少即是多:中小學科學教科書關鍵詞彙探勘之研究(S901)
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In the ever-changing technology, information explosion era, digital literacy is essential for everyone to effectively capture knowledge. This study uses data mining to extract the keywords in climate change appeared in the domestic news corpus and textbooks; then, the network of target words is visualized in order to explore students’ understanding of the vocabulary network. The characteristics of the network of target words are as follows: 1. huge amount and empirical, 2. with critical concepts, 3. with creative thinking, 4. with critical reflection. First, the network of target words objectively represents the huge empirical data and is visualized for students to read information effectively. Second, the network of target words with critical concepts is easy for students to understand the relationship among phrases and explore the meanings of keywords. Third, it is helpful for students’ creativity; they learn new associations by breaking the traditional context constraints. Fourth, the process above helps students reflect the connotation of scientific news. In the past, experts scrutinized the keywords of the text and reached the consensus on the keywords through discussion. This study breaks the restrictions on exploring information to capture keywords with computational linguistics techniques. Then, it builds the validity and reliability of the measurement instrument through multiple verification and provides the prototype of the open tool for exploring keywords. We expect the results can provide instructional guidance and textbook design as references.