The processing of compound words has long been a fascinating research subject since it can provide valuable insights into the structure and working mechanism of the mental lexicon. Using a lexical decision task and two cross-language priming experiments, the study explored the role of semantic transparency and lexicality, and tested the hypothesis of cross-language priming asymmetry. The findings argue that Chinese has a role to play in the processing of English compound words by Chinese EFL learners, and that compound decomposition is an inevitable stage in processing. Compound words are represented in the bilingual lexicon in a way different from the way they are represented in the monolingual lexicon mainly because of the intervention of L1 between L2 and the semantic representation.
Contents
Chapter 1 Introduction1
1.1 Context of the Study1
1.2 Research Questions and Relevant Concepts3
1.3 Significance of the Study7
1.4 Organization of the Book9
Chapter 2 Theoretical Background： Compounding Morphology and Approaches to Processing Morphologically Complex Words12
2.1 The Linguistic Description of Compound Words12
2.2 Compound Words in Chinese21
2.3 Theoretical Background of the Research on Morphologically Complex Words24
2.4 Summary31
Chapter 3 Literature Review： Compound Word Processing as a Research Domain33
3.1 The Processing of L1 Compound Words34
3.2 The Processing of Chinese Compound Words47
3.3 The Processing of L2 Compound Words52
3.4 The Present Study60
3.5 Summary65
Chapter 4 Experiment 1： Lexical Decision on English Compound Words by Chinese EFL Learners68
4.1 Hypotheses68
4.2 Method69
4.3 Results80
4.4 Discussion83
4.5 Summary87
Chapter 5 Experiments 2 & 3： Cross-language Priming in Compound Word Processing by Chinese EFL Learners88
5.1 Hypotheses89
5.2 Method91
5.3 Results103
5.4 Discussion113
5.5 Summary118
Chapter 6 General Discussion120
6.1 Morphological Decomposition in L1 and L2 Compound Processing120
6.2 Cross-language Activation in L2 Compound Processing125
6.3 The Time Course of L2 Morphological Processing133
6.4 Semantic Transparency in L1 and L2 Compound Processing135
6.5 Summary137
Chapter 7 Conclusion139
7.1 Overall Summary of the Findings140
7.2 Implications142
7.3 Limitations and Future Research Directions145
Bibliography148
Abbreviations164
Appendices165
Appendix I： Familiarity Rating165
Appendix II： Semantic Transparency Rating English170
Appendix III： Semantic Transparency Rating Chinese173
Appendix IV： Morpheme Translation English to Chinese177
Appendix V： Morpheme Translation Chinese to English179
Appendix VI： Critical Test Items and Rating Results in Experiment1 181
Appendix VII： Primes and Targets in Experiment 2182
Appendix VIII： Primes and Targets in Experiment 3183
List of Tables
Table 4.1 English Compound Words Rated as Transparent and Opaque in Experiment 173
Table 4.2 Critical Items of Experiment 176
Table 4.3 Average Level of Familiarity and Transparency for 4 Conditions in Experiment 177
Table 4.4 Mean ARs SDs and RTs SDs in 4 Conditions in Experiment 1 by Subjects81
Table 4.5 Mean ARs SDs and RTs SDs in 4 Conditions in Experiment 1by Items81
Table 5.1 Sample Items of Experiments 2 and 393
Table 5.2 Critical Items Targets of Experiment 398
Table 5.3 Means of Frequency Rankings, Number of Strokes and Transparency for Target Items in Experiment 399
Table 5.4 Means of Frequency RankingsFrequency and Number of StrokesLetters for Primes in Experiments 2 & 399
Table 5.5 Mean ARs SDs and Priming Effects in Experiment 2104
Table 5.6 Mean RTs SDs and Priming Effects in Experiment 2 by Subjects107
Table 5.7 Means RTs SDs and Priming Effects in Experiment 2 by Items108
Table 5.8 Mean ARs SDs and Priming Effects in Experiment 3111
Table 5.9 Mean RTs SDs and Priming Effects in Experiment 3 by Subjects112
Table 5.10 Means RTs SDs and Priming Effects in Experiment 3by Items112
List of Figures
Figure 2.1 The Representation of Compound Words in the Decomposition a, Fulllisting b, and Dual-route c Models26
Figure 2.2 The Processing of Morphologically Complex Words in the Early Decomposition a, Full-listing b, Parallel Dual-routeMRM c and AAM d Models28
Figure 3.1 The Representation of Transparent and Opaque Compound Words at Three Levels Adapted from Libben, 199845
Figure 3.2 The Bilingual Lexicon in Word Association Model a, Concept Mediation Model b, and Revised Hierarchical Model c Cheng et al., 201154
Figure 5.1 Sequence of a Trial in Experiment 2102
Figure 5.2 Sequence of a Trial in Experiment 3103
Figure 5.3 Accuracy Rates through the Course of Processing in Experiment 2105
Figure 5.4 Response Time in the Transparent Left and Opaque Right Conditions through the Course of Processing in Experiment 2109
內容試閱：
With deep appreciation and sincere gratitude, I would like to acknowledge many individuals who have given me guidance, support, and encouragement in the completion of this book which was based on my PhD dissertation.
My greatest gratitude should be first expressed to my PhD supervisor, Prof. Chen Yongjie, for his professional advice and constant support during the process of formulating a research plan, collecting literature, conducting experiments and composing and revising the dissertation. He is the driving force that prevents me from giving up and the bright beacon that helps put things in the right perspective.
I would also like to thank Prof. Wang Tongshun, Prof. Jin Yan, Prof. Zhu Zhengcai, and Prof. Wu Shiyu from Shanghai Jiao Tong University, and Prof. Gong Rong from East China University of Science and Technology, for their challenging questions and constructive suggestions at the early stage of my work. Many thanks are also due to Prof. Liu Longgen, Prof. Wang Zhenhua, Prof. Lei Xiuyun, Prof. Chang Hui and Associate Prof. Zhen Fengchao from Shanghai Jiao Tong University, who either gave me informative teaching in my first year as a doctoral candidate or provided solid advice and selfless help in writing this dissertation.
Special thanks also go to professors from the Linguistics Department of the University of Kansas in the United States, especially Dr. Joan Sereno, Dr. Allard Jongman, Dr. Annie Tremblay, Dr. Robert Fiorentino and Dr. Utako Minai, whose classes taught me indispensable knowledge and skills for this work. I am especially grateful to Dr. Joan Sereno, who always shared her time and advice when I was studying as a visiting scholar in her department. Roberts neurolinguistics lecture and Utakos research method class have left a deep impression on me. I was lucky to have that opportunity, for the graduate program in the Linguistics Department of KU has had the tradition of studying compound word processing. It was in there that I obtained valuable research materials which were not yet available at home. I also benefited greatly from the nourishing environment provided by such wonderful researchers.
When I was preparing for the experiments, it took me much time and energy to settle on the target English and Chinese compound words and to design the experiment procedure. Along the way many teachers and students from East China University of Science and Technology have helped me with the questionnaires and the pilot tests. Their time and attention spent on the tasks were great contributions to my data collection. They are Shi Xiaohui, Feng Zongying, Zheng Guofeng, Yang Dairuo, Zhu Xiaoqin, Dong Huimin, Zhang Jie, to name just a few. I am deeply thankful to them.
In addition, I wish to acknowledge the participation and collaboration of my dear students in the three online experiments. I am particularly indebted to Fang Xiaoliang, a former student of mine, for kindly assisting me with the administration of the lexical decision experiment. His help made the process much smoother.
Finally, my heartfelt appreciation is dedicated to my beloved family, to Dad, who has forgotten a lot of things, but never forgets to ask how I am doing with my dissertation writing, to Mom, who gives me and my son unconditional love and care, to my husband, who helps with household chores and tolerates my bad temper, and to my son, who provided timely distractions whenever I was struggling in the process.
Thank you all.
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