Yeh, H.-C., Yang, Y.-F., & Wong, W.-K. (2010). Interaction Chain Patterns of Online Text Construction with Lexical Cohesion.
Educational Technology & Society, 13 (1), 55–68.
Interaction Chain Patterns of Online Text Construction with Lexical Cohesion
Hui-Chin Yeh1, Yu-Fen Yang1 and Wing-Kwong Wong2
1
Graduate school of applied foreign languages and 2Department of Electronic Engineering, National Yunlin
University of Science & Technology, Douliu, Yunlin, Taiwan, R. O. C. // [email protected] //
[email protected] // [email protected]
ABSTRACT
This study aims at arousing college students’ metacognition in detecting lexical cohesion during online text
construction as WordNet served as a lexical resource. A total of 83 students were requested to construct texts
through sequences of actions identified as interaction chains in this study. Interaction chains are grouped and
categorized as a meaningful entity in order to investigate the students’ thinking process and behavior in general
and to understand the interaction between the computer and the students in particular. From the interaction
chains, it was found that some students revised incorrect sentences to correct ones. In making correct revision,
they needed to assess incoming information, interpret and organize textual information, engage in thinking what
they know, monitor their own meaning construction process, and take remedial actions to reach comprehension.
The rate of correct sentence selection increased from 34.04% to 55.02% in three sequential text construction
tasks. The recognition of lexical cohesion was found to be a determining factor for successful construction of a
text.
Keywords
Interaction patterns; Lexical cohesion, Reading comprehension, Metacognition, Text construction
Introduction
Lexical cohesion has been widely defined as a property of text to connect sentences. According to Halliday and
Hasan (1976), cohesive devices present a necessary semantic continuity between sentences for the purpose of
interpreting and comprehending a text. The interpretation of each sentence in a text may depend on both the selection
of vocabulary and its cohesive relations with other sentences. Halliday and Hasan further address that “typically, in
any text, every sentence except the first exhibits some forms of cohesion with a preceding sentence, usually with the
one immediately preceding” (p. 293). They also point out that “cohesive ties between sentences stand out more
clearly because they are the only source of texture…..it is the inter-sentence cohesion that is significant, because that
represents the variable aspect of cohesion, distinguishing one text from another” (p. 9). As such, lexical cohesion is
derived from the selection of vocabulary items. Lexical cohesive ties, namely, pairs of cohesive words, provide a
context for identifying the connections between the concepts embedded in a text. Hasan (1984) and Hoey (1991)
suggested that 40 to 50 percent of cohesive ties in a text are composed of lexical cohesion. It is worth further
investigation to what extent lexical cohesion can help students construct meaning in a text.
Many studies have affirmed the significance of the role that lexical cohesive ties play in the comprehension of a text
(Bridge & Winograd, 1982; Chapman, 1982; Rogers, 1974; Staddord, 1991; Nunan, 1993, Nunan, 2004; McCarthy,
1991, Wang, 1998). Nunan (1993) stresses the fact that the ability to detect the cohesive relationships across
sentence boundaries is significant for students to comprehend a text. When the sequence of sentences are scrambled
or altered, the meaning of the text is surely distorted or even radically changed. According to the results of
Bensoussan and Laufer’s study (1984), the major reading difficulty that English as a Second Language (ESL) or
English as a Foreign Language (EFL) college students encountered was their failure in recognizing the connections
among the sentences in a text. Along this line of research, Chu, Swaffar, and Charney (2002) pointed out that most
Taiwanese EFL students were found to be less aware of cohesive devices when reading English texts, as they occur
less often in Chinese. In other words, Taiwanese EFL students rarely use cohesive devices for integrating textual
information (Chen, 2003; Sharp, 2003). Their difficulty in identifying cohesive ties and finding out the relationships
among these devices in a text lowers their English proficiency.
Some researchers suggest that learners should take an active role and obtain a metacognitive ability to manage their
learning for better effectiveness (El-Hindi, 1997; Yang, 2002). Particularly, computer-assisted language learning
(CALL) environment has been reported to have had a positive impact on learners’ learning process, because the ease
of text manipulation facilitates the revelation of cognitive processes (Dewitt, 1996; Forbes, 1996; Hirvela, 2004,
2005). Some studies also indicate that CALL environment can help explore and facilitate students’ thinking and
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55
critical learning skills (Dreyer & Nel, 2003; Sinclair, Renshaw, & Taylor, 2004; Yeh & Lo, 2001; Yeh, 2003)
because the computer “is a good tool to expand human cognitive development and knowledge construction” (Yeh,
2003, p. 613). In the past, it was extremely challenging to study either a learner’s thinking process, except with a few
labor-intensive and time-consuming methods: naturalistic observations, interviews, or think-aloud protocols
(Schacter, Herl, Chung, Dennis, & O’Neil, 1999). When these methods were used, the learners’ thinking and
learning processes were often disrupted so that the data obtained might be distorted as well.
This study reports on our design of a text construction system, in which EFL college students actively construct and
reconstruct text meanings among sentences. The constructing and reconstructing process also rely much on the use of
metacognitive abilities perceived as formative assessment skills or the ability to “think about thinking” (Abromitis,
1994; Underwood, 1997; Kolić--Vehovec & Bajsanski, 2001). Metacognition involves active control over the
cognitive processes engaged in learning” (Livingston, 1997, p. 1), and "active monitoring and consequent regulation
and orchestration of cognitive process to achieve cognitive goals" (Flavell, 1976, p. 252). By exercising
metacogntive skills, learners are in control of their learning process in assessing the new information they read, and
retrieving the knowledge needed for understanding the written text (Abromitis, 1994).
For example, during reading, readers are monitoring their comprehension process that activates their prior
knowledge, their failures of comprehension, and the strategies that can help them understand the text (Kolić-Vehovec
& Bajsanski, 2001; Brown, 1985). They will in turn attempt to modify their reading process to match their purpose
of understanding the text. In other words, they have to activate their metacognition by firstly acquiring the concepts
from the text while adjusting the concepts in the light of subsequent information (Baker & Brown, 1984a, 1984b;
Yang, 2002).
Metacognition refers to the consciousness of people when they are aware of monitoring and regulating their
cognitive activities in the process of performing a cognitive task (Baker & Brown, 1984a, 1984b). They should be
“monitoring ongoing activities to determine whether comprehension is occurring” and “taking corrective action”
(Baker & Brown, 1984a, p. 354). When encountering problems, metacognitive learners can address the problems
consciously, and act remedially. As learners “recognize mistakes and inconsistencies in texts and understand that
they impair readers’ comprehension” (Ruffman, 1996, p. 33), and “take remedial action” (Yang, 2006, p. 67) to
resolve the inconsistencies, they are actually engaged in metacognition to improve their proficiency. The learner
should be continuously encouraged to detect inconsistency and to make revision in order to achieve full
comprehension.
Brown (1987) also specifically characterized four components in metacognition: planning, monitoring, evaluating,
and revising. Planning refers to the deliberate activities that organize the entire learning process, including setting the
goal, sequence, strategies, and expected time for learning. Monitoring involves the activities that moderate the
current progress of learning. Evaluating one’s own learning process involves an assessment of the current progress of
the activity. This evaluation can assist learners to develop the necessary skills and strategies. Revising one’s own
learning process refers to the modifications of previous strategies related to goals and other possible learning
approaches. These four components of metacognition all lead to the improvement of comprehension.
Based on our design of the computer-based text construction task, students’ intensive engagement of metacognition
can be expected. At first, students will use tutoring and trial practice to get familiar with both the lexical cohesion
and the computer-based learning environment. This is the process of planning in this system for students have to be
aware of the ultimate goal of the text construction task and of what they are expected to do next. On the way to insert
sentences to construct a text, they will be required to first identify the lexical cohesive items, select types of lexical
cohesion, and select inter-sentential relations since these are key elements to establish a paragraph. The selection of
lexical cohesion types and sentence relation is defined as the process of monitoring in this system for students do not
have to achieve the ultimate goal of inserting a correct sentence. Instead, students merely need to monitor if they are
on the right track to approach the ultimate goal. The process of evaluating occurs when students have to evaluate
four optional sentences and select a correct one to be related to the previous sentence in a text. This process differs
from that of monitoring since correct sentence insertion is students’ ultimate and only goal in text construction. After
the submission of a sentence, students are allowed to revise their sentences. This is the process of revising in this
system. These four components make it possible to investigate the students’ comprehension and learning process
while students are required to exercise their metacognitive ability to identify lexical cohesive ties and inter-sentential
relations and select the correct sentence to complete the text construction task. The system is designed to serve as a
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cognitive tool for a student to assess incoming information, interpret and organize textual information, engage in
thinking what he knows, monitor his own meaning construction process, and take remedial action to reach
comprehension. When constructing a text and identifying lexical cohesion in the computer system, the student
undergoes a dynamic and recursive process to reestablish the consistency of the text, while simultaneously searching
the lexical cohesion between sentences to achieve comprehension. The system aims to enhance his metacognition
and make his thinking process visible to both himself and the teacher.
The learning system used in this study is also a computer-supported interaction environment. With the Recording
module, the system would trace and document each action a student takes in order to understand his thinking
process. The student’s metacognition could then be further analyzed as he makes revision while comprehending the
text. The ability to determine “what has been done right or wrong,” and “to take remedial action when
comprehension failures occur” is a self-regulatory behavior (Yang, 2006, p. 67). Based on this definition, the
sequences of actions students take in this study are identified as interaction chains. The interaction chains are
grouped and categorized as a meaningful entity in order to investigate a student’s thinking process and behavior in
general and to understand the interaction between the computer and the student in particular. Several patterns are
used to explain both the students’ monitoring process and what facilitates or hinders their comprehension. The
interaction chain patterns can be used by a teacher to examine the students’ comprehension process. They also
provide the details of how the students utilized the system’s scaffolding to improve their metacognition.
Method
Participants
A total of 83 freshman students were recruited from two EFL classes in a technological university in central Taiwan.
These two classes were from two different departments, English and Engineering. The distribution of students is
shown in Table 1.
Department
Table 1. The distribution of students
Number of participants
Class A
English
41
Class B
Engineering
42
Gender
Male: 8
Female: 33
Male: 37
Female: 5
A total of 83 students participated in this study. Class A was comprised of eight males and thirty-three females and
Class B was comprised of thirty-seven males and five females.
Material
In order to provide appropriate English texts for the EFL college students to construct, the study adopted the
following criteria for the selection of the texts for the text construction task. First, the readability level of the English
texts should be controlled. The texts were all selected from College Reading Workshop (Malarcher, 2005). Second,
the texts should be similar in length. Three texts were chosen: The Best Travel Bargains (Text 1), with 168 words, 8
sentences and 6 lexical cohesive pairs; Traditional Markets VS. Modern Markets (Text 2), with 206 words, 11
sentences and 15 lexical cohesive pairs, and Fat to Store or Fat to Burn (Text 3), with 188 words, 10 sentences and
13 lexical cohesive pairs.
System architecture
The system built for this study includes three modules: user interface, recording module, and feedback module. The
relationships among these three modules are presented in Figure. 1. The teacher sets the objectives of the course,
selects the appropriate texts and enters the texts into a database through the teacher interface. The recording module
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documents students’ constructive behavior and process. The lexical cohesion and relations of sentences that are
identified will be recorded in a database. The feedback module looks up WordNet, matches the lexical cohesive
items, and provides candidate words back to students when they have a hard time identifying the lexical cohesion.
These modules will be discussed in detail.
Figure 1. System architecture
User Interface
The user interface includes a teacher interface and a student interface. The teacher interface allows the teacher to
manage a course, provide the texts to be constructed, and analyze the students’ constructive process and behavior.
The student interface is where a student undertakes text construction tasks.
Figure 2. Student interface
As shown in Figure 2, the student interface is divided into five areas. The main text area (Ⅰ) presents the text that is
being constructed. An “insert” button tagged with a serial number represents a missing sentence that a student should
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identify based on the first and the last sentences (in boldface) of a paragraph. A “Revise” button allows the student to
revise before final submission. Next, the area of multiple-choice items (Ⅱ) provides four sentences, tagged A, B, C,
and D for the student to select from. Three distracting sentences were randomly picked from the rest of the text
except the first and the last sentences. In the area of lexical cohesion (Ⅲ), students are asked to fill in two cohesive
items from the current sentence and its preceding sentence. They can get hints of cohesive words by clicking the
“Search” buttons or “Answer” buttons that are created based on the number of cohesive word-pairs embedded in the
two sentences.
In the area of cohesion types (Ⅳ), students have to fill in the relations between the two cohesive items from the text
fields A and B. The lexical cohesion types include: repetition, synonym, hypernym, hyponym, meronym. From the
menu of inter-sentential relations, students have to choose the relation between the two sentences. The relations
include: addition, clarification, comparison, contrast, example, location or spatial order, cause and effect, summary
and time (Sharp, 2003).
Recording Module
The system uses a recording module to trace students’ constructive process and behavior, which is presented as
interaction chains. The teachers can analyze the interaction chains and identify the difficulties students encounter and
the different performance among various proficiency groups. The analysis of interaction chains reveal whether the
students make good use of the scaffolding in identifying lexical cohesions during text construction. The records are
also helpful for the teacher to modify his instruction according to the demonstrated strengths and weaknesses of the
students. The module uses some predicates to record students’ behavior data (Table 2).
Table 2. The predicates for recording students’ data
Description
Search(W, S, t)
use WordNet search word W and type t at sentence S
Insert a sentence [n] (S)
insert a sentence s at sentence n
Identify cohesive words(w1, w2, t)
Identify cohesive words w1 and w2 and cohesive type t
Select relation(T)
Select inter-sentential relation T
Answer(S)
Provide a pair of lexical items as Answer for sentence S
Revise [n] (S, T)
Sentence n is revised from sentence S to sentence T
Predicates
An example of how the recording module traces students’ learning process of using WordNet to search for
hypernyms of cost, inserting sentence 1, identifying lexical cohesion and selecting sentence relation is shown in
Table 3.
Explanation
1.
1.Sentence:X
2.
2.Cohesion:0/2
3.
4.
5.
3. Relation:O
Table 3. Records of a student’s construction process
Sequence of interaction chain
Search (“cost”, “The best way to get a cheap airline ticket used to be by reserving a ticket
at least 21 days before you planned to travel.”, “Hypernym”)
Insert a sentence: [The best way to get a cheap airline ticket used to be by reserving a
ticket at least 21 days before you planned to travel.]
Identify cohesive words_1: [travel, travel, Repetition]
Identify cohesive words_2: [plan, plan, Repetition]
Select relation: [Addition]
Feedback Module
Among the above lexical cohesion, repetition, synonym, hypernym, hyponym, and meronym are found most
commonly in WordNet. WordNet 2.1 (Miller et al., 2005) is used in the current system to find these five types of
lexical cohesion. It also assists the student to identify the relationships between given lexical cohesive items.
WordNet is an online lexical database with a hierarchical structure, where a node is a synset (a set of synonyms) and
59
is linked to other nodes with some relationship. WordNet is thus adopted in the current computer system as the
knowledge source for the lexical semantic relationship utilized in matching cohesive words. In the past, WordNet has
been utilized as a corpus to analyze discourse automatically. It has been rarely used in a learning systems to assist
learners to comprehend a text.
In this study, a “SEARCH” button was designed to scaffold the student’s text construction. The candidate lexical
cohesive words generated from WordNet are shown in red color in both the main text and the multiple-choice items.
For example, when the student enters the word “Brazil” in text field A and chooses hypernym as the type of lexical
cohesion, the cohesive words “Brazil” and “country” found in WordNet will be highlighted in the text (Figures 3 and
4).
Figure 3. An example of using SEARCH button
Figure 4. Search results of “Brazil” (hypernym)
The student can click the “ANSWER” button to get a pair of lexical cohesive items, Brazil and country, when he
encounters difficulty in figuring out the cohesive items (Figure 5), but he still needs to decide which type of lexical
cohesion these two words form.
Figure 5. Example of using ANSWER button
After the student finishes constructing the text, the system will match the student’s inserted sentences, cohesion, and
sentential relation with the correct answers. The system takes a few steps to match the correct answers. First, when
60
the student inserts sentence S, the system would match the answer to the target text. Next, after the student identifies
lexical cohesive items (word 1 and word 2), the system would match the items against the lexical cohesion list.
Finally, after the student selects the sentence relation R, the system would match the selected relation with the target
answers.
Procedures of Data Collection
Eight three students were asked to construct three texts online at three different periods of time with one-month
intervals. Before the instructor introduces the strategy, identifying lexical cohesion and sentence relation in text
comprehension, the students undertook the text construction task for the first time. They were asked to complete the
second text after strategy instruction for a month and to finish the final text after instruction for two months. The
system recorded and traced the students’ construction process. The text construction tasks were to identify the target
sentence from the multiple choices, pairs of lexical devices and their cohesion type, and finally the sentential
relation. The online computer system graded the students’ text-construction by giving one score point to each correct
answer of (1) sentences of the constructed text, (2) pair of cohesive words, (3) type of lexical cohesive ties, and (4)
sentence relation.
Procedures of Data Analysis
The collected data were analyzed in terms of the students’ text construction product and process. Text construction
product refers to the students’ overall scores. Text construction process includes the students’ constructive process
and behavior traced by the system. Revision and no-revision behaviors were categorized into different interaction
chain patterns. The trace results revealed the students’ difficulty in the constructive process and how they improved
their understanding of the text.
Results
Product of Text Construction
The current study focused on understanding the students’ cognitive product and process in constructing online texts.
The data of 83 students’ performances on Text 1 (The Best Travel Bargains), Text 2 (Traditional Markets VS.
Modern Market), and Text 3 (Fat to Store or Fat to Burn) were analyzed. The overall reading performance is
presented in Table 4. The total score for sentence selection in Text 1 was 4 and that for lexical cohesive ties was 6.
The total score for sentence selection in text 2 was 7 and that for lexical cohesive ties was 17. The total score for
sentence selection in text 3 was 6 and that for lexical cohesive ties was 13.
Table 4. Results of the Correct Sentence Selection
Text 1
Text 2
Participant
Css*mean
SD
Css* mean
SD
3.80/7
1.36/4
2.11
1.37
All students
(54.28%)
(34.00%)
5.39/7
2.12/4
2.01
1.5
English major
(77.00%)
(53.00%)
2.77/7
0.77/4
2.21
1.24
Engineering major
(39.57%)
(19.25%)
*Css: Correct sentence selection
Text 3
Css* mean
3.30/6
(55.00%)
3.70/6
(61.67%)
2.61/6
(43.5%)
SD
1.69
1.45
1.93
As shown in Table 4, almost all the students made progress in three sequential text construction tasks as the
percentage of correct sentence selection increased from 34.04% to 55.02%. Specifically, the developmental progress
was evident for the engineering students. Their percentage of correct sentence selection increased from 19.25% to
43.5%.
61
Table 5. Results of the Correct Lexical Cohesive Ties
Text 1
Text 2
Participant
Clct** mean
SD
Clct** mean
SD
1.16/6
4.00/17
All students
1.19
2.30
(19.33%)
(23.53%)
1.64/6
5.52/17
English major
1.10
2.11
(27.33%)
(32.47%)
3.26/17
0.87/6
2.49
1.28
Engineering major
(19.18%)
(14.50%)
**Clct: Correct lexical cohesive ties
Text 3
Clct** mean
4.96/13
(38.15%)
5.55/13
(42.69%)
4.81/13
(37.00%)
SD
2.98
2.66
3.3
This was also true for their performance in lexical cohesive ties. The engineering students progressed from 14.5%
(Text1) to 37% (Text 3). The English-major students also made progress from 27.33% (Text1) to 42.69% (Text 3).
Process of Text Construction
According to the design of this system, the student must follow the steps to construct and reconstruct the text. One of
the major functions in the system is the “Revise” button, which encourages the students to activate their
metacognition. The steps of the students’ revision and no-revision processes are shown in Figure 6. If students
detected an inconsistency between the sentences, they would revise their thinking in order to reach new
understanding. Otherwise, they did not undertake revision. For the step of “search cohesive items,” students can
choose to use or not to use WordNet to search for cohesive items before completing the task.
Figure 6. Revision and no-revision processes
Table 6. Three revision patterns
Pattern
A
Incorrect→Correct
B
Incorrect→Incorrect
C
Correct→Incorrect
Description
An incorrect sentence was revised correctly with correct
identification of lexical items and their types of lexical cohesion.
An incorrect sentence was revised incorrectly with incorrect
identification of lexical items and their types of lexical cohesion.
A correct sentence was revised with incorrect identification of
lexical items and the types of lexical cohesion.
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Patterns of Revision in the Text-construction Task
The students clicked on the “Revise” button to revise a sentence. The way a sentence could be revised can be
grouped into three different interaction chain patterns (Table 6). In a sample text given below, the first and the last
sentences of the paragraph were provided initially while sentence 1 and sentence 2 were inserted by a student.
Sentence 1 was used to illustrate the three major revision patterns.
Sample text
One reason that finding good prices for travel is so complicated is because airlines have complex formulas for
inventory management so they can maximize profits by filling plans. 1 When there are lots of reservations (during
peak seasons), these companies can charge higher prices and still be sure that somebody will need their services no
matter how much it costs. 2 On the other hand, during the off-peak season, demand is low, so companies cut their
prices to try and attract people who would normally not travel at that time. One good place in which to find these
last-minute bargains is on the Internet.
In Patten A, the students revised an incorrect sentence to the correct one by detecting the lexical items and the types
of lexical cohesion. Figures 8 and 9 shows an example for Pattern A taken from the record of a student.
Figure 7. Interaction chain of Pattern A
Figure 8. A graphical illustration of Figure 7
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In Figure 7 the first three actions the student took for his text-construction activities were to insert sentence (action
13), identify lexical cohesion (actions 14, 15) and select sentence relation (action 16). These three actions constituted
a meaningful entity (circled in an oval shape with a dotted line in Figure 9). Before final submission, he reread the
sentence and searched for lexical items to confirm his ideas (action 18). Yet, he was aware of the inconsistency
between the sentences. In the construction process, the student asked for help in his text comprehension and
searching for the candidate lexical items. Thus, he revised both the sentence and the lexical cohesion correctly
(actions 19-21) after the search.
As shown in the graphical illustration of Figure 8, before the student took remedial actions 17 and 18 to obtain the
correct answers, he underwent a rereading process to reconsider his first answers. It is evident that the ability to
identify the key lexical cohesion contributed to the student’s comprehension of the text.
Figure 9. A graphical illustration of Pattern B
In Pattern B, the student revised the incorrect sentence to another incorrect one because he could not identify the
lexical items and the types of lexical cohesion correctly (Figure 9). The student did not use the “Search” function.
Though he detected the inconsistency between sentences, he did not get the correct sentence. He would have a better
chance getting the correct answer if he used the system to help detect the correct lexical cohesion.
With regard to Pattern C, the student replaced the correct sentence with an incorrect one because he could not
identify the lexical items and the types of lexical cohesion correctly no matter whether they revised or not (Figure
11). Though the student revised the sentence without asking for the assistance, the student did not fully understand
the text or the lexical cohesion.
D
E
Correct
Incorrect
Table 7. Two no-revision patterns
A student selects the correct sentence and fills in correct lexical cohesion
Student selects the incorrect sentence and fills in incorrect lexical cohesion
Among the students who did no revision, Pattern D characterizes those who selected the correct sentence and filled
in the correct cohesion while Pattern E characterizes those who selected the incorrect sentence and filled in the
lexical cohesion incorrectly (Table 7).
The student in Pattern D selected the sentence and lexical cohesion correctly. The student did not undergo the
complex reading process as those in the revision group. The student in Pattern E apparently did not detect the
inconsistency between sentences. He neither asked for feedback nor revised the sentence. Only when the student can
identify the inconsistency between sentences can they take remedial actions as reading strategies to fix the problem.
In summary, five different patterns emerged to classify how students behaved in their learning process and what
fostered or hindered their comprehension.
The relationship between metacognition and students’ learning outcomes
As Trainin and Swanson (2005) mentioned, the employment of metacognitive strategies is positively linked to
students’ learning outcomes in academic environments. In this study, all participants’ correctness rate in revision is
shown in Table 8. It could be seen that students learned to make more revisions from text 1 to text 3. As they made
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more revisions, their correctness rate in selecting correct sentences of text construction also increased from 34.04 %
to 55.02% (see Table 9). The result of the Pearson product-moment correlation coefficient between revision and
correct sentence selection is shown in Table 10. The correctness rate of revision has a positive correlation with that
of sentence selection. That is, the more the participants revised their sentences, the higher scores they obtained in text
construction.
Number of Students
Percentage of correct revisions
Table 8. Students’ correctness rate in revision
Text 1
Text 2
83
83
26 %
31.5 %
Table 9. Students’ correctness rate in inserting sentences
Text 1
Text 2
Participant
Css*
Css*
mean
mean
1.36/4
3.80/7 (54.28%)
All students
(34.00%)
2.12/4
English major
5.39/7
(77.00%)
(53.00%)
0.77/4
2.77/7
Engineering major
(19.25%)
(39.57%)
*Css: Correct sentence selection
Table 10. The correlation between revision and correct sentence selection
Text 1
Text 2
N
PC
PC
83
.70
.76
*N: the number of participants
*PC: Pearson’s correlation
Text 3
83
42.6%
Text 3
Css*
mean
3.30/6
(55.00%)
3.70/6
(61.67%)
2.61/6
(43.50%)
Text 3
PC
.81
All these consciousness-raising requests designed in the system aim to arouse students’ metacognition so that they
can improve their cognitive process. That is, in each text construction and reconstruction, the previous process served
as a cognitive stimulus for the next process. The positive result might derive from whether students can actively take
on revision and search for the clues, such as lexical cohesion, in WordNet to facilitate their comprehension. Without
metacognition, students might remain in the original status of cognitive process for an extensive time without further
improvement.
Conclusion
In this study, the text construction system served as a medium for the students to monitor and regulate their
comprehension and for the teacher to understand the students’ learning behavior and process. The system is designed
to encourage the learners to use their metacognition by identifying the lexical cohesive ties across sentences and the
types of lexical cohesion. Some conclusions can be drawn from both the students’ text construction product and
process. The students made progress in three sequential text construction tasks as the percentage of correct sentence
selection increased from 34.04% to 55.02%. The improvement for their performance in lexical cohesive ties is also
evident as the percent of correct lexical cohesive ties increased from 19.28% to 38.18%. In the process of text
construction, five different interaction patterns emerged to characterize not only how the system supports the
student’s learning but also what processes the learners undergo while completing the required tasks. For the revision
group, three different patterns described how students revised from incorrectness to correctness, from incorrectness
to incorrectness, and from correctness to incorrectness. For the no-revision group, two different patterns
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characterized: (1) how the student selected a correct sentence and filled in the correct lexical cohesion and (2) how
the student selected an incorrect sentence and filled in an incorrect lexical cohesion.
In the system, a Recording module traced and documented the student’s learning process and behavior in general and
their revision actions in particular. Interaction sequences presented in a chain manner illustrate the students’
metacognitive process. Different patterns generated from the data informed the teacher of how the students activated
their awareness to detect the inconsistency in sentences and how they took action to repair their understanding.
Through the construction tasks, the students had to carefully access incoming information by reading the preceding
sentence and the options from the multiple choices. The students also had to interpret and organize those incoming
information by reading between lines. When they were requested to identify the lexical cohesive items in text, they
were engaged in thinking what they knew and building the consistency between sentences. In this engagement, they
would try to monitor their constructive process and detect the inconsistency. From the findings, we can also learn
that the previous process of either taking on revision or asking for assistance from WordNet served as a cognitive
stimulus for the next process. There is a strong correlation between revision and correct sentence selection. In other
words, successful comprehension might result from whether students can actively take on revision and search for the
clues, such as lexical cohesion, in WordNet to facilitate their comprehension. Without metacognition, students might
remain lost in their cognitive process and would not be able to take any step to mend any comprehension breakdown.
Finally, if there were any comprehension failures, the students had the autonomy over taking remedial actions or not.
The students’ difficulties through the construction process in detecting lexical cohesion were examined and analyzed.
It was found that the recognition of lexical cohesion was a determining factor in successful construction of a text.
Whether or not the students could detect the lexical cohesion was a crucial factor in facilitating their learning process
and comprehension. It was also found that more proficient students tended to make good use of the feedback to
understand the connections in the text, and less proficient students seldom used the scaffolding provided by the
system. Future study would focus on the different interaction chains generated from students at different proficiency
levels in order to understand their text construction behavior and process, and explore the issues of how students at
different levels of proficiency benefit from the current system.
Based on the analysis and generalization from the trace results, the teacher could assist the students in overcoming
their difficulty not only in text construction per se but the lexical cohesion itself. Different interaction chain patterns
can possibly allow the teacher to analyze the students’ metacognitive process and understand what factors hinder
their successful text construction. The trace results provided by the system would serve as a guide for the teacher to
prepare for the instructional materials and effective teaching approaches. Their ability to identify correct lexical
cohesion as well as their metacognition were critical for successful text construction and comprehension. It is hoped
that this system can be used for a variety of course designs in additional to EFL courses because university courses
make extensive use of academic materials written in English (Carrell, 1998).
The teacher can select appropriate texts for the students to construct their meanings through the text construction
task. The students are encouraged to read across sentences instead of solely focusing on individual sentences in
detecting lexical cohesion. While completing the tasks, the students need to activate their metacognition and detect
the lexical cohesion across sentences. In future studies, we can generalize this approach to other types of cohesion
mechanisms, such as anaphora. When students encounter any difficulty or confusion, they are encouraged to ask for
feedback from the system to scaffold their comprehension. Then the scaffolding provided by the system can guide
the students to achieve full reading comprehension.
Acknowledgement
This study was supported by National Science Council in the Republic of China, Taiwan (NSC 97-2410-H-224-017MY2). The research grant made the continuation of this study possible.
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