When high school students begin the college search, they are repeatedly bombarded with the same information about class size, department strength, learning goals, etc. from every university they encounter.  Each institution, in the interest of attracting students to apply, wants to put its best foot forward.  Understanding this motive behind the information Bucknell (as well as other colleges) makes publicly available on its website invites further scrutiny: does the information change once students commit to Bucknell?

The Bucknell mission statement, learning goals, college core curriculum goals, and department summaries are available to anyone on the university website.  All of this information essentially communicates the same thing: enabled by a Bucknell education, students grow into more mindful, critically thinking, capable, creative, and culturally aware contributing members of the global community.  Does the information only available to people with a Bucknell login, such as course descriptions and the specific classes that fill particular CCC requirements, is the carry the same content and cadence?  Is the public face of Bucknell, constructed through its publicly accessible website information, representative of a Bucknell student’s educational reality?

My personal stake in this research has to do with the difficulty I had selecting a major.  Every adviser tells incoming freshmen to take their time exploring, start by filling general education requirements before settling into a major.  I was told I had plenty of time to decide, but when the time came to declare a major I didn’t feel as though twelve credits-worth of experience was enough to go off of.  Coming from a fairly generic high school, I had no idea what it would mean to be an anthropologist, economist, creative writer, or comparative humanist because I had no experience and knew of no one who had experience in these fields.  If the publicly accessible department descriptions are not truly representative of the field, it puts more pressure on course selection in order for students to gain insight into a branch of knowledge.  But how can students be expected to choose courses they will enjoy and gain meaningful experiences from if the selection process is a gamble?

I began with a specific interest in the materials studied in the three comparative humanities core courses.  Visualizing genre and author/artist gender and ethnicity drew attention to the gaps in the courses’ coverage; specifically a lack of women and non-western authors.  (Visualizations below created in Palladio: on the left a graph view dividing the course materials based on gender, on the right a map view plotting the materials’ location of publication.)

From there, I became interested in broadening the scope of the visualization to the university as a whole.  Since I do not have access to all the syllabi in every department, I had to shift the focus of the visualization to a different, but related, set of data: course descriptions and requirements as seen in the online course catalog.  This data is especially intriguing because, although it is easily accessible for all Bucknell students making choices about which classes to take, its presentation (a glorified spreadsheet) is indigestible and makes comparison difficult.  My goal was to find a way to view all, or as much as possible, of the data at once in order to access a macro-perspective.  Initially I planned to use Stefanie Posavec’s “Writing Without Words” (below left) as a guide for the tree-like structure I wanted to create.  As “Writing Without Words” reveals Kerouac’s structural style in On The Road, I thought a similar design could reveal the structure of Bucknell’s course offerings.  After some experimentation, I realized my data appeared confusing and sloppy in such a format.  Instead, I borrowed Borris Muller’s circular structure of “Poetry on the Road” (below right) to give shape to my data.

The “Poetry on the Road” model enabled me to more closely follow Tufte’s principles of display architecture, which include: “(1) documenting the sources and characteristics of the data,” which the visualization accomplishes through its shape, designed to reflect the relationships between departments via CCC requirements; “(2) insistently enforcing appropriate comparisons,” made possible through the various options for node sizing; “(3) demonstrating mechanisms of cause and effect,” by the simple organization of data into the democratic, circular structure in which the viewer’s eye is not drawn to a particular area for any reason other than the concentration of edges; “(4) expressing those mechanisms quantitatively,” as I did by sizing and connection each node based on quantitative data from the course catalog; “(5) recognizing the inherently multivariate nature of analytic problems,” shown through the combination of variables such as node color, size, and location, and different CCC requirements; “and (6) inspecting and evaluating alternative explanations,” as we explore in Nadeem’s interactive network visualization for each department (Tufte 53).

Inspired by “Poetry on the Road,” I organized all of Bucknell’s academic departments into rings based on the size of each College/School (above).  The outer two rings, with nodes colored purple, represents the College of Arts and Sciences.  Since the College is so big, I split it further into an Arts and Humanities ring and a Science (hard and social) ring in order to make the visualization easier on the eyes.  The center ring, with red nodes, represents the College of Engineering.  The inner ring, with blue/green nodes, represents the School of Management.  In this particular visualization I chose to size nodes based on the number of unique courses offered in each department for the Fall 2015 semester.  For example, the music department has the highest number of unique courses (73) so it is represented by the largest node, and astronomy is one of the departments tied for the lowest number of unique courses (1) so it is represented by the smallest node.  I initially intended to make node size a variable for comparison by creating alternative visualizations with nodes sized based on number of total courses offered or the number of possible ways to fill CCC requirements in a particular department, but altering node size did not fit seamlessly into the narrative of the project as a whole.

Since my intention was to create a means to view as much of the course catalog information at once as possible, I first tried to map the edges for all the CCC requirements at once (above left).  Although it made for a decent website header image, the colorful quagmire is too cluttered to be analytically useful.  Even including as few as two CCC requirements on the same image does more harm in the clarity department than it does good for comparison purposes (above right, Quantitative Reasoning and Diversity in the US requirements pictured).

Although visualizing one CCC requirement at a time on top of the department nodes is simple enough to convey the data clearly, I decided to simplify even further by removing the nodes (Arts and Humanities requirement pictured above).  It became necessary to include a template of the nodes without any CCC requirements under the narrative tab in order for the visualization to make sense; but the visualization is still ledgible because the division of the different rings is intuitive enough to grasp without looking directly at the location of the nodes.  And the image is more visually impactful with just the edges.

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When it came time to combine the static and interactive aspects into a single visualization with a reasonably linear narrative, we decided to use the macro>relationship>micro view structure.  Starting with a macro view, a visualization will “facilitate the understanding of the network’s topology, the structure of the group as a whole, but not necessarily of its constituent parts” through a holistic view of the visualization, enabling users to see its overall pattern” (Lima 91).  Our macro view is located in the narrative (above left).  It offers both an overview of Bucknell’s academic structure through the listing of learning goals and college core curriculum design taken directly from Bucknell’s website, and a color-coded comparison of Bucknell’s learning goals to its CCC design.  This choice contextualizes the visualization for viewers who may not be familiar with Bucknell’s academic mission.  From the narrative tab, the viewer is prompted to select the college core curriculum tab to access the relationship view (above center), which “is concerned with an effective analysis of the types of relationships among the mapped entities” (Lima 92).  The edges of our static relationship view offer a perspective on the relationships between different departments through CCC requirements.  Finally, the user can click on a node to explore a singular department in more depth in the micro view (above right).  Although the micro view offers the most narrow perspective, it offers comprehensive, explicit, and “detailed information, facts, and characteristics on a single-node entity,” which helps to “clarify the reasons behind the overall connectivity pattern” (Lima 92).

http://curriculum.blogs.bucknell.edu/

Curriculum visualization (Nadeem Nasimi’s) http://nadeem.io/270/