Post 1 – Mapping and Interview

I started my project by creating a site map of  the Banner website using a free online service called GlooMaps. This gave me a better sense of the organization and content of each page. I listed information about each page along with a description of the services it provides on a Google Docs spreadsheet. This was made more difficult by the fact that many pages on Banner are accessible from multiple different points in the hierarchy and there is a high degree of redundancy in the services provided. I found many pages which offer single services for related tasks that could easily be condensed into one page. One particular example of this the Student Information tab where there are separate pages for changing personal information, changing your ethnicity, and viewing your ethnicity. There are also a lot of pages which redirect to external websites but require multiple levels of navigation to access. I would hypothesis that the overlap in page function, lack of discrete pathways for navigation, obscuring of external links, over segregation of tasks, and vague category labels account for almost all the problems users encounter when trying to navigate Banner.

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Update 3 and Summary – Optimization of Tribe Pathways

This is the final update and summary of the project thus far. I am happy to say data transcription and mapping are finally finished.  Below is the simplified map I created based off of the data I collected on campus. Compared to the official campus map available on the William and Mary website, the new set of data includes multiple new paths, does not show buildings or pathways which no longer exist, and contains data on the features of each pathway in the code. This new map is not intended to be used to navigate but offers the opportunity to display the data I collected.

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Update 2 – Optimization of Tribe Pathways

Since the last update, I have gathered all data needed to create a map of campus. Working with the timeline I set up at the beginning of the project, it would not be feasible to map the entirety of campus. Instead, I spent two days on campus walking paths and recording data for a smaller section of the map. I made sure to include all different kinds of path features in the area I selected and that the area was used enough so that the program could still be useful. Adding the rest of campus would not require changing anything or adding new features, only inputting more data. This choice was based off of time constraints and not technical difficulty.

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Update 1 – Optimization of Tribe Pathways

At this point in time, I have finished coding the core structure of the algorithm in python. Given a point on a map, the program will output the shortest distance from the start point to every other point on the map and record the path it takes to get there. For the next step in the project, I hope to organize the single script into a class with multiple functions contained within it. I have tested the algorithm enough to be certain that it functions correctly, but there may be some bugs in the programming I have not yet encountered. There is also a fair bit of optimization that could go into the program and there needs to be an easier way to input map data. That being said, with the small sample graphs I have been using, the results are almost instantaneous.

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