Skip to main content Accessibility help
×
Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-27T22:14:54.923Z Has data issue: false hasContentIssue false

11 - Microgenetic Methods

from Part II - Methodologies

Published online by Cambridge University Press:  14 March 2022

R. Keith Sawyer
Affiliation:
University of North Carolina, Chapel Hill
Get access

Summary

Microgenetic methods are used to analyze moment-to-moment processes of learning, reasoning, and problem-solving. Microgenetic methods are useful when studying learning that does not occur in a straight line from lesser to greater understanding, but rather occurs through a learning trajectory that includes iterative and unpredictable paths and sometimes even setbacks or failure. Microgenetic methods are also useful in studying learning that is mediated by tools and artifacts in the learning environment, and what role those artifacts play in the developing learning trajectory. These methods are time-consuming and it’s not practical to conduct studies with large sample sizes or that occur over very long periods of time; rather, the focus is on developing a deep and thorough understanding of a specific learning environment and then to generalize those findings to a broader range of contexts. Microgenetic methods are particularly well-suited to five types of research questions: questions about the variability or stability of strategies; events that precipitate or initiate change; co-occurring events and processes; trajectories or paths of change; and the rate of change.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2022

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alibali, M. W., Nathan, M. J., Wolfgram, M. S., et al. (2014). How teachers link ideas in mathematics instruction using speech and gesture: A corpus analysis. Cognition and Instruction, 32(1), 65100.Google Scholar
Altebarmakian, M., Alterman, R., Yatskar, A., Harsch, K., & DiLillo, A. (2016). The microgenetic analysis of staged peer collaboration for introductory programming. In Proceedings of the 2016 IEEE Frontiers of Education Conference (FIE), October 12–15, Eire, PA (pp. 18).Google Scholar
Bakeman, R., Adamson, L. B., & Strisik, P. (1989). Lags and logs: Statistical approaches to interaction. In Bornstein, M. H. & Bruner, J. S. (Eds.), Interaction in human development: Crosscurrents in contemporary psychology (pp. 241260). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Broaders, S. C., Cook, S. W., Mitchell, Z., & Goldin-Meadow, S. (2007). Making children gesture brings out implicit knowledge and leads to learning. Journal of Experimental Psychology: General, 136(4), 539550.Google Scholar
Buckland, L. A., Chinn, C. A., & Duncan, R. G. (2010, May). Epistemic growth in model-based argumentation. Paper presented at the annual meeting of the American Educational Research Association, Denver, CO.Google Scholar
Catán, L. (1986). The dynamic display of process: Historical development and contemporary uses of the microgenetic method. Human Development, 29(5), 252263.Google Scholar
Chi, M. T. H. (1997). Quantifying qualitative analyses of verbal data: A practical guide. Journal of the Learning Sciences, 6(3), 271315.Google Scholar
Chi, M. T. H., de Leeuw, N., Chiu, M., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439477.Google Scholar
Chinn, C. A. (2006). The microgenetic method: Current work and extensions to classroom research. In Green, J. L., Camilli, G., & Elmore, P. (Eds.), Handbook of complementary methods in education research (pp. 439456). Washington, DC: American Educational Research Association.Google Scholar
Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In Resnick, L. B. (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 453494). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Crowley, K., Shrager, J., & Siegler, R. S. (1997). Strategy discovery as a competitive negotiation between metacognitive and associative mechanisms. Developmental Review, 17(4), 462489.Google Scholar
Darque, N., Sweller, N., & Jones, M. P. (2019). When our hands help us understand: A meta-analysis into the effects of gesture on comprehension. Psychological Bulletin, 145(8), 765784.Google Scholar
Ericsson, K. A., & Simon, H. A. (1993). Protocol analysis: Verbal reports as data (revised ed.). Cambridge, MA: MIT Press.Google Scholar
Goldin-Meadow, S., Alibali, M. W., & Church, R. B. (1993). Transitions in concept acquisition: Using the hand to read the mind. Psychological Review, 100(2), 279297.Google Scholar
Gupta, A., Elby, A., & Sawtelle, V. (2016). Bridging knowledge analysis and interaction analysis through understanding the dynamics of knowledge in use. In diSessa, A. A., Levin, M., & Brown, N. J. S. (Eds.), Knowledge and interaction: A synthetic agenda for the learning sciences (pp. 260291). New York, NY: Routledge.Google Scholar
Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based and inquiry learning: A response to Kirschner, Sweller, and Clark (2006). Educational Psychologist, 42(2), 99107.Google Scholar
Jadallah, M., Anderson, R. C., Nguyen-Jahiel, K., et al. (2011). Influence of a teacher’s scaffolding moves during child-led small-group discussions. American Educational Research Journal, 48(1), 194230.Google Scholar
Jordan, B., & Henderson, A. (1995). Interaction analysis: Foundations and practice. Journal of the Learning Sciences, 4(1), 39103.Google Scholar
Kuhn, D. (1995). Microgenetic study of change: What has it told us? Psychological Science, 6(3), 133139.Google Scholar
Kuhn, D., & Phelps, E. (1979). A methodology for observing development of a formal reasoning strategy. New Directions for Child Development, 5, 4557.Google Scholar
Lavelli, M., Pantoja, A. P. F., Hsu, H.-C., Messinger, D. S., & Fogel, A. (2005). Using microgenetic designs to study change processes. In Teti, D. M. (Ed.), Handbook of research methods in developmental science (pp. 4065). Malden, MA: Blackwell.Google Scholar
Mayer, R. E. (2004). Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. American Psychologist, 59(1), 1419.Google Scholar
Mercer, N. (2000). Words and minds: How we use language to think together. London, England: Routledge.Google Scholar
Mercer, N. (2013). The social brain, language and goal-directed collective thinking: A social conception of cognition and its implications for understanding how we think, teach, and learn. Educational Psychologist, 48(3), 148168.Google Scholar
Parnafes, O. (2012). Developing explanations and developing understanding: Students explain the phases of the moon using visual representations. Cognition and Instruction, 30(4), 359403.Google Scholar
Renström, L., Andersson, B., & Marton, F. (1990). Students’ conceptions of matter. Journal of Educational Psychology, 82(3), 555569.Google Scholar
Rittle-Johnson, B., & Alibali, M. W. (1999). Conceptual and procedural knowledge of mathematics: Does one lead to the other? Journal of Educational Psychology, 91(1), 175189.Google Scholar
Schauble, L. (1996). The development of scientific reasoning in knowledge-rich contexts. Developmental Psychology, 32(1), 102119.Google Scholar
Schneider, B., & Pea, R. (2013). Real-time mutual gaze perception enhances collaborative learning and collaboration quality. International Journal of Computer-Supported Collaborative Learning, 8(4), 375397.CrossRefGoogle Scholar
Schoenfeld, A. H., Smith, J. P., & Arcavi, A. (1993). Learning: The microgenetic analysis of one student’s evolving understanding of a complex subject matter domain. In Glaser, R. (Ed.), Advances in instructional psychology (Vol. 4, pp. 55175). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Sherin, B. L. (2013). A computational study of commonsense science: An exploration in the automated analysis of clinical interview data. Journal of the Learning Sciences, 22(4), 600638.Google Scholar
Sherin, B. L., Kersting, N. B., & Berland, M. (2018). Learning analytics in support of qualitative analysis. 13th International Conference on the Learning Sciences, 1, 464471.Google Scholar
Sherin, B. L., Krakowski, M., & Lee, V. R. (2012). Some assembly required: How scientific explanations are constructed during clinical interviews. Journal of Research in Science Teaching, 49(2), 166198.Google Scholar
Sherin, M. G., Russ, R. S., Sherin, B. L., & Colestock, A. (2008). Professional vision in action: An exploratory study. Issues in Teacher Education, 17(2), 2746.Google Scholar
Shvarts, A., & Abrahamson, D. (2019). Dual-eye-tracking Vygotsky: A microgenetic account of a teaching/learning collaboration in an embodied-interaction technological tutorial for mathematics. Learning, Culture and Social Interaction, 22.Google Scholar
Siegler, R. S. (1996). Emerging minds: The process of change in children’s thinking. New York, NY: Oxford University Press.Google Scholar
Siegler, R. S. (2006). Microgenetic analyses of learning. In Damon, W., Lerner, R. M., Kuhn, D., & Siegler, R. (Eds.), Handbook of child psychology: Vol. 2. Cognition, perception, and language (6th ed., pp. 464510). Hoboken, NJ: Wiley.Google Scholar
Siegler, R. S., & Chen, Z. (1998). Developmental differences in rule learning: A microgenetic analysis. Cognitive Psychology, 36(3), 273310.Google Scholar
Siegler, R. S., & Crowley, K. (1991). The microgenetic method: A direct means for studying cognitive development. American Psychologist, 46(6), 606620.Google Scholar
Siegler, R. S., & Jenkins, E. (1989). How children discover new strategies. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Smith, C., Snir, J., & Grosslight, L. (1992). Using conceptual models to facilitate conceptual change: The case of weight-density differentiation. Cognition and Instruction, 9(3), 221283.Google Scholar
Taylor, J., & Cox, B. D. (1997). Microgenetic analysis of group-based solution of complex two-step mathematical word problems by fourth graders. Journal of the Learning Sciences, 6(2), 183226.Google Scholar
Vygotsky, L. S. (1978). Mind in society (Kozulin, A., Trans.). Cambridge, MA: Harvard University Press.Google Scholar
Worsley, M. (2012). Multimodal learning analytics: Enabling the future of learning through multimodal data analysis and interfaces. Proceedings of the 14th ACM International Conference on Multimodal Interaction (pp. 353–356).CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×