“I Am Iron Man” Priming Improves the Learnability and Memorability of User-Elicited Gestures

Title of the Paper

“I Am Iron Man”: Priming Improves the Learnability and Memorability of User-Elicited Gestures

Paper Information

• Domain: Human-Computer Interaction (HCI), User Interaction Design, Touch Gesture Usability
• Keywords: Distributed Interaction Design, User Priming, Learnability, Memorability, Crowdsourcing, Legacy Bias, Sci-Fi and HCI

Research Background and Problem

• Problem or Challenge:

  • "Legacy bias" in user priming studies, a phenomenon where users are influenced by existing technologies and provide conservative and uninnovative suggestions.
  • How to design user gestures that are easier to learn and remember, thereby reducing legacy bias.

• Significance:

  • In emerging technologies such as Mixed Reality (MR), traditional legacy gestures may not meet the demands of technological advancement.
  • Gesture learnability and memorability directly impact user experience and technology adoption.

• Research Motivation and Related Work:

  • Morris et al. proposed using "visual priming" techniques from psychology to enhance user creativity and reduce legacy bias.
  • Current research on the effects of visual priming in user elicitation lacks statistical significance and sufficient study scale.
  • Drawing on psychology and the intersection of sci-fi and HCI, the authors aim to scientifically validate the impact of visual priming on user gesture elicitation.

Solution

• Proposed Method/Solution:

  • Utilizing two forms of visual priming:

    1. Sci-fi movie clips (e.g., Iron Man, Minority Report) as references.
    2. Creative mindset activation by asking participants about their past creative experiences to stimulate innovative thinking.

  • Designing and conducting a large-scale distributed user elicitation experiment with 167 participants, involving 10 gesture design tasks related to MR media player functionalities.

• Innovations:

  • Exploring the potential value of sci-fi movies as visual priming tools and validating their effects on reducing legacy bias while improving learnability and memorability.
  • Employing the Crowdlicit platform for distributed design, overcoming limitations of traditional experimental environments.
  • Conducting independent studies on the learnability and memorability of user-designed gestures.

• Implementation Steps:

  1. Conducting a distributed user elicitation experiment: participants propose their own gestures to address 10 functional requirements.
  2. Evaluating gesture identifiability.
  3. Performing distributed learnability studies by having participants learn and execute gestures through repeated video viewing.
  4. Conducting distributed memorability assessments, testing participants' ability to recall gestures accurately one week later.
  5. Comparing the performance differences between the no-priming group, sci-fi priming group, and creative mindset priming group.

Research Findings

• Specific Results:

  • Learnability: Gestures in the sci-fi priming group were learned the fastest, requiring an average of only 1.22 video views; the control group required 1.60 views, and the creative mindset group required 1.56 views.
  • Memorability: One week later, the sci-fi priming group achieved an 80% accuracy rate in gesture recall, compared to 73% for the creative mindset group and only 43% for the control group.
  • Engagement: Ratings of enjoyment and perceived fit indicated that visual priming enhanced gesture acceptance.

• Advantages Over Existing Solutions:

  • Expands the methodology of user elicitation research by introducing large-scale (online) distributed experiments, providing statistically more reliable results compared to typical small-sample studies.
  • Demonstrates that visual priming improves gesture identifiability and enhances user engagement.

• Experimental or Evaluation Results:

  1. Results from 167 distributed participants showed that visual priming effectively reduced legacy bias without significantly impacting gesture identifiability.
  2. Sci-fi visual priming significantly improved initial learnability and overall learning efficiency of gestures.
  3. Gestures elicited under sci-fi visual priming exhibited far superior memorability compared to the control group.

• Limitations and Future Directions:

  • Limitations:
    1. Participants designed gestures based on imagined systems rather than real-world interaction contexts.
    2. Potential confounding effects of participants directly mimicking gestures seen in movies.
  • Future Directions:
    • Validate the performance of visually primed gestures on actual mixed reality devices.
    • Explore the impact of other forms of visual priming on gesture learnability and memorability.
    • Investigate whether visual priming is effective for other forms of human-computer interaction, such as voice commands or graphical interface label design.