Integrating fabrication activities into existing video games provides opportunities for players to construct objects from their gameplay and bring the digital content into the physical world. In our prior work, we outlined a framework and developed a toolkit for integrating fabrication activities within existing digital games. Insights from our prior study highlighted the challenge of aligning fabrication mechanics with the existing game mechanics in order to strengthen the player aesthetics.
In this paper, we address this challenge and build on our prior work by adding fabrication components to the Mechanics-Dynamics-Aesthetics (MDA) framework. We use this f-MDA framework to analyze the 47 fabrication events from the prior study. We list the new player-object aesthetics that emerge from integrating the existing game mechanics with fabrication mechanics. We identify connections between these emergent player-object aesthetics and the existing game mechanics. We discuss how designers can use this mapping to identify potential game mechanics for integrating with fabrication activities.
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A Computational Model of Suspense for Non-Narrative Gameplay
In recent years, various mechanisms have been proposed
to optimize players’ emotional experience. In this paper,
we focus on suspense, one of the key emotions in gameplay. Most
previous research on suspense management in games focused on
narratives. Instead, we propose a new computational model of
Suspense for Non-Narrative Gameplay (SNNG). SNNG is built
around a Player Suspense Model (PSM) with three key factors:
hope, fear, and uncertainty. These three factors are modeled as
three sensors that can be triggered by particular game objects
(e.g., NPCs) and game mechanics (e.g., health). A player’s feeling
of suspense can be adjusted by altering the level of hope, fear, and
uncertainty. Therefore, an SNNG-enhanced game engine could
manage a player’s level of suspense by adding or removing game
objects, diverting NPCs, adjusting game mechanics, and giving
or withholding information. We tested our model by integrating
SNNG into a Pacman game. Our preliminary experiment with
nine subjects was encouraging.
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- Award ID(s):
- 1852516
- NSF-PAR ID:
- 10315350
- Date Published:
- Journal Name:
- Proceedings of the 24th International Conference Information Visualisation
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IV51561.2020.00136
