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Exploring undergraduate students mental representation and its correlation with information processing and their knowledge in learning plant transport using diagram convention

机译:利用图式约定探索大学生的心理表征及其与信息处理及其在植物运输学习中的知识的相关性

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Application of diagram convention in learning helps students to understand biological concepts. This diagram is integrated in formation of facts of a concept. The aim of this study was to analyze the correlation between mental representation (MR) of undergraduate students when reading diagram convention with information processing and their knowledge. The 27 participants consist of undergraduate students of biology education in Bandung who are studying plant transport. MR data in form of causal network is obtained through worksheet instrument developed based on CNET protocol while information processing and knowledge through an essay instrument. There's a strong correlation between MR with information processing (r = 0.578; p 0.05) and MR with knowledge (r = 0.679; p 0.05). This result indicates that to represent a diagram being studied requires knowledge as a bridge to connect the information contained in the diagram. Important information in diagram is processed in working memory to form causal interactions between information elements and emerge in form of causal network. Two MR patterns are found namely linear (Markov chain) and simple branching (feedback control with a single measurement). Differences in MR patterns indicate the ability of students understand the information contained in the diagram.
机译:在学习中采用图式惯例有助于学生理解生物学概念。该图集成在概念事实的形成中。这项研究的目的是分析大学生阅读带有信息处理的图表惯例时的心理表征(MR)与他们的知识之间的相关性。 27名参与者包括正在研究植物运输的万隆生物教育本科学生。因果网络形式的MR数据是通过基于CNET协议开发的工作表工具获得的,而信息处理和知识是通过随笔工具获得的。有信息处理的MR(r = 0.578; p <0.05)与有知识的MR(r = 0.679; p <0.05)之间有很强的相关性。该结果表明,要代表正在研究的图,需要知识作为连接图中包含的信息的桥梁。图中的重要信息在工作存储器中进行处理,以形成信息元素之间的因果相互作用,并以因果网络的形式出现。发现了两种MR模式,即线性(马尔可夫链)和简单分支(一次测量即可得到反馈控制)。 MR模式的差异表明学生了解图表中信息的能力。

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