Convergent Adaptation in Small Groups: Understanding Professional Development Activities Through a Complex Systems Lens

Yoon, Susan; Liu, Lei; Goh, Sao-Ee

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Convergent Adaptation in Small Groups: Understanding Professional Development Activities Through a Complex Systems Lens

Yoon, S., Liu, L. & Goh, S.E. (2010). Convergent Adaptation in Small Groups: Understanding Professional Development Activities Through a Complex Systems Lens. Journal of Technology and Teacher Education, 18(2), 319-344. Chesapeake, VA: SITE.
Retrieved from http://www.editlib.org/p/31362.

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Journal Information

Journal of Technology and Teacher Education
ISSN 1059-7069
Volume 18, Issue 2, April 2010
Society for Information Technology & Teacher Education Chesapeake, VA

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Authors

Susan Yoon, Lei Liu, Sao-Ee Goh, University of Pennsylvania, United States

Abstract

Understanding the dynamics of individual or group adaptation can provide valuable information for constructing professional development strategies to increase chances of instructional success. This paper reports on an exploratory study that identifies indicators of convergent vs. non-convergent adaptation in two cases of teachers working together on a technology-based curriculum construction activity and explores the relationship between group characteristics and adaptation processes. We have used the core complex systems concept of adaptation as a lens for understanding how and why some teachers are better able to adapt to the educational program requirements. The results show that processes of convergence and non-convergence influenced adaptive outcomes, and that the more similar the teaching characteristic index (TCI) number was among group members, the more likely it was that group dynamics would result in convergent adaptive outcomes.

Keywords

References

Abrami, P. C. (2001). Understanding and promoting complex learning using technology. Educational Research and Evaluation, 7, 113–136.
Arrow, H., McGrath, J., & Berdahl, J. (2000). Small groups as complex systems. Thousand oaks, Ca: Sage Publications.
Arthur, W.B. (1999). Complexity and the economy. Science (284), 107–109.
Au, K. (1990). Changes in teacher’s views of interactive comprehension instruction. In L. C. Moll (ed.), Vygotsky and education (pp. 271–286). New York: Cambridge university Press.
Becker, H. J. (2000). Who’s wired and who’s not: Children’s access to and use of computer technology. The Future of Children, 10(2), 44–75.
Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User Adapted Interaction, 11, 87–110.
Bullough, R. V., & Baughman, K. (1997). “First year teacher” eight years later: An inquiry into teacher development. New York: Teachers College Press.
Chi, M. (2005). Commonsense conceptions of emergent processes: Why some misconceptions are robust. Journal of Learning Sciences, 14(2), 161–199.
Coburn, C. (2003). Rethinking scale: Moving beyond numbers to deep and lasting change. Educational Researcher, 32(6), 3–12.
Cuban, L., Kirkpatrick, H., & Peck, C. (2001). High access and low use of technologies in high school classrooms: explaining an apparent paradox. American Educational Research Journal, 38(4), 813–834.
Dede, C., & Honan, J. (2005). Scaling up success: a synthesis of themes and insights. In C. Dede, J. Honan, & L. Peters (eds.), Scaling up success: Lessons learned from technology-based educational improvement (pp. 227– 239). San Francisco: Jossey-Bass.
Dillenbourg, P., & Schneider, D. (1995). Mediating the mechanisms which make collaborative learning sometimes effective. International Journal of Educational Telecommunications, 1, 131–146.
Elmore, R. (1996). Getting to scale with good educational practice. Harvard Educational Review, 66(1), 1–26.
Fishman, B., Marx, R., Blumenfeld, P., Krajcik, J., & Soloway, E. (2004). Creating a framework for research on systemic technology innovations. Journal of the Learning Sciences, 13(1), 43–76.
Fishman, B., & Pinkard, N. (2001). Bringing urban schools into the information age: Planning for technology vs. Technology planning. Journal of Educational Computing Research, 25(1), 63–80.
Fullan, M. (1993). Change forces: Probing the depths of educational reform. The Falmer Press: London.
Fullan, M. (1999). Change forces: The sequel. The Falmer Press: London.
Fullan, M. (2003). Change forces with a vengeance. RoutledgeFalmer: London.
Garet, M. S., Porter, A. C., Desimone, L., Birman, R. F., & Yoon, K. (2001). What makes professional development effective? Results from a national sample of teachers. American Educational Research Journal, 38(4), 915– 945.
Goldman, S. (2005). Designing for scalable educational improvement. In C. Dede, J. Honan, & L. Peters (eds.), Scaling up success: Lessons learned from technology-based educational improvement (pp. 67–96). San Francisco: Jossey-Bass.
Grotzer, T. (2005). Role of complex causal models in students’ understanding of science. Studies in Science Education, 41, 117–166.
Hadley, M., & Sheingold, K. (1993). How exemplary computer-using teachers differ from other teachers: implications for realizing the potential of computers in school. Journal of Research on Computing in Education, 26, 291–321.
Hmelo-Silver, C., Surabhi, M., & Liu, L. (2007). Fish Swim, Rocks Sit, and Lungs Breathe: expert-novice understanding of Complex Systems. Journal of the Learning Sciences, 16(3), 307-331.
Hughes, J. E., & Ooms, A. (2004). Content-focused technology inquiry groups: Preparing urban teachers to integrate technology to transform student learning. Journal of Research on Technology in Education, 36(4), 397–411.
Jacobson, M. (2001). Problem solving, cognition, and complex systems: Differences between experts and novices. Complexity, 6(3), 41–49.
Jacobson, M., & Wilensky, U. (2006). Complex systems in education: Scientific and educational importance and implications for the learning sciences. Journal of the Learning Sciences, 15(1), 11–34.
Kauffman, S. (1995). At home in the universe. New York: oxford university Press.
Liu, L., & Hmelo-Silver, C. E. (2009). Promoting complex systems learning through the use of conceptual representations in hypermedia. Journal of Research in Science Teaching, 46, 1023-1040.
Means, B., & Penuel, W. R. (2005). Scaling up technology-based educational innovations. In C. Dede, J. P. Honan, & L. C. Peters (eds.), Scaling up success: Lessons from technology-based educational improvement. San Francisco: Jossey-Bass.
O’Donnell, A. M., & O’Kelly, J. B. (1994). Learning from peers: Beyond the rhetoric of positive results. Educational Psychology Review, 6, 321–349.
Penner, D. (2000). Explaining systems: investigating middle school students’ understanding of emergent phenomena. Journal of Research in Science Teaching, 37(8), 784–806.
Prigogine, I., & Stengers, I. (1984). Order out of chaos. New York: Bantam Books.
Reiser, B. J., Spillane, J. P., Steinmuller, F., Sorsa, D., Carney, K., & Kyza, E. (2000). Investigating the mutual adaptation process in teachers’ design of technology-infused curricula. In B. Fishman & S. O’Conner-Divelbiss
Resnick, M. (1996). Beyond the centralized mindset. Journal of the Learning Sciences, 5, 1–22.
Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. Journal of the Learning Sciences, 2(3), 235–276.
Rosebery, A. S., Warren, B., & Conant, F. R. (1992). Appropriating scientific discourse: Findings from language minority classrooms. Journal of the Learning Sciences, 2(1), 61–94.
Russell, T. (1988). From pre-service teacher education to the first year of teaching: a study of theory into practice. In J. Calderhead (ed.), Teachers’ professional learning (pp. 13–34). London: Falmer Press.
Russell, T. (1995). Returning to the physics classroom to re-think how one learns to teach physics. In T. Russell & F. Korthagen (eds.), Teachers who teach teachers (pp. 95–112). London: Falmer Press.
Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In B. Smith (ed.), Liberal Education in a Knowledge Society (pp. 67-98). Chicago: open Court.
Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.
Shulman, L. S. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57, 1–22.
Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep or a firefly: Learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171–209.
Yoon, S. (2008a). Using memes and memetic processes to explain social and conceptual influences on student understanding about complex socio-scientific issues. Journal of Research in Science Teaching, 45(8), 900-921.
Yoon, S. (2008b). An evolutionary approach to harnessing complex systems thinking in the science and technology classroom. International Journal of Science Education, 30(1), 1-32.
Yoon, S. & Klopfer, E. (2006). Feedback (F) Fueling adaptation (a) network Growth (n) and Self-organization (S): a complex systems design and evaluation approach to professional development. Journal of Science Education and Technology, 15(5-6), 353-366.

These references have been extracted automatically and may have some errors. If you see a mistake in the references above, please contact info@editlib.org.

[1] Abrami, P. C. (2001). Understanding and promoting complex learning using technology. Educational Research and Evaluation, 7, 113–136.

[2] Arrow, H., McGrath, J., & Berdahl, J. (2000). Small groups as complex systems. Thousand oaks, Ca: Sage Publications.

[3] Arthur, W.B. (1999). Complexity and the economy. Science (284), 107–109.

[4] Au, K. (1990). Changes in teacher’s views of interactive comprehension instruction. In L. C. Moll (ed.), Vygotsky and education (pp. 271–286). New York: Cambridge university Press.

[5] Becker, H. J. (2000). Who’s wired and who’s not: Children’s access to and use of computer technology. The Future of Children, 10(2), 44–75.

[6] Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User Adapted Interaction, 11, 87–110.

[7] Bullough, R. V., & Baughman, K. (1997). “First year teacher” eight years later: An inquiry into teacher development. New York: Teachers College Press.

[8] Chi, M. (2005). Commonsense conceptions of emergent processes: Why some misconceptions are robust. Journal of Learning Sciences, 14(2), 161–199.

[9] Coburn, C. (2003). Rethinking scale: Moving beyond numbers to deep and lasting change. Educational Researcher, 32(6), 3–12.

[10] Cuban, L., Kirkpatrick, H., & Peck, C. (2001). High access and low use of technologies in high school classrooms: explaining an apparent paradox. American Educational Research Journal, 38(4), 813–834.

[11] Dede, C., & Honan, J. (2005). Scaling up success: a synthesis of themes and insights. In C. Dede, J. Honan, & L. Peters (eds.), Scaling up success: Lessons learned from technology-based educational improvement (pp. 227– 239). San Francisco: Jossey-Bass.

[12] Dillenbourg, P., & Schneider, D. (1995). Mediating the mechanisms which make collaborative learning sometimes effective. International Journal of Educational Telecommunications, 1, 131–146.

[13] Elmore, R. (1996). Getting to scale with good educational practice. Harvard Educational Review, 66(1), 1–26.

[14] Fishman, B., Marx, R., Blumenfeld, P., Krajcik, J., & Soloway, E. (2004). Creating a framework for research on systemic technology innovations. Journal of the Learning Sciences, 13(1), 43–76.

[15] Fishman, B., & Pinkard, N. (2001). Bringing urban schools into the information age: Planning for technology vs. Technology planning. Journal of Educational Computing Research, 25(1), 63–80.

[16] Fullan, M. (1993). Change forces: Probing the depths of educational reform. The Falmer Press: London.

[17] Fullan, M. (1999). Change forces: The sequel. The Falmer Press: London.

[18] Fullan, M. (2003). Change forces with a vengeance. RoutledgeFalmer: London.

[19] Garet, M. S., Porter, A. C., Desimone, L., Birman, R. F., & Yoon, K. (2001). What makes professional development effective? Results from a national sample of teachers. American Educational Research Journal, 38(4), 915– 945.

[20] Goldman, S. (2005). Designing for scalable educational improvement. In C. Dede, J. Honan, & L. Peters (eds.), Scaling up success: Lessons learned from technology-based educational improvement (pp. 67–96). San Francisco: Jossey-Bass.

[21] Grotzer, T. (2005). Role of complex causal models in students’ understanding of science. Studies in Science Education, 41, 117–166.

[22] Hadley, M., & Sheingold, K. (1993). How exemplary computer-using teachers differ from other teachers: implications for realizing the potential of computers in school. Journal of Research on Computing in Education, 26, 291–321.

[23] Hmelo-Silver, C., Surabhi, M., & Liu, L. (2007). Fish Swim, Rocks Sit, and Lungs Breathe: expert-novice understanding of Complex Systems. Journal of the Learning Sciences, 16(3), 307-331.

[24] Hughes, J. E., & Ooms, A. (2004). Content-focused technology inquiry groups: Preparing urban teachers to integrate technology to transform student learning. Journal of Research on Technology in Education, 36(4), 397–411.

[25] Jacobson, M. (2001). Problem solving, cognition, and complex systems: Differences between experts and novices. Complexity, 6(3), 41–49.

[26] Jacobson, M., & Wilensky, U. (2006). Complex systems in education: Scientific and educational importance and implications for the learning sciences. Journal of the Learning Sciences, 15(1), 11–34.

[27] Kauffman, S. (1995). At home in the universe. New York: oxford university Press.

[28] Liu, L., & Hmelo-Silver, C. E. (2009). Promoting complex systems learning through the use of conceptual representations in hypermedia. Journal of Research in Science Teaching, 46, 1023-1040.

[29] Means, B., & Penuel, W. R. (2005). Scaling up technology-based educational innovations. In C. Dede, J. P. Honan, & L. C. Peters (eds.), Scaling up success: Lessons from technology-based educational improvement. San Francisco: Jossey-Bass.

[30] O’Donnell, A. M., & O’Kelly, J. B. (1994). Learning from peers: Beyond the rhetoric of positive results. Educational Psychology Review, 6, 321–349.

[31] Penner, D. (2000). Explaining systems: investigating middle school students’ understanding of emergent phenomena. Journal of Research in Science Teaching, 37(8), 784–806.

[32] Prigogine, I., & Stengers, I. (1984). Order out of chaos. New York: Bantam Books.

[33] Reiser, B. J., Spillane, J. P., Steinmuller, F., Sorsa, D., Carney, K., & Kyza, E. (2000). Investigating the mutual adaptation process in teachers’ design of technology-infused curricula. In B. Fishman & S. O’Conner-Divelbiss

[34] Resnick, M. (1996). Beyond the centralized mindset. Journal of the Learning Sciences, 5, 1–22.

[35] Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. Journal of the Learning Sciences, 2(3), 235–276.

[36] Rosebery, A. S., Warren, B., & Conant, F. R. (1992). Appropriating scientific discourse: Findings from language minority classrooms. Journal of the Learning Sciences, 2(1), 61–94.

[37] Russell, T. (1988). From pre-service teacher education to the first year of teaching: a study of theory into practice. In J. Calderhead (ed.), Teachers’ professional learning (pp. 13–34). London: Falmer Press.

[38] Russell, T. (1995). Returning to the physics classroom to re-think how one learns to teach physics. In T. Russell & F. Korthagen (eds.), Teachers who teach teachers (pp. 95–112). London: Falmer Press.

[39] Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In B. Smith (ed.), Liberal Education in a Knowledge Society (pp. 67-98). Chicago: open Court.

[40] Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.

[41] Shulman, L. S. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57, 1–22.

[42] Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep or a firefly: Learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171–209.

[43] Yoon, S. (2008a). Using memes and memetic processes to explain social and conceptual influences on student understanding about complex socio-scientific issues. Journal of Research in Science Teaching, 45(8), 900-921.

[44] Yoon, S. (2008b). An evolutionary approach to harnessing complex systems thinking in the science and technology classroom. International Journal of Science Education, 30(1), 1-32.

[45] Yoon, S. & Klopfer, E. (2006). Feedback (F) Fueling adaptation (a) network Growth (n) and Self-organization (S): a complex systems design and evaluation approach to professional development. Journal of Science Education and Technology, 15(5-6), 353-366.

Convergent Adaptation in Small Groups: Understanding Professional Development Activities Through a Complex Systems Lens

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