Scientific inquiry involves a variety of abilities scientists use to investigate the natural world. In order to develop students' scientific inquiry, researchers and educators have developed different curricula and a variety of instructional resources, which make features and descriptors of scientific inquiry in teaching and learning even more diverse and complex. For revealing how the multi-facets of scientific inquiry are inherently correlated, this study identified descriptors representing features of scientific inquiry and automatically reviewed the research abstracts where these descriptors were used. A cluster analysis was used to analyze 171 relevant article abstracts published in Web of Science from 1986 to 2010, by using the data mining software WordStat v6.1. Networks of descriptors and of research strands showed the inter-relationships among descriptors and the research strands. Through triangulating the categorization results from automatic data-mining and expert researchers' qualitative reviewing, this study identified seven clusters of high-frequency descriptors and nine major strands of current research studies. The nine strands can further be grouped into five research themes: NOS, Knowledge Construction, Inquiry Ability, Explanatory-driven Inquiry, and Professional Development. With different levels of cohesiveness in network, these themes demonstrated that scientific inquiry was composed of different levels of abilities students need to achieve as well as the endeavors of teachers. Through exploring the network shared among most researchers, this study is expected to provide novice researchers information about elements that expert researchers usually consider and further, it is expected to give expert researchers some new directions to explore in research designs.
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