. However, with the newly developed computer technology in Chinese word processing, those difficulties have been becoming less and less a concern for Chinese writers. With any of the currently available Chinese processing software, such as Nan Ji Star, Xin Tian Ma, Twin Bridge, Xia Li Ba Ren, entering Chinese words and editing Chinese files are much faster than handwriting on paper, even faster than English word processing on computer. A recent study conducted by Japanese researchers found that entering Kana (Chinese characters) in computer is about 10 times faster than entering Romaji (Romanized form) for the same words (Xu, 1992). In a Chinese processing procedure, the writer does not have to enter each letter or syllable to get the word. But in English or other alphabetic languages, every single letter must be entered one after another. A function which is called lianxiang (related thinking) is always in action to help a writer to produce a phrase or even a sentence by pressing one or a limited number of keys. An informal observation of skilled typists of Chinese in China and the authors' personal experience in typing Chinese and English also indicate that with further refinement of the software and up-grading the hardware, there is still more room to improve the already fast typing speed in Chinese.

The computer revolution has been exercising a great impact on the Chinese written language reform. The degree of impact by the computer is only limited by our imagination. Ten years ago, when some Chinese word processing software was first on market, some Chinese intellectuals felt what computer would mean for Chinese written language reform. As Taylor and Taylor (1995) observed at a national conference on language and scripts was convened in Beijing in 1986, "in some ways the greatest achievement of the conference was that it passed over in silence the issues of alphabetization and the elimination of Chinese characters."

In sum, the major concerns of the Chinese written language reform advocates are being removed by our increasingly large amount of computer knowledge. Additionally, we hope findings in this current research project can help make the issue clearer.

Besides other explanations, the finding is generally accounted for by the difference in scripts between the two languages. The logographic or ideographic nature of the Chinese writing system may provide advantages to some extent for the Chinese readers: they may not have to decode the word phonologically to know its meaning. If this is true, one step in reading process is saved for Chinese readers: they do not always have to decode a Chinese character into pronunciation before they understand the meaning of the character. In Chinese, there is a compliment phrase for fast readers, "yi mu shi hang," meaning to read "ten lines with one glimpse." It is more possible to read ten lines with one glimpse for a Chinese reader than for an English reader because of the difference in language processing procedure between logographs and alphabets. However, this hypothesis has to be put to the test in future research. Research in clinical linguistics and psycholinguistics with sophisticated experimental design and facilities is needed to investigate the difference in reading procedure between Chinese and English.

The current research used college freshmen as subjects to estimate the reading speed and comprehension difference between English and Chinese. Although we have tried all what we could to make the samples as comparable as possible, there could still be some differentiation in intelligence or verbal ability between the students at Capital Normal University (CNU) in Beijing, China and the students at Brigham Young University (BYU) in Provo, Utah. Given the percentage of the Chinese youth who have a chance to attend college compared to that of American young people, we might be able to match the CNU freshmen with the BYU freshmen in terms of intelligence or aptitudes in some aspects. Provided the limited funding for this thesis research, this may be the best we can do. Future research with better funding is suggested to study other populations who are more easily compared, such as professors from two similar universities, working class people who can read and write, Ph.D. candidates who are studying in the same program, etc.

ADDED MATERIAL

Xuehong Lü

SUNY University at Buffalo

Jie Zhang

SUNY College at Buffalo

ACKNOWLEDGMENTS

The authors want to thank Dr. Shenghua Jin, Professor of Psychology at Beijing Normal University for his assistance in data collection. Please direct all correspondence to Xuehong Lü, M.A., Chinese Language and Culture Program, Department of Modern Languages and Literatures, State University of New York at Buffalo, 910 Clemens Hall, Buffalo, New York 14260.

Table 1 Demographic characteristics of the subjects under study

Chinese English Total

Sample Sample

(N = 126) (N = 111) (N = 237)

Gender

Male 52 52 104

Female 74 59 133

Age

16-17 5 4 9

18-20 107 101 208

21-22 14 4 18

23 and more 0 2 2

Area of Study

science 24 13 37

technology 15 7 22

soc science 87 40 127

humanities 0 15 15

undecided 0 36 36

Edu. Level Freshmen Freshmen

Table 2 Results of reliability tests of the instruments

For All For Odd For Selected

Items (16) Items (8) Items (5)(FN*)

Total Eng. Chi. Total Eng. Chi. Total Eng. Chi.

Mean(FN**) .774 .712 .828 .733 .683 .777 .870 .855 .882

Minimum .577 .469 .564 .577 .565 .564 .826 .813 .837

Maximum .906 .898 .935 .838 .832 .843 .906 .898 .934

Variance .011 .012 .010 .009 .013 .010 .001 .001 .002

Alpha .795 .739 .773 .676 .664 .635 .450 .483 .399

FOOTNOTES

* The five randomly selected items are No. 2, No. 5, No. 8, No. 11, and No. 14.

** Since the answer to question was coded as 1 or 0, with 1 as correct and 0 as wrong, and the mean score for each passage is calculated by the number of correct answers divided by the number of questions in the passage, the maximum mean score for each passage is a 1.

Table 3 Results of the multiple regression models predicting reading speed and comprehension

Model with Speed as the Dependent Variable

Variable B SE B Beta T Sig T

COMPRHESION .072623 .049936 .103226 1.454 .1472

ORTHOGRAPHY -2.318955 .708219 -.232407 -3.274 .0012

(Constant) 23.393444 2.243646 10.427 .0000

F = 5.36128 Signif F = .0053

Model with Comprehension as the Dependent Variable

Variable B SE B Beta T Sig T

SPEED .123347 .084814 .086779 1.454 1.472

ORTHOGRAPHY 6.394913 .846269 .450897 7.557 .0000

(Constant) 40.675691 2.334862 17.421 .0000

F = 28.55178 Signif F = .0000

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