Hybrid learning style identification and developing adaptive problem-solving learning activities.
Learning style refers to an individual’s approach to learning based on his or her preferences, strengths, and weaknesses. Problem solving is considered an essential cognitive activity wherein people are required to understand a problem, apply their knowledge, and monitor behavior to solve the issue....
| Publicado en: | Computers in Human Behavior Vol. 55; pp. 552 - 562 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Elsevier B.V.
Feb2016 Part A
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=111011645&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 111011645 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07475632 JC4 jtl: Computers in Human Behavior issn: 07475632 maglogo: N pubinfo: dt: Feb2016 Part A vid: 55 pid: 2410 pub: Elsevier B.V. artinfo: ui: 111011645 10.1016/j.chb.2015.07.004 ppf: 552 ppct: 10 formats: tig: atl: Hybrid learning style identification and developing adaptive problem-solving learning activities. aug: au: Hung, Yu Hsin Chang, Ray I. Lin, Chun Fu affil: Department of Engineering Science and Ocean Engineering, National Taiwan University, 1, Roosevelt Road, Sec. 4, Taipei 106, Taiwan, ROC su: Academic achievement Undergraduates College teacher attitudes Algorithms Learning strategies Problem-based learning Data mining sug: subj: Academic achievement Undergraduates College teacher attitudes Algorithms Learning strategies Problem-based learning Data mining keyword: Architecture for educational technology systems Intelligent tutoring systems Teaching/learning strategies Architecture for educational technology systems Intelligent tutoring systems Teaching/learning strategies ab: Learning style refers to an individual’s approach to learning based on his or her preferences, strengths, and weaknesses. Problem solving is considered an essential cognitive activity wherein people are required to understand a problem, apply their knowledge, and monitor behavior to solve the issue. Problem solving has recently gained attention in education research, as it is considered an essential ability for effective learning. This study aims to investigate the relationship between learning styles and learning performance. To provide adaptive suggestions for optimizing problem-solving abilities, developed a hybrid learning style identification (HLSI) mechanism based on a k-means clustering algorithm was developed. The participants were 67 undergraduate students. The experiment demonstrated that HLSI can successfully cluster learning styles into three or four combinations based on learning performance, which suggests that the data mining technique can successfully explore multiple learning styles in problem-solving abilities. Additionally, 13 teachers were included in the study to discuss the effectiveness of the HLSI mechanism, and the results indicated a 95% probability of obtaining an above-average acceptance of the proposed system. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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