TY - JOUR
T1 - Learning analytics architecture to scaffold learning experience through technology-based methods
AU - Baalsrud Hauge, Jannicke
AU - Stanescu , Ioana Andreea
AU - Moreno-Ger, Pablo
AU - Arnab, Sylvester
AU - Lim, Theodore
AU - Serrano-Laguna, Angel
AU - Lameras, Petros
AU - Hendrix, Maurice
AU - Kiili, Kristian
AU - Ninaus, Manuel
AU - De Freitas, Sara
AU - Mazzetti, Alessandro
AU - Dahlbom, Anders
AU - Degano, Cristiana
PY - 2015/1/29
Y1 - 2015/1/29
N2 - The challenge of delivering personalized learning experiences is often increased by the size of classrooms and online learning communities. Serious Games (SGs) are increasingly recognized for their potential to improve education. However, the issues related to their development and their level of effectiveness can be seriously affected when brought too rapidly into growing online learning communities. Deeper insights into how the students are playing is needed to deliver a comprehensive and intelligent learning framework that facilitates better understanding of learners' knowledge, effective assessment of their progress and continuous evaluation and optimization of the environments in which they learn. This paper discusses current SOTA and aims to explore the potential in the use of games and learning analytics towards scaffolding and supporting teaching and learning experience. The conceptual model (ecosystem and architecture) discussed in this paper aims to highlight the key considerations that may advance the current state of learning analytics, adaptive learning and SGs, by leveraging SGs as an suitable medium for gathering data and performing adaptations.
AB - The challenge of delivering personalized learning experiences is often increased by the size of classrooms and online learning communities. Serious Games (SGs) are increasingly recognized for their potential to improve education. However, the issues related to their development and their level of effectiveness can be seriously affected when brought too rapidly into growing online learning communities. Deeper insights into how the students are playing is needed to deliver a comprehensive and intelligent learning framework that facilitates better understanding of learners' knowledge, effective assessment of their progress and continuous evaluation and optimization of the environments in which they learn. This paper discusses current SOTA and aims to explore the potential in the use of games and learning analytics towards scaffolding and supporting teaching and learning experience. The conceptual model (ecosystem and architecture) discussed in this paper aims to highlight the key considerations that may advance the current state of learning analytics, adaptive learning and SGs, by leveraging SGs as an suitable medium for gathering data and performing adaptations.
KW - Game mechanics
KW - GLEANER
KW - Personalization
KW - Learning analytics
KW - Scaffolded learning
U2 - 10.17083/ijsg.v2i1.38
DO - 10.17083/ijsg.v2i1.38
M3 - Article
VL - 2
SP - 29
EP - 44
JO - International Journal of Serious Games
JF - International Journal of Serious Games
SN - 2384-8766
IS - 1
ER -