| Summary: | 碩士 === 國立臺北科技大學 === 互動設計系 === 106 === The purpose of this research is to develop a visual note interface by using Google’s knowledge graph concept. From the perspective of machine, we try to calculate the depth and breadth of the knowledge graph, established by adolescent to understand their cognitive style and information seeking behavior in the field of learning popular science knowledge. In the process of learning, there are different levels of cognitive load will occur due to the differences in prior knowledge or other factors. Cognitive load is associated with working memory, therefore, in order to verify whether the interface of this research can help adolescent reduce their cognitive load effectively, we use EEG to measure the physiological signals and to analyze the signals associated with working memory. According to the result, the visual note interface can effectively reduce the cognitive load through the comparison between the experimental group and the control group. while the adolescent with innovative cognitive style have influence on deep thinking and breadth thinking, and have positive correlation. Among them, the broadest relevance is the most relevant. Adolescent who can learn about innovative cognitive styles are more inclined to think extensively. Finally, in the results of PLS path analysis, it is found that the positive motivation, ease of use, accessibility of interface, diagnosis and information seeking behavior of retrospective and search and thinking mode, these factors have a correlation and causal relationship.
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