1 / 59

Social, Cognitive, and Linguistic Markers of Collaborative Knowledge Building

Social, Cognitive, and Linguistic Markers of Collaborative Knowledge Building. Jianwei Zhang ( 張 建 偉 ) State University of New York at Albany http://tccl.rit.albany.edu. Acknowledgements of co-authors/collaborators. Mary Lamon Richard Messina Richard Reeve Marlene Scardamalia Yanqing Sun.

irisa
Download Presentation

Social, Cognitive, and Linguistic Markers of Collaborative Knowledge Building

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Social, Cognitive, and Linguistic Markers of Collaborative Knowledge Building Jianwei Zhang(張建偉) State University of New York at Albany http://tccl.rit.albany.edu

  2. Acknowledgements of co-authors/collaborators • Mary Lamon • Richard Messina • Richard Reeve • Marlene Scardamalia • Yanqing Sun

  3. A Driving Question Facing a knowledge-based society, how can schools engage students into knowledge-creating practices, with support of new technologies?

  4. Knowledge Building • Knowledge building: the creation of knowledge as a social product (Bereiter, 2002; Scardamalia & Bereiter, 2006). • Knowledge and ideas have a social life out in the world(Bereiter, 2002; Brown & Duguid, 2000;Popper, 1972); • Knowledge creation is a social and collective process (Csikszentmihalyi, 1999; Sawyer, 2003).

  5. A Framing of Knowledge-Creating World 3: Objective knowledge (e.g., in books) World 2: The subjective/ mental world World 1: The physical world (Popper, 1972)

  6. Community knowledge databases World 3 World 2 World 1 CSCL Simulations, data logging Augment Knowledge-Creating with Technologies • Technologies as “reorganizers” of cognitive functioning (Pea, 1985, 1993) -- the relations/ distributions.

  7. Knowledge building collaborative processes and outcomes; emergent goals; depth of understanding; diverse expertise. Traditional learning Individual Pre-designed Content coverage Standard content Challenges to Researchers

  8. This Presentation • Collective responsibility, emergent knowledge building processes • Literacy growth through disciplinary knowledge building • Knowledge Building Measures that Matter

  9. Collective responsibility, emergent knowledge building processes • Sustained, creative knowledge work can be better supported through distributed, flexible, adaptive, social structures than centralized, rigid, or fixed structures (Amar, 2002; Chatzkel, 2003; Engeström 2008; Gloor, 2006; Sawyer, 2003; Williams & Yang, 1999). • “Collaborative improvisation”(Sawyer, 2003) • Emergent goals(Valsiner & Veer, 2000) • Collectively setting agenda(Barab et al., 1999) • Moving between groups, leading to spread and contacts of ideas(Bielaczyc & Collins, 2005)

  10. Collective Knowledge Work: An Example The Design of Boeing 787: Total engineers: 4925

  11. An Example: The Design of Boeing 787

  12. Collective Cognitive Responsibility: A Key and Difficult Principle • Responsibility for the success of a group effort is distributed across all the members; • Tangible tasks + Staying cognitively on top of tasks and ideas as they evolve (e.g., what’s happening, goals, agendas) (Scardamalia, 2002); • Connecting one’s own interests/expertise with those of the community (Amar, 2002).

  13. Collaborative Learning Design “Fixed” small-group collaboration (Davis, 1993): • The teacher designs and divides a project; • Assigns different parts to different teams; • Develops a time-line; • Group presentation.

  14. A Spectrum of Designs Opportunistic-Collaboration Fixed Small-Groups Specialized Groups Interacting Groups (Zhang et al., in press)

  15. A 3-Year Design Experiment • Research design: A three-year “design experiment” (Collins, Joseph, & Bielaczyc, 2004) • Participants: A teacher working with three different classes of fourth-graders (22 each year) • Content domain: Light • Environment: Knowledge Forum

  16. Three Designs • Year 1: A specialized-group model • Year 2: An interacting-group model • Year 3: An opportunistic-collaboration model

  17. Classroom talk on the Grade 3 notes about how worms sense light The initial Light view New views: Colours of Light; Shadows; Reflection (later changed to “Light and Materials”); Other Light The Other Light view evolved into four new views: How Light Travels All We See Is Light? Natural and Artificial Light Images in Our Eyes and in Films Discourses in the Colours of Light view Knowledge building in Year 3

  18. Analyses of the online discourse Social Network Analysis (SNA) Two types of interactions: Note reading, note linking (build-on, rise-above, reference) Content analysis (Chi, 1997) of the teacher’s notes Inquiry threads analysis (Zhang, 2004; Zhang et al., in press) Assessing knowledge gains based on individual portfolio notes C1 C5 C2 A C3 C4 • Emailing

  19. Measuring Collective Cognitive Responsibility

  20. Community awareness: Networks of note-reading Students’ note reading contacts (i.e., who read whose notes): density 0.97, 0.95 and 0.99 (p > .10).

  21. Collaborative and Complementary Contributions: Clique Structures • Clique: “a sub-set of actors who are more closely tied to each other than they are to actors who are not part of the group”(Hanneman, 2001, p. 77). • Higher collective responsibility  pervasive collaboration  a larger number of overlapping cliques, instead of a few isolated sub-groups.

  22. Cliques (sub-communities) Year 1: Specialized-group

  23. Cliques (sub-communities) Year 1: Specialized-group

  24. Cliques (sub-communities) Year 1: Specialized-group

  25. Cliques (sub-communities) Year 1: Specialized-group

  26. Cliques (sub-communities) Year 1: Specialized-group

  27. Cliques (sub-communities) Year 1: Specialized-group

  28. Cliques (sub-communities) Year 1: Specialized-group

  29. Year 2: Interacting-group

  30. Year 3: opportunistic-collaboration

  31. Specialized-group Opportunistic-collaboration Interacting-group

  32. Centralized vs. Distributed Framework: Freeman’s Graph Centralization Measures C1 A C5 C2 C3 C4 A star network: the most centralized network

  33. Teacher: “I need to understand: why plastic shopping bags are usually white. Is there a good reason for the colour? …” SS: “I think shopping bags are white because … that colour stands out.” HM: “I have not found out yet but I think plastic shopping bags are white because if they were black the food inside would be very hot.” DA: “The white in the shopping bag reflects the sunlight so that the food doesn’t go bad.” five more notes Teacher-Student Exchange Patterns • Questions for ideas • Questions on ideas(“I thought worms do not have eyes, so then how do they sense light?” )

  34. Categories of the teacher’s notes in the three years • Questions for ideas (X2 = 21.78, df = 2, p < .001) • Questions on ideas (X2 = 8.87, df =2, p < .05)

  35. Students’ Knowledge Gains • Knowledge diffusion (Brown et al., 1993). • Identified 25 common inquiry themes (e.g., eclipse, rainbow) • Coded each student’s portfolio note, e.g., “There are two kinds of eclipses[,] one is a lunar eclipse which happens when the earth gets between the sun and the moon and a solar eclipse is when the moon gets in between the sun and earth.” (by RI, about “eclipses”)

  36. Students’ Knowledge Gains • Depth of understanding: epistemic complexity X scientific sophistication • Epistemic complexity: 1 - unelaborated facts, 2 – elaborated facts, 3 – unelaborated explanations, and 4 - elaborated explanations; • Scientific sophistication: 1 - pre-scientific, 2 - hybrid, 3 - basically scientific, and 4 - scientific.

  37. Knowledge Diffusion Specialized-group Interacting-group opportunistic-collaboration • Number of inquiry themes about which a student reported knowledge advances in his/her portfolio note (F(2, 63) = 64.14, p < .001, 2 = 0.88).

  38. Depth of Understanding Student ideas were rated based on scientific sophistication and epistemic complexity(F(2, 63) = 5.69, p < .01, 2 = 0.15).

  39. The Evolution of the Community Knowledge Space in the Third Year • Conversation threads: conversation turns, build-on trees. No content! • Inquiry threads: An inquiry thread is a conceptual line of conversation consisting of a series of notes that address a shared principal problem (Zhang, 2004; Zhang et al., 2007).

  40. An Example of Inquiry Threads The inquiry thread of “shadows,” lasting from early February to mid-April, included 11 notes authored by 11 students seeking a deeper understanding of the nature of shadows, with all 22 students as readers.

  41. Diverse Participation • On average, each inquiry thread engaged students as writers 7.52 (SD=4.92) and readers 18.07 (SD=4.48) (all writers were also readers). • Every student contributed to multiple inquiry threads as an author (M=9.91, SD=2.52). • A strong relationship between the number of cliques a student belonged to and the number of inquiry threads s/he participated in as a writer (Pearson r = 0.58, p = .001).

  42. Progressive Questioning in a Thread • Identify what they need to know, and address increasingly complex problems. • The thread on rainbows (#5): • How are rainbows made? Rain droplets split sunlight... • How can a big thing like a rainbow “be activated by mere raindrops”? (by SL) • “There are lots of colors of the rainbows, why are they always in the same order”? (by KT)

  43. Contributing New Information and Data to a Thread • Introducing resources vs. Going beyond resources • Reporting observations/experiences vs. explanatory use of evidence

  44. Idea Improvement in a Thread • Code ideas on a four-point scale (1 - pre-scientific, 2 - hybrid, 3 - basically scientific, and 4 - scientific) (F(2, 159) = 13.51, p < .001, 2= 0.15).

  45. Map the Threads to the Curriculum • These inquiries covered all the required topics listed in The Ontario Curriculum of Science and Technology for Grade 4, as well as many topics expected for Grade 8, for instance, light waves, color vision, colors of opaque objects, concave and convex lenses.

  46. This Presentation • Collective responsibility, emergent knowledge building processes • Literacy growth through disciplinary knowledge building • Knowledge Building Measures that Matter

  47. Rationale • Two challenges facing education: • To raise literacy of all students, close gaps; • To develop creative capacity • Literacy as a complex social practice is best learned through dialogic communication and apprenticeship into literate discourse communities (Applebee, Langer, Nystrand, & Gamoran, 2003). • Vocabulary learning in the knowledge building contexts. • Lexical Frequency Profiles of student authentic written discourse (Laufer, 1994; Nation, 2001).

  48. Links to other views An opened note A build-on note A note Contexts • A class of 22 students in Grade 3 and then 4; • KB/KF over two school years.

  49. e.g., theory, evidence, hypothesis, approach, challenge, clarify, identify, expand, adjust, category, conclude (Sun, Zhang, & Scardamalia, in press)

More Related