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Problem solving in biochemistry: assessment, learning strategies, and preconceptions
Author(s) -
Sensibaugh Cheryl A.,
Osgood Marcy P.
Publication year - 2013
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.27.1_supplement.329.2
Subject(s) - domain (mathematical analysis) , curriculum , mathematics education , problem based learning , range (aeronautics) , computer science , multivariate statistics , management science , psychology , mathematics , pedagogy , machine learning , engineering , mathematical analysis , aerospace engineering
Discipline‐based education research has produced varied perspectives on defining and assessing scientific problem solving. The goals of this dissertation work are to describe and explain longitudinal performance gaps across a two‐year biochemistry curriculum, as well as to synthesize a more advanced pedagogical understanding of scientific problem solving from previously fragmented sources. Student performance will be measured using the Individual Problem Solving Assessment (IPSA), and achievement rates in each domain of problem solving will describe longitudinal performance. The results of a pilot study indicate that after the first year of the curriculum, domain achievement rates for students pursuing a B.S. in Biochemistry range from 9% to 64%. To explain performance gaps, potential contributors will also be investigated, using two additional measures that reflect alternate views of problem solving. The impact of our corresponding problem‐based learning strategies will also be evaluated. Multivariate multiple linear regression analyses will be used to generate quantitative models of the performance phenomena. Additionally, students’ preconceptions about problem solving are being identified. This study will ultimately elucidate connections among emerging theories of defining and assessing scientific problem solving. Research support is provided under NSF TUES Award #DUE‐1043079.