TY - GEN
T1 - A mixed method approach for evaluating and improving the design of learning in puzzle games
AU - Scozzi, Monica Visani
AU - Iacovides, Ioanna
AU - Linehan, Conor
N1 - Publisher Copyright:
© 2017 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
PY - 2017/10/15
Y1 - 2017/10/15
N2 - Despite the acknowledgment that learning is a necessary part of all gameplay, the area of Games User Research lacks an established evidence based method through which designers and researchers can understand, assess, and improve how commercial games teach players game-specific skills and information. In this paper, we propose a mixed method procedure that draws together both quantitative and experiential approaches to examine the extent to which players are supported in learning about the game world and mechanics. We demonstrate the method through presenting a case study of the game Portal involving 14 participants, who differed in terms of their gaming expertise. By comparing optimum solutions to puzzles against observed player performance, we illustrate how the method can indicate particular problems with how learning is structured within a game. We argue that the method can highlight where major breakdowns occur and yield design insights that can improve the player experience with puzzle games.
AB - Despite the acknowledgment that learning is a necessary part of all gameplay, the area of Games User Research lacks an established evidence based method through which designers and researchers can understand, assess, and improve how commercial games teach players game-specific skills and information. In this paper, we propose a mixed method procedure that draws together both quantitative and experiential approaches to examine the extent to which players are supported in learning about the game world and mechanics. We demonstrate the method through presenting a case study of the game Portal involving 14 participants, who differed in terms of their gaming expertise. By comparing optimum solutions to puzzles against observed player performance, we illustrate how the method can indicate particular problems with how learning is structured within a game. We argue that the method can highlight where major breakdowns occur and yield design insights that can improve the player experience with puzzle games.
KW - Breakdowns
KW - Evaluation methods
KW - Games
KW - Games user research
KW - Learning curves
KW - Player experience
UR - https://www.scopus.com/pages/publications/85034650684
U2 - 10.1145/3116595.3116628
DO - 10.1145/3116595.3116628
M3 - Conference proceeding
AN - SCOPUS:85034650684
T3 - CHI PLAY 2017 - Proceedings of the Annual Symposium on Computer-Human Interaction in Play
SP - 217
EP - 228
BT - CHI PLAY 2017 - Proceedings of the Annual Symposium on Computer-Human Interaction in Play
PB - Association for Computing Machinery, Inc
T2 - 4th ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play, CHI PLAY 2017
Y2 - 15 October 2017 through 18 October 2017
ER -