Advanced Learning Chinese Characters Strategy Based on the Characteristics of Component and Character Frequency

Advanced Learning Chinese Characters Method Based on the Characteristics of Component and Character Frequency Chung-Ching Wang (stanleyccwang1987@gmail.com), Ming-Liang Wei(N26011623@mail.ncku.edu.tw) Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan Yu-Lin Chang (gtyulin@gmail.com), Hsueh-Chih Chen(chcjyh@ntnu.edu.tw) Department of Educational Psychology and Counselling, National Taiwan Normal University, Taipei, Taiwan Yi-Ling Chung (lydia193@gmail.com), Jon-Fan Hu(jfhu@mail.ncku.edu.tw) Department of Psychology, National Cheng Kung University, Tainan, Taiwan Abstract Chinese has been recognized as one of most major languages in the world, and it is evident that more and more people are in- terested in understanding or using Chinese. Thus, developing an efficient approach for learning Chinese characters is con- sidered as an important issue. Certain previous studies have suggested various methods to learning Chinese characters for the purpose of showing students how to read Chinese charac- ters. In Chinese, the components can offer learners phonolog- ical and morphological meanings similar to the prefixes and suffixes in English, and character frequency provides learners a character list which can be widely used in daily life. How- ever, very few studies have considered integrating the charac- teristics of component and character frequency. In this study, we have developed an effective and systematic approach for learning Chinese characters based on both components and character frequency. The purpose of the study is to propose a traditional Chinese character learning metric and to present a method for learning only a few components and then the re- sulting reading of more high frequency characters made up of these components. Combining components and character fre- quency advantages, it can present an effective, systematic and rapid mechanism for learning traditional Chinese characters. Keywords: Learning Chinese; Character frequency; Compo- nents. Background Chinese is a popular and widely used language in the world, and it is quite difficult and complicated to read and write Chi- nese characters. In the field of Chinese character recogni- tion research, previous studies have actively involved Chinese character encoding strategies(Hayes, 1988), and character recognition strategies, such as meaning recognition(Everson, 1998), orthographic effect(Lin, 2000), and the reading process(Ke, 1998). These studies have contributed many ap- proaches to improve Chinese character recognition. Also, when learning Chinese characters, one can assume that char- acters that correctly match phonetic and orthographic pat- terns are easier to absorb(Ellis & Beaton, 1993). Moreover, numerous studies have offered well developed strategies for learning Chinese characters by using radicals or components. These studies have briefly indicated that the internal compo- nent structure of a Chinese character helps learners to clearly remember that character(Taft & Chung, 1999). Since compo- nents are the unit of characters and because they can consist of many distinct characters, even the characteristics of a com- ponent can provide its meaning, phonological and morpho- logical, because characters have the meaning of their internal components. Consequently, learners are able to readily and rapidly recognize and write characters by using components. For example, 木(pin-yin: mu4, meaning: tree) is a compo- nent, and two 木(tree) can compose 林(pin-yin: lin2, mean- ing: wood) and three 木(tree) can constitute 森(pin-yin: sen1, meaning: forest). Obviously, we are able to readily figure out their meanings due to such processes. Hence, most cogni- tive strategies frequently use components to teach students of Chinese how to read characters(Shen, 2004). In addition, many studies have extensively exploited strategies related to character frequency because humans are sensitive to the fre- quencies of events in their daily life and remember these things correctly (Ellis, 2002). Therefore, character frequency can help learners memorize characters correctly and can also contribute to retention. However, only using this strategy to learn Chinese is not suitable. Most Chinese characters characterized by high frequency have intricate construction, such as 謝 謝(meaning: thank you) and 對 不 起(meaning: sorry). Beside, frequency is also an important factor with respect to education. Previous studies have the impact of high frequency characters on learning Chinese characters for beginners(Wang, Hung, Chang, & Chen, 2008), and found the learners could learn approximately 700 high frequency char- acters with ease. Therefore, the present study presumes that most learners are able to absorb high frequency characters ef- fectively. A recent study used character network construction to establish an efficient strategy for learning Chinese characters(Yan, Fan, Di, Havlin, & Wu, 2013). This strat- egy exploits the network of Chinese characters in a hierarchi- cal structure and the weight of the network nodes to develop a Chinese character metric called distributed node weight (DNW). However, the character network of the DNW strat- egy merely considers associations between characters and character frequency. Actually, a component can be made up of many distinctive characters, but most of these are not high frequency characters. Reviewing the DNW strategy, it is suggested that characters having high frequency that are also composed of many components that constitute high fre- quency characters should be learned first. In this study, we have tightly integrated the component and character frequency characteristics in order to develop an ap-