TY - GEN
T1 - An approach towards designing problem networks in serious games
AU - Parakh, A.
AU - Chundi, P.
AU - Subramaniam, M.
N1 - Funding Information:
This research has been supported by NSF award #1623380
Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Integrating of subject matter onto serious games is an important problem that has been shown to impact the learning potential of serious games. A novel approach, inspired by peer-to-peer (P2P) networks, towards designing and deploying a series of problems in game scenarios is described. Given a set of problems involving a set of concepts the proposed approach automatically generates a problem network graph akin to P2P network that can then traversed by a player to collect all the concepts that are necessary to learn a topic of interest. A network traversal algorithm is described, which identifies the relevant problems and produces an efficient route through the network for learning the topic. We also describe an algorithm for mapping the problem network graph onto a game scenario by identifying groups of problems that can be placed in a single location of the game like the level of a building, arcade, or a room, physical barriers that separate, and the conditions for passing through these barriers. The proposed approach has been validated through a quantum cryptography game QuaSim and has been played by over 100 students to learn quantum cryptography basics and cryptography protocols.
AB - Integrating of subject matter onto serious games is an important problem that has been shown to impact the learning potential of serious games. A novel approach, inspired by peer-to-peer (P2P) networks, towards designing and deploying a series of problems in game scenarios is described. Given a set of problems involving a set of concepts the proposed approach automatically generates a problem network graph akin to P2P network that can then traversed by a player to collect all the concepts that are necessary to learn a topic of interest. A network traversal algorithm is described, which identifies the relevant problems and produces an efficient route through the network for learning the topic. We also describe an algorithm for mapping the problem network graph onto a game scenario by identifying groups of problems that can be placed in a single location of the game like the level of a building, arcade, or a room, physical barriers that separate, and the conditions for passing through these barriers. The proposed approach has been validated through a quantum cryptography game QuaSim and has been played by over 100 students to learn quantum cryptography basics and cryptography protocols.
KW - Game design
KW - Peer-peer networks
KW - Quantum computing
KW - Quantum cryptography
KW - Serious games
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U2 - 10.1109/CIG.2019.8848055
DO - 10.1109/CIG.2019.8848055
M3 - Conference contribution
AN - SCOPUS:85073110348
T3 - IEEE Conference on Computatonal Intelligence and Games, CIG
BT - IEEE Conference on Games 2019, CoG 2019
PB - IEEE Computer Society
T2 - 2019 IEEE Conference on Games, CoG 2019
Y2 - 20 August 2019 through 23 August 2019
ER -