As previously stated, the texts were analyzed for the number of words and the five discourse components of the students’ texts: narrativity, syntactic simplicity, word concreteness, referential cohesion, and deep cohesion in response to the research questions. The statistical data on the number of words and the other five discourse components are presented in following sections.
Number of words
The number of words contained in the 80 texts is shown in Table 2. The reported descriptive data and the discussions are also presented in the following section.
Table 2. The descriptive statistics of the number of words in texts
|
|
|
|
n
|
Minimum
words
|
Maximum
words
|
M
|
SD
|
|
Word count on task 1
|
40
|
271.00
|
895.00
|
511.86
|
173.00
|
|
Word count on task 2
|
40
|
296.00
|
1121.00
|
575.97
|
200.63
|
The average number of words on the writing task 1 was 511 in length, while it was 575 words on the writing task 2. By comparing the number of words from both writing tasks, it was found that 29 participants (69%) wrote longer texts on the second writing assignment, making significantly higher number of words in length, t(41) = -8.57, p<.05.
Regarding the number of words in texts, findings from several studies suggest that successful writers tend to produce linguistically longer texts (McNamara et al.,2013; Crossley, et al., 2014); however, these results of the analyses cannot solely define a successful writer without investigating further for other linguistic properties or text components that could also influence students’ writing performances. Then, further investigations into discourse components and linguistic features were conducted and reported in the following sections.
Discourse components across writing assignments
Research question 1: Based on the results of the text analyses, what are the characteristics of the students’ writing performances?
A z-score is a standardized metric in standard deviation units, with the value of zero being the mean. The z-scores are higher and positive when the texts are easier on the component and more negative when the texts are more difficult. The following sections present statistical data of each discourse component as well as illustrating the results of the analyses in the forms of extracts or passages to characterize participants’ writing performances.
Narrativity
Table 3 shows the results of the narrativity analysis between the participants’ texts generated for the writing tasks. Of the 80 texts, the z-scores ranged from -0.4 to -0.5, making the texts were complicated and rather difficult to read especially on those assigned for the writing task 2. The results also reflect the degree to which a story is being told by using characters, places, events, or other things familiar to readers.
Table 3 The results of the narrativity analysis
|
Z-score range
|
NT1
(n = 40)
|
NT2
(n = 40)
|
|
-1.0 to < -0.5
|
3
|
1
|
|
-0.5 to < 0.0
|
12
|
16
|
|
0.0 to < 0.5
|
18
|
13
|
|
0.5 to < 1.0
|
6
|
7
|
|
1.0 to < 1.5
|
-
|
2
|
|
1.5 to < 2.0
|
1
|
1
|
Note: NT1 = narrativity on writing task one; NT2 = narrativity on writing task two
A passage sample (1) from the first writing assignment illustrates that the writer employed high frequent words and simple syntax in his/her writing. The following passage demonstrates these characteristics.
(1) Internet is one of the important things to me. I spend my time with it about ten hours per day. I like to watch the movies or drama series, listen to music, and read some articles in Facebook. Furthermore, I often use it to communicate with my friends. Nevertheless, I cannot connect the internet when I come back home.
This passage (1) has a fairly strong beginning as it states how the Internet is important in the writer’s life by giving examples in the second and the third sentences. Notice that the writer repeated the pronoun “I ” several times in almost all the sentences demonstrating that the writer strongly emphasizes personal experiences relevant to the topic. Likewise, Li (2014) states that the use of first person pronoun like ‘I’ is identified as a writer’s visibility and its over use is regarded as inappropriate and rather informal in academic writing.
The following passage from the writing task 2 exemplifies the different characteristics of the texts through the uses of verbs and intentional actions that the writer used to convey the messages to his/her readers. For example:
(2) I use YouTube to listen to music, watch movies, and something which makes me fun. Accordingly, access to the Internet makes me feel so relaxed after having studied so hard.
The passage (2) illustrates the uses of verbs and intentional actions in writer’s anticipated experiences of a week without an access to the Internet. The writer used the verbs, such as use, listen, and watch to visualize the actions that he/she routinely does in everyday life.
Syntactic simplicity
Table 4 shows the results of syntactically simple texts between the writing task 1and 2. In reference to the results, the passage samples are presented to demonstrate the characteristics of the texts.
Table 4 The results of syntactically simple analysis
|
Z-score range
|
SS1
(n = 40)
|
SS2
(n = 40)
|
|
-1.5 to < -1.0
|
2
|
1
|
|
-1.0 to < -0.5
|
5
|
8
|
|
-0.5 to < 0.0
|
14
|
13
|
|
0.0 to < 0.5
|
15
|
10
|
|
0.5 to < 1.0
|
4
|
8
|
Note: SS1 = syntactic simplicity on writing task one; SS2 = syntactic simplicity on writing task two
Statistically, the texts on the writing task 1 (n = 21, 52.5%) and on the writing task 2 (n = 22, 55%) were less than the mean value, identifying that their levels of syntactic simplicity was not significantly different.
Nevertheless, the researcher investigated in depth found that some participants performed better writing on their second assignment. The following passage samples illustrated this finding. The passages were written by the same student showing the differences of the syntactic structures across his/her writing tasks. The first passage was assigned for the writing task 1 on the topic of “Is education useless in the 21st century?”
(3) First of all, learning from schools is really important for children. Schools help their parents for take care of them while they are working. Children can play and meet their friends. It makes them learning each other and learning to handle with people.
With regard to syntax, the writer of the passage (3) tends to write choppy sentences resulting his/her writing relatively unsophisticated and disconnected. The syntactically simple structures apparently demonstrate the participant’s writing ability. In particular, the writer infrequently used transitional words (e.g. moreover, furthermore, then) or coordinating conjunctions (e.g. and, but, so) resulting disconnected ideas in the passage and less expression of the new descriptions to the texts.
Compare the previous passage sample (3) with the following passage (4) from the same writer who wrote it on the topic of “A week without access to the Internet.”
(4) Firstly, Thai students lack of taking their responsibility. In the morning, some students are like to attend the class lately. Moreover, they do not realize it will be the reason to lead them to become lazy person. Furthermore, some of them are likely to procrastinate on their task or duty. They might look like lazy person. But learning online must take a lot of responsibility on them because no one can force or motivate you to do it like learning in class. Then this is the reason that Thai students are not ready for learning online.
The passage (4) shows the uses of because and that illustrating a more elaborated text with more complex syntactic structures. This writer also produced a longer text with less choppy sentences as well as using transitional words (e.g. moreover, furthermore, then) more often to describe the associations between the ideas in the passage.
Word concreteness
In general, Coh-Metrix analyzed texts that contain concrete and meaningful words that can easily evoke mental images. A high number of word concreteness corresponds to easier and more understandable texts. The results of the word concreteness analysis are shown in Table 5.
Table 5 The results of word concreteness analysis
|
Z-score range
|
WC1
(n = 40)
|
WC2
(n = 40)
|
|
-2.5 to < -2.0
|
-
|
2
|
|
-2.0 to < -1.5
|
2
|
6
|
|
-1.5 to < -1.0
|
6
|
19
|
|
-1.0 to < -0.5
|
17
|
7
|
|
-0.5 to < 0.0
|
13
|
6
|
|
0.0 to < 0.5
|
2
|
-
|
Note: WC1 = word concreteness on writing task one; WC2 = word concreteness on writing task two
The results of the analysis show that almost all texts across the two writing tasks were less than the mean value (0.0), meaning that the writers tend to use a larger number of abstract words in their writings that generated more complicated texts to read.
The following passages were written by the same writer to illustrate these characteristics:
(5) Basically, education makes life better. Educated people are different from uneducated one in many way, such as attitude, lifestyle, and social status. Even at the present time, there are many jobs that everybody can do without knowledge,but those jobs are not good enough to make a living and to be accepted by society.
By contributing importantly to greater uses of abstract ideas, the writer of the passage (5) on the second writing assignment seems to have in part the abilities to perceive abstract concepts with reference to particular instances (e.g., educated, attitude, lifestyle) and verbs (e.g. make a living, be accepted) to distinguish relationships among ideas and to express the writer’s experience into the text. This is associated with the writer’s background knowledge and experience he/she shared with readers that could draw on to express himself or herself.
(6) Another important reason that make Thai students are not ready to learn English online is they might not understand what they are learning because they do not have a right direction.
Action verbs (e.g. make, learn, understand) were found densely written in the passage (6) to describe the actions that the subject might do in each situation and expressed opinions with supported explanations of English learning experiences.
Referential cohesion
The results shown in Table 6 determine the degree to which words and ideas overlap across texts. Texts that contain a higher number of referential cohesion express distinct connections between ideas, so they are easier to read and comprehend.
Table 6 The results of referential cohesion analysis
|
Z-score range
|
RC1
(n = 40)
|
RC2
(n = 40)
|
|
-1.5 to < -1.0
|
3
|
-
|
|
-1.0 to < -0.5
|
10
|
3
|
|
-0.5 to < 0.0
|
11
|
15
|
|
0.0 to < 0.5
|
7
|
11
|
|
0.5 to < 1.0
|
7
|
3
|
|
1.0 to < 1.5
|
1
|
6
|
|
1.5 to < 2.0
|
-
|
1
|
|
2.0 to < 2.5
|
-
|
1
|
|
2.5 to < 3.0
|
-
|
-
|
|
3.0 to < 3.5
|
-
|
-
|
|
3.5 to < 4.0
|
1
|
-
|
Note: RC1 = referential cohesion on writing task one; RC2 = referential cohesion on writing task two
Sixty percent of the texts from the writing task 1 (n = 24) were less than the mean value, indicating that the texts were high in referential cohesion that showed explicit connections between ideas in the texts. In contrast, a further analysis points to 45% of the texts from the writing task 2 (n = 18) contained a lower number of referential cohesion, indicating that the texts were relatively difficult to read and comprehend. Instead of using a variety of pronoun references, repeated pronouns were frequently found in the texts. The passage below illustrates this characteristic:
(7) For a decade that the internet has become accessible in Thailand. It makes people’s life more convenient. For example, people do not have to go to the library when they need to find some information, or they can learn new lessons through online courses when they do not want to leave home.
The writer tends to reiterate what was mentioned in the previous sentences with the same words or pronouns. As shown in the passage, ‘they’ was repeated three times. The last one of them in the extract “…when they do not want to leave home” shows the redundancy in the passage that seems to be a flaw because the writer failed to provide the noun they referred to as it was expected to appear.
Consider again by comparing the previous passage sample (7) with the following extract (8) from the writing task 2 written by the same student.
(8) As a result, Thai students do not gain adequate learning. For example, English is not our mother tongue language; therefore, the students cannot question about unknown knowledge when they do not comprehend their lesson.
Notice that in this passage (8), it extends the semantic domain of the concept of Thai students to include different lexical items like the students and they respectively. It can be assumed that the students showed an ability to adapt their writing to the requirements of the task at hand, thereby displaying an awareness of linguistic repertoires beyond that of the writing task 1. This is to suggest that uses of referential cohesion will reflect the degree to which words and ideas go beyond a text. Texts contain higher referential cohesion tend to show associations between ideas in the texts leading to more feasible to read.
Deep cohesion
The analysis of deep cohesion shows the degree to which the texts contain causal or intentional connectives in the sentences that help readers form a more coherent and deeper understanding of the causal events, processes, or actions in the texts. The results of deep cohesion analysis are presented in Table 7.
Table 7 The results of deep cohesion analysis
|
Z-score range
|
DC1
(n = 40)
|
DC2
(n = 40)
|
|
0.0 to < 0.5
|
3
|
-
|
|
0.5 to < 1.0
|
6
|
2
|
|
1.0 to < 1.5
|
7
|
7
|
|
1.5 to < 2.0
|
11
|
11
|
|
2.0 to < 2.5
|
7
|
11
|
|
2.5 to < 3.0
|
2
|
4
|
|
3.0 to < 3.5
|
2
|
3
|
|
3.5 to < 4.0
|
2
|
2
|
Note: DC1 = deep cohesion on writing task one; DC2 = deep cohesion on writing task two
The results of the analysis show that a major range of the z-scores from the writing task 1 and 2 was 1.0-2.5, which is 62.5% (n = 25) and 72.5% (n = 29) respectively. The texts on the writing task 2 were at a higher and positive degree of z-scores than those of task 1, meaning that deep cohesion on the task 2 generates easier texts to comprehend. The following passage (9) on the second writing assignment illustrates the finding mentioned earlier.
(9) Firstly, education is essential as of the world today. In the present, the world is moving fast and keep on going. Technologies have developed and are more advanced as time passes. New inventions are being discovered rapidly. Therefore, it is important to keep the knowledge up to the standards of those new innovations.
The passage (9) shows that the writer attempted to use coordinating conjunction ‘and’ to connect the two different verbs in the present perfect and past participle forms as well as using conjunctive adverb ‘therefore’ to make a sequence of sentences. The uses of conjunction create cohesion in the passage as well as extending and enhancing the text.
Besides, a majority of the texts from the first writing assignment expressed a fewer number of coordinating conjunctions (e.g. and, but, so) and conjunctive adverbs (e.g. still, even though) to supply cohesive ties across sentence boundaries. In addition, the z-scores reflected a fewer number of cohesive ties found in the overall texts causing relatively low in the associations of the lexical and grammatical structures, and the less sentence sequences to be understood as connected discourse (Halliday & Hasan, 1976).
In conclusion, the analyses provide evidence for the fact that the writers demonstrated linguistic flexibility across the texts that they produced. The participants wrote longer texts on the writing task 2 compared with those shorter texts on the task 1. The writers tend to develop more ideas around the writing topics as well as employing more sophisticated words in their texts on their second writing assignment. A majority of the participants could perform their abilities to use English vocabulary, extend their concepts, and express their complexity of English language. However, the findings also suggested that the participants may need to use a variety of lexical items to elaborate their writings, explicitly express ideas, and give new information to their readers.
In response to the research question 2, the results of the further analysis on correlations between the discourse components are presented in the following sections.
Multiple-variable correlations
Research question 2: Is there any significant correlation between those discourse components of the texts across the writing tasks?
The data from the 80 texts were examined to indicate the correlations between the results of analyses on the five discourse components.
Table 8 Correlations between the components
|
Variable
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
|
1. Nar1
|
-
|
|
|
|
|
|
|
|
|
|
|
2. Nar2
|
.227
|
-
|
|
|
|
|
|
|
|
|
|
3. Syn1
|
-.262
|
-.111
|
-
|
|
|
|
|
|
|
|
|
4. Syn2
|
-.156
|
.029
|
.614**
|
-
|
|
|
|
|
|
|
|
5. WC1
|
-.132
|
.145
|
-.144
|
.066
|
-
|
|
|
|
|
|
|
6. WC2
|
-.004
|
-.469**
|
.033
|
.087
|
.127
|
-
|
|
|
|
|
|
7. RC1
|
.656**
|
.274
|
-.511**
|
-.167
|
.005
|
-.102
|
-
|
|
|
|
|
8. RC2
|
.176
|
.482**
|
-.411**
|
-.397**
|
.160
|
-.209
|
.444**
|
-
|
|
|
|
9. DC1
|
.099
|
-.020
|
.148
|
-.105
|
.114
|
-.023
|
-.159
|
-.006
|
-
|
|
|
10. DC2
|
-.006
|
.472**
|
.144
|
.091
|
.267
|
-.286
|
.032
|
.300
|
.076
|
-
|
Note. 1 = writing task 1; 2 = writing task 2; Nar = Narrativity; Syn = Syntactic Simplicity;
WC = Word Concreteness; RC = Referential Cohesion; DC = Deep Cohesion
** Correlation is significant at the .01 level (2-tailed)
* Correlation is significant at the .05 level (2-tailed).
As shown in Table 8, the referential cohesion was found associated with syntactic simplicity on the writing task 1 (r = -.51, p = .00), and on the writing task 2 (r = -.39, p = .00) respectively. One possible reason for the associations between the referential cohesion and complex syntactic sentences could be that more proficient writers tend to use deliberately syntactic structures by using cohesion to associate the lexicon with the grammar in texts, generating sentence sequences as connected discourse of the texts (Halliday & Hasan, 1976; Ferretti & Lewis, 2019).
Amongst the variables on the second writing task, the narrativity was found significantly related to word concreteness (r = -.46, p = .00), referential cohesion (r = .48, p = .00), and deep cohesion (r = .47, p = .00). In particular, the participants’ narrative flexibility was found associated with certain components that could influence the overall participants’ writing performances of the argumentative texts they produced. Likewise, Allen, Likens, and McNamara (2019) found that the narrative flexibility and referential cohesion were positively associated. Overall, linguistic flexibility and discourse components of texts were associated at a certain degree. The associations amongst the discourse components give another indication that the writers were able to tell their stories, expand, and connect their ideas through the concrete words and cohesion. More-skilled writers tend to have a greater number of working words to develop their writing, thereby expressing their ability to use sophisticated language and more diversity of words in their writings (Crossley, et al., 2016). The results of the analysis on syntactic simplicity from both writing tasks were found significantly related (r = .61, p = .00), indicating an interaction to a higher degree as syntactic sentences, and a shorter length of texts can predict the quality of the texts (Polio & Shea, 2014; Bulté, & Housen, 2014).
Overall, the abilities to use linguistic features and discourse components of texts are varied by writers, meaning that to a certain degree their individual differences, prior knowledge, or writing ability can influence on writing performance. Besides, the results of the analyses also emphasize the importance of investigating a multi-dimensional perspective revolving around the linguistic features from basic levels to complicated discourse components. In doing this, writing teachers or researchers will have a better understanding of how to improve students’ writing skill with more specific details in linguistic and syntactic dimensions.