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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.

Conducts a scenario-based usability test with 10 data analysts using visual querying (visually analyzing data with interactive graphics). Details a range of difficulties found in visual selection that, at times, gave rise to inaccurate selections, invalid conclusions, and misguided decisions. Argues that support for visual selection must be built into User Interfaces and Help and describes the forms this assistance should take. (SR)

Explores the practical implications of constructivist theory for documentation that is targeted to complex tasks and experienced users. Examines the conceptual underpinnings of current task-oriented documentation and proposes why it falls short for experienced users and complex tasks. Discusses constructivist views of knowing, learning, and doing and their implications for the design and content of documentation for complex tasks. (SG)

Designs a technical-communication course for software-engineering majors to take concurrently with their capstone project course in software design. Studies effects of writing on students' user-centered beliefs and design practices and on usability of their product. Suggests the synergy of this interdisciplinary approach sensitized students to user-centered design. (PA)

Surveys 25 people who use databases at work to discover the ways in which social and organizational factors affect users' tasks and their acquisition of knowledge and skills. Finds that learning to use databases for complex tasks in work entails more than simply learning concepts and procedures for executing program functions. (PRA)

Identifies how researchers have defined active learning, and synthesizes current findings on the instructional designs that facilitate hands-on problem solving. Proposes three additional areas of inquiry into the instructional needs of active learners. (SR)

Examines in-house documentation situations in which software manual writers and project managers intersect the manual writing project with ongoing organizational dynamics. Analyses two strategies that in-house writers need for project management: conducting contextual audience analyses and acting as liaisons in their workplaces. (KEH)

Abstract Background Understanding the biomedical implications of data from high throughput experiments requires solutions for effective cross-scale and cross-domain data exploration. However, existing solutions do not provide sufficient support for linking molecular level data to neuroanatomical structures, which is critical for understanding high level neurobiological functions. Results Our work integrates molecular level data with high level biological functions and we present results using anatomical structure as a scaffold. Our solution also allows the sharing of intermediate data exploration results with other web applications, greatly increasing the power of cross-domain data exploration and mining. Conclusions The Flex-based PubAnatomy web application we developed enables highly interactive visual exploration of literature and experimental data for understanding the relationships between molecular level changes, pathways, brain circuits and pathophysiological processes. The prototype of PubAnatomy is freely accessible at:[http://brainarray.mbni.med.umich.edu/Brainarray/prototype/PubAnatomy]

In visual querying, users analyze data for their decisions and problems by interacting with graphics that are dynamic and linked. This querying paradigm is new, a dramatic break from the more familiar retrieving of data via search statements and displaying of it in static charts and graphs. For this new visual querying paradigm, analysts conceptually and operationally need to master new approaches. To discover salient relationships, they need to manipulate displays. To drill down for detail or causes, they have to select data of interest directly from a graph. And to draw inferences, they have to consider meanings across several dynamically linked graphics. With the aim of studying users' success in these new approaches, particularly focusing on the approach of directly selecting data from graphs, I conducted a scenario-based usability test with 10 data analysts. They interacted with visualizations to complete a realistic complex analysis--evaluating employee performance. Test findings reveal a range of difficulties in visual selection that, at times, gave rise to inaccurate selections, invalid conclusions, and misguided decisions. To overcome these difficulties, support for visual selection needs to be built into interfaces and help. Results and recommended improvements are presented.