For user research, we had to devise ways to remotely study patients and medical personnel involved in a patient’s medical journey. Without taking too much time away from each participant, we also were aiming get rich information out of them. We devised short cards, aimed at some overlapping but also different information, for participants.

Research card methods

Medical Timeline Interaction Demo from Sungjoon Steve Won on Vimeo.

We started off with Affinity Diagramming to set our focus.

With this, we decided to set initial focus on personal assistance, bagging, and produce products. With those in mind, each of us went to do field study at differnt places that offer self-checkouts already to validate our focus and look for any other problems. We interviewed and observed shoppers, and some of us also tried the self-checkout service ourselves.

We found problems that relate to different areas such as selecting a lane to use, preparing to scan items, scanning and bagging items, and paying. Based on our findings, we narrowed down our scope to self-checkout systems in grocery stores (Specifically, Giant Eagle).

Modeling a customer’s experience in the current system helped us map out what the problematic areas are.

Current Model at Giant Eagle grocery store

Current model of customer self-checkout process at Giant Eagle

Some of the problems we observed include (more details in the model above):

• Negative expectations about self-checkout service
• People ignore rules regarding full vs. express lanes.
• There is no way convenient to return unwanted items.
• There is limited and uncomfortable space for scanning and bagging.
• Card payment device is disconnected from the main interface.

At this point, we proposed a new model that will change customer’s entire experience from entrance until exit. This model works to accommodate as many of the problems we found during user research and in our modeling of the current process.

Proposed Model

Redesigning the entire shopping experience

We present BLINK, which aims to redefine your shopping experience.

Entrance

Welcome screen & Ring

Easy access

Adding items

Display

Produce weigher & Wireless sync

Paying & Bagging

Exit

Initially, we got together for brainstorming sessions to get a consistent understanding of what primary care system is and map out which areas need to be addressed. It was really interesting for us, because each member had a unique background where the health systems were different. From this phase, we generated our hunt statement, which aims

To structure existing primary care systems in a new way to give patients a more complete health care support system.

Then, we created a territory map which visualizes our understanding of the current practices in primary care system.

Territory Map

We put the patient as our main focus.

Surrounding the patient are other groups of people, such as primary care physicians, specialists, nurses, insurance agents, family, and more. However we put more importance in relationship among the patients, primary care physicians ,and specialists, because of the amount of communication and interaction among them and their importance in building patient's experience with primary care systems.

There are related physical places, such as home, primary doctor

We realized that there are different factors that surround and affect elements throughout the territory map in one way or another. We broke these down into society, culture, diagnosis, technology, management, political, and economic factors. For example, economic factors include financial plan and budget, while culture factors include religion, behavior patterns, ethnicity, and more.

The white dotted lines are used to show the involved process in primary care system. Communication among different groups of people (primary care physicians, specialists, patients, hospitals, etc), scheduling appointments, transfer of medical-related documents, and transportation between physical places are some examples of work involved to make the system run.

This is a complicated mix and layout, and there is discontinuity throughout. We plan to focus on this as the main problem as we continue into the project.

What’s next

Now that we have identified and narrowed down on a problematic area, we would like to validate and also explore this area different methods, such as role-playing, Contextual Inquiry, shadowing, interviews, Think Alouds, and survey.

I’ve started playing with Arduino this semester.

My initial project involved a monkey doll and detecting how close someone is. The main components included LEDs, infrared proximity sensor, protentiometer, and the Arduino board.The biggest problem I had was getting the infrared proximity to get correct readings (which I couldn’t get working in time), and opted out to using a potentiameter as a replacement. Please assume I used a proximity sensor below.

The monkey had a set of LED’s, three rows where each row had different color, in the front.

If someone is very far away, the LEDs would fade in and out as if they were pulsing. Once someone is closer, each row of LEDs would blink alternatively (at a faster rate as someone gets closer). Once someone is very close, all the LEDs would all blink together (at a faster rate as someone gets closer).

Video demo

Blinking Monkey from Sungjoon Steve Won on Vimeo.

Related Bugs/Patches: 

• Bug 374524 
• Bug 383803 

–End of Edit–

Tagging Extension is available to try out now. Download here.

It uses textbox<->button interaction I’ve been working on and also some of the Places API.

A couple of things to get this set up and working.

* Extension was tested on the Alpha 5 release.

* Setting up the extension

1. Install the xpi file.

2. (After restarting) Right click on toolbar and then “customize”.

3. Find the tagging icon (titled as “Tagging UI Prototype 1″) and drag it to the toolbar.

If you get to try this out, any feedback would be greatly appreciated.

Thanks and enjoy!

A couple of things…
1. Now you can also press “tab” to start a new input textbox.

2. You can traverse through different tags left and right using “ctrl + left” and “ctrl + right”.

3. The width of the editor field is set based on the initial browser window size.

4. Whenever you visit a previously annotated tag and press a comma or a tab, it will be inserted at the very end of the editor field instead of its previous spot.

5. All blank characters in the beginning of a text input will be ignored… so input like ” ,” shouldn’t create a tag button with label ” ” anymore.

Here’s the link to the updated prototype.

If you get a chance to play around with it, any feedback would be greatly appreciated. Thanks!

Hoping to have some people try it out, I created a xul file for the Taggin interaction. A major part of the interaction is each keyword turning into a button after being tagged and also being able to edit previously tagged keywords by clicking on the buttons. To finish the input, the user can either type in a comma or unfocus from the input text by clicking on other parts of the box containing all tags.

Here’s the link to the xul file if anyone wants to try it out. Get it!

Also, any feedback would be greatly appreciated!

I am also currently working on a fully functional extension (also based on Alex Faaborg’s prototype [4]) that will utilize the new Places backend.