Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study
Barbara Mirel1, Anuj Kumar2, Paige Nong3
1School of Education, University of Michigan, Ann Arbor, Michigan.
Journal of Science Education and Technology
|February 16, 2016
Summary
Undergraduate biology students can feasibly use visual analytics tools for data exploration. Enhancing tool usability and instructional methods can further support their learning of these essential scientific skills.
Area of Science:
- Genomics Education
- Visual Analytics in Biology
- Undergraduate Science Pedagogy
Background:
- Life scientists widely use visual analytics for large dataset exploration and hypothesis generation.
- Visual analytics is an underdeveloped area in undergraduate biology curricula.
- There is a need to integrate modern data analysis methods into biology education.
Purpose of the Study:
- To assess the feasibility of undergraduate biology majors using interactive data visualizations for exploratory analysis.
- To compare undergraduate student use of visual analytics tools with practicing scientists' methods.
- To identify student performance patterns, efficiencies, and challenges in visual analytics tasks.
Main Methods:
- Qualitative and quantitative analysis of 22 upper-level undergraduates in a genomics course.
- Students engaged in case-based inquiry using an interactive heat map visualization.
- Analysis focused on visual analytic behaviors, reasoning, outcomes, and tool-related difficulties.
Main Results:
- Undergraduate engagement with visual analytics tools is feasible.
- Students demonstrated patterns in performance, efficiencies, and task completion.
- Difficulties were identified in applying knowledge and skills, linked to tool design.
Conclusions:
- Undergraduate visual analytics engagement is feasible and can be improved through better tool usability.
- Specific tool usability improvements are identified to enhance student learning.
- Instructional considerations are suggested to further support visual analytics in case-based learning modules.
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