Our design - Prototype to Final

Our design started to take its final form after the Expert and Heuristics evaluations. We now started to sketch on our prototype as seen in the blog post:

http://f5slattarna.blogspot.se/2016/06/look-how-far-weve-come.html

We used Invision as our tool to design the prototype.

Although we didn't set out to use an evaluation framework like DECIDE, and despite the linear progression of the course's exercises, the nature of the design process forced us to go back and iteratively re-evaluate our work and assumptions — especially the Exploration of questions and Determination of goals. Coming at these iterations with different assumptions and from new angles enabled us to triangulate our users and their needs.

Since the course didn't go beyond a basic (though high-fidelity, and without much horizontal or vertical compromise) digital prototype, it didn't have enough interactivity to meaningfully apply any GOMS model or investigate Fitt's law. We also didn't do any dedicated gathering of statistics from our users or evaluators in form of questionnaires or such. Which in turn means that nearly all of the data that informed our iterations was qualitative.

Furthermore, although we recognize the usefulness of user-centered design and making the users active stakeholders — especially in the face of having our assumptions changed/expectations managed by both the interviews and the think-alouds; what actually transpired was mostly what we'll humbly refer to as genious design. But an argument could be made that we were ourselves prospective users of the final product. This is especially true in the case of group members who had not been present during the creation of the app, who gave the group feedback from walkthroughs which resulted in several new functionalities being added.

We used pen and paper for our low-fidelity sketches, and used InVision as our prototyping tool for the final prototype. The GUI for the app reuses established mobile interface norms. 

An example of the iteration process for specific icons is seen in this blog post:

http://f5slattarna.blogspot.se/2016/05/creating-our-train-icon.html

Our train icon combines similarity of the train shape with an analogy between available seating and colour (green is free, red is occupied). We also use the arbitrary but commonly established symbolism of a pointing arrow for "exit".

http://f5slattarna.blogspot.com/2016/06/proposed-changes-to-physical-metro.html

Our updates to the stations are static, but of course the users can interact with them — by choosing to read/look at them and choosing how much of their information they take in.

Here is a short summery of what the final design does:

• Add more points of interest to the exit signs.
• Make sure that all exits are color-coded.
• Use color coding to show the different exits on maps on the stations.
• Make the color coding clearly visible to the commuters, use lines/dots/arrows to guide them to their desired color.
• The lines/arrows should guide users to their destination, improving the general people flow and reducing crowding.
• Integrate the color coding system in the SL-App, it should tell users what exit color they should take.
• On bigger and more complicated stations, add extra detail to the color-coding system, (inspired from Hong kong), using letters or letter-digit-combinations (A1, A2, etc). Same colors should be together however, to make it easier to find for the users.
• Also let the SL-App tell users where they should sit on the train. It should inform
• Where to sit that is closest to your exit
• Where to sit if you want to avoid crowds.

Look how far we've come...

Design process starting from field studies.

To sketches of app and of adjustments to physical metro stations.

To a finished prototype! Click it!

Seriously, click it and check out the interactive prototype!

Summary of Think-Alouds

Everyone used a similar usability test on the prototype in form of answering:

Find the way from T-Centralen to Södermalmstorg using the prototype.

Some main comments from the think- alouds were:

-          App is clear. But there might me some frustrating excessive confirmation.

-          The crowding information should be on the platforms as well.

-          The red and green text should only be green at the word “red” and “green”.

Some of the most emotional reactions from the users of the prototype was that it was working or dong things for you that the “real” app does not. Maybe the prototype was too simple in to get focus on the main features.

The tests was done in a fast mention and without any longer breaks which might indicate that the app doesn't require the highest level of counciouss decisionmaking that interferes with spoken language that Gulan mentioned on his lectures.

The users understood quickly that the trains indicated crowding information but not in which way. The question mark, showing further information of the train icon, was in some case spotted and used but in others not used.  In the case where it was used the reaction was that it was understandable.

For our final design we should probably change the information in the app based on the feed- back and also change the symbols used for lines and exits (discussed in the “övning 5”).

Think- Aloud - Niklas Lindqvist

The assignment given was to find, with help from the prototype, the fastest way from T-centralen to Södermalmstorg in Stockholm. The user was Anna, a 20 year old student at KTH.

Part 1 - The App

Translated notes:

- Okay, ah, I think i should use this app. I recognize it since i have a similar one on my phone.

(clicks the icon)

-wow! it works. Ill try to write the start point here.

 (clicks upper bar)

-Oh, alright it did it for me. Nice.

(pushes the search button)

-Oh, Okay. I guess I'm done now.

- Oh nice, there is some crowding information I guess (points at the train in the application), and also witch exit i should use.

Questions:

Q1: What is new in this prototype compared to yours?

- It shows crowding information and exit.

Me: If you press the "?" what happens.

-Oh, okay, it shows me information about the picture of the train, I understand.

Q2: What do you think about the changes?

I like them, i would like to have this in my existing app.

Part 2 - The images

Q3: what do you see in these images?

- I can see the same arrows as the once used in the app. probably pointing towards the exit.. And also that the dots represents the exits at the information sign.

- Oh, i see that the color also show on the map, that is cool. Does this map exist at the stations?

Me/Q4: no, its made in Photoshop. Do you think there are any improvements to be done?

- I would like to see the crowding information on the platform as well, since i do not check my phone every time i travel. Also the red text might be reduced to only the word red. Its a bit to much color i think.  

Seminar 2 - Summary

Recollection of discussed topics during seminar 2

• We have learned the importance of evaluating, but sometimes it is hard to user-test something beforehand (scale, patents, secrecy). We also discussed ways to circumvent this.
• For testing our own design, we could use testing in the wild: adding markers and prototypes to the SL stations, and have people try to accomplish tasks (getting from A to B while using our prototype app). This would be testing in a natural setting involving users.
• We could use people from Copenhagen (which has a similar system in place) to heursitically evaluate our prototype and tell us what they feel are the good parts and bad parts of our system when it is adjusted to Stockholm.
• We could also take Stockholmers to Copenhagen and let them see what they like and don’t like about that system, and see how they compare it to stockholm.
• This would be be a kind of triangulation: we see the problem both from the perspective of users who have used it for a long time, and users who are using it for a first time. Their combined heuristics would give us a better view of the actual good and bad sides of our idea.
• Also, Opportunistic Evaluation is a thing that we can actually, practically do (not assuming infinite resources etc). We could even ask the group we’re presenting to what they think, since they are almost surely users of the public transportation. We can also interview people in the subway and present our design to the, ask what they think.
• We discuss how we should evaluate the different parts of our designs, since it is quite broad. It might be good to evaluate each part on its own, ut we also need to evaluate the whole together since we need to know how well the prats cooperate.

Individual notes, Seminar 2 - Niklas Lindqvist

Chapter 13 – Introducing Evaluation

This chapter presents an introduction on how to evaluate a design. It focuses on both the usability of the design and the user’s experience/satisfaction.

The problem with a design often occur when the producers find the product useful but don’t understand that other users don’t understand how to use it. This I find true in numerous of cases, for example webpages where it’s almost impossible to find what you are looking for. Evaluation of a product enables them to check that their design fit others as well, and should probably be used more often.

There are 3 main types of evaluation:

• Controlled settings involving users (labs, everything is measured)
• Natural setting involving users (field work)
• Any setting not involving users (models and analytics)

Doing a combination of the evaluations is something I would like to aim for in our project following something similarly to:

Chapter 14 - Evaluation studies: From controlled to natural settings

Chapter 14 describes how to evaluate in different types of environments. For example controlled lbs and natural settings. Usability testing is the focus of the chapter.

An interesting concept is the in the wild studies where the researchers are far away and monitor the user with different methods let the users act more “natural”. This is a study that probably have become much easier to implement with new technology and might be improved even further in the future.

Chapter 15 - Evaluation: Inspections, Analytics, and Models

Inspection evaluation methods are in focus of this chapter but I find the Predictive model to be the most interesting. In Fitts' Law where predicting the time it takes to complete a small task with a pointing device such as the mouse on a computer can be used to estimate the total time of a complex task in the same program. This could be develop further using time it takes to press certain keys on a keyboard or other bottoms on a special dashboard when the final design in to expensive to produce iterate to its final stat.

Question for seminar:

What sort of evaluation will be able for us to do on our design? 

Third Design Concept

Third Design Concept

In the third design concept we focus on a new pain point: Crowding. The design is based around two simple ideas, the first being a new typ of method for entering the train, and the second one being a clear information board regarding the crowding information on incoming trains. 

The new doors are integrated in a glass wall along the platform making sure that you can not fall down on the railway. This would hopefully create new space for the passengers waiting for the train since you now can stand closer to the edge of the platform without being afraid of falling down on the rail. The platforms is around 150-200 meter and today around half a meter to the edge is not in use. This means that there is 75-100 m^2 of space wasted on the platform today but with the new doors this might be used more efficiently.

Guiding arrows on the ground to help people locate their wanted exit and marked areas on the ground close to the entrance to make sure that passengers entering the train are not in the way when people are exiting the train.

The goal of the new board is to give travelers on the station information on the upcoming trains crowding level to help the travelers position them self depending on their preference. If a passenger wants a free seat they should know where to be standing to increase their chances of getting it.

State of the art analaysis - Summary

Doing our state of the art analysis’ we had a broad perspective to try gather as much diverse and useful insights posible to what might be useful for our own project. This made ofcource that common ground for all of them was hard to find but a few topics that was brought up in most was regarding information.

            What information are available for the user?

            Is the information easy accessible?

            Is it well presented?

            Is it useful?

A repeated opinion during the interviews was the frustration when forced to make a choice without any information i.e. when there’s major delays, should one wait for the train or try an alternate itiniary, if so which one? Two of the state of art analyses regarded interaction design based on real-time information and both have shown good results in user satisfaction. The information is often times already acessable for the designers such as precise locations of transport because necessary technology is already in place. The issue lies to transform the data to a user oriented purpose. The most critical information for users must be accurate and easy aviable.

It might also be fair to compare the SL app to more generalized travel applications such as Google maps. What SL lacks is the integration of other means of travel such as riding a bike to the train and when leving the train show a map to the destination wished for. To make the app useful doing things that naturally combines with travel might increase satisfaction with the app.

State of the art analysis – Niklas Lindqvist

State of the art analysis – Niklas Lindqvist

In 2015 a student at KTH, named Yizhou Zhang, did his Master of Science thesis in the field of “Real time crowding information” (RTCI). The concept was to help passengers plan their travel and allow operators to utilize there limited space in a more efficient manner. Four systems was used: projection system, communication system, speaker system and recording system.

The English version of the speaker system was in five short messages as followed:

“1). Welcome to Tekniska Högskolan, here is real-time crowding information for the next metro.

2). The first unit train is almost full, it is overcrowded &The first unit train is half full with some standing areas &The first unit train is less crowded, it might have seats left.

3). The second unit train is almost full, it is overcrowded &The secondunit train is half full with some standing areas & The Second unit trainis less crowded, it might have seats left.

4). The last unit trainis almost full, it is overcrowded &The last unit train is half full with some standing areas &The last unit trainis less crowded, it might have seats left

5). We wish you a pleasant journey in Stockholm.”

The projection system had a display next to the already existing information provider at the subway station.

All of the systems was tested at the subway station at KTH with good results. Three types of data was analysed: “passenger load data analysis, video record analysis and interview result analysis”.

Link to the report:

http://www.diva-portal.se/smash/get/diva2:857965/FULLTEXT01.pdf

This report shows that with the right information given in a clear way passengers feel more satisfied with their travelling as well as utilizing the space in a better way. About 90% of the passengers felt more satisfied with the RTCI system and 43% of the interviewees thought that the information was useful for them. The video analysis showed that 25 % of the passengers changed there position on the platform thanks to the information provided. Also 8 % more travelers chose the last cart of the subway and a 4% decrees in passengers where showed in the first and middle cart. 

This study brings great ideas that we might want to use in our own project!

Seminar 1 - Individual notes Niklas Lindqvist

This is a short summary of the chapters regarding data gathering, data analysis and establishing requirements

The first chapter is about Data gathering, where different techniques is explained and discussed. The main gathering techniques for interaction design is interviews, questionnaires and observations.  One of the most interesting parts from the chapter is the five issues that are broth up. These five issues should be taken in account for a data gathering to be successful. In the sub chapter about the interviews we learn the importance of how to construct an interview and how it might affect the result. To choose a Focal group that you want to make a product for and not choose a Focal group that likes your product is clearly shove in this chapter.

In the following chapter the difference between quantitative and qualitative data and analysis. Quantitative data could be summarized to a data that can easily be described in numbers, where qualitative data is data that include descriptions, quotes from interviews, images and more. Also that one data gathering techniques can result in both types of data. This got me thinking, should we maybe expand our data gathering method with questionnaires and more observations?

How to analyse the gathered data is described in different methods, where I find the sub chapter about analyses of qualitative data and the three methods: Grounded theory, Distributed cognition and Activity theory the most interesting due to my personal gathered data being of a qualitative typ.

In the last chapter, establishment of requirements, we learn that it is important to set up requirements for the project such as required gathering, required analysis and in our case required presentation in the form of who our presentation needs to be clear, and just to our ides.