Repo Dosen ULM

TURNITIN :: Computer support collaborative learning-retrosynthetic analysis model to improve students'problem solving ability

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dc.contributor.author Iriani, Rilia
dc.date.accessioned 2021-04-20T08:21:47Z
dc.date.available 2021-04-20T08:21:47Z
dc.date.issued 2020
dc.identifier.issn 1742-6596
dc.identifier.uri https://repo-dosen.ulm.ac.id//handle/123456789/19567
dc.description.abstract Problems encountered are too difficult for students to understand organic chemistry, including stereochemistry, organic reaction synthesis. So, we need a way to overcome this problem in order to increase the quality of learning processes through the implementation of the multimodel Computer Support Collaboration Learning-Retrosynthetic Analysis (multimodel CSCL-RA) in organic chemistry. This study is action research with descriptive qualitative approach with students of Organic Chemistry III in Chemical Education Program, ULM. Thirty pair dyads of students participated in a problem task. The instrument of research was in the form of problem-solving ability and cognition test instrument, observation sheet of teacher and student activity. Data were analyzed using percentage of students’ problem-solving ability and achievement. The results showed that the implementation of CSCL-RA multimodel in organic chemistry increased the quality of learning with indicators of increasing students' problemsolving abilities and learning outcomes. The implication for future research could provide further: (1) students’ interactions in CSCL, (2) CSCL with metacognitive training in problemsolving. en_US
dc.publisher Journal of Physicsl conference Series en_US
dc.relation.ispartofseries Vol. 1422;No. 1, Hal: 1-8
dc.subject Research Subject Categories::SOCIAL SCIENCES::Other social sciences en_US
dc.subject Research Subject Categories::NATURAL SCIENCES::Chemistry::Theoretical chemistry en_US
dc.title TURNITIN :: Computer support collaborative learning-retrosynthetic analysis model to improve students'problem solving ability en_US
dc.type Other en_US


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