Process * Work * Process *
Process * Work * Process *
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One of our team members, Maddy, brings valuable insights from her experience in cycling and working at a bike shop. She highlighted the various barriers that impede the accessibility of beginner cyclists. Lack of familiarity with the bike servicing and maintenance process can create an intimidating learning curve. In response to this, our goal is to explore how an Augmented Reality (AR) app can effectively engage regular bike riders. The aim is to help them better comprehend their bikes and, simultaneously, teach riding techniques to enhance their overall riding experience ⁕
Team Members ⁕ Roslyn Nip, Nicole How, Maddy North, Saumya W

Tools ⁕ Figma | Aero | PowerPoint

Maddy identified several current barriers to this process, including gatekeeping within the cycling industry, complex codes and nomenclature for bike parts that complicate simple repairs, a deficiency in well-designed resources for clientele, and challenges in keeping professionals and clients updated on current modifications. Additionally, there's a need to organize a comprehensive database of bike parts and tools ⁕
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Via AR App that visually teaches users about their bike and provides recommendations and descriptions on maintenance ⁕

Enhance the overall bike maintenance experience for all types of bikers and use cases, including off-roading, tricks, and transportation. This improvement can extend to modding and customizing bikes for advanced cyclists. Additionally, focus on identifying errors and preventing tool misuse during the fixing processes ⁕

The autoethnography process informed our design considerations for typical bike riding experiences. Utilizing this method, we thoroughly documented and considered both Maddy's anecdotal experiences and the sentiments of casual or beginner cyclists. Our group, consisting of novice and casual cyclists, engaged in this process to gather insights. Notably, our autoethnography research focused on 4 feminine-presenting individuals under 5’5”, revealing discomfort during and after rides. While this demographic is a minority, it offers valuable representation of casual cycling experiences ⁕

In this process, we took our autoethnography and converted this into some personas. As our autoethnography didn’t have as many participants, for future steps we would have liked to have more data ideally to inform our personas ⁕

The next step we took was making use of different diagramming methods to begin assembling ideas to consider how a user will interact with an AR app ⁕

Our group focused on four highlighted flows in our project:

FLOW 1: Maintenance of Tire Treads
FLOW 2: Bike Anatomy Learning Module
FLOW 3: Major Repair + Troubleshoot Flow for saving to fix something later
FLOW 4: Repairing a flat tire after saving Fix Module

Each flow incorporates features such as simple design and personalization, utilizing AR to identify parts in reference to the user's own bike. Users can identify technical errors with the AR tool, enabling them to address issues independently. If the problem exceeds the app's explanation scope, users are directed to a bike servicing shop. For more specialized users, the app facilitates searching for compatible parts and visualizing products in context with their own bike. The app also provides an index of parts, their compatibility, and information on where to purchase them ⁕

Our branding evokes the bold speeds and construction-esque graphics. We aim to communicate a feeling of gender-neutral confidence, while still remaining friendly ⁕
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App Prototype: Figma Link

In grappling with limited resources for extensive research, our team turned to autoethnography, leveraging the representation of diverse users within our group. While acknowledging the ideal scenario of a larger participant pool, this approach allowed us to glean valuable insights. Additionally, our foray into AR prototyping posed challenges as we navigated the unfamiliar terrain of demonstrating the feature's appearance using new software, ultimately opting for Adobe Aero to strike a balance between effectiveness and learning curve ⁕

To enhance accessibility for users with varying skill levels, we focused on solving the challenge of displaying complex information. Strategies included incorporating contrast checkers, designing modules with a balanced mix of essential information and simplicity, and limiting AR use to scanning and static elements. Improvements encompass refining content through extensive user testing, exploring third-party app connections like Strava, and expanding the app's utility for bike service shops. Additionally, we considered features catering to advanced users, envisioning capabilities for visualizing custom bike builds and recording ride data to meet the needs of experienced cyclists ⁕