教師著作

Permanent URI for this collectionhttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/37077

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    Are you SLiM? – Developing an instrument for civic scientific literacy measurement (SLiM) based on media coverage
    (SAGE Publications, 2012-08-01) Rundgren, C. J.; Chang Rundgren, S. N.; Tseng, Y. H.; Lin Pei-Ling; Chang, C. Y.
    The purpose of this study is to develop an instrument to assess civic scientific literacy measurement (SLiM), based on media coverage. A total of 50 multiple-choice items were developed based on the most common scientific terms appearing in media within Taiwan. These questions covered the subjects of biology (45.26%, 22 items), earth science (37.90%, 19 items), physics (11.58%, 6 items) and chemistry (5.26%, 3 items). A total of 1034 students from three distinct groups (7th graders, 10th graders, and undergraduates) were invited to participate in this study. The reliability of this instrument was 0.86 (KR 20). The average difficulty of the SLiM ranged from 0.19 to 0.91, and the discrimination power was 0.1 to 0.59. According to participants’ performances on SLiM, it was revealed that 10th graders (Mean = 37.34±0.23) performed better than both undergraduates (Mean = 33.00±0.33) and 7th graders (Mean = 26.73±0.45) with significant differences in their SLiM.
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    Mining concept maps from news stories for measuring civic scientific literacy in media
    (Elsevier, 2010-08-01) Tseng, Y. H.; Chang, C. Y.; Chang Rundgren, S. N.; Rundgren, C. J.
    Motivated by a long-term goal in education for measuring Taiwanese civic scientific literacy in media (SLiM), this work reports the detailed techniques to efficiently mine a concept map from 2 years of Chinese news articles (901,446 in total) for SLiM instrument development. From the Chinese news stories, key terms (important words or phrases), known or new to existing lexicons, were first extracted by a simple, yet effective, rule-based algorithm. They were subjected to an association analysis based on their co-occurrence in sentences to reveal their term-to-term relationship. A given list of 3657 index terms from science textbooks were then matched against the term association network. The resulting term network (including 95 scientific terms) was visualized in a concept map to scaffold the instrument developers. When developing an item, the linked term pair not only suggests the topic for the item due to the clear context being mutually reinforced by each other, but also the content itself because of the rich background provided by the recurrent snippets in which they co-occur. In this way, the resulting instrument (comprised of 50 items) reflect the scientific knowledge revealed in the daily news stories, meeting the goal for measuring civic scientific literacy in media. In addition, the concept map mined from the texts served as a convenient tool for item classification, developer collaboration, and expert review and discussion.