Epistemic agency and patterns of collaboration in

computer-supported inquiry

Kai Hakkarainen& Tuire Palonen

Presenter: Sami PaavolaDepartment of Psychology

University of Helsinki

www.helsinki.fi/science/networkedlearning

Problem• Whether elementary school students, collaborating

within a computer-supported classroom, would be able to productively participate in progressive discourse interaction focused on advancing their explanations.

• The present study focused on examining the nature of CSILE students’ social network, especially to identify various degrees of epistemic agency assumed by the participants.

Epistemic Agency(Scardamalia, 2002)

• Characteristic of epistemic agency is that the students themselves manage advancement of their knowledge.

• They coordinate their personal ideas with others’, and also monitor how their collaborative efforts are proceeding.

• Rather than subsuming their thinking under the teachers’ cognitive authority, students take responsibility for their own thinking and problem solving.

Reanalyzing Earlier Studies

• Epistemology of inquiry was addressed in an earlier study by examining the relative proportion of explanatory knowledge produced by individual students.

• This approach did not provide detailed information about each student’s pattern of participating in collaborative process of inquiry or specific knowledge building roles assumed by the participants.

• Epistemic agency is an inherently relational phenomenon that cannot be adequately understood by examining only individual attributes

Social Network Analysis• The present study focused on uncovering the patterns

of CSILE students’ networking activity by applying methods of social network analysis (SNA)

• SNA provides statistical tools for examining relational data rather that merely characterizing attributes of individual actors.

• SNA focuses on describing patterns of relationships among actors, and analyzing the structure of these patterns.

Participants and Study Material

• Technical infrastructure: CSILE/Knowledge Forum® that provided a shared database for building and sharing knowledge

• Participants: 28 grade 5/6 students (Toronto)• Study material: 504 written comments

produced by the students and their teacher to CSILE’s database

Qualitative Content Analysis• Two types of CSILE students’ discourse

interaction were distinguished- Knowledge Sharing Comments: comments in

which the students shared their explanatory theories- Distributed regulation of inquiry (DRI):

comments requesting explication of explanatory relations

- The subsequent analyses focused on examining patterns of the students’ participation in these types of interaction.

An Example of Knowledge-sharing Comment

• NI [New Information]: I have found out how a wire turns an iron spike into a magnet. It is not the iron spike that is the magnet, but the wire. When we connect a wire to a battery we engage an electric force field. When we coil the wire we intensify the field. We can intensify it again when we wrap it around the iron spike. This creates a force field strong enough to pull other objects into its grasp. … (16f3, emphasis added)

Examples of Distributed Regulation of Inquiry (DRI)

• I think that you should describe and tell more in your theory about how the UNIVERSE will change in the future and less about how the people will change in the future and how they will know more about the universe in the future because that is not really the question you are researching. (4f2)

• 9f3 and 12f3 you are not quite answering your note. Your problem says: Why do you get some diseases once, and some diseases many times, and your theory is just telling information about what happens when you only get it once. (13f3)

Centralization of Interaction

Network A Network B

a

d

c

bf

ef

ab

c

e

d

How strongly interaction was organized around the most active and visible actors in the community?

Centrality varies between 0 and 100%. It was 24% and 28% in the case of sent and received comments, respectively

Freeman’s ’Betweenness’

• Freeman's ‘betweenness’ value for a given student shows how often that student is found in the shortest path between two other students.

• Betweenness measure indicates an actor’s centrality in regulating interaction within a community.

Bridging Structural Holes• Actor A has a high betweenness in the below

presented social network

d

b

a

c h

g

f

A

Structural hole

Table. Cluster Centres Concerning Levels of Epistemic Agency

Variables Level 1 Level 2 Level 3 Level 4

Outdegree of knowledge sharing

3 5 9 13

Outdegree of distributed regulation of inquiry (DRI)

6 12 7 9

Betweenness of knowledge sharing

17 44 86 131

Betweenness of distributed regulation of inquiry (DRI)

13 44 73 27

Number of dialogue partners

3 5 8 5

Number of students 17 4 4 3

Levels of Epistemic agency• Level 1: Taking responsibility only for advancing one’s

own inquiry (17 students).

• Level 2. Relatively intensive interaction with one’s immediate peers (4 students).

• Level 3. High betweenness centrality in distributed regulation of inquiry in terms of systematically asking their fellow students to engage in deepening inquiry and explicate their explanations (4 students).

• Level 4. Assuming the role of socio-cognitive brokers of CSILE students’ knowledge-sharing network in terms of crossing boundaries between male and female students, as well as less and more advanced students. (3 students).

1m1

2f2 3f3

4f2

5f36m3

7f3

8m3

9f311f3

12f313f314m3

15f2

16f317m2

18f219f3

20f2

21m2

22f3

23m3

24f1

25f1

26f127f3

28m2

-2.0

-1.5

-1.0

-0.5

0.0

0,5

1.0

1.5

2.0

2.5

2.01.51.00.50.0-0.5-1.0-1.5-2.0

Dimension 1

Dim

ensi

on 2

Teacher

**

*

**

*

*

MDS of knowledge sharing

female female, level 3-4 epistemic agency malemale, level 3-4 epistemic agency

MDS of Distributed regulation of inquiry (DRI)

1m1

2f23f3

4f2

5f3

6m3

7f3

8m3

9f3

10m3

11f312f3

13f3

14m315f2

16f3

17m218f2

19f3

20f2

21m222f3

23m3

24f1

25f1

26f127f3

28m2

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

2.01.51.00.50.0-0.5-1.0-1.5-2.0-2.5 2.5

Dim

ensi

on 2

Dimension 1

Teacher**

*

*

**

*

femalefemale, level 3-4 epistemic agency malemale, level 3-4 epistemic agency

Concluding Remarks• Students with a high level of epistemic agency had a

cognitively central knowledge-building role within the classroom involving crossing boundaries between groups of students and coordinating their collaborative activities.

• Knowledge brokering characterized their activity, i.e., creating connections and establishing networks between agents, students ideas as well as scientific knowledge artifacts (cf., Sverrisson, 2001).

• They assumed collective responsibility for the advancement of the whole community’s rather than solely for their own inquiry.

Relational Skills• Students with a high level of epistemic agency appeared to

develop relational skills involving metaknowledge of other persons’ and communities’ skills and competencies within the inquiry community (Nishiguchi, 2001).

• They focused on encouraging participation of students who did not themselves had equally strong academic skills.

• They made intellectual resources available by knowing “who know what, who can and is willing to be helpful in what”, and who is in need of new knowledge.

Strong Teacher Guidance• CSILE students’ advanced inquiry practices

relied on a strong teacher guidance.• Over time the teacher had cultivated a very

high level of inquiry culture within the classroom so that all classroom activities supported progressive inquiry

• Knowledge-building community appears to presuppose an expansive learning community.