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An intelligent agent model for learning group development in the digital learning environment: A systematic literature review
Putro B.L.a, Rosmansyah Y.a, Suhardia
a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020, Institute of Advanced Engineering and Science. All rights reserved.Group development is the first and most important step for the success of collaborative problem solving (CPS) learning in the digital learning environment (DLE). A literacy study is needed for studies in the intelligent agent domain for group development of collaborative learning in DLE. This paper is a systematic literature review (SLR) of intelligent agents for group formation from 2001 to 2019. This paper aims to find answers to 4 (four) research questions, namely: 1) What components to develop intelligent agents for group development; 2) What is the intelligent agent model for group development; 3) How are the metrics for measuring intelligent agent performance; and 4) How is the Framework for developing intelligent agent. The components of the intelligent agent model consist of: member attributes, group attributes (group constraints), and intelligent techniques. This research refers to Srba and Bielikova’s group development model. The stages of the model are formation, performing and closing. An intelligent agent model at the formation stage. A performance metric for the intelligent agent at the performance stage. The framework for developing an intelligent agent is a reference to the stages of development, component selection techniques, and performance measurement of an intelligent agent.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Collaborative problem solving,Digital learning environment,Group development,Group development model,Intelligent agent,Metrics performance[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]Praise Allah for all the blessings that He has given. Thanks also to our parents, wife, children and friends for their participation and support, and to the Indonesian Ministry of Education and Finance Ministry for the funding of the BUDI-DN scholarship.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.11591/eei.v9i3.2009[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]