title: Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines.
abstract: Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students' visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students' successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules.
authors.affiliation: School of Education, University of Michigan, Ann Arbor, Michigan.
authors.forename: Barbara
authors.initials: B
authors.lastname: Mirel
authors.affiliation: Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, Michigan.
authors.forename: Anuj
authors.initials: A
authors.lastname: Kumar
authors.affiliation: Leondale Germiston, South Africa.
authors.forename: Paige
authors.initials: P
authors.lastname: Nong
authors.affiliation: Molecular and Behavioral Neuroscience Institute, University of Michigan Medical School, Ann Arbor, Michigan.
authors.forename: Gang
authors.initials: G
authors.lastname: Su
authors.affiliation: Molecular and Behavioral Neuroscience Institute, University of Michigan Medical School, Ann Arbor, Michigan.
authors.forename: Fan
authors.initials: F
authors.lastname: Meng
keywords: Case-based instruction; College biology; Critical thinking; Data visualization; Technology; Visual analytics