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Contextual Inquiry

After some deliberation following last class’ project idea brainstorming session, our group selected to prototype the Power of Language Suggestion Tool for the purposes of this class. We decided to call the product MIRANDA in honor of a Professional Communications professor at RIT who stressed the importance of powerful language in the workplace. In this case, MIRANDA stands for Metacognitive Inline Reader Administering Non-submissive Dialogue Automation.

Today’s lecture covered Contextual Inquiry; the act of interviewing and observing your target audience perform the task which your software seeks to improve, or face the problem your software is designed to solve. We were tasked with planning out a rough interview, as well as finding and executing this interview plan with 5 women in computing. In addition, our team decided to give the same interview to a few computing students who do not identify as feminine, to really understand how our problem space uniquely affects female computing students.

[Expand this post to read about our awesome interviews we will be conducting]

For our interview plan, we decided it was best to try to open with some simple friendly banter, then cut right into a scenario-based activity. We considered opening with some contextually relevant questions, but the decided that by suggesting we were looking for patterns in grammatical structure and vocabulary, that it could lead the interviewees to use language they otherwise may not have.

Our first scenario should play out something like this: 

You’re working at main headquarters, but your boss works from a remote office. You feel you deserve a raise, and you happen to know that a male co-worker with identical qualifications and slightly less work throughput makes more than you. A female friend of yours in the office confides in you that she agrees you deserve a raise, but mentions that your mutual boss can be unreasonable at times. Write an email to your boss asking for a raise.

This situation is designed to put the interviewee in a position where they have tools at their disposal that they could use to ask for a raise- the idea that a comparable co-worker earns more with less to show for it. We hypothesize that the female subjects we interview will use less active voice statements, and vocabulary that is less demanding than their male counterparts.

As a secondary scenario, we want to analyze how women speak differently in technical discussions than men might. For this situation, the interviewee will be shown a pull request written by someone with a clearly masculine username, and be asked to leave comments about the code they see. This code will be intentionally low quality, so there should be plenty to write about. We want to see how strongly they express their technical opinions to a male co-worker, on a project they are told they have stake in.

In closing, we will finish the interviews out with questions regarding how the interviewee felt about the scenarios, their feelings about their writing, and any similar situations they’ve experienced in the classroom or on co-op. Questions like, “Have you ever felt anxious to leave technical feedback to a co-worker?”, or “How many times do you re-read through an email before sending it?”.

We hope the information we collect from our peers will help guide us to design a solution experience that helps the user navigate these situations with more ease and less anxiety, that empowers them to succeed and excel in their field.