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FINDINGS OF SMALL-GROUP-DISCUSSION TASK

Note Percentages were rounded to the nearest whole number

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The three groups were randomly observed during different weeks to examine their

face-to-face interaction functions. The total observation time was not equal for all three

groups, and similarities as well as differences were noted between them. For example,

all three groups manifested a number of responses related to asking for and giving

language-related information and suggestions that was higher than their number of

responses related to asking for and giving opinions (see Figure 5.4). However, the

frequency and type of these responses varied across groups. The students in OG1 spent

a great deal of time discussing language-related and topic-related information, whereas

the members of OG2 and OG3 were more focused on providing information and

suggestions.

These similarities and differences notwithstanding, the responses across the groups

indicate that all three groups of students relied on face-to-face interactions to solve

language-related problems. OG2 and OG3 further depended on a face-to-face mode to

solve problems related to task implementation. Notably, OG2 did not display any

responses intended to solve topic-related problems, and OG1 made no responses related

to solving personal problems. The absence of these two items indicates that it is not

inevitable for topic-related problems and personal problems to occur or to elicit a

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Figure 5.4: Frequency analysis of each interaction functions across groups

Online Participation and Interaction

Online discussion was another significant mode of learning observed during small

group discussions that required a group of students to collaborate in producing a group

argument to a given controversial question. The number of online posts and the number

of contributing members of all three groups were analysed to examine online

participation rates over an eight-week online discussion. An analysis of the data showed

that the three groups of students generated 91% (217 posts) of the total number of posts

while teachers contributed 9% (22 posts). Among the students’ posts, only 35% were

independent messages, suggesting a high response rate of 65%. Among the three groups,

OG1 contributed the highest number of posts while OG2 generated the lowest number.

OG1 produced 40% of the posts; OG2 was responsible for 21% of the total and OG3

contributed 39 % (Figure 5.5). The posting contributions among all three groups

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students mainly led their own dialogues by expressing thoughts, elaborating opinions

and giving comments.

Figure 5.5: Number of posts generated across groups

Note. Percentages were rounded to the nearest whole number

An analysis of the students’ weekly posts reveals that students in OG2 and OG3

generated more posts during the last four weeks of the observation period (Figure 5.6).

Although this phenomenon was not as clearly noticeable when viewing the weekly

contributions of the OG1 students, the number of posts during the last four weeks also

appeared to be consistently higher in that group when compared with those produced

during the first five weeks of the observation period. The number of contributors

remained inconsistent throughout; some weeks showed more contributors than others

during the eight-week discussion period. Notably, all students in OG2 contributed to the

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participation rate was relatively higher during the last four weeks than over the first five

weeks.

Figure 5.6: Number of weekly posts and contributors across groups

Group 1 Group 2 Group 3

The students’ online discussion postings, including independent messages and

interactive messages, were analysed to examine the interaction functions. Independent

messages refer to postings without responses, while interactive messages consist of

online utterances with responses from other discussants. Of 217 posts, 225 codes were

analysed based on a revised and expanded Zhu’s model (1998) (Section 4.5.2). This

analysis of the data identified discussion (55.1%), comment (27.1%) and synthesizing

(10.7%) as the three main interaction functions (Figure 5.7) present. Other interaction

functions such as question (5.8%), information-sharing (0.9%), and answer (0.4%) had

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Figure 5.7: Percentage of online interaction types identified

Both similarities and differences were found between groups with regard to students’

online interactions with their group members. Data analysis (see Figure 5.8) showed

that the three groups of students primarily expressed thoughts and opinions (discussion

function) and provided comments (comment function) when engaging in the online

discussions. However, the frequency of each type of function used varied relatively

within groups. OG3 members contributed most discussion statements, while OG1

students exceeded OG2 and OG3 members in comment statements. OG2 students

contributed the least number of both types of statements. The number of synthesizing

statements contributed was not high, but displayed similar frequency across groups.

Students rarely raised questions, shared information or provided answers to

information-seeking questions. The overall data suggests that all three groups shared

similar interactions among their members, but differed in the level of interaction among

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Figure 5.8: Frequency of online interaction across groups

The discussion interaction function is defined as consisting of online statements that

express individual thoughts and elaborate individual opinions related to the topics under

discussion. Online responses that included clarification, explanation and elaboration in

responding to others’ questions and statements were also classified into this interaction function. Within this function, expression of thoughts accounted for 61% of the

statements, whereas elaboration of opinions represented 39%, thus indicating that

students spent more time expressing their thoughts (online response 1) rather than

elaborating opinions (online response 2). An examination of students’ online discussion

logs reveals that most of the discussion statements were independent posts made in

response to discussion questions, not interactive messages posted in response to

prompting questions or others’ opinions; this finding points out that students appear

keen to express their thoughts or elaborate their individual ideas (as illustrated below)

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Online response 1

“I thought that the aboriginal arts culture is one of Taiwan’s characteristics.” (Discussion-Expression of thoughts – Tian - Week 5: Endangered Taiwanese traditional handicrafts)

Online response 2

“I think aboriginal arts have some hindrance. For example, [the] aboriginal are repeled [repelled] by social environment. They are very the minority. And their education is also question. [They are the minority and they have problems to get education.]” (Discussion-Elaboration of opinions –Jing - Week 5: Endangered Taiwanese traditional handicrafts)

Note: For the purpose of English practice, students’ online responses are required to

present in English. The square brackets are the corrections of students’ English errors.

The comment interaction function comprises online utterances that show agreement or

disagreement, or offer affirmative or negative comments. Expressing agreement and

offering affirmative comments represents support, while expressing disagreement or

negative comments indicates conflict. Non-substantive comments accounted for 48% of

the statements corresponding with this function while substantive comments represented

52% of the statements. Substantive comments refer to those comments provided that

include further personal opinions (online response 3), whereas non-substantive

comments present personal positions without further opinions (online response 4).

The percentages reflected the students’ preference for providing comments with

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response to discussion questions; they commented in part on other members’ opinions

and most often agreed with others, instead of disagreeing and challenging their views

(online response 5).

Online response 3

“I disagree to allow the collection agents to be legally formed to collect debts. This way may effect [affect] social order. It would make another problem of committing a crime.” (Substantive comment – Cai, OG1, Week 14: Agree or disagree to allow the collection agents to be legally formed?)

Online response 4

“I disagree.” (Non-substantive comment – Hua, OG3, Week 14: Agree or disagree to allow the collection agents to be legally formed?)

Online response 5

“I also agree [with] your opinion. Taiwan have [has] more experience than China and the government has worked to create a macro environment favourable to high-tech development.” (Substantive comment – Zhou, OG3, Week 6: To invest Taiwan’s hi-tech industry or not)

The synthesizing interaction function pertains to online statements that compile related

information or summarize discussion messages; this function appeared only in the last

group discussion posting in which all members’ opinions were compiled to form a group argument. A final argument that consisted only of one member’s post without

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statements were rarely found in individual student posts. Although the number of

synthesizing statements was relatively low compared to the number of discussion and

comment statements, their inclusion represents a significant interaction function that is

essential in achieving the task goal.

The question interaction function is represented by online inquiries that seek

information or attempt to start a dialogue; this function was performed mostly to elicit

more opinions for elaboration requests, clarification requests, or explanation requests.

Students seldom raised questions to seek information or to start a dialogue that enquired

about their group members’ opinions; only one such post appeared in the discussions of

OG2, and one in the discussions of OG3. OG1 members generated the most question

statements. One particular student in OG1, Niya, was the most prolific contributor of

this type of interaction, producing a total of 12 posts primarily to ask for elaborations

(online response 6), as illustrated in the example below:

Online response 6

“I support to live in [the] Mars because it have [has] a lot of water. What do you guys think?” (Question-Elaboration request – Niya, OG1, Week 4 Space colonies) “So what is our discussion major?” (Question-Information seeking – Niya, OG1, Week 5 Endangered Taiwanese traditional handicrafts)

“Could you tell me ‘destroy the ecology of a landscape and the local way of life’ in detail?” (Question-Explanation request – Niya, OG1, Week 16: Tourism today)