Unpacking “Boardgames With Apps”: The Hybrid Digital Boardgame Model

Title of the Paper

Unpacking “Boardgames with Apps”: The Hybrid Digital Boardgame Model

Bibliographic Information

• Subject Area: Human-Computer Interaction, Hybrid Digital Boardgame Design and Research
• Keywords: Boardgames, Hybrid Games, Digital Tools, Game Design, Player Experience, HCI, Applications, Typology

Research Background and Problem

• Issues or Challenges:

  • As modern boardgames increasingly incorporate digital applications and tools, researchers have identified a lack of detailed classification regarding the roles and functions of these “Hybrid Digital Boardgames” (HDBs).
  • Current research often focuses on specific aspects of games (e.g., technical implementation or user experience) but lacks a structured description of the specific functions performed by digital tools in boardgames.

• Significance:

  • Digital tools can enhance traditional boardgame play in various ways, including randomization, resource management, storytelling, and instructional functions. These not only impact player experience but are also significant for game design.
  • Providing a clear model and classification for researchers and game designers is crucial for advancing this emerging field of hybrid digital boardgames.

• Research Motivation and Related Work:

  • The authors argue that while the concept of hybrid games has been studied in the field of HCI, the specific functions of “hybrid boardgames” have received limited attention.
  • Existing related work primarily focuses on technical implementations (e.g., digital game board interfaces) or high-level design principles (e.g., social interaction features), lacking a systematic functional classification model.

Solution

• Research Methods:

  • A mixed-methods qualitative research design was adopted, including a survey of 237 boardgame players, interviews with 18 designers and publishers, and “critical play” experiments with key games.
  • Functions were grouped and hierarchical relationships were created using coding and affinity mapping, with multiple iterations, testing, and adjustments.

• Proposed Model:

  • The authors proposed a Hybrid Digital Boardgame (HDBs) model comprising “eight functional domains,” including: timing, randomization, resource management, information provision, storytelling, memory functions, computation, and teaching.

• Implementation Steps and Key Techniques:

  1. Data Collection: Gathered attitudes toward hybrid boardgames and descriptions of digital tool functions through surveys and interviews.
  2. Affinity Mapping Analysis: Coded and grouped data, constructing a functional classification hierarchy using software tools.
  3. Function Testing: Validated the model’s logic and consistency through online card-sorting activities.
  4. Model Presentation: Developed a well-defined functional framework covering both existing functions and potential application areas.

• Innovations:

  • Provided a technology-neutral and detailed classification model that systematically describes the specific functions of digital tools in boardgames.
  • Incorporated feedback from players and designers, making the model applicable not only to current research but also to future design practices.

Research Outcomes

• Specific Results:

  • Proposed a model encompassing eight functional domains, ranging from basic time management to complex information processing and storytelling functions.
  • Identified new trends related to “memory functions,” such as cross-session game records and achievement unlocking.
  • Provided coherent and detailed examples for support, including functional analyses of specific games like Alchemists, Detective: A Modern Crime Board Game, and Chronicles of Crime.

• Comparison with Existing Solutions:

  • The classification model presented in this paper is more granular than previous studies, better supporting researchers and designers in understanding and developing hybrid digital boardgames.
  • The authors emphasized that their model not only captures current practices but also supports future functional expansions through its categorical design.

• Experimental Results and Evaluation:

  • Collected diverse perspectives on digital functions from players and designers through surveys and interviews.
  • Verified the reliability of the model’s hierarchical structure through card-sorting activities and refined the functional classification based on these data.

• Limitations and Future Directions:

  • Limitations include: the study’s scope being restricted to currently available HDBs in the market, excluding boardgames with “non-smart” electrical or electronic components; low participation from women and non-binary individuals.
  • The authors suggest future research directions, including exploring non-smart hybrid games, HDBs supporting remote distributed play, and studying new game types (e.g., “informal” hybrid tools and applications).

Conclusion

This study fills a scholarly gap in the field of hybrid digital boardgames by systematically uncovering the specific functions of these tools and providing a classification model with practical and academic significance. The proposed model can be further expanded in the future, offering additional insights for both the boardgame industry and academia.