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Knowledge based recommender system and web 2.0 to enhance learning model in junior high school
Wonoseto M.G.a, Rosmansyah Y.a
a School of Electrical Engineering and Informatics, ITB, 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]© 2017 IEEE.Current educational trend is education based on student-centered activities, personalize and collaborative. Along with the development of technology, blended learning becomes very popular in education. A good blended learning is a blended learning that fits the current educational challenges of combining learning activities, supported by tools and technologies such as web 2.0 tools and recommender systems. In previous research, has been built a recommender system that recommends e-tivity, possible collaborators, web 2.0 tools, and bits of advice. The recommender system was built with collaborative filtering and content-based techniques. Collaborative filtering and content-based have problems in terms of dependency with data history, so it is possible to ramp-up and gray sheep on the recommendation. One way to overcome the problem of ramp-up and gray sheep is with knowledge-based. This paper proposes a knowledge-based recommender system to improve learning model in schools. Recommendations are based on VAK learning styles and collaborative learning theory. This research uses Design Research Methodology. The results showed that the experimental class score was higher than the control class. Using inferential statistics, it can be concluded that proposed knowledge-based recommender system significantly enhance learning in school.[/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]Collaborative learning,Content-based techniques,Design research methodologies,Inferential statistics,Knowledge-based recommender systems,Learning Style,Tools and technologies,Web 2.0[/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 Learning,Knowledge-Based Recommender System,VAK Learning Style,Web 2.0[/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/10.1109/ICITSI.2017.8267937[/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]