中国外语学习者公式化语言加工研究
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摘要
公式化语言在语言交际和习得过程中起着至关重要的作用。研究者们发现本族语人士在语言表达中使用大量的公式化语言,它也可以促进第二语言学习者语言的流利度和地道性。但是,公式化语言也是二语习得过程中的一个难点。学习者们常常由于过多、过少或是误用某些公式化语言而导致他们的语言表达缺乏地道性。因此,公式化语言能力,即在口头和书面交际中使用公式化语言的能力,被认为是二语习得者语言学习过程中的“瓶颈”。
不少研究者都试图解释公式化语言如何能够提高语言的地道性和流利度。Wray和Perkins (2000)的整体加工假说提出公式化语言是以整体的形式储存和提取的,因此在交际中更容易使用。Bybee (1985,1995)提出了语言加工的网状模型,认为高频的具有复杂形态的词可以以整体形式储存在大脑中。在此基础上,Sosa和MacFarlane (2002)提出比词更大单位的公式化语言,也可以以整体形式储存在词库中。其他一些研究者也提出了类似的观点。然而,公式化语言的整体加工特性长期以来都只是一个理论上的假说,少有实证研究去证明它。
最近十年,公式化语言的研究又掀起了新的热潮。研究者们尝试用心理语言学的实验手段来验证其整体加工。研究发现公式化语言在本族语者的语言加工过程中具有整体性,但是在第二语言学习者的语言加工中是否具有整体性,尚缺乏一致的结论。
其他一些研究对本族语者和非本族语者公式化语言加工的各个因素进行了研究。他们发现频率、互信息、公式化语言长度等因素对本族语者和非本族语者产生不同的影响。在此基础上,Ellis等人(2008)提出了一个语言习得的模型,即在语言学习的初级阶段,频率对学习者产生较大影响,而互信息在语言学习的较高阶段对学习者产生较大影响。但是他们的研究没有考虑学习者对公式化语言的熟悉度,有研究表明熟悉度比频率能更好地预测学习者公式化语言加工的情况。因此,将熟悉度这一指标纳入考察的范围十分必要。同时,现有的研究大都以本族语人士和高水平二语学习者为研究对象,没有对较低水平的二语学习者进行研究,也没有研究不同水平的二语学习者在公式化语言加工中的不同特点和发展过程。另外,现有研究对公式化语言频率的统计主要基于本族语语料库,对二语学习者的语言输入特征的分析不够准确。
基于上述理论和研究发现,本论文采用心理语言学手段研究影响中国外语学习者公式化语言加工的各个因素。具体的研究问题是：1)中国外语学习者如何加工公式化语言?2)与母语使用者相比,频率、互信息、公式化语言长度和熟悉度如何影响中国外语学习者的公式化语言加工?3)这些不同的因素如何用一个语言习得的模型来解释?根据前人的研究和理论分析,我们提出了六个假设,分别是：1)中国外语学习者公式化语言的加工速度快于非公式化语言的加工速度；2)中国外语学习者高频公式化语言的加工速度快于低频公式化语言的加工速度；3)中国外语学习者在加工不同互信息值的公式化语言时没有明显差异；4)中国外语学习者对较长公式化语言的加工速度慢于较短公式化语言的加工速度；5)中国外语学习者对高熟悉度公式化语言的加工速度快于低熟悉度公式化语言的加工速度；6)不同水平的中国外语学习者的公式化语言加工过程存在差异。我们设计了三个研究工具来验证这些假设。三个研究工具分别是：眼动阅读任务,在线语法判断任务和朗读任务。20名高校非英语专业以汉语为母语的英语学习者参加了眼动阅读实验,37名高中以汉语为母语的英语学习者和7名英语本族语人士作为对照组参加了语法判断实验,21名高中以汉语为母语的英语学习者和2名英语本族语人士作为对照组参加了朗读实验。
研究发现在很大程度上验证了研究假设。首先,中国英语学习者加工公式化语言的速度比加工非公式化语言快。其次,频率和熟悉度对中国英语学习者的公式化语言加工有显著影响。第三,公式化语言的长度对中国英语学习者的公式化语言加工没有显著影响,但是对英语本族语者的公式化语言加工有显著影响。第四,不同语言水平的中国外语学习者在加工公式化语言时具有不同的特点。与研究假设不同的是,本研究发现互信息对中国英语学习者的公式化语言加工有显著影响,但这种影响不同于其对英语本族语者的影响。中国英语学习者加工高互信息的公式化语言时速度减慢,而英语本族语者加工高互信息的公式化语言时速度更快。
研究对Ellis等人(2008)提出的习得模型进行了补充。他们的模型提出,在语言学习的初始阶段,频率对学习者的语言习得起较大影响,即公式化语言的频率越高,加工速度越快；随着学习者的水平提高,互信息对学习者的语言习得发生较大影响,即公式化语言的互信息越高,加工速度越快。我们的研究对象主要是中等水平的中国英语学习者,与Ellis等人(2008)的研究对象相比,英语水平更低。我们的研究发现,互信息对更低水平的学习者起阻碍作用,即公式化语言的互信息越高,加工速度越慢。因此,我们的研究对Ellis等人(2008)的习得模型进行了补充,即对中级外语学习者而言,公式化语言的频率和互信息都对他们的语言加工产生较大的影响。其中,公式化语言的频率越高,加工速度越快；公式化语言的互信息越高,加工速度越慢。随着学习者语言水平的提高,互信息对他们的影响逐渐从阻碍变为促进。
本研究的贡献主要体现在以下几个方面：
首先,在理论上,本研究发现二语习得者的公式化语言的本质特性与母语习得者的公式化语言存在差异。英语本族语者的公式化语言为习得性公式化语言,他们在语言习得阶段积累了大量的公式化语言,从而整体地储存和使用这些公式化语言,而外语学习者公式化语言在加工过程中的整体性主要来自练习。
第二,在方法上,本研究采用了眼动实验和反应时实验等心理语言学的在线研究方法研究中国外语学习者的公式化语言加工过程。在线研究方法具有直观可靠的特点,可以即时地观测学习者在进行语言加工过程中的各种表现。同时,本研究的数据基于自建的小型教材语料库,与以往的研究相比,可以更准确地反映中国外语学习者的语言输入特点。
第三,本研究以不同水平的汉语为母语的英语学习者为研究对象,以英语本族语者为对照,对汉语为母语的英语学习者的公式化语言加工过程进行研究。以往的研究大多以高水平二语习得者为研究对象,没有研究不同水平的二语学习者的公式化语言加工特点。本研究的发现补充了Ellis等人(2008)的语言习得模型,指出在语言学习的初始阶段,互信息对学习者的语言加工起阻碍作用。随着语言水平的提高,互信息对外语学习者公式化语言加工的影响逐渐从阻碍转为促进。
Formulaic sequences play an important role in native-like selection and native-like fluency (Pawley&Syder,1983). They are found to constitute a large part of native-speakers'spoken and written discourse. However, second language learners are often found to overuse, underuse or misuse formulaic sequences, which lead to their unidiomatic linguistic output. A large number of researchers have attempted to explain how formulaic sequences can contribute to native-like selection and native-like fluency. The holistic processing hypothesis proposed by Wray and Perkins (2000) contends that formulaic sequences tend to be stored and retrieved as a whole, making them easier to use in communication. The Network model (Bybee,1985,1995) proposes the holistic representation for frequent morphologically complex words. Based on her model, Sosa and MacFarlane (2002) propose that larger units, such as non-idiomatic phrases and constructions, may also be stored in the lexicon and processed as single units. Many other researchers put forward similar assumptions. However, until recently, the holistic processing of formulaic sequences remained a theoretical assumption. Not many empirical studies were carried out to prove it.
The past decade has witnessed a renewed interest in the role of formulaic sequences. Some researchers attempted to test the holistic processing hypothesis by experimental studies. Their findings generally support the view that formulaic sequences are processed faster than non-formulaic ones among native speakers, but whether it plays the same role among second language learners still needs further study.
Some other studies examined the role of various factors in the processing of formulaic sequences among native speakers and non-native speakers. They found that frequency, mutual information (MI), and n-gram length influence native speakers and non-native speakers in different ways. Based on this finding, Ellis et al.(2008) propose a model of acquisition where frequency exerts more influence at the beginning stage of language learning and MI exerts more impact at a more advanced level. However, in their study, they did not consider the factor of familiarity, which might influence learners'processing of formulaic sequences, too. In addition, all previous studies take advanced second language learners as participants and do not include lower proficiency learners in their study. Neither do they adopt a cross-sectional study with learners at different proficiency levels and attempt to analyze the characteristics in processing formulaic sequences by learners at different proficiency levels. The frequency count of formulaic sequences in previous studies is mainly based on native speaker corpus and may not reflect the actual input characteristics for second language learners.
On the basis of the above analysis, the present study takes a psycholinguistic approach to investigate the factors that influence Chinese EFL learners'processing of formulaic sequences. More particularly, it endeavors to explore:(a) how Chinese EFL learners process formulaic sequences;(b) compared with native-speaker controls, how frequency, mutual information (MI), n-gram length and familiarity of formulaic sequences influence Chinese EFL learners'processing of formulaic sequences, and (c) how the different factors can be explained by a model of language acquisition proposed by the author in this study. Six hypotheses were established as follows:
H1:Chinese EFL learners process formulaic sequences faster than non-formulaic sequences.
H2:Chinese EFL learners process higher-frequency formulaic sequences faster than lower-frequency formulaic sequences.
H3:Chinese EFL learners do not process higher-MI formulaic sequences faster than lower-MI formulaic sequences.
H4:Chinese EFL learners process larger n-gram formulaic sequences more slowly than smaller n-gram formulaic sequences.
H5:Chinese EFL learners process higher-familiarity formulaic sequences faster than lower-familiarity formulaic sequences.
H6:Chinese EFL learners at different proficiency levels process formulaic sequences in different ways.
These hypotheses were investigated in three tasks, i.e., an eye-tracking reading task (ETRT), a grammaticality judgment task (GJT), and a reading task (RT). The latter two experiments were carried out using the E-prime software measuring participants'reaction times.20Chinese college non-English major students representing two English proficiency levels participated in the eye-tracking reading task.37Chinese high-school students representing two English proficiency levels and7native speakers took part in the grammaticality judgment task.21Chinese high-school students representing two English proficiency levels and2native speakers participated in the reading task.
Empirically, the current research finds that frequency, MI, familiarity and proficiency influence Chinese EFL learners'processing of formulaic sequences in different ways. First, the study finds that Chinese EFL learners process formulaic sequences faster than non-formulaic sequences. Frequency and MI are found to influence Chinese EFL learners'processing of formulaic sequences. The higher the frequency of a formulaic sequence, the faster Chinese EFL learners process it. But for MI, the higher the MI score of a formulaic sequence, the slower the processing speed on the part of Chinese EFL learners. N-gram length does not influence Chinese EFL learners'processing of formulaic sequences, but it is a significant factor for native speakers'processing of formulaic sequences. Familiarity influences Chinese EFL learners'processing of formulaic sequences to a certain extent. The correlation between proficiency and processing speed is partially supported by the data.
The results, to a large extent, confirmed the hypothesized developmental route. As the subjects in the present study represent the mid-proficiency and low-proficiency group, the data complement the model proposed by Ellis et al.(2008). Their model deals with advanced second language learners and native speakers and proposes that frequency influences learners at a lower proficiency and MI influences them at a higher proficiency. The data from the present study found that MI also influences lower proficiency learners, but in a different way. Instead of being a facilitating factor in language processing, it poses as a barrier in low proficiency learners'processing of formulaic sequences.
The contribution of the study lies in the following aspects.
Theoretically, the research finds that the nature of formulaic sequences among EFL learners differs from that of native-speakers. According to Wray (1999), formulaic sequences are stored and used as a whole among native-speakers. When they acquire their mother tongue, they memorize sentences and phrases they hear and later start to separate them and form rules. From the present study, it is found that frequency and familiarity are both influencing how a person processes a sequence. If learners are very familiar with a certain sequence, they will process it faster than other sequences. In other words, this processing advantage comes from exposure and practice, not from holistic storage in the first place. Learners process unfamiliar formulaic sequences in a similar way when they approach novel non-formulaic sequences, which indicates that their first reaction towards them is to use rules to interpret them instead of understanding them as a whole.
Secondly, the present study is the first one in the field to include the role of familiarity in EFL learners'processing of formulaic sequences. Previous studies include frequency as a factor but neglect familiarity in the study of the processing of formulaic sequences and get inconsistent results. The addition of familiarity helps to shed new light on our understanding of the processing of formulaic sequences by EFL learners.
Thirdly, the present study investigates the role of frequency, MI, familiarity, n-gram length and proficiency on the part of Chinese EFL learners. Most previous studies use advanced second language learners as participants and native speakers as controls. But only studying these two groups of subjects can not reveal the process of development on the part of the learners. Therefore, a cross-sectional study with learners at different proficiency levels is needed to explore how learners proceed when their proficiency level is enhanced. The advanced second language learners in existing studies are mostly college students studying in English-speaking countries. In contrast, Chinese EFL learners study English mainly through classroom instruction and practice. As one of the objectives of the present study is on the role of frequency in learners'processing of formulaic sequences, the input characteristics are important to the results. Therefore, taking Chinese EFL learners as subjects can help us to determine the difference between language learning in natural settings and in the classroom settings.
Fourthly, the present study discusses a possible model of language acquisition and may deepen our understanding of the second language acquisition process. Ellis et al.(2008) found that in the processing of formulaic sequences, second language learners are influenced by frequency and n-gram length while native speakers are under the influence of MI and n-gram length. Based on their findings, they proposed a model of language acquisition. In their model, at the beginning of the language acquisition process, frequency and practice play a large role. Frequent exposure and practice can consolidate the mental representation of a linguistic form. However, learners still need to establish an association between the linguistic forms and their functions in communication. They gradually acquire the form-function mapping of the language. So they will be more influenced by MI. The higher the MI score of a formulaic sequence, the faster it will be processed. But in their model, they did not take into account the lower level learners'linguistic development process. Therefore, with the addition of intermediate learners as subjects, we complete this model of acquisition.
Fifthly, the present study uses a textbook corpus to provide data on the input characteristics. Previous studies do not have such input characteristics and only use intuition or borrow from native speaker corpus to infer the input characteristics, which can not reflect the true properties of learners'input. In the present study, a corpus is made based on textbooks learners have learned in all their previous school years. It can be regarded as a more accurate source of learner input, as Chinese EFL learners mainly learn the language from classroom instruction and most of their language input is based on their textbooks.
Sixthly, the present study utilizes on-line methods to study Chinese EFL learners' processing of formulaic sequences. In contrast to the traditional off-line methods, the on-line methods record learners'processing features while the subjects are processing the data. The results are more direct and are supposed to reflect accurate situations. The present study uses the eye-tracking paradigm to study the online processing of formulaic sequences among Chinese EFL learners.
不少研究者都试图解释公式化语言如何能够提高语言的地道性和流利度。Wray和Perkins (2000)的整体加工假说提出公式化语言是以整体的形式储存和提取的,因此在交际中更容易使用。Bybee (1985,1995)提出了语言加工的网状模型,认为高频的具有复杂形态的词可以以整体形式储存在大脑中。在此基础上,Sosa和MacFarlane (2002)提出比词更大单位的公式化语言,也可以以整体形式储存在词库中。其他一些研究者也提出了类似的观点。然而,公式化语言的整体加工特性长期以来都只是一个理论上的假说,少有实证研究去证明它。
最近十年,公式化语言的研究又掀起了新的热潮。研究者们尝试用心理语言学的实验手段来验证其整体加工。研究发现公式化语言在本族语者的语言加工过程中具有整体性,但是在第二语言学习者的语言加工中是否具有整体性,尚缺乏一致的结论。
其他一些研究对本族语者和非本族语者公式化语言加工的各个因素进行了研究。他们发现频率、互信息、公式化语言长度等因素对本族语者和非本族语者产生不同的影响。在此基础上,Ellis等人(2008)提出了一个语言习得的模型,即在语言学习的初级阶段,频率对学习者产生较大影响,而互信息在语言学习的较高阶段对学习者产生较大影响。但是他们的研究没有考虑学习者对公式化语言的熟悉度,有研究表明熟悉度比频率能更好地预测学习者公式化语言加工的情况。因此,将熟悉度这一指标纳入考察的范围十分必要。同时,现有的研究大都以本族语人士和高水平二语学习者为研究对象,没有对较低水平的二语学习者进行研究,也没有研究不同水平的二语学习者在公式化语言加工中的不同特点和发展过程。另外,现有研究对公式化语言频率的统计主要基于本族语语料库,对二语学习者的语言输入特征的分析不够准确。
基于上述理论和研究发现,本论文采用心理语言学手段研究影响中国外语学习者公式化语言加工的各个因素。具体的研究问题是：1)中国外语学习者如何加工公式化语言?2)与母语使用者相比,频率、互信息、公式化语言长度和熟悉度如何影响中国外语学习者的公式化语言加工?3)这些不同的因素如何用一个语言习得的模型来解释?根据前人的研究和理论分析,我们提出了六个假设,分别是：1)中国外语学习者公式化语言的加工速度快于非公式化语言的加工速度；2)中国外语学习者高频公式化语言的加工速度快于低频公式化语言的加工速度；3)中国外语学习者在加工不同互信息值的公式化语言时没有明显差异；4)中国外语学习者对较长公式化语言的加工速度慢于较短公式化语言的加工速度；5)中国外语学习者对高熟悉度公式化语言的加工速度快于低熟悉度公式化语言的加工速度；6)不同水平的中国外语学习者的公式化语言加工过程存在差异。我们设计了三个研究工具来验证这些假设。三个研究工具分别是：眼动阅读任务,在线语法判断任务和朗读任务。20名高校非英语专业以汉语为母语的英语学习者参加了眼动阅读实验,37名高中以汉语为母语的英语学习者和7名英语本族语人士作为对照组参加了语法判断实验,21名高中以汉语为母语的英语学习者和2名英语本族语人士作为对照组参加了朗读实验。
研究发现在很大程度上验证了研究假设。首先,中国英语学习者加工公式化语言的速度比加工非公式化语言快。其次,频率和熟悉度对中国英语学习者的公式化语言加工有显著影响。第三,公式化语言的长度对中国英语学习者的公式化语言加工没有显著影响,但是对英语本族语者的公式化语言加工有显著影响。第四,不同语言水平的中国外语学习者在加工公式化语言时具有不同的特点。与研究假设不同的是,本研究发现互信息对中国英语学习者的公式化语言加工有显著影响,但这种影响不同于其对英语本族语者的影响。中国英语学习者加工高互信息的公式化语言时速度减慢,而英语本族语者加工高互信息的公式化语言时速度更快。
研究对Ellis等人(2008)提出的习得模型进行了补充。他们的模型提出,在语言学习的初始阶段,频率对学习者的语言习得起较大影响,即公式化语言的频率越高,加工速度越快；随着学习者的水平提高,互信息对学习者的语言习得发生较大影响,即公式化语言的互信息越高,加工速度越快。我们的研究对象主要是中等水平的中国英语学习者,与Ellis等人(2008)的研究对象相比,英语水平更低。我们的研究发现,互信息对更低水平的学习者起阻碍作用,即公式化语言的互信息越高,加工速度越慢。因此,我们的研究对Ellis等人(2008)的习得模型进行了补充,即对中级外语学习者而言,公式化语言的频率和互信息都对他们的语言加工产生较大的影响。其中,公式化语言的频率越高,加工速度越快；公式化语言的互信息越高,加工速度越慢。随着学习者语言水平的提高,互信息对他们的影响逐渐从阻碍变为促进。
本研究的贡献主要体现在以下几个方面：
首先,在理论上,本研究发现二语习得者的公式化语言的本质特性与母语习得者的公式化语言存在差异。英语本族语者的公式化语言为习得性公式化语言,他们在语言习得阶段积累了大量的公式化语言,从而整体地储存和使用这些公式化语言,而外语学习者公式化语言在加工过程中的整体性主要来自练习。
第二,在方法上,本研究采用了眼动实验和反应时实验等心理语言学的在线研究方法研究中国外语学习者的公式化语言加工过程。在线研究方法具有直观可靠的特点,可以即时地观测学习者在进行语言加工过程中的各种表现。同时,本研究的数据基于自建的小型教材语料库,与以往的研究相比,可以更准确地反映中国外语学习者的语言输入特点。
第三,本研究以不同水平的汉语为母语的英语学习者为研究对象,以英语本族语者为对照,对汉语为母语的英语学习者的公式化语言加工过程进行研究。以往的研究大多以高水平二语习得者为研究对象,没有研究不同水平的二语学习者的公式化语言加工特点。本研究的发现补充了Ellis等人(2008)的语言习得模型,指出在语言学习的初始阶段,互信息对学习者的语言加工起阻碍作用。随着语言水平的提高,互信息对外语学习者公式化语言加工的影响逐渐从阻碍转为促进。
Formulaic sequences play an important role in native-like selection and native-like fluency (Pawley&Syder,1983). They are found to constitute a large part of native-speakers'spoken and written discourse. However, second language learners are often found to overuse, underuse or misuse formulaic sequences, which lead to their unidiomatic linguistic output. A large number of researchers have attempted to explain how formulaic sequences can contribute to native-like selection and native-like fluency. The holistic processing hypothesis proposed by Wray and Perkins (2000) contends that formulaic sequences tend to be stored and retrieved as a whole, making them easier to use in communication. The Network model (Bybee,1985,1995) proposes the holistic representation for frequent morphologically complex words. Based on her model, Sosa and MacFarlane (2002) propose that larger units, such as non-idiomatic phrases and constructions, may also be stored in the lexicon and processed as single units. Many other researchers put forward similar assumptions. However, until recently, the holistic processing of formulaic sequences remained a theoretical assumption. Not many empirical studies were carried out to prove it.
The past decade has witnessed a renewed interest in the role of formulaic sequences. Some researchers attempted to test the holistic processing hypothesis by experimental studies. Their findings generally support the view that formulaic sequences are processed faster than non-formulaic ones among native speakers, but whether it plays the same role among second language learners still needs further study.
Some other studies examined the role of various factors in the processing of formulaic sequences among native speakers and non-native speakers. They found that frequency, mutual information (MI), and n-gram length influence native speakers and non-native speakers in different ways. Based on this finding, Ellis et al.(2008) propose a model of acquisition where frequency exerts more influence at the beginning stage of language learning and MI exerts more impact at a more advanced level. However, in their study, they did not consider the factor of familiarity, which might influence learners'processing of formulaic sequences, too. In addition, all previous studies take advanced second language learners as participants and do not include lower proficiency learners in their study. Neither do they adopt a cross-sectional study with learners at different proficiency levels and attempt to analyze the characteristics in processing formulaic sequences by learners at different proficiency levels. The frequency count of formulaic sequences in previous studies is mainly based on native speaker corpus and may not reflect the actual input characteristics for second language learners.
On the basis of the above analysis, the present study takes a psycholinguistic approach to investigate the factors that influence Chinese EFL learners'processing of formulaic sequences. More particularly, it endeavors to explore:(a) how Chinese EFL learners process formulaic sequences;(b) compared with native-speaker controls, how frequency, mutual information (MI), n-gram length and familiarity of formulaic sequences influence Chinese EFL learners'processing of formulaic sequences, and (c) how the different factors can be explained by a model of language acquisition proposed by the author in this study. Six hypotheses were established as follows:
H1:Chinese EFL learners process formulaic sequences faster than non-formulaic sequences.
H2:Chinese EFL learners process higher-frequency formulaic sequences faster than lower-frequency formulaic sequences.
H3:Chinese EFL learners do not process higher-MI formulaic sequences faster than lower-MI formulaic sequences.
H4:Chinese EFL learners process larger n-gram formulaic sequences more slowly than smaller n-gram formulaic sequences.
H5:Chinese EFL learners process higher-familiarity formulaic sequences faster than lower-familiarity formulaic sequences.
H6:Chinese EFL learners at different proficiency levels process formulaic sequences in different ways.
These hypotheses were investigated in three tasks, i.e., an eye-tracking reading task (ETRT), a grammaticality judgment task (GJT), and a reading task (RT). The latter two experiments were carried out using the E-prime software measuring participants'reaction times.20Chinese college non-English major students representing two English proficiency levels participated in the eye-tracking reading task.37Chinese high-school students representing two English proficiency levels and7native speakers took part in the grammaticality judgment task.21Chinese high-school students representing two English proficiency levels and2native speakers participated in the reading task.
Empirically, the current research finds that frequency, MI, familiarity and proficiency influence Chinese EFL learners'processing of formulaic sequences in different ways. First, the study finds that Chinese EFL learners process formulaic sequences faster than non-formulaic sequences. Frequency and MI are found to influence Chinese EFL learners'processing of formulaic sequences. The higher the frequency of a formulaic sequence, the faster Chinese EFL learners process it. But for MI, the higher the MI score of a formulaic sequence, the slower the processing speed on the part of Chinese EFL learners. N-gram length does not influence Chinese EFL learners'processing of formulaic sequences, but it is a significant factor for native speakers'processing of formulaic sequences. Familiarity influences Chinese EFL learners'processing of formulaic sequences to a certain extent. The correlation between proficiency and processing speed is partially supported by the data.
The results, to a large extent, confirmed the hypothesized developmental route. As the subjects in the present study represent the mid-proficiency and low-proficiency group, the data complement the model proposed by Ellis et al.(2008). Their model deals with advanced second language learners and native speakers and proposes that frequency influences learners at a lower proficiency and MI influences them at a higher proficiency. The data from the present study found that MI also influences lower proficiency learners, but in a different way. Instead of being a facilitating factor in language processing, it poses as a barrier in low proficiency learners'processing of formulaic sequences.
The contribution of the study lies in the following aspects.
Theoretically, the research finds that the nature of formulaic sequences among EFL learners differs from that of native-speakers. According to Wray (1999), formulaic sequences are stored and used as a whole among native-speakers. When they acquire their mother tongue, they memorize sentences and phrases they hear and later start to separate them and form rules. From the present study, it is found that frequency and familiarity are both influencing how a person processes a sequence. If learners are very familiar with a certain sequence, they will process it faster than other sequences. In other words, this processing advantage comes from exposure and practice, not from holistic storage in the first place. Learners process unfamiliar formulaic sequences in a similar way when they approach novel non-formulaic sequences, which indicates that their first reaction towards them is to use rules to interpret them instead of understanding them as a whole.
Secondly, the present study is the first one in the field to include the role of familiarity in EFL learners'processing of formulaic sequences. Previous studies include frequency as a factor but neglect familiarity in the study of the processing of formulaic sequences and get inconsistent results. The addition of familiarity helps to shed new light on our understanding of the processing of formulaic sequences by EFL learners.
Thirdly, the present study investigates the role of frequency, MI, familiarity, n-gram length and proficiency on the part of Chinese EFL learners. Most previous studies use advanced second language learners as participants and native speakers as controls. But only studying these two groups of subjects can not reveal the process of development on the part of the learners. Therefore, a cross-sectional study with learners at different proficiency levels is needed to explore how learners proceed when their proficiency level is enhanced. The advanced second language learners in existing studies are mostly college students studying in English-speaking countries. In contrast, Chinese EFL learners study English mainly through classroom instruction and practice. As one of the objectives of the present study is on the role of frequency in learners'processing of formulaic sequences, the input characteristics are important to the results. Therefore, taking Chinese EFL learners as subjects can help us to determine the difference between language learning in natural settings and in the classroom settings.
Fourthly, the present study discusses a possible model of language acquisition and may deepen our understanding of the second language acquisition process. Ellis et al.(2008) found that in the processing of formulaic sequences, second language learners are influenced by frequency and n-gram length while native speakers are under the influence of MI and n-gram length. Based on their findings, they proposed a model of language acquisition. In their model, at the beginning of the language acquisition process, frequency and practice play a large role. Frequent exposure and practice can consolidate the mental representation of a linguistic form. However, learners still need to establish an association between the linguistic forms and their functions in communication. They gradually acquire the form-function mapping of the language. So they will be more influenced by MI. The higher the MI score of a formulaic sequence, the faster it will be processed. But in their model, they did not take into account the lower level learners'linguistic development process. Therefore, with the addition of intermediate learners as subjects, we complete this model of acquisition.
Fifthly, the present study uses a textbook corpus to provide data on the input characteristics. Previous studies do not have such input characteristics and only use intuition or borrow from native speaker corpus to infer the input characteristics, which can not reflect the true properties of learners'input. In the present study, a corpus is made based on textbooks learners have learned in all their previous school years. It can be regarded as a more accurate source of learner input, as Chinese EFL learners mainly learn the language from classroom instruction and most of their language input is based on their textbooks.
Sixthly, the present study utilizes on-line methods to study Chinese EFL learners' processing of formulaic sequences. In contrast to the traditional off-line methods, the on-line methods record learners'processing features while the subjects are processing the data. The results are more direct and are supposed to reflect accurate situations. The present study uses the eye-tracking paradigm to study the online processing of formulaic sequences among Chinese EFL learners.
引文
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