Cognition, Computers, and Synthetic Science: Building Knowledge and Meaning through Modeling

Abstract

Recent studies suggest that elementary and high school students perceive science largely as a passive process of observing and recording events. In their view, good scientists are those who attend acutely and who keep accurate and complete records of all that they observe (Carey, Evans, Honda, Jay, & Unger, 1989; Songer & Linn, 1991). Although attending to phenomena is a crucial part of science, the construal of science as passive observation is at serious odds with the practices of professional scientists. Students' views of science, unfortunately, are consistent with science as experienced in most elementary and high schools. Science education in school typically focuses on accumulating facts and formulas. Scientific activity is often restricted to prepackaged experiments that are little more than demonstrations of the state of current scientific knowledge. The tacit goal in these experiments is to reproduce a known effect. This is not to deny that theory verification is an important aspect of science (Popper, 1962), although it is an open question whether students understand that verification is what they are engaged in. However, verification is only a small aspect of scientific practice. Educational practices that either explicitly or implicitly suggest otherwise do a disservice to students. Science education needs to move beyond the demonstrations and so-called experiments that are characteristic of school science. This requires that researchers and educators consider ways of engaging students that involve them in seeking to understand and explain natural phenomena. The practices of professional science provide some ideas of what this type of engagement might entail. Science, as the quotation that started this chapter suggests, is the practice of trying to make sense of the world around us. In contrast to mainstream practices of school