Thematic Progression Patterns and the Texts of the
Department Required English Test
Chun-Mei Shieh
*
, Kuan-Ru Sunny Lin**
Abstract
Reading ability serves as a crucial index to successful test-takers. Therefore, in Taiwan, in 2002, the Department Required English Test (DRET) began incorporating a new individual test component called the Discourse Structure Test (DST). The test-takers have to choose sentences or phrases from among several alternatives to restore a text. In order to solve the test problems, it is important that test takers have the concept of texture to look for clues and organize meanings beyond the sentence level at the stratification of text structure. However, research done on the application of textual metafunction in analyzing and interpreting DST is rare. Therefore, the aim of this study is to explore Theme-Rheme relationship and thematic progression in the texts. This research adopts a discourse analysis method and collects the years of 2002 to 2008 DSTs as corpus data. The quantitative analysis of the corpus data is conducted and the results are represented by descriptive statistics. The results of this study show that unmarked theme and constant thematic progression (TP) type distribute most. This study hopes to utilize the textual metafunction as a base to provide learners an entry to approach written discourse, as well as to understand the distribution of information, through the analysis of marked and unmarked theme, TP in texts.
Keywords: textual metafunction, discourse structure test, department required English test, Theme-Rheme structure, thematic progression, systemic functional linguistics
Introduction
Reading instruction is now part of the mainstream of teaching English as a foreign language (EFL) in senior high schools in Taiwan. EFL teachers and their students are making efforts to improve both reading skills and comprehension (Cheng, 2007). Apparently, in Taiwan, the significance of English reading ability is emphasized in all kinds of tests and examinations, such as the Scholastic Aptitude of English Test (SAET), the Department Required English Test (DRET) and General English Proficiency Test (GEPT). Especially DRET, which is a test that every senior high school graduate has to take, seems to determine more than one hundred thousand high school students’ futures (Fan, 2008; Cheng, 2007). Hence, it is necessary to discuss ways to promote English reading comprehension in DRET.
Moreover, in 2002, a new test mode called the Discourse Structure Test (DST) was adopted in the DRET. Chen (2003) emphasized that those senior high students who are not proficient in English reading tended to be overwhelmed by the DST because they are not equipped with effective strategies for taking this type of test. Thus, students have to struggle desperately for the meaning of the text before selecting an appropriate answer from the potential items.
Former reading tests focused mainly on cloze test, which tested knowledge on orthography and syntax at the sentence level. However, new test mode DST may challenge students’ reading ability and comprehension because the goal of the “Discourse Structure” test has shifted its focus to the inter-sentence level, that is, to test the understanding and command of text structure, which certainly involves the unity and overall coherence of text (Yeh, 2002) (as cited in Chen, 2003). Chen (2003) found that teaching cohesion is rewarding for improving high school students’ performance on DST. Furthermore, Carrell (1982) argues that cohesion theory operates on the superficial surface structure of a text in establishing the cohesive ties. As in Liu’s (2009) study, she found that cohesive devices are closely related to Theme structure. Hence, in this study, the researcher attempts to attest that the notion of Theme/Rheme and Thematic Progression are highly useful in the comprehension of texts.
patterns of Theme and Rheme. The ultimate aim of this study is to help students effectively monitor their reading process through the aid of the function of textual metafunction in Systemic Functional Linguistics. SFL can provide power analytical tools in evaluating texts as later will be demonstrated in this study. However, little research in Taiwan utilizes SFL as a tool to facilitate teaching reading. Michio (2009) stated that, if incorporating some of SFL’s insights, especially the Theme choices and progression into the discussion of texts in the classroom could be quite beneficial. To put it further, the focus of teaching English reading from the perspective of prescriptive instruction on orthography and syntax at the sentence level is not enough. Learners should be also taught to trace Themes of clauses and discover the focuses and structure of the text.
Purpose of the Study
Research in the field of reading comprehension identifies two distinct types of prior knowledge of schema with respect to reading: knowledge of textual content and knowledge of textual structure (Song, 2006; Tai, 1997). The understanding of textual structure can be achieved by exploring textual metafunction. This study endeavors to explore the frequency of TP models mainly proposed by Danes in DSTs. By focusing on the DST part of the DRET, the researcher hopes to come up with some suggestions for diagnosing students’ reading difficulties.
Theoretic Framework of Thematic Progression
Theme-Rheme structure use, however, relatively little attention has been paid to explore Theme-Rheme structure used by senior high school students. For this reason, there is a need to explore Theme-Rheme structure use for this educational level, as it has a great potential to improve reading ability progressively.
Theme makes a significant contribution to the cohesion and coherence of a text by determining or influencing the way thematic elements succeed each other (Eggins, 2004; Lock, 1996). Many experts put much effort on the issue of thematic progression. In the former studies, many TP patterns and their features have been proposed by researchers (e.g., Qin, 2009; Tan & Sun, 2010; Wang, 2009). Liu (1999) also points out the diversity of choices for Theme structures. Therefore, seven main patterns of thematic development can be put forth:
1. First, Eggins (2004) postulates Theme reiteration, which some linguists label the “Continuous or Constant Theme” (Bloor & Bloor, 1995; Chao, K. H., 2002; Danes, 1974). This kind of thematic pattern often appears in short biographical passages and narratives. It is also frequently found in textbooks and descriptions of factual information.
Text 1 (below), in which the Theme of each clause refers wholly to it or Fiction as the main topic of the text, provides a further illustration of the use of Theme reiteration (Liu, 1999).
Text 1
Fiction is the name we use for stories that are make-believe, such as the Harry
Potter books or Alice’s Adventures in the Wonderland. But fiction isn’t always
different from the way things usually are. It can also be so close to the truth that it seems as real as something that may have happened to you this morning; or, fiction can be as fantastic as the most unbelievable of fairy tales. (adapted from JCEE center, DST of 2002 AST)
clause 1 Theme Rheme
clause 2 Theme Rheme
clause 3 Theme Rheme
Figure 1. The zig-zag pattern of Thematic development. (adapted from Eggins,
2004, 324)
3. A third common type of thematic progression is the multiple-Rheme pattern. Bloor, T. & Bloor, M. (1995) proposes a Split-Rheme Pattern, which is essentially the same thing as a multiple-Rheme pattern. This multiple-Rheme pattern is common in longer expository texts. It occurs when the Rheme of a clause has two or three components, each of which is taken in turn as the Theme of a subsequent clause (see Figure 2).
Figure 2. The multiple-Rheme pattern of Thematic development (adapted from Eggins,
2004, p.325)
Example [1]:
New Jersey is flat along the coast and southern portion; the north-western region is mountainous. The coastal climate is mild, but there is considerable cold in the mountain areas during the winter months. Summers are fairly hot. The leading industrial production includes chemicals, processes food, coal, petroleum, metals and electrical equipment. The most important cities are Newark, Jersey City, Paterson, Trenton, Camden. Vacation districts include Asbury Park, Lakewood, Cape May, and others (Danes, 1974, p. 120) (as cited in Lan, 2008).
In this example, we can see that each individual clause Theme is different; Theme 1
The coastal climate, Theme 2 The leading industrial production and Theme 3 The most important cities are individually different themes but all related under the hypertheme
of New Jersey.
5. Concentrative progression T1──R1
Figure 3. The concentrative pattern of Thematic development (adapted from Wang,
2007, p.127)
The following are examples of TP with concentrative pattern:
Example [2]
A: English (T1) is a country (R1). France (T2) is country (R2). Turkey (T3) is another country (R3). Egypt, Italy and Poland (T4) are other countries (R4). B: In Kenya’s Tsavo Game Park, five thousand elephants (T1) were slaughtered
(R1). In Zambia the game department (T2) killed (R2) 1,500 elephants in the Luangwa Valley. In Lusaka and Ndola, elephants (T3) were also thinned out (R3) and their meat sold in the butcher’s shops (Qin, 2009).
In this kind of pattern, each Theme carries different new information; Rheme carries the same given information, featuring similar characteristics of various information. Moreover, functional purpose is more emphasized.
│
T2─R2 (=R1) │
6. Crossing pattern T1──R1
Figure 4. The crossing pattern of Thematic development (adapted from Wang, 2007, 127)
The following is an example of TP with crossing pattern:
Example [3]
The play (T1) was interesting (R2), but I (T1) didn’t enjoy it (R2). A young man and young woman (T3) troubled me (R3). I (T4) turned round looked at them (R4), but they (T5) didn’t play any attention to me (R5). (Wang, 2007, p.127)
This kind of progression model is displayed as a circuitous textual pattern between discourse organizations. Themes and Rhemes intersect proceeding between sentences. In terms of semantics, the head and the tail correspond; it is obvious that the text coheres.
7. Juxtaposition pattern
<T1 R1> <T2 R2> <T3( =T1) R3> <T4( =T2) R4>
<T2N+1( =T1) R2N+1> <T2N( =T2) R2N>
The following is an example of TP with juxtaposition pattern:
Example [4]
Americans eat with knives and forks; Japanese eat with chopsticks. Americans say “Hi” when they meet; Japanese bow. Many American men open door for women; Japanese men do not. (Huang, 1988, p.84)
Juxtaposition usually used as a tool to contrast different topics in discourse. Two kinds of themes (T1, T3, T5 and T2, T4, T6) alternately appear with each other;
therefore, the Rheme follows to change (Li & Fan, 2008; Tan & Sun, 2010; Zhang & Li, 2009).
Those above are only common structures of Thematic Progression while usually most thematic progressions on text level are complex, which are often combined with various kinds of thematic progression.
TP, actually, implies the semantic relationship between sentences which form the discourse. Hence, TP analysis can be used on the level of text. Sentences of text can be divided into Themes and Rhemes based on their appearing sequences. Through this readers can get what the text suggests more easily. We can keep an eye on what an author of text wants to convey, how he recognizes text, how he explains his topic idea and how he answers what he claims. Accordingly, we can easily grasp the whole text, including topic idea, structure and implied points.
Text Types in Relation to TP
technological text, linear TP is the mostly appeared model. Second, in travel manual genres, constant TP occupies primarily. For narrative text, Zhang and Wang (2001) claimed that only constant TP pattern was performed in the analysis.
A number of studies have shown that patterns of TP are not arbitrary but dependent on the content of texts. Therefore, the present study attempts to explore the TP models of SFL for textual analysis. As mentioned above, the researcher adopts seven types that may appear in the articles to see if it is beneficial carried out in the DSTs for readers to pay attention to.
Method
The present study conducted belongs to the method of discourse analysis. Discourse analysis provides a device to more systematically engage in the descriptive analysis and comparison of written texts. Goldman and Wiley (n.d.) argue that discourse analysis of written text is a method for describing the ideas and the relations among the ideas that are present in a text. The method takes advantage of work in a variety of disciplines, including rhetoric, text linguistics, and psychology. These disciplines provide ways to describe and analyze how the structure and content of the text encode ideas and the relations among ideas (Goldman & Wiley, n.d.). In depicting these relations it is important to initially define the genre to which the text belongs because structures vary across genres. For instance, narrative stories differ from persuasive essays; news articles have a different style than editorials; and fiction texts have different structures than nonfiction ones. Differences in structure infer different relations among the ideas in the texts.
Data Collection
understanding of text structure, which involves the unity and coherence of text. Therefore, in a description of the criteria for designing the DST, it stated that enough clues should be provided for each blank (Chen, 2003). Chen (2003) also proposed that DST involves reading a passage which has five gaps; the deleted sentences then serve as alternative items; that is, the test taker reads a passage containing five gapped sentences. Thus, the DST obviously poses a greater difficulty for the test taker than does a traditional cloze test, which has a single word or phrase missing from each sentence. To conclude, the DST demands that the test taker have a greater facility with English, particularly reading comprehension, effective reading strategies, and most of all, an awareness of English textual structure.
A Brief Introduction to the Chosen Texts
The eight texts chosen for this study are from the sequence of DSTs that appeared in the year from 2002 to that of 2008 in DRET. The texts are accessible on the Joint College Entrance Exam website (http://www.ceec.edu.tw/). All eight texts are brief, about 200 words, and feature a variety of topics. Each passage serves as the basis for a set of five questions, hence, a total of 40 DST items.
The first text is a discussion about the format of fiction and non-fiction; it is a common type of expository text (Hu, et. al., 2005). The second text, which is also from the 2002 DRET, talks about the invention of windshield wipers. The researcher classifies this second text as a form of narrative text, because it describes a series of events. The essay starts by mentioning the inventor of windshield wipers and then continues with a discussion about how the manufacturer presented the creative idea of wipers to the public. The topic of the third text is animals and it falls under the classification of description. Then, the remaining five texts belong to the classification of exposition.
Table 1 Topics of Discourse Structure Test of DRET
No. of test items Topic Category Text Type
No.41-45 Fiction Literature Exposition
2002
No.46-50 Biography Invention Narration
2003 No.41-45 Raising Pets Animals Description
2004 No.41-45 Chinese brush painting Arts Exposition
2005 No.41-45 Intelligence Science Exposition
2006 No.41-45 E-mail Daily Life Exposition
2007 No.41-45 Aging population Social studies Exposition
2008 No.41-45 Paris cafés Humanities Exposition
Data Analysis
Three criteria utilized to analyze the data are unmarked and marked theme, TP types, and cohesive ties. To begin with, it will be useful to make a distinction between Theme and Rheme drawing on the categorization of Eggins’ (2004). Theme serves as the essential basis of analysis whereby the researcher determines the TP pattern. Then, the researcher reported the proportion of the frequency of each pattern according to the order of subsequent types.
The seven TP types which perform a textual analysis of the eight pieces of DSTs are as follows:
A) simple linear progression B) constant progression C) split progression
D) derived hyperthematic progression E) concentrative progression
F) crossing pattern G) juxtaposition pattern
Results
frequency of TP categories in the DSTs carried out. From the results obtained, it can be concluded that most TP patterns focused on constant TP, linear TP and concentrative TP. For example,
Mary, sitting on her seat, quickly drew her device in her sketchbook. Her solution was simple. Mary’s device allowed the motorman to use a level inside the streetcar to activate a swinging arm on the windshield to wipe off the snow and ice. (DST of 2002 DRET)
The above paragraph is a typical example of constant TP.
In this example, although the Theme for each clause is different but Theme 1, Theme 2 and Theme 3 all refer to the same topic Mary.
The following example demonstrates the model of linear TP, in which the given information in each sentence topic refers anaphorically to the new information in the last occurring comment.
Japan is dealing with a problem that’s just starting to sweep the world-an aging population combined with a shrinking work force. Therefore, aged Japanese are now being encouraged to work longer in life. By so doing, it is hoped that Japan’s government will save its increasingly burdened pension… (DST of 2007 DRET) Below is a DST with the concentrative TP pattern.
I drove around for 10 minutes and left Derek in a park. But when I pulled into the driveway, there was the puppy. The next day, with the help of a map, I left the doggie 30 minutes away, but Derek beat me home again. (DST of 2003 DRET) Here each clause has got different Theme but same Rheme.
Table 2
Frequency of TP Categories in the DSTs of DRET
TP
Constant TP Linear TP Year of DST Total number of TPs
number percentage number percentage
2002-2 DST (Text 2) 15 4 26.7% 4 26.7% 2003 DST (Text 3) 23 1 4.3% 7 30.4% 2004 DST (Text 4) 17 7 41.2% 0 0 2005 DST (Text 5) 18 6 33.3% 4 22.2% 2006 DST (Text 6) 19 4 21.1% 4 21.1% 2007 DST (Text 7) 16 9 56.3% 3 18.8% 2008 DST (Text 8) 18 4 22.2% 7 38.9% Mean 18.63 5.38 28.9% 3.88 20.8% Table 3
Frequency of TP Categories in the DSTs of DRET
TP
Split-Rheme TP Derived Hyper TP Concentrative TP Year of DST
number percentage number percentage number percentage
2002-1 DST (Text 1) 0 0 0 0 2 8.7% 2002-2 DST (Text 2) 0 0 0 0 3 20% 2003 DST (Text 3) 0 0 0 0 9 39.1% 2004 DST (Text 4) 0 0 0 0 2 11.8% 2005 DST (Text 5) 2 11.1% 0 0 3 16.7% 2006 DST (Text 6) 2 10.5% 0 0 4 21.1% 2007 DST (Text 7) 2 12.5% 0 0 0 0 2008 DST (Text 8) 0 0 0 0 0 0 Mean 0.75 4% 0 0 2.875 15.4% Table 4
Frequency of TP Categories in the DSTs of DRET
TP
Crossing TP Juxtaposition TP Year of DST
number percentage Number percentage
2002-1 DST (Text 1) 1 4.3% 0 0
2003 DST (Text 3) 1 4.3% 0 0 2004 DST (Text 4) 1 5.9% 0 0 2005 DST (Text 5) 0 0 0 0 2006 DST (Text 6) 0 0 0 0 2007 DST (Text 7) 1 6.3% 0 0 2008 DST (Text 8) 1 5.6% 0 0 Mean 0.75 4% 0 0
In addition, the results also showed that there was no derived Hyper TP at all. Split- Rheme TP and crossing TP both accounted for 4% of the DSTs. Juxtaposition TP was also being found no pattern in the texts.
Discussion
The results listed above showed that constant TP, linear TP and concentrative TP reached 65.1 % among the eight DSTs which accounted for the two-thirds of the all corpus. With regard to constant TP, it was repeatedly used in Text 1 which was somewhat lacking of cohesive strategy. As Li and Fan (2008) illustrated that constant TP was the most typical TP in texts. Concerning linear TP, it was found 30.4 % in Text 3 and 38.9 % in Text 8 respectively. The reason why the percentage in these two texts surpassed other texts might be that linear TP ensured the fluency for describing things (Li & Fan, 2008).
are richly used in Text 3.
Conclusion
The purpose of the study was to investigate the TP patterns manifested in DSTs. The TP categories in the DSTs of DRET, constant TP and linear TP predominated the frequency of occurrence followed by concentrative TP. Split-Rheme TP and crossing TP both appeared the same frequency in eight DSTs. There was no hyper derived TP and juxtaposition TP in DSTs.
Theme and Rheme construct can be a valuable instrument for teachers because it allows students to focus on the level of text, and to thereby explain to students where they are losing effectiveness while reading due to problems with either TP or Thematic selection, or both. Belmonte and McCabe-Hidalgo (1998) pointed out that the notions of TP and Thematic selection can also provide material for classroom activities. Students will then be able to draw on when reading their articles. Activities like having students expand on texts by adding simple linear development to texts consisting of only constant topic progression, or providing texts in which the Rheme of some of the clauses have been gapped out (Belmonte & McCabe-Hidalgo, 1988).
insights for teaching reading and writing as well as a beneficial plan for students learning language.
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