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Selection of learning materials based on students’ behaviors in 3DMUVLE

Rasima, Rosmansyah Y.a, Langi A.Z.R.a, Munirb

a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Bandung, Indonesia
b Department of Computer Science Education, Universitas Pendidikan Indonesia, Bandung, Bandung, 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]© 2018 Universitas Ahmad Dahlan.Learning in 3-dimensional virtual environments has been widely used as a complement to traditional learning. Multi User Virtual Learning Environment in 3 Dimensions (3DMUVLE) provides many benefits and can support lifelong learning. In its implementation, this learning has not supported personal learning. This study aims to build a 3DMUVLE with personalized materials based on students’ models. The system development model uses the Linear Sequence model by integrating MOODLE, SLOODLE and OPENSIM. Student’s model in this research is Myer Briggs Type Indicator (MBTI) and determination of type uses fuzzy logic. The results of this study are 16 types of students and each type consists of 3 levels: low, medium and high. Each level has a specific learning material. The implication of this research is the level of MBTI type so that the learning material is more specific.[/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]3DMUVLE,Fuzzy logic,MBTI,Personal learning[/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][/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/10.12928/TELKOMNIKA.v16i5.7994[/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]