Chapter 3 Methodology
3.4 Data Analysis
In the current experiment, the E-Prime 2.0 software from Psychology Software Tools,
Inc. was used under the Windows XP system to present the experimental stimuli and to
record the subjects' behavioral data (i.e. reaction time (RT) and response accuracy). The
software SPSS 18 was used to analyze the data collected from subjects.
Only data with accuracy rate higher than 95% were included and only trials with
correct responses were analyzed. Also, if the reaction time was slower/faster than mean
score plus/minus two SDs, the data were excluded.
Behavioral data (RTs and accuracy rate) were analyzed with a two-way repeated
analysis of variance (ANOVA) with the factors of separability (separated, unseparated) and
semantic transparency (Opaque (similar to VOCs in the traditional term), In between, and
Transparent (similar to VOPs in the traditional term)). An alpha value of 0.05 (two-tailed)
34
was adopted, with the Greenhouse-Geisser correction applied when the Mauchly's test of
Sphericity was violated. As for follow-up paired t-tests, a two-tailed alpha level of 0.05 was
chosen and Bonferroni corrected.
35
Chapter 4
Results
The current study recruited 39 subjects for the experiment. Five subjects’ data were
excluded due to the fact that their RTs were slower than the criterion (mean score plus two
SDs). There was no data excluded due to RTs which are faster than mean score minus two
SDs. The data from the rest of the 34 subjects were further analyzed.
First of all, 34 subjects’ mean RT and accuracy rate are illustrated in Table 4. The data
revealed that the accuracy rates were high among all the conditions. As for the RTs, no matter
in separated condition or unseparated condition, the RTs in the transparent groups were the
highest. .
Table 4. Behavioral data of the subjects. (OS, opaque, separated; OU, opaque, unseparated;
IS, in between, separated; IU, in between, unseparated; TS, transparent, separated; TU, transparent, unseparated). Note: S.D. is indicated in parenthesis
Conditions OS OU IS IU TS TU For the subjects' RTs, a 2 x 3 repeated ANOVA with the factors of separability
36
(separated, unseparated) and transparency (opaque, in between, transparent) was conducted.
The results showed that there was a main effect of transparency (F(2,66)=7.91, p<.005),
while no main effect of separability (F(1,33)=.61, p=.44) and no interaction between the two
factors (F(2,66)=.59, p=.555) were found. The results of follow-up paired t-test on
comparing the VO separated condition and the VO unseparated condition in each semantic
transparency level are summarized in Table 5. The results confirmed that there was no
significant RT difference between the two conditions.
Table 5. Separability effect: T-test results of reaction time in VO unseparated and separated conditions (OS, opaque, separated; OU, opaque, unseparated; IS, in between separated; IU, in between, unseparated; TS, transparent, separated; TU, transparent, unseparated).
Transparency Separablilty (S/U) Mean(S.D)ms t(33) p Opaque (O) OS vs. OU -2.86 (89.13) -.188 .852
In between (I) IS vs. IU 2.94 (84.52) .203 .840
Transparent (T) TS vs. TU 24.09 (137.25) 1.024 .313
On the other hand, the follow-up t-tests on the transparency effect revealed that there
were significant differences between the Opaque and the Transparent groups and also
between the Transparent group and the In between groups (Opaque vs. In between: t (67)
=-.12, p = 1; In between vs. Transparent: t (67) =-3.05, p < .01, Transparent vs. Opaque: t
37
(33) =3.30, p < .01) The summary of t-test is provided in Table 6.
Table 6. Transparency effect: T-test results of reaction times between conditions.
Comparison t(67) p
Opaque vs. In between -.12 1
In between vs. Transparent -3.05 .009*
Transparent vs. Opaque 3.30 .006*
(* p < .01)
Although there was no interaction between transparency and separability, planned
comparisons were conducted to further examine the effect of transparency in the separated
and the unseparated conditions. The results showed that there was no RT difference
regarding transparency in the separated conditions (F(2,66)=2.01, p=.142 ;), but there was a
significant RT difference in the unseparated conditions (F(2,66)=6.54, p<.005. Follow-up t
tests in the unseparated conditions revealed that the transparent condition took longer to
process than the other two conditions (TU>OU=IU) (Opaque vs. In between: t (33) =-.31, p
= 1; In between vs. Transparent: t (33) = -2.58, p < .05, Transparent vs. Opaque : t (33)
=3.08, p < .05). The results are summarized in Table 7.
38
Table 7. Transparency effect in separated and unseparated conditions: T-test results of reaction times between conditions (OS, opaque, separated; IS, in between separated; IS, in between separated; TS, transparent, separated; TS, transparent, separated; OS, opaque, separated /OU, opaque, unseparated; IU, in between, unseparated; IU, in between, unseparated ; TU, transparent, unseparated; TU, transparent, unseparated OU, opaque, unseparated).
Comparison t(33) p Comparison t(33) p
OS vs. IS .09 1 OU vs. IU -.31 1
IS vs. TS -1.69 1 IU vs. TU -2.58 .042*
TS vs. OS 1.61 .34 TU vs. OU 3.08 .012*
(* p < .05)
As to the accuracy rate of subjects' responses, a two-way repeated measures ANOVA
with the factors of semantic transparency and separability showed that there was a main
effect of separability (F (1, 33)=4.33, p=.045), with the unseparated condition having a
higher accuracy rate than the separated one. There was no main effect of transparency (F(2,
66)=.39, p=.594) and the interaction between the two factors did not reach significance,
either (F(2,66)=1.20, p=.293). To find out if transparency played a role in processing the VO
sequence in the separated and the unseparated conditions, planned comparisons between
separated and unseparated conditions at each semantic transparency level were conducted
and are summarized in Table 8. As Table 8 shows, no accuracy difference was present
39
between separated and unseparated condition in all the semantic transparency conditions. (In
the separated condition: Opaque vs. In between: t (33) =-.94, p = 1; In between vs.
Transparent: t (33) =1.15, p =.771, Transparent vs. Opaque: t (33) =-1.00, p =.975 ; in the
unseparated conditions: Opaque vs. In between: t (33) =.70, p = 1; In between vs.
Transparent: t (33) =-.32, p =1, Transparent vs. Opaque: t (33) =-.44, p =1)
Table 8. Transparency effect in separated and unseparated conditions: T-test results of accuracy rates between conditions: (OS, opaque, separated ; IS, in between separated; IS, in between separated; TS, transparent, separated; TS, transparent, separated; OS, opaque, separated /OU, opaque, unseparated; IU, in between, unseparated; IU, in between,
unseparated ; TU, transparent, unseparated; TU, transparent, unseparated OU, opaque, unseparated).
Comparison t(33) p Comparison t(33) p
OS vs. IS -.94 1 OU vs. IU .70 1
IS vs. TS 1.15 .771 IU vs. TU -.32 1
TS vs. OS -1.00 .975 TU vs. OU -.44 1
40
Chapter 5
Discussion
The purpose of the current study was to empirically examine whether native speakers of
Mandarin Chinese process an opaque VO sequence (similar to VOCs in the traditional term)
differently from a transparent VO sequence (similar to VOPs in the traditional term). By
manipulating semantic transparency as well as the separability of the VO sequence, we
hoped to capture the process of lexicalization in the subjects’ mind.
To begin with, the results of reaction times showed that the participants reacted faster to
unseparated VO structures in the Opaque and In between groups than to those in the
Transparent group, but did not have such an RT difference among the three conditions in
processing separated VO structures. Since unseparated VO structures in the Opaque and In
between groups fall into the traditional categorization of VOCs, our data revealed that
compared with transparent VO sequence, VO structures in the Opaque and the In between
groups might be processed as a lexical unit without decomposition. Once VO structures
were separated, the VO structures in the Opaque and In between groups would be processed
like phrases, as those VO structures in the Transparent group.
Also, our results revealed that the accuracy rate mirrored the result of sentence
41
naturalness. It was reported in Chapter Three that VO separated sentences were rated less
natural than VO unseparated sentences. In line with the result of sentence naturalness,
people were more likely to give wrong answers when the stimuli were separated VO
structures. It is not surprising since in previous literature (Yi, 2007), it was attested that the
unseparated VO form was the default form of VOCs. However, it should be noted that
though the accuracy rate was statistically different between separated and unseparated
sentences, the accuracy rate was higher than 97% in all the conditions.
As mentioned in Chapter 2, there are three main standpoints about the identity of
VOCs: (1) VOCs should be defined as a lexical unit (Chao, 1968; Li & Thompson, 1983; Yi,
2007; Wang, 2009), (2) VOCs that could be used with separate constituents should be
treated as phrases (Lu, 1979; Paul, 1988; Sybesma, 1999) and (3) VOCs are words when
they are in unseparated form, and are phrases when they are in separated form (Liu1967;
Zhang, 2010). Some researchers furthered the last point of view by suggesting that VOCs are in a “middle-state”: they are in a continuum of lexicalization, the process of creating
items out of syntactic units (Cabrera et al., 1998). The results of the current study support
the third standpoint. It can be seen from the RTs that people indeed treated unseparated
opaque VO structured verbs ( as in verbs in Opaque and In between group) as a lexical unit
because the time they used to process these items was much shorter than that in processing
unseparated transparent VO structured verbs (verbs in the Transparent group). Also,
42
subjects treated separated opaque VO structured verbs like phrases since there was no
significant RT difference among separated VO structured verbs in the Opaque, In between
and Transparent categories. It should be mentioned that the In between condition behaved
more like the Opaque group in the unseparated condition. Future studies are needed to see if
semantic transparency is indeed a defining factor for the status of VOCs and to see if there
is a way to better quantify it: how “opaque” a VO structure should be to be treated as a
lexical item by language users.
From a psycholinguistic viewpoint, the processing mechanism of VOCs in people’s
mind can be inferred from the current results. As mentioned in Chapter 2, whether
morphologically complex words are stored in the mental lexicon in their full form or
whether only their morphemes are stored is a controversial issue. Three related models are:
full-listing models (Butterworth, 1983; Bybee, 1995), full-parsing models (Libben, Derwing,
& de Almeida, 1999; Taft, 2004; Taft & Forster, 1976) and the dual-route models (Gunter, &
Friederici, 2003; Koester, Gunter, & Wagner, 2004, 2007; Zwitserlood, 1994). In the
dual-route models, a complex word can either be stored completely or be decomposed into
its morphological constituents. Based on this type of models, frequently used compounds
and opaque compounds are usually stored in their full form since it would be more efficient
to retrieve a whole unit than repeatedly (de)compose it. In contrast, the meanings of
transparent and less-frequently used compounds are more likely to be derived by
43
decomposing/combining its constituents (Sandra, 1990; Zwitserlood, 1994). The results of
the current study showed that the processing of the opaque VO sequence can be adequately
captured in terms of the dual-route models. The RT difference between Opaque and In
between groups(similar to VOCs in traditional term) and Transparent group (similar to VOPs
in traditional term) showed that the opaque VO sequence might be stored as a whole unit
while the transparent VO sequence need to be decomposed. On the other hand, the equal
amount of RT between the opaque VO sequence and the transparent VO sequence in the
separated forms showed that, under the influence of interposing elements, the opaque VO
sequence might be processed through the decomposition / combinatory route, just like how
transparent VO sequences were processed. The result thus reflected that dual-route models
are a more plausible approach on explaining the opaque VO sequence processing.
It should be noticed that within each semantic transparency condition (Opaque, In
between and Transparent), there was no RT difference between separated and unseparated
forms, suggesting that the processing of lexical units and short phrases, especially when they
are of the same length (3 characters long in the current study), is equally automatic. Future
studies using electrophysiological techniques are needed to find out whether there are
qualitative differences in brain responses in processing separated vs. unseparated VO
sequences despite the quantitative similarity in the RTs.
44
Chapter 6
Conclusion
To sum up, the current study adds to the literature of theoretical linguistics and
psycholinguistics. It confirms previous theoretical linguists’ view (Chao, 1968; Li &
Thompson, 1983; Yi, 2007) and shows that semantic transparency is indeed a crucial factor
in defining VOCs. It also shows that separability does play a role in defining the status of
VOCs: opaque VO sequences are lexical units when unseparated and are phrases when
separated. Finally, the study demonstrates that opaque VO sequences may be accessed via
dual routes in the mental lexicon: they are retrieved as a whole unit when they are in an
unseparated form but are retrieved morpheme by morpheme when they are in a separated
form.
Finally, the current study has a limitation. Since a behavioral study can only reflect how
fast a participant processes the VO sequences, how he/she processes the inner structure
within a VO sequence is still unknown. It was mentioned in Chapter Two that a recent study
conducted by Cappelle et al. (2010) showed that English phrasal verbs are perceived as a
lexical unit and that the relationship between the verb and the particle is not a syntactic one.
Future ERP studies on the VO sequence inner relationship may shed some light on this
45
issue.
46
References
Baayen, R. H., Dijkstra, T., & Schreuder, R. (1997). Singulars and plurals in Dutch: Evidence for a parallel dual-route model. Journal of Memory and Language, 37, 94–117.
Butterworth, B. (1983). Lexical representation. In B. Butterworth (Ed.), Language production (pp. 257–294). San Diego, CA: Academic Press.
Bybee J. (1995). Regular morphology and the lexicon. Language and Cognitive Processes. 425–455.
Cappelle, Bert, Shtyrov, Y., & Pulvermuller, F. (2010). Heating up or cooling up the brain?
MEG evidence that phrasal verbs are lexical units. BRAIN AND LANGUAGE, 115(3), 189–201.
Carlisle, J. F. (2000). Awareness of the structure and meaning of morphologically complex words: Impact on reading. Reading and Writing, 12(3), 169-190.
Chao, Yuen-ren. (1948). Mandarin Primer. Cambridge, MA: Harvard University Press.
Chao, Yuen-ren. (1968). A Grammar of Spoken Chinese. Berkeley and Los Angeles:
University of California Press.
Chung, K. S. (2004). Mandarin compound verbs. Universiteit Leiden.
Chung K. K. H., T. X., Liu P. D., McBride-Chang C., Meng X. (2010). The processing of morphological structure information in Chinese coordinative compounds: an
event-related potential study. Brain Res. 1352, 157-166.
Christina L. Gagné , T. L. S. (2008). Constituent integration during the processing of compound words: Does it involve the use of relational structures? Journal of Memory and Language, 20-35.
Fang, C.方瑾(2008)。論現代漢語詞素、詞、詞組之界定及其教學啟示。Master thesis, National Taiwan Normal University Department of Chinese as a Second Language.
47
Frisson S., Niswander-Klement E., Pollatsek A. The role of semantic transparency in the processing of English compound words. British Journal of Psychology. 2008;99:87–
107.
Gagne, C. L., & Spalding, T. L. (2009). Constituent integration during the processing of compound words: Does it involve the use of relational structures? Journal of Memory and Language, 60, 20–35
Koester D., Gunter T.C., Wagner S. The morphosyntactic decomposition and semantic composition of German compound words investigated by ERPs. Brain and
Language. 2007;102:64–79.
Koester D., Gunter T.C., Wagner S., Friederici A.D. Morphosyntax, prosody, and linking elements: The auditory processing of German nominal compounds. Journal of Cognitive Neuroscience.2004;16:1647–1668
Huang, James C.-T., 1984. Phrase structure, lexical integrity, and Chinese compounds.
Journal of the Chinese Language Teachers Association 19, 53–78.
Haarmann, H. J., Cameron, K. A., & Ruchkin, D. S. (2003). Short-term semantic retention during on-line sentence comprehension. Brain potential evidence from filler-gap constructions. Cognitive Brain Research, 15(2), 178-190.
Isel F., Gunter T.C., Friederici A.D. Prosody-assisted head-driven access to spoken German compounds.Journal of Experimental Psychology: Learning, Memory, and
Cognition. 2003;29:277–288.
Jia, X., Wang, S., Zhang, B., & Zhang, J. X. (2013). Electrophysiological evidence for relation information activation in Chinese compound word comprehension.
Neuropsychologia,51(7), 1296-1301.
Ji, H., Gagné, C. L., & Spalding, T. L. (2011). Benefits and costs of lexical decomposition and semantic integration during the processing of transparent and opaque English compounds. Journal of Memory and Language, 65(4), 406-430.
Katz, L., Rexer, K., & Lukatela, G. (1991). The processing of inflected words.Psychological
48
research, 53(1), 25-32.
King, J. W., & Kutas, M. (1995). Who did what and when? Using word-and clause-level ERPs to monitor working memory usage in reading. Journal of cognitive
neuroscience,7(3), 376-395.
Koester, D., Gunter, T. C., & Wagner, S. (2007). The morphosyntactic decomposition and semantic composition of German compound words investigated by ERPs. Brain and Language, 102(1), 64-79.
Libben, G., Derwing, B. L., & Almeida, R. G. (1999). Ambiguous novel compounds and models of morphological parsing. Brain and Language, 68, 378–386.
Libben, G., Gibson, M., Yoon, Y. B., & Sandra, D. (2003). Compound fracture: The role of semantic transparency and morphological headedness. Brain and Language, 84, 50–64.
Li, Charles N., and Sandra A Thompson. (1981). Mandarin Chinese: A functional Reference Grammar. Berkeley: University of California Press.
Li, P., Bates, E., & MacWhinney, B. (1993). Processing a language without inflections: A reaction time study of sentence interpretation in Chinese. Journal of Memory and Language, 32(2), 169-192.
Liu, Z.W. 陸志偉. (1957). 汉语的构词法.
Lieber, R., & Stekauer, P. (Eds.). (2009).The Oxford handbook of compounding. Oxford University Press.
Lu, S.X. 吕叔湘. (1979). 汉语语法分析问题. 商务印书馆, p.22.
MacGregor, L. J., & Shtyrov, Y. (2013). Multiple routes for compound word processing in the brain: Evidence from EEG. Brain and Language, 126(2), 217-229.
Myers, J., Derwing, B., & Libben, G. (2004). The effect of priming direction on reading Chinese compounds. Mental Lexicon Working Papers, 1, 69-86.
49
Myers, J., Huang, Y. C., & Wang, W. (2006). Frequency effects in the processing of Chinese inflection. Journal of Memory and Language, 54(3), 300-323.
Paul, W. (1988), The Syntax of Verb-Object Phrases in Chinese: Constraints and Reanalysis.
Paris: Langages croises, VIII-232.;26cm.
Packard, Jerome Lee. (1998). New Approaches to Chinese Word Formation: Morphology, Phonology and the Lexicon in Modern and Ancient Chinese. New York: Mouton de Gruyter.
Packard, Jerome Lee. (2000). The Morphology of Chinese: A Linguistic and Cognitive Approach. Cambridge: Cambridge University Press.
Pollatsek A., Hyönä J. The role of semantic transparency in the processing of Finnish compound words.Language and Cognitive Processes. 2005;20:261–290.
Pulvermuller, F., & Shtyrov, Y. (2003). Automatic processing of grammar in the human brain as revealed by the mismatch negativity. Neuroimage, 20, 159–172 Pulvermüller, F., Shtyrov, Y., Hasting, A. S., & Carlyon, R. P. (2008). Syntax as a reflex:
Neurophysiological evidence for early automaticity of grammatical processing. Brain and Language, 104(3), 244-253.
Sandra D. On the representation and processing of compound words: Automatic access to constituent morphemes does not occur. Quarterly Journal of Experimental Psychology A:
Human Experimental Psychology. 1990;42:529–567.
Smith, S. (1999) Discontinuous compounds in Mandarin Chinese. University of Manchester Institute of Science. Department of Language Engineering.
SIEWIERSKA, A., JIAJIN, X., & XIAO, R. (2010). Bang-le yi ge da mang (offered a big helping hand): a corpus study of the splittable compounds in spoken and written Chinese. Language sciences, 32(4), 464-487.
Tang, Ting-chi. (1989). Hànyǔ cífǎ jùfǎ lùjí (Studies on Chinese morphology and syntax).
Taipei: Taiwan Xīnxuéshēng Book Co.
50
Taft M. Morphological decomposition and the reverse base frequency effect. The Quarterly Journal of Experimental Psychology. 2004;57A:745–765.
Taft, M., & Forster, K. (1976). Lexical storage and retrieval of polymorphemic and polysyllabic words. Journal of Verbal Learning and Verbal Behavior, 15, 607–620.
Wang, C.C. 王楚蓁(2008)。現代漢語詞類劃分與教學語法。Master thesis. National Taiwan Normal University. Department of Chinese as a Second Language.
Wang, H.F.王海峰. (2009). 基於大型語料庫的現代漢語離合詞定量研究. 華語文教學研 究,6(1), 59-89.
Xing, J. Z. (2006). Teaching and learning Chinese as a foreign language: A pedagogical grammar. Hong Kong: Hong Kong University Press.
Chao, Y. R. (1968). A grammar of spoken Chinese. University of California Press.
Yu, N. S. S. (2003). Discontinuous Verb-Object Compounds in Cantonese. Second North American Summer School in Language, Logic and Information Student Session Proceedings, 52.
Yi, H.M. (2007)。現代漢語「離合詞」之研究及其在教學上之運用的探討。Master thesis.
National Taiwan Normal University, Department of Chinese as a Second Language.
Youyi Liu , P. L., Hua Shu , Qirui Zhang , Lang Chen (2010). Structure and meaning in Chinese: An ERP study of idioms. Journal of Neurolinguistics, 615-630.
Zhang, Y.張楊. (2010). 谈影响词离合运用的主要因素. 语文学刊: 高等教育版, (2), 87-88.
Zhang, H., Yang, Y., Gu, J., & Ji, F. (2013). ERP correlates of compositionality in Chinese idiom comprehension. Journal of Neurolinguistics, 26(1), 89-112.
Zhang F. Z. (2013).A Study on Separable Words in Modern Chinese Master thesis National Taiwan Normal University. Department of Chinese as a Second Language
Zhou, X., & Marslen-Wilson, W. (1994). Words, morphemes and syllables in the Chinese mental lexicon. Language and Cognitive Processes,9(3), 393-422.
51
Zhou X., Marslen-Wilson W. Lexical representation of compound word: Cross-linguistic evidence.Psychologia. 2000;43:47–66.
Zhu, D. X. (1982). 语法讲义. 商务印书馆.
Zwitserlood P. The role of semantic transparency in the processing and representation of Dutch compound words. Language and Cognitive Processes. 1994;9:341–368
52
Appendices
A. The rating questionnaire for stimulus’ semantic transparency
漢語詞彙處理歷程研究 (透明度問卷)
53
B. The rating questionnaire for stimulus’ familiarity
漢語詞彙處理歷程研究 (熟悉度問卷)
問卷說明
您好:
感謝您協助填寫此問卷。此份是有關漢語詞彙的問卷,填寫問卷者須符合以下的資格:
感謝您協助填寫此問卷。此份是有關漢語詞彙的問卷,填寫問卷者須符合以下的資格: