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PERC 2016 Abstract Detail Page

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Abstract Title: Addressing Relational Data in Students' Representation Use with Network Analysis
Abstract: Network analysis is aligned with a theoretical framework that values relational questions and connection between quantities. One of the problems of using frequentist statistics in education is that most statistical analyses (such as t-tests and analysis of variance) require normally distributed data set, with observations that are independent of one another; however, when studying students in a classroom, these assumptions are often violated.  Students interact with each other, instructors, and course material, allowing ideas to be transferred in a variety of ways.  Learning is embedded in these interactions and can be an exciting area to research but fundamentally requires a research design that captures relational data. This poster will present an example from our work on students' use of representations to demonstrate the types of questions that network analysis can answer, highlight a variety of the analyses that can be run with relational data, and address some of the challenges we faced in using this methodology.
Abstract Type: Symposium Poster
Parallel Session: Expanding Research Questions by Expanding Quantitative Methodologies

Author/Organizer Information

Primary Contact: Daryl McPadden
Florida International University
and Co-Presenter(s)
Jesper Bruun and Eric Brewe