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Negotiation based adaptive learning sequences: Combining adaptivity and adaptability

机译:基于协商的自适应学习序列:结合适应性和适应性

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This study proposes a negotiation-based approach to combine the notion of adaptivity (system-controlled adaptation) and adaptability (user-controlled adaptation) for an adaptive learning system. The system suggests adaptations and the student also submits his/her adaptation preference. When the student preference opposes the system suggestion, the student then negotiates with the system to reach an agreement of adaptation. A negotiation-based adaptive learning system (NALS) is implemented to support the generation of personalized adaptive learning sequences by system negotiations with students regarding assessments of learning performance (i.e. negotiated open student model) of the current content and choices of the next learning content (i.e. negotiation of adaptation). Students require two metacognitions in deciding adaptive learning sequences: self-assessment for evaluating their understanding of the current content and regulation for choosing appropriate learning content. Negotiated open student model are used for assist student self-assessment and negotiation of adaptation are used for assist student regulation of content choices. An experiment was conducted to compare a system-controlled adaptive learning system (SALS, adaptivity), a user-controlled adaptive learning system (UALS, adaptability), and a NALS. The results revealed that NALS promoted better metacognitions in student calibration (i.e. self-assessment) accuracy and learning content choices (i.e. regulation). Preliminary evidences also showed that NALS promoted better student performance in a delay test. The results further suggested that students with poor calibration accuracy and inappropriate content choices were not suitable to use UALS and were suitable to use SALS. The NALS can also be used for training students to make appropriate adaptation for learning. (C) 2015 Elsevier Ltd. All rights reserved.
机译:这项研究提出了一种基于协商的方法,将适应性(系统控制的适应性)和适应性(用户控制的适应性)概念相结合,构成了适应性学习系统。系统会建议改编,并且学生还会提交他/她的改编偏好。当学生偏好反对系统建议时,学生然后与系统协商以达成适应协议。实施基于协商的自适应学习系统(NALS),以通过与学生就当前内容的学习成绩评估(即协商的开放学生模型)和下一个学习内容的选择进行系统协商来支持个性化自适应学习序列的生成(即谈判适应)。在确定适应性学习顺序时,学生需要两个元认知:评估自己对当前内容的理解的自我评估和选择适当学习内容的规则。协商的开放学生模型用于帮助学生进行自我评估,而适应的协商则用于帮助学生调节内容选择。进行了一个实验,以比较系统控制的自适应学习系统(SALS,适应性),用户控制的自适应学习系统(UALS,适应性)和NALS。结果表明,NALS在学生校准(即自我评估)准确性和学习内容选择(即法规)方面促进了更好的元认知。初步证据还显示,NALS在延迟测试中可以提高学生的学习成绩。结果进一步表明,校准准确度低且内容选择不当的学生不适合使用UALS,也适合使用SALS。 NALS还可以用于培训学生以使其适应学习。 (C)2015 Elsevier Ltd.保留所有权利。

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