Driving Engagement in Interactive Experiences
by Zafer Bilda, PhD
How do people experience interactive installations, and what can designers learn from this?
It’s been ten years since I completed research around this question. Now I feel it is time to talk about it again. Why? Because we are already designing for new interface paradigms (sound, gesture, conversation) and interactions beyond the screen. Experience designers will be hired to design in mixed realities with multiple interfaces, in rooms, buildings or outdoors. Our aspirations may also shift, from today’s service experiences helping users complete a list of tasks to creating experiences that facilitate emotional break-throughs, mindfulness and creativity.
In my research, I investigated how people experienced interactive in an experimental space called Beta Space in Power House Museum, Sydney, Australia. The room set up had a large screen on one side, surrounded with speakers, sensor floor pads and cameras.
In a typical scenario, the visitors often walked with curiosity into the room to see the installation. At first, they need to be actively engaged with the work and sustain this state. One of the challenges was to identify and measure the engagement using an uncontrolled research set up in a public space — where families, kids, group of teenagers randomly walk into the installation space. Within all the diversity of the data, I was curious about finding a consistent and descriptive model to explain the interactive behaviour in different contexts, relationships and timelines.
The outcome of my research was a model to describe engagement with interactive installations — representing the intentions, expectations and movements of participants who walk into the exhibition space, interact with the work, stay engaged throughout the different experience phases. The model is based on long-term analysis of direct and lateral audience observations and qualitative analyses of verbal reports and interviews — experience data of nearly hundred sessions from ten different artwork installations in Beta Space over a three-year period between 2004–2007.
The key to understanding interactive engagement is to learn about participants’ intentions in performing certain actions, how they interpret the outcomes of their actions and make sense of their experience.
To be more specific, I will give you an example of an interactive installation experience session. The participant entered the Beta Space, she looked at the big black screen and wondered how she can make it do anything. After a while, she realized that it was actually tracking her movements, and she could see colour plumes were related to where she moved in the physical space. Below is an excerpt from the video cued recall session of the participant.
“I wanted to see how subtle the movements were which is why I started moving really slowly at first and then I wanted to know where the cameras were so I then I started moving to see the outer spheres of where the camera angles were … Then I thought if I stuck my hand out I can work out if the cameras are above me or below me or to the sides … Then I realised it must have been on top of me because when I moved my hand on my head I was a small circle.”
Using the detailed narratives of the participants, I have identified their intentions, plan of actions and expectations accordingly. I then documented behavioural patterns that are common across participants. This investigation has been critical in understanding and modelling the interactive experience and developing a “psychological model of engagement” described in this journal article.
Four main engagement phases that drive an interactive experience
Here is a summary of the four main engagement phases I found that drive an interactive experience:
1: Uncertain Encounter
There is often uncertainty in the first-time interactions, as the participant has little or no idea about what the installation does — so she interacts without an intention — in an unintended mode.
Here are a few design principles to support “uncertain encounters”:
- Set clear and encouraging expectations: In this phase, it can help to inform participants in a clear and encouraging way but not prescriptive of what is going to happen (not to spoil it).
- Invite to uncertainty: Consider simulating the initial interaction in an inviting and obvious manner, making the initial interaction easy. For example, it is easier to walk into a room with dynamic lights, rather than a dark room. This may also set the expectation that the installation will engage participants with some dynamic lighting later on.
- Make it obvious: Provide visible and noticeable outcomes from the unintended initiation and just enough for the participant to realise the interactivity (visual, sound, touch).
2: Anticipation
Early interactions with installations are often about trial and error, learning how the system works, and what it does. Participants often want to learn quickly and feel they are in control of the system and their interactions.
Anticipation is not always an end state, there are situations where interactions might still be engaging and lasting for participants; for example, kids might be watching the same video clip over and over without getting bored — just because they purely enjoy it.
Here are the design principles to support “anticipation”:
- Make it intriguing: Try creating situations where the participant initiates an interaction unintentionally and is surprised about the outcome.
- Stage the interaction: Provide a chance for the audience to anticipate the interaction one stage at a time — rather than puzzling them continuously.
- Facilitate learning in situ: Provide multiple ways of learning the interactivity and the environment — if the interaction cannot be simple and inviting.
3: Adaptation to the Uncertainty
Once the participants learn the rules of the interactions and predict what is to come, they might not find more meaning or enjoyment in repeating the same interactions. One way to maintain engagement is to introduce unexpected changes to the experience, where the participant might be challenged. For example, the system might start to respond in a new and unexpected way to the same input — while interactions still feel familiar, the unpredictability creates curiosity to maintain engagement.
The key is to provide sufficient adaptation time for the participant to practice and learn the new rules interactions. If there is a bombardment of feedback and changes in the environment at once, they probably won’t have enough time for adaptation. This is similar to getting frustrated being around an erratic person, one might immediately disengage and avoid any further interaction. However, a mildly unpredictable person might be interesting to explore. As designers, we should consider introducing one change at a time, allowing time for participant’s adaptation, then maybe introduce another one — depending on participants appetite for a challenge.
Here are the design principles to facilitate “adaptation to uncertainty”:
- Allow time for adaptation: Provide sufficient ‘adaptation’ time for the participants to practice the interactivity
- Provide consistent feedback: Adaptation is easier when there is clear and consistent feedback from the system. When interactions are consistent, participants can maintain focus and adapt to the system easier.
- Reward participants: Reward them with a sense of achievement or control
4: Deeper Understanding
In phase 3 — during the uncertain mode, because the participants’ intentions and expectations are misaligned, they might interpret the interactivity as unconventional or uncomfortable. In order to stay engaged, they need to shift their thinking of the new situation. This shift can, in return, initiate a new way of making sense of their experience.
As the participant starts seeing new ways of interacting, they reach a more complete understanding of the installation and what their relationship is to the work. In this phase, they judge and evaluate at a higher, conceptual level. They may discover an aspect of the interaction, a new meaning or an exchange she was not aware of before.
Here are the design principles to facilitate a “deeper understanding”:
- Delay Anticipation: Anticipation sustains engagement until it is perceived as boring. To avoid boredom, you may purposefully delay anticipation however, the key is to understand how long a participant would stay engaged to reach that state.
- Create a balance for predictability: Switch between a ‘sense of uncertainty’ and ‘sense of control’ to keep participants challenged and interested
A Summary of What I Learned
To understand and decode engagement, designers have to observe and understand participants’ intentions in the context of the interactive system. Once you understand the most common and intriguing intentions, then you may design interactions that support those intentions.
As a designer, you will need to explore the consequences of your design decisions e.g. whether to align or not to align system feedback with the participants’ intentions. You may Introduce ‘unexpected’ changes to the participants’ experience, where they might be challenged. If you go down this path, then you may provide guidance for the ‘unexpected’ situations or continue to challenge participants with uncertainty — especially when participants seek closure.
I’ve found in many cases, as participants continue to think about the interaction episodes they tend to appreciate their experience more. The feeling is similar to thinking about an event in a movie days after seeing it and recognising patterns in life that were not obvious to you before seeing the movie. Similarly, a deeper understanding phase occurs if the interactive experience triggers new conceptual layers and realisations into the future.
Hopefully, the engagement phases and design principles may guide the artists and designers who have the ambition to design for engaging, influential and creative experiences.
Thanks to my research supervisors Linda Candy & Ernest Edmonds who introduced me to interactive arts. Special thanks to Jason Mesut for his constructive feedback shaping this article and Luke Thompson for reviewing it.
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