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Analyzing Results of Usability Testing

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Analyzing the results of Usability Testing
By Ben Homrig and Justin Stephenson

For our presentation, we were assigned with analyzing the results of usability testing. Usability is defined as the process or technique used to interactively test and assess the user-interface of a product, method or set of instructions. Presenting and analyzing data are very important steps in process. The improvements developers and technical writers make with their data define exactly how the end product will be when completed. Understanding the differences in the types of data tabulated is vital to understanding how results are analyzed.
In usability testing, there are two types of data – qualitative and quantitative. Quantitative research must measure the products in an objective, quantitative and statistically valid way. This type of data recorded must be hard evidence, free of context and exact. Qualitative data is collecting, analyzing and interpreting data by observing how people respond through their opinions and actions. Data is generally collected through gathering information from focus groups and in-depth interviews with users. Quantitative research is defined as objective, while qualitative is subjective.
The differences between qualitative and quantitative data are very important in improving a product, method or set of instructions. In our case, we established our primary example as that of a tester documenting the experience a user has while trying out a new iPhone game application for the first time. With the purpose of reporting and analyzing the data, having two different types of data are at the center of improving the user experience.
The Quantitative data from a user’s experience with the app might be how long it took them to complete the game, where exactly a glitch occurred in programming, if there was a punctuation error on the third level’s instructions, or how long it took the app to open when the first clicked it. Qualitative data from a user’s experience with the app might be if the lighting is too dark for them to follow the set of instructions, if the sound is too soft for them to hear a narrator’s instructions, if the font is too close together to read, or whether or not the user thinks the game is fun, confusing or difficult.
Once a developer or technical writer has all the information available, then they are able to properly understand the optimal user experience. A tester will see corrections must be made and revert to the user-testing phase of the project. After doing qualitative and quantitative research, the process repeats itself. The cycle of testing, analyzing and then making changes is very time consuming, but ultimately leaves the tester with an end product.
Upon achieving that end product, the question is asked what to do with the results after the data has already been reapplied to enhancing the user experience. Simply put, a tester can sell, store, or report the data. If we repeat the example of the iPhone game application, a person or company might be able to sell data to a competitor, store their results for their own future use, or to form a report for a higher-up at the company. Most of the analyzing and implementation of data is completed in the testing phase. A product, method or set of instructions is never considered complete or set to go to market unless it is perfect. Once all data is compiled an analyzed, final production begins on any manuals outlining a set of instructions and the process is complete although problems may arise in the future on an individual basis. Most companies will also repeat the steps with several test to get the most data and to make sure the beta is perfect before the final is released. Numerous results of usability tests are all everywhere you look in manuals, methods and sets of instructions. If you buy a new car, countless hours are spent on ensuring the instructions in an owner’s manual are completely perfect. In a building on campus, a document on the wall showcases the quickest route to exit the building in the event of a fire. Each of these sets of instructions likely has a significant amount of usability analysis involved before publishing. Properly analyzing the data and ensuring you’ve done your due diligence is vital to a correct document.

Bibliography

Fagan, J., Mandernach, M., Nelson, C., Paulo, J., & Saunders, G. (2012). Usability Test Results for a Discovery Tool in an Academic Library . Information Technology and Libraries, March, 83-112. Retrieved March 24, 2014, from http://ejournals.bc.edu/ojs/index.php/ital/article/viewFile/1855/1745.

Johnson, M. (2013). Usability Test Results for Encore in an Academic Library. Information Technology and Libraries, September, 60-85. Retrieved March 24, 2014, from http://ejournals.bc.edu/ojs/index.php/ital/article/viewFile/4635/pdf

LIBRARYFIND: SYSTEM DESIGN AND USABILITY TESTING OF ACADEMIC METASEARCH SYSTEM . Journal of the American Society for Information Science and Technology, N/A, 56-86. Retrieved March 24, 2014, from http://ir.library.oregonstate.edu/xmlui/bitstream/handle/1957/21871/CHapter%204.pdf?sequence=6
Reporting Usability Test Results. (n.d.). Home. Retrieved March 24, 2014, from http://www.usability.gov/how-to-and-tools/methods/reporting-usability-test-results.html
Schade, A. (n.d.). Nielsen Norman Group. Making Usability Findings Actionable. Retrieved March 24, 2014, from http://www.nngroup.com/articles/actionable-usability-findings/

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