Formulating or Fixating: Effects of Examples on Problem Solving Vary as a Function of Example Presentation Interface Design

Document Title

Formulating or Fixating: Effects of Examples on Problem Solving Vary as a Function of Example Presentation Interface Design

Document Information

• Subject Area: Human-Computer Interaction (HCI), creative support tool design, problem solving
• Keywords: creativity, problem solving, examples, interface design, Human-Computer Interaction (HCI), performance evaluation, inspiration modeling, fixation effect, exploratory tasks, cognitive strategies

Research Background and Problem

• Identified Issues or Challenges:

  1. In creative problem-solving processes, examples can provide inspiration but may also trigger the "fixation effect," limiting innovation.
  2. There is a lack of clear theoretical guidance on how to design interactive systems to optimize user interaction with examples.
  3. The way examples are presented (e.g., list, dropdown menu, or contextual embedding) may influence how users utilize examples to complete tasks, but the specific effects remain unclear.

• Significance:

  • Effective use of examples can significantly enhance the quality of creative thinking and problem solving.
  • Theorizing this interaction model can not only advance tool design but also identify optimal methods for creative support.

• Research Motivation and Related Work:

  • Designers need a better understanding of how the design of example interaction interfaces affects users' creative behaviors and performance.
  • While much research has focused on the characteristics of examples (e.g., diversity, conceptual distance), the relationship between example interface characteristics and creative behavior has been underexplored.

Solution

• Proposed Approach:

  • Conduct an experimental study to systematically investigate the effects of example presentation methods (context embedding, list, dropdown menu) and example diversity on performance in exploratory creative tasks.
  • Nest examples within the task core (problem-solving space) in different interfaces to examine how diversity and interaction styles influence user behavior and problem-solving effectiveness.

• Innovative Aspects:

  • Map example interaction interface designs to potential psychological mechanisms (e.g., "inspiration stimulation effect" and "problem reconstruction effect").
  • Systematically compare the practical effects of three common example interaction interface designs (context embedding, list, dropdown menu).

• Implementation Steps:

  1. Develop an experimental task: the WildCat Wells task, which simulates an exploratory task environment.
  2. Conduct the experiment with 182 participants, using high-diversity (HD) and low-diversity (LD) example sets.
  3. Compare the effects of three interface conditions (context embedding, list, dropdown menu) on task performance and example usage strategies.

Research Findings

• Specific Findings:

  1. Interface Design Impacts Performance:
     • The list interface negatively affected task performance, with users performing significantly worse than in the context embedding and dropdown menu interfaces.
     • High-diversity examples (HD) generally improved task performance quality.
  2. Differences in Psychological Mechanisms:
     • The context embedding interface more effectively guided participants to adopt "problem reconstruction" (model-based) strategies.
     • The list interface tended to encourage "inspiration stimulation" (stimulation-based) strategies but was more prone to causing the "fixation effect."
  3. Interaction and Behavioral Patterns:
     • Dropdown menu users were more likely to ignore examples and often adopted spontaneous exploratory strategies.

• Advantages:

  • Compared to traditional list interface designs, context embedding significantly reduced the limitations on search capabilities caused by the "fixation effect."
  • Although dropdown menu users utilized examples less frequently, their performance was comparable to that in the context embedding condition, suggesting that reducing inefficient example usage may be a beneficial strategy.

• Experimental or Evaluation Results:

  • Under the LD condition, during the first to the 30th clicks, participants using the list interface exhibited a clear "hill-climbing" local search behavior consistent with the "inspiration stimulation" strategy, while context embedding participants demonstrated a more global understanding and exploration.
  • Examples directly embedded in context significantly reduced users' cognitive load and enhanced the linkage between examples and the problem space.

• Limitations and Future Directions:

  • The task design was overly simplistic (e.g., a single solution goal), leaving a gap with more complex real-world creative problems.
  • Future research should extend to more complex task domains (e.g., user interface design or advertising creativity) to verify applicability.
  • The interaction between interface design and cognitive styles (e.g., visuospatial reasoning ability) was not deeply analyzed in the current study.
  • Further exploration of theoretical mechanisms regarding the effects of example combinations and abstraction levels is needed.