Florence R. Sullivan, Ph.D.


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NSF Supported Research Project

Microgenetic Learning Analytics

The goal of the Microgenetic Learning Analytics project is to develop a new computational method for analyzing student problem-solving conversations recorded in co-present small group interactions. Microgenetic analysis seeks to understand conceptual change over short time periods (minutes, hours, days). We aim to use tools drawn from the field of natural language processing to aid our microgenetic analysis of discourse data. Our corpus of small group talk is derived from middle school aged girls and boys working in collaborative problem solving groups to solve robotics problems. The challenge of our work is finding effective means for interpreting contextual talk that widely features indexical and pronomial elements, as opposed to a specific content-based vocabulary. Microgenetic analysis is viewed by educational researchers as one of the most robust methods for understanding how human learning happens. Microgenetic analysis is a labor intensive method that is usually performed in a case study format involving one or a few students. Our goal is to develop a method that will expand possibilities for performing microgenetic analysis over larger data sets, and to expand the scope of research questions that may be asked and answered with such data sets. The below video provides information on the current state of our solution to this educational research problem using computational means.


Papers related to our work have been presented at AERA 2015 and 2016 as well as CSCL 2015 and 2017 and the International Conference on Computational Thinking Education (CTE 2017).

Sullivan, F.R., & Keith, P.K. (2017). Emergent roles, collaboration and computational thinking in the multi-dimensional problem space of robotics. Proceedings of the 2017 meeting of the International Conference on Computational Thinking Education, Hong Kong, PRC July 13 - 15, 2017. Download here.

Sullivan, F.R., Poza, R., & Keith, P.K. (2017). Girls, robotics learning and internalized stereotypes: is there a relationship? Paper presentation at the 2017 Bi-Annual Meeting of Computer Supported Collaborative Learning, Philadelphia, Pennsylvania June 16 - 20, 2017. Download here.

Sullivan, F.R., Keith, P.K., & Poza, R. (2016). Internalized stereotypes: do they play a role in girls' robotics learning? Paper presentation to the annual meeting of the American Educational Research Association, Washington, DC, April 8-12, 2016. Download here.

Sullivan, F.R., Keith, P.K., & Wilson, N.C. (2016). Learning from the periphery in a collaborative robotics workshop for girls. Paper presentation to the annual meeting of the American Educational Research Association, Washington, DC, April 8-12, 2016. Download here.

Sullivan, F.R., Adrion, W.R. & Keith, P.K. (2015). Microgenetic learning analytics: A computational approach to research on student learning. Paper presentation at the annual meeting of the American Educational Research Association, Chicago, IL, April 16-20, 2015. Download here.

Sullivan, F.R., Keith, P.K., & Wilson, N.C. (2015). Examining power relations in an all girl robotics learning environment. Proceedings of the 2015 Bi-Annual Meeting of Computer Supported Collaborative Learning, Gothenburg, Sweden, June 7 - 11, 2015, vol. 2, 861-863. Download here.