Wanderlust. Jim Inoue - Documentation David Opincarne - Design Josiah Cheslik - Development Vince Blas - Team Manager Carolyn Scoville - User Testing

Transcription

1 Jim Inoue - Documentation David Opincarne - Design Josiah Cheslik - Development Vince Blas - Team Manager Carolyn Scoville - User Testing Wanderlust URL: cs.washington.edu/education/courses/cse440/12au/projects/roses/taskanalysisessay.pdf

2 Problem Solution Overview Problem Statement: There are a plethora of current methods to aid the process of researching a point of interest (POI) or event, but there is no easy way to find out about local points of interest or events that are currently going on. Some of the tools to research points of interest include Yelp.com, TripAdvisor.com, and guidebooks. In addition to using online tools and guidebooks, most people talk to their friends or use social media to discover points of interest. The issues arise when an individual wants to lookup a local event or point of interest in real-time. Solution: Our design incorporates crowdsourcing and the posting of photos and descriptions of points of interest in an area to our application to help users discover new points of interest, both at home and abroad. In this way, our app can be used to check out points of interest around the user when they are bored and have some time to kill, as well as when planning a trip. Standard Task Analysis Questions 1. Who is going to use the system? Our results from our contextual inquiry suggest that there are two main users. First, we have the typical tourist that is looking for something to do in a location in which he or she is not familiar. Second, we have locals that are looking for something to do in their home city. While these locals may be familiar with the area, there are several events or points of interests that they have not yet explored. 2. What tasks do they now perform? From our contextual inquiry, most tourists will research a given point of interest online as a starting point. From there, they will gather opinions and advice from friends and family. The next step is to create an itinerary or simply a list of the events or points of interest they want to experience while in this new location. Finally, some of these users will write about their trip in a blog or on a review site. For locals, they mostly ask friends and family about new locations or events. There is some searching online but asking friends and family (especially since they are in the area), is the most common method of inquiring about new points of interest. 3. What tasks are desired? From one of our contextual inquiries, we found that users desire looking up events in real-time that are nearby. While online tools will help users find events what happened in the past, they struggle to inform a user about current events or points of interest. 4. How are the tasks learned? Most users learn how to perform these tasks by engaging in the activity on a regular basis. From one of our interviews, the individual would use the Washington Trails Association website in addition to asking other hikers which hikes to explore. She went through this process every time she looked for a new hike; hence, she learned through her routine.

3 In addition to learning through experience, most users have an intuition regarding how to search for information. Users are accustomed to researching unknown phenomena via the internet -- looking up new points of interest uses the same process. 5. Where are the tasks performed? Based on our contextual inquiries, the task of looking up new points of interest can be performed anywhere there is access to the internet. Most users would research points of interests at home or the library, but even when users are on the go, they will share information about a place they are currently exploring via social media or look up new points of interest on their mobile device using yelp. 6. What s the relationship between customer & data? One of the major obstacles in finding interesting locations is the overwhelming amount of data available. Most methods of research (guide books, internet, etc) do not permit granularity below the level of towns or large neighborhoods. Conversely, consulting one s social network can yield more localized or personal results, but is generally slower, more labor intensive, and overall far less data is available. Our CIs indicated that people native to the area were most often the best source of information, while seeking out static data sources (maps/signs/etc) was often unreliable. 7. What other tools does the customer have? A customer s means of transportation is one of their most important tools. Whether they are on a bicycle, riding the bus, or in a car determines what locations they can easily access. Credit cards - and money in general - also determine what activities a customer can engage in, as the customer can be required to pay to enjoy or participate in certain venues. Finally, maps can be an important tool in unfamiliar territory where local assistance is scarce; they allow the user to navigate an area without outside assistance. 8. How do users communicate with each other? Most location- and exploration- specific communication exists on travel websites like TripAdvisor or Yelp. Our CI s revealed that many individuals in high-traffic areas act as information aggregators, absorbing and dispensing information to interested parties, thereby facilitating communication between separate groups. Social media (i.e. Facebook) is the other major avenue of communication, where users share and request relevant information with their social network. 9. How often are the tasks performed? The tasks most often occur in focused bursts, reflecting the user dedicating a specific span of time to exploration or research. Outside of that they are sporadic, with intermittent tasks arising when users are bored or otherwise looking for a short-term diversion. Our CIs also indicate that tasks are performed continuously during exploration as the user updates their information and their goals. 10. What are the time constraints on the tasks? Several situations with time constraints exist. One such example is a fork in the road scenario, where a user determines their route depending on what attractions are available on each; their transportation may limit the time they have to decide, i.e. getting off at the next stop, or taking a turn at the intersection. On a larger scale, time constraints often exist around the time of day (venues closing), or even the duration of the trip, which can be anywhere from a few hours to several days.

4 11. What happens when things go wrong? One major problem is a lack of nearby Points of Interest. Not much can be done about this aside from making the whole world more interesting. More relevant is the issue of accurate directions and getting lost. On several occasions during our CIs, the subjects became disoriented or had to ask for directions multiple times from different people because there were no clear directions available. Three Tasks Simple Task: Looking up for a point of interest nearby (low importance, high frequency) Our CI participants were able to investigate a new point of interest by using various tools such as internet, newspaper, and local people. Furthermore, we figured out that people usually look for a new local point of interest, rather than a distant one, because visiting a new local point of interest is simpler, easier, and it saves time. To streamline the whole task of searching for new points of interest even further, the customer needs to be able to search for a new local point of interest in virtually no time. Our task analysis likewise confirms that this is just as important for our customers who want a head start on their adventurous day with new undiscovered points of interest. Moderate Task: Creating a point of interest (high importance, medium frequency) Following the feedback we received concerning our moderate task analysis and additional analysis of or complex task, we came to realize that usage patterns would vary, depending upon user intent. With this in mind, we reconsidered how tolerant mid-level users would be towards complexity. We identified Creating a point of interest as a task that a mid-level user would likely consider important to the app s functionality and one they would access with a moderate to high degree of frequency. We have made a distinction between creating a point of interest, which a user might wish to save for future reference, and more complex tasks related to sharing and promoting POIs. Our revised moderate task asks the question: how can users generate information about points of interest and events to be saved for additional action? Complex Task: Sharing an event with other app users in real time (high importance, medium frequency) Previously, our moderate task was finding points of interest through user filter options. After further discussion and clarification of our problem statement, we realized that sharing events in real time was one of the main points of our problem statement and a factor that really sets our app apart from the competition. Currently, a person can rely on guide books, tourism websites, and word of mouth to hear about events, but none of those options are in real time unless that person is following someone on a social media site who happens to be at the event and writes about it, or gets a text/call/ from someone at the event. In other words, a person is limited to finding out about events through friend circles. We want our app to let everyone in the area know about an event, rather than just certain people who tell their friends. We realized that our users could benefit from sharing an event (such as an outdoor concert) in real time because it would let users find out about points of interest and events that are only shown for a limited amount of time and therefore open up their avenue of exploration if they happen to be in the area and have free time.

5 Sketches Fig 1 (Above): View of sidewalk and street through AR glasses Fig 2 (Left): Overlaying Event Horizons based on required arrival time at destination and user preference, suggesting nearby POIs

6 Fig 3 (Above): Different methods for finding and suggesting POIs Fig 4 (Above): Real-time notifications from other users of current & nearby events Fig 5 (Left): Thumbnail search window with adjustable distance slider and tag search

7 Possible discovery modes