TY - JOUR
T1 - UNFOLDING LEARNING BEHAVIORS: A SEQUENTIAL ANALYSIS APPROACH IN A GAME-BASED LEARNING ENVIRONMENT.
AU - LIAO, Calvin C. Y.
AU - CHEN, Zhi-Hong
AU - CHENG, Hercy N. H.
AU - CHAN, Tak-Wai
N1 - Accession Number: 85289256; LIAO, Calvin C. Y. 1; Email Address: [email protected]; CHEN, Zhi-Hong 2; Email Address: [email protected]; CHENG, Hercy N. H. 1; Email Address: [email protected]; CHAN, Tak-Wai 1; Email Address: [email protected]; Affiliations: 1 : Graduate Institute of Network Learning Technology, National Central University, No. 300, Jhongda Road, Jhongli City, 32001, Taoyuan County, Taiwan, ROC.; 2 : Department of Information Communication, Yuan Ze University, No. 135, Yuan-Tung Road, Jhongli City, 32003, Taoyuan County, Taiwan, ROC.; Source Info: Mar2012, Vol. 7 Issue 1, p25; Thesaurus Term: Learning; Thesaurus Term: Classroom environment; Thesaurus Term: Education; Thesaurus Term: Educational games; Thesaurus Term: Motivation (Psychology); Subject Term: Sequential analysis; Subject Term: Virtual pets; Author-Supplied Keyword: behavior; Author-Supplied Keyword: Game-based learning; Author-Supplied Keyword: sequential analysis; Number of Pages: 20p; Illustrations: 4 Color Photographs, 2 Diagrams, 6 Charts, 1 Graph; Document Type: Article
PY - 2012/3
Y1 - 2012/3
N2 - During the past two decades, conducting game-based learning research poses several predicaments. In particular, two primary challenges have been raised: the lack of long-term intervention in a real world and the lack of the revelation of learning process for understanding students' engagement. Hence, in order to overcome the two challenges gradually, a previous study developed a game-based learning environment, entitled My-Pet-My-Quest (MPMQ), for arithmetic practices. The MPMQ provides pet-keeping tasks and learning tasks, so that students can play the role of pet-keepers who can interact with their virtual pets and solve a series of small quests that sustain students' motivation and engagement. For understanding students' behaviors in the environment, two processes were carried out. This study first attempted to implement long-term intervention in an elementary afterschool club as well as students' home, and then to analyze the learning process. Furthermore, this study adopted a sequential analysis approach, based on a designing framework, to help us examine and understand the each aspect of behaviors in students' learning and playing. These results can provide suggestions and references for the design of efficient game-based learning environments in the future. [ABSTRACT FROM AUTHOR]
AB - During the past two decades, conducting game-based learning research poses several predicaments. In particular, two primary challenges have been raised: the lack of long-term intervention in a real world and the lack of the revelation of learning process for understanding students' engagement. Hence, in order to overcome the two challenges gradually, a previous study developed a game-based learning environment, entitled My-Pet-My-Quest (MPMQ), for arithmetic practices. The MPMQ provides pet-keeping tasks and learning tasks, so that students can play the role of pet-keepers who can interact with their virtual pets and solve a series of small quests that sustain students' motivation and engagement. For understanding students' behaviors in the environment, two processes were carried out. This study first attempted to implement long-term intervention in an elementary afterschool club as well as students' home, and then to analyze the learning process. Furthermore, this study adopted a sequential analysis approach, based on a designing framework, to help us examine and understand the each aspect of behaviors in students' learning and playing. These results can provide suggestions and references for the design of efficient game-based learning environments in the future. [ABSTRACT FROM AUTHOR]
KW - Learning
KW - Classroom environment
KW - Education
KW - Educational games
KW - Motivation (Psychology)
KW - Sequential analysis
KW - Virtual pets
KW - behavior
KW - Game-based learning
KW - sequential analysis
M3 - Article
SN - 1793-2068
VL - 7
SP - 25
EP - 44
JO - Research & Practice in Technology Enhanced Learning
JF - Research & Practice in Technology Enhanced Learning
IS - 1
ER -