A Qualitative Method to Analyze Collaborative Patterns of Virtual

Groups

Consuelo García

Universidad Internacional de la Rioja, (UNIR University), Avda. de la Paz, 137. 26002, Logroño (La Rioja), Spain

Keywords: Collaboration, Qualitative Method, Virtual Groups, Knowledge Construction.

Abstract: This study aims to describe a qualitative method to analyze different patterns of organization that students

show during their interaction in a virtual group. Literature review has shown that collaborative patterns have

a relationship with knowledge construction. This method involves the analysis of the messages exchanged

within the virtual group and the application of five indicators that help to identify these patterns: equality of

contributions, distribution of responsibilities, reciprocity, revision of the final report and degree of

consensus. Our results show that the procedure is useful for analyzing and identifying how virtual groups

are organized. Likewise, as previous studies, three main collaborative patterns were detected: aggregation,

integration and addition. Practical implications of these results point out the relevance of guiding the groups

not only throughout the task but also in relation to the organizational decisions.

1 INTRODUCTION

For several years, information and communication

technologies have caused a remarkable

transformation in traditional university institutions,

prompting many organizations to increasingly use

instructional designs based on the interconnection of

students, given the ease of collaboration from

different time zones and in distributed locations

(Putnam, 2001). As a consequence, the use of

collaborative learning activities in virtual learning

environments has grown, since group tasks provide a

natural space for processes of a certain cognitive

demand such as conflict resolution, argumentation or

inquiry in community.

When students have to work out a complex task,

such as solving a case or developing a group project,

they need to organize the task development as a

team. Students exchange messages concerning the

task (conceptual contents) and others related to the

procedures necessary to develop it (non-conceptual

participations). Students need to agree on processes,

times, milestones and dates, as well as how to do the

work, such as breaking it down into parts or working

it out together. Several studies have shown that an

important part of communication among group

members in a virtual group focuses on planning,

coordinating and supervising the joint work (Arvaja,

Salovaara, Häkkinen & Järvelä, 2007; Hara, Bonk &

Angeli, 2000; Van der Meijden &Veerman, 2005;

Veldhuis-Diermanse, 2002). Even more Liu and

Tsai (2006) showed on their study of small virtual

groups collaborating on a programming task, that the

greater frequency of interactions among members

corresponded to questions and suggestions on how

to coordinate the work effectively and not on the

content of the task itself. For this reason, several

researchers (Kanselaar, Erkens, Prangsma, &

Jaspers, 2002) consider that the analysis of students’

participation in a virtual group that develops a

common product should be carried out at two levels:

in relation to the content of the task and in relation to

the socio-organizational level or collaborative

pattern.

Besides, Thomas and McGregor (2005)

conducted a study among university students on a

project-based learning activity in a virtual learning

environment. They found that the groups of students

who participated in a rich dialogue, with a high

degree of exchange of ideas, soon began with the

task, were consistent with the frequency in which

they sent their messages and were good organizers

and coordinators of the task within the virtual

environment. On the other hand, the students who

were late collaborators and showed an erratic and

inconsistent behaviour in the publication of their

messages were as well not effective in organizing

García, C.

A Qualitative Method to Analyze Collaborative Patterns of Virtual Groups.

DOI: 10.5220/0006705402750279

In Proceedings of the 10th International Conference on Computer Supported Education (CSEDU 2018), pages 275-279

ISBN: 978-989-758-291-2

275

and carrying out their task.

Collaborative patterns of virtual groups are one

of the elements of their interaction and influence

their group outcomes. It is therefore important to

propose methods that allow practitioners to identify

how each group organizes and to provide guidelines

meanwhile. This study contributes to provide

educators with elements to identify the way in which

virtual groups organize and share knowledge.

Considering that previous research show that

knowledge construction requires active commitment

and high participation by its members, early

detection of the type of collaborative pattern that a

group uses can help educators reorient students in

their shared learning process.

2 PATTERNS OF GROUP

COLLABORATION

Previous researches have identified different patterns

of group collaboration. Basically the distinction is

made between a lower or higher degree of co-

participation shown by group members. In one end

there is the individualistic way, which implies that

students work on their own and after they share their

ideas in the group. And in the opposite end there is

the collaborative mode, which would reflect a joint

elaboration of the task.

A first proposal comes from the analysis carried

out by Paulus (2005). He made a distinction between

cooperative or collaborative organizational

structures in virtual groups. In cooperation, the task

is distributed and carried out independently and then

combined and added to the efforts in a final product,

while in collaboration, the members undertake a

mutual commitment to clarify concepts and build the

final product through a process of dialogue and

negotiation (Rose, 2002). Paulus (2005)

distinguished between conceptual and non-

conceptual functional moves (logistic, social and

technical) to establish differences between

cooperation and collaboration.

In other research carried out by Engel and

Onrubia (2010), they found three types of

organizational structures of virtual groups to develop

a collaborative report: (1) “jigsaw coordination”, a

cut-and-paste type, in which each member of the

group contributed with a different part and the final

document was a juxtaposition of these parts and a

person was responsible for the final outcomes; (2)

“star coordination”, in which students decided that

everyone completed the entire activity individually,

and then produced the joint product, and finally (3)

“chain coordination”, where one group member

presented a document that constituted an initial task

proposal and the other members of the group

contributed successively to this document, proposing

and justifying modifications or discussing whether

they were in agreement with what had been

previously written. The proposal of these three

patterns was based on the analysis of interactions

specifically associated with the organization of the

task by the students: “The organizational segments

basically involve the decision made by students on

how to carry out the task that occupies them at all

times. The focus of these segments is, therefore, the

planning and management of the joint work, and in

particular the coordination of the actions of the

different members of the group” (Engel & Onrubia,

2010, p. 520)

Some of these collaborative patterns presented

significant relationships to the phases of

collaborative knowledge construction of

Gunawardena et al., (1997), although they observed

that not only a certain type of pattern allowed to

reach a certain phase of knowledge construction, but

that these could be achieved by groups of students

with different collaborative patterns.

Finally, Ng (2008) analyzed the postings of the

members of virtual groups that carried out a

collaborative task, in this case of a semi-structured

nature. This author found three types of

collaborative organizational patterns: (1) based on

the active collaboration of all team members, like

everybody reading each other’s postings, with one

member facilitating the interaction; (2) centred on

the leader of the group, in which one of the members

contributed the main content and the rest accepted it

and made suggestions, and (3) lack-of-coherence

collaboration, showing contributions separately from

each member of the group.

Based on this theoretical framework, the present

study seeks to facilitate a qualitative method to

provide insight into different collaborative patterns

that virtual groups develop to achieve their common

goal.

3 METHOD

3.1 Context

The research was carried out within the framework

of a professional master's degree from the Graduate

University Institute. This is a Higher Education

centre in Spain that delivers online graduate

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education in Social Sciences, Media and Education.

The study was done in the Masters degree on

Technologies applied to Education, aimed at

teachers and education professionals.

The main aim of the study was to apply a

qualitative method in order to identify collaborative

patterns that virtual groups develop to achieve their

common goal and compare our results with those of

previous researchers.

3.2 Participants

Forty students participated in the study. They had

previous experience as teachers (between 3 to 15

years). Twenty-seven participants were female and

thirteen were male, located in different parts of

Spain and Latin America. Average age was 40. The

study was done during course two about integrating

ICT strategies in schools. They were allocated

randomly at the beginning of the course in groups of

four people. They worked collaboratively to develop

a report on how to integrate ICT in schools

following a structure facilitated by their instructor.

They could access contents developed by experts

in html in the virtual learning environment and

access Internet whenever they needed it. Participants

exchanged messages and files during four weeks by

means of a restricted forum. At the end of the four

weeks, their report was evaluated and got a mark.

3.3 Data Collection

Messages and files exchanged by the groups that

participated in the study were collected at the end of

the educational period from the various

asynchronous forums. A total of 1,161 messages

were collected from 10 groups.

The complete message was used as unit of

analysis. Rienties’ et al., (2009) method was applied

to the analysis of messages. The message was

considered a unit unless coders considered that a

message consisted of several elements. So, the

message was then divided when two or more coders

thought that a message consisted of multiple

elements.

3.4 Data Analysis

The messages were analyzed considering categories

that respond to the patterns mentioned in the

literature review (table 1): equal contribution to the

task, distribution of responsibilities, reciprocity,

review of final report, degree of consensus (Engel,

2008). Besides, three qualitative values for each one

of the categories were applied: high, average and

low.

Table 1: Categories of analysis.

Equal contribution

to the task

Degree of contributions of

participants to the whole task, to

a single part or to different

pieces of the report; being low

if the task was done separately

and high if it was done together.

Distribution of

responsibilities

Degree of responsibility of

members concerning the final

outcome, being low if a member

was responsible for a part and

only one, and high, if they all

were responsible for all parts of

the report.

Reciprocity Degree of acceptance of peer

proposals. The lower end

implies little acceptance and

therefore little subsequent

modification of the content and

the high end implies acceptance

and positive valuation, and

therefore, integration of the

contributions of all members of

the group.

Review of the final

report

It refers to the degree (high or

low) in which the members of

the group examine, evaluate and

contribute to the final result of

the written report.

Consensus It would be high if almost all

the members of the group

expressed their agreements and

possible disagreements and

have reached a consensus, and

low if they have provide any

opinion or have not reached a

common opinion.

Thus, groups with lower levels in almost all

categories would have used a collaborative

summative pattern, groups with the highest levels an

integrative collaborative pattern, and groups with

intermediate levels a collaborative aggregation

pattern.

Then, we selected the students' participations,

previously categorized as related to organization,

and we gathered them in the same text file. We

analyzed the messages concerning the distribution of

work and the assignment of responsibilities.

Secondly, we analyzed messages about the

development of the work, the degree of reciprocity

of the contributions of the members of the group, the

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critical acceptance of the proposals by all

participants, the degree of review of the final work

and the degree of consensus on the final document to

be delivered. We gave a value to each group in each

category.

The procedure for encoding the data was as

follows. First the qualitative scale was translated

into a quantitative value: 5 points corresponding to a

high rating, 3 to an average value and 1 to a low

value.

The units of analysis of each group were then

separated according to each of the 5 categories:

equal contribution to the task, distribution of

responsibilities, reciprocity, review of final report,

degree of consensus

Each group was given a score in each category.

Groups that obtained a total score between 5 and

11 points were given the category of summative

collaborative pattern, those who obtained a total

score of between 12 and 18 points, the category of

aggregation collaborative structure and, finally, the

groups that obtained a total score of more than 19

points, the category of integration collaborative

pattern.

4 RESULTS

The evaluation carried out provided the following

results (table 2): two groups (6 and 10) adopted an

addition pattern, another five (1, 2, 7, 8 and 9) an

aggregation pattern and finally three groups (3, 4

and 5) an integration pattern.

As seen in table 2, this qualitative method helps

to identify clearly three collaborative patterns. These

patterns move along a continuum that ranges from a

more or less homogeneous division of labour with

minimal overall supervision (summative or addition

pattern), to a democratic contribution model

(integration pattern), through an intermediate model

where, starting from of a leader's work, the

contributions of others are added (aggregation).

Table 2: Collaborative patterns.

Addition Students decide to distribute the

task among all the members and

develop the document by joining

different pieces prepared

independently by each student.

The final document is basically a

sum of differentiated parts with

few revisions and virtually no

final feedback or questions

between them.

Aggregation Students approve an initial text

(usually provided by one of

them), which is added with partial

contributions of group members,

and they finally make a review of

the final document between them,

with little feedback.

Integration Students decide to contribute

practically to all the sections of

the report and work together in

the text with interaction, review

and feedback in an integrated

manner. Practically all the

members provide feedback and

the final text collects the revisions

of all.

In order to validate the results of the analysis

carried out on the students' participations, an inter-

judge concordance analysis was applied.

For this, we counted on two external evaluators

with experience in higher education and online

teaching-learning processes. Judges were provided

with 26% of the total messages (discussions of

groups 1, 4 and 10) and a template for their

categorization. The intraclass correlation coefficient

(ICC) was used for the analysis. The ICC between

the two evaluators and the researcher was 0.627 in

relation to the collaborative pattern of the groups.

The result of the inter-judges analysis is high,

which implies that the application of the five

mentioned categories of analysis can be used as a

qualitative method to analyse collaborative patterns

of virtual groups.

5 CONCLUSIONS

The students use different ways to organize and

elaborate the task in the group: three groups chose to

do the task contributing in an equal way and

working together in the text (integration pattern),

two elaborated the product adding parts made

independently by each member (addition pattern),

and five chose to elaborate the task using a first

document prepared by one of them and aggregating

or progressively modifying the main text with partial

contributions (aggregation structure).

The use of five different categories of analysis to

assess what type of collaborative pattern each group

followed, allowed us to clearly identify the

functioning of the groups. Given that the

collaborative patterns are related to the degree of

interaction, and the shared construction of

knowledge, it seems very relevant to be able to

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identify how the groups decide to organize their

work and elaborate their texts in a virtual learning

environment.

The collaborative organizational patterns found

in our study follow those organizational

coordination strategies in virtual groups found by

Engel and Onrubia (2010) in their research on

collaborative writing strategies and knowledge

construction phases in CSCL environments:

“jigsaw”, “star” and “chain” coordination patterns.

Our results on how the groups were organized to

carry out the written report through the

asynchronous forum, are also similar to those found

by Ng (2008) about virtual groups that performed

semi-structured tasks: a structure based on the active

collaboration of all, which is similar to our

“Integration Pattern” Another structure based on

collaboration focused on a group leader, as our

“Aggregation Pattern”, and a third structure with a

disjointed collaboration, like our “Addition Pattern”.

It is evident that our study has certain limitations.

On the one hand, the size of the sample prevents us

from applying significant statistical analysis. On the

other hand, it would be convenient to analyze the

relationship between these collaborative patterns and

learning results at an individual and group level. It

would be interesting to relate patterns with the

learning outcomes after a collaborative task in a

virtual group: an analysis of relationships between

collaborative patterns and learning outcomes, in the

sense of knowing if a type of collaborative pattern

facilitates a better learning outcomes at the

individual level or at the final group outcome.

Finally, technology plays a mediating role, so the

study should also be done with other applications or

collaborative tools, whether asynchronous or

synchronous. However, it seems relevant to have a

qualitative analysis tool to deepen these issues, since

currently this type of educational activity has

become popular with the growth of virtual learning

programs and the use of collaborative environments

and applications.

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