Week 1 : April 30th – May 6th
As part of my Interaction Design masters at NCAD, we are required to undertake a major project of our own choosing over the summer months. This week involved defining our project space and identifying an actionable project in the form of a project proposal booklet. I’ve decided to focus my project on the area of early stage prototyping for AR, exploring how effective different methods and approaches are while testing new techniques with users and experts.
Approaches to Early Stage Prototyping of Augmented Reality Interfaces for Designing Useful & Enjoyable User Experiences
I wanted to target the barriers to entry of design for AR and focus on aspects of user experience prior to development & implementation, especially for those interested in the area but may not have the necessary coding experience to carry out their ideas. The PDF of my project proposal booklet can be found here:
Project Proposal Booklet PDF
I intend to test, iterate and analyse different forms of early stage prototyping for AR in order to discover what does and doesn’t work, and what needs to be approached differently due to the medium to gather information on positive user experiences. Alongside testing the prototyping methods, I will be developing AR interfaces based on the feedback from the user testing conducted. I believe that the approach to carrying out the user testing will need to be clearly defined and consistent in order to be valid and wothwhile. I will also need to be aware of the most up to date information on AR from professionals in the space, and the literature.
Some AR projects have borrowed on early stage prototyping methods used for other mediums, such as paper prototyping, role playing & model making. From what I have seen in this space so far, I am not entirely convinced by the usefullness and the efficacy of how the methods have been approached. The methods may have simply been used as a “token” part of the process, a byproduct of their success in designing for screens or physical products. I would like to explore if these methods are in fact viable approaches, and not a box ticking exercise for a photo opportunity.
Another major part of early stage prototyping techniques will be reliable analysis of the information into tangible insights. As this project will focus primarily on the approach and process of early stage prototyping, I will have time to spend on understanding how to analyse the outputs from the testing and rapidly implement the feedback into future tests.
I would like to develop an approach for early stage prototyping in AR for designers to bring their concept through user testing, analysis and iteration prior to development, with a focus on user experience.
Project North Star
Project North Star from Leap Motion is definitely a source of inspiration for this project. They’re currently developing an open source hardware and software headset for AR, which they claim to cost less than $100 when manufactured at scale. This will be huge for AR development as people will be able to get their hands on something within a reasonable price range. If it can do half of what they claim, it really has the potential to kick off a new surge of AR development and adoption.
Not only is Project North Star an accessible AR development kit, Leap Motion have shifted their focus to user experience and interactions. They see North Star as the flagship for creating new and enjoyable interactions for AR; my goals are definitely aligned with Leap Motion on this.
“The fundamental limit in technology is not its size or its cost or its speed, but how we interact with it.” – David Hols
Carrying on from Project North Star, I recently received my own Leap Motion controller and have been playing around with it. I hope to implement Leap Motions hand tracking technology into some aspects of my prototyping approaches and user testing. It’s very intuitive to set up and get going with it, and very fun to play around with your digital hands. I’m looking forward to combining it with technology like Raspberry Pi, Arduino and Kinect, all of which I believe could make up viable and accessible modes of user testing for AR.
After more testing with the Leap Motion in Processing, I created a quick and simple drawing program. The leap motion tracks the location of your index fingers and draws a coloured circle at that location. The size of the circle is determined by the z coordinate measured by the leap motion. Pinching your index finger to your thumb allows you to change the drawing colour, and making a fist with both hands clears the screen. It’s quite a fun application and definitely helped to progress my understanding of coding for leap motion.
User acceptance in the usage of AR applications; for mobile and head mounted displays will need to be addressed. An article in the journal of Technological Forecasting & Social Change examined user acceptance in a review of studies using the Technology Acceptance Model (TAM) for four AR applications (markered and markerless).
Rese, A., et al., How augmented reality apps are accepted by consumers: A comparative analysis using scales and
opinions, Technol. Forecast. Soc. Change (2016)
User acceptance systems can be broken into two areas: hedonic and utilitarian. Hedonic features focus on user enjoyment and the pleasure of interacting with the system. Utilitarian features however focuses on functionality and supporting the user in achieving their goals.
“With regard to the hedonic aspects of the respective app most studies included “perceived enjoyment” or “playfulness” as an investigated element. In contrast, focusing on utilitarian aspects of AR apps concentrating on content being augmented with functional information and reflected in constructs such as perceived informativeness (PI) or information quality was quite rare.”
According to the article, studies more frequently have a tendancy to focus more on the hedonic features of AR applications. The TAM model can be broken into different elements when testing features of technology: Perceived enjoyment (PE), Perceived informativeness (PI), Perceived ease of use (PEOU), Perceived usefulness (PU), Attitude toward using (AT) and Behavioral intention to use (BI). For my project, it will be important to determine the important aspects to measure while testing, their influence on each other, and the balance of hedonic & utilitarian style features.
“the impact of PU on AT and BI was highly significant (Hypothesis 5). The impact of the utilitarian (PI) and hedonic (PE) variables on PU was confirmed (Hypothesis 2, 3).”
AR has the potential to be extremely hedonic or utilitarian focused in it’s application. The superimposition of relevant and useful data (Intel Vaunt) could influence working efficiency, while the manipulation of digital forms (Tiltbrush) used only for enjoyment could exist on the same platform. In another study, the helpfulness of user reviews were analysed and AR products with hedonic aspects were ranked more highly than utilitarian products. This brings in the question of what people are looking for in AR, and is this influenced by limited knowledge or understanding about the technology. Are AR applications currently ranked on instant pleasure, or does the nature of AR require enjoyment in use?
Pan, Y., Zhang, J.Q., 2011. Born unequal: a study of the helpfulness of user-generated
product reviews. J. Retail. 87 (4), 598–612.