Epistemic agency and patterns of collaboration in computer-supported inquiry

1. Epistemic agency and patterns of collaboration in computer-supported inquiry Kai Hakkarainen& Tuire Palonen Presenter: Sami Paavola Department of Psychology University of Helsinki www.helsinki.fi/science/networkedlearning

2. 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.

3. 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.

4. 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

5. 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.

6. 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

7. 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.

8. 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)

9. 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)

10. b b a f c f d e a c e d Centralization of Interaction How strongly interaction was organized around the most active and visible actors in the community? Network A Network B Centrality varies between 0 and 100%. It was 24% and 28% in the case of sent and received comments, respectively

11. 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.

12. g A a b f h c d Structural hole Bridging Structural Holes • Actor A has a high betweenness in the below presented social network

13. Table. Cluster Centres Concerning Levels of Epistemic Agency

14. 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).

15. MDS of knowledge sharing female female, level 3-4 epistemic agency male male, level 3-4 epistemic agency

16. female female, level 3-4 epistemic agency male male, level 3-4 epistemic agency MDS of Distributed regulation of inquiry (DRI)

17. 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 brokeringcharacterized 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.

18. 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.

19. 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.