283 Michael R. Matthews P H I L O S O P H Y O F E D U C A T I O N 2 0 0 3 Data, Phenomena, and Theory: How Clarifying the Concepts Can Illuminate the Nature of Science Michael R. Matthews University of New South Wales Learning about the Nature of Science (NOS) has been an item in most science curricula reforms for the past few decades. 1 It has been given special prominence in recent U.S. science reform projects such as the National Science Teacher Association’s (NSTA) Scope Sequence and Coordination; 2 American Association for the Ad- vancement of Science’s (AAAS) The Liberal Art of Science, 3 Project 2061 4 and Benchmarks for Science Literacy; 5 the U.S. National Academy of Science’s Na- tional Science Education Standards, 6 and their subsequent publication Inquiry and the National Science Education Standards: A Guide for Teaching and Learning. 7 Elsewhere I have advocated a “softly, softly” approach to teaching NOS, an approach whereby one concentrates on case studies, drawing out their significant features as the occasion, students, and circumstances allow; this case study method is tantamount to an inductive approach to NOS. 8 A softly, softly approach is not without its problems — such as identifying and justifying the criteria for selecting cases, and deciding how directive we should be in seeing that the proper method- ological lessons are learned. I want here to continue the “softly, softly” approach and investigate a tripartite distinction between data, phenomena and theory (DPT). 9 The investigation sheds some light on NOS matters, and perhaps some light on research in science education. DATA, PHENOMENA, AND THEORY IN EDUCATION DOCUMENTS The DPT constellation is commonly mentioned in science education docu- ments. For instance, Science for All Americans in its chapter on NOS notes that: Sooner or later, the validity of scientific claims is settled by referring to observations of phenomena. Hence scientists concentrate on getting accurate data. Such evidence is obtained by observations and measurements taken in situations that range from natural settings (such as a forest) to completely contrived ones (such as the laboratory).…Scientists do not work only with data and well-developed theories. Often, they have only tentative hypotheses about the way things may be.…Scientists strive to make sense of observations of phenomena by inventing explanations for them that use, or are consistent with, currently accepted scientific principles. Such explanations — theories — may be either sweeping or restricted. 10 NSTA’s blueprint for reform, Scope, Sequence, and Coordination, notes that: Empirical law is a generalization of a relationship that has, through observation or measure- ment, been established among the phenomena represented by two or more concepts…but which rely on no theory or model for its expression or utilization.…A theory is used to explain facts, observations, phenomena, and empirical laws.…A model is a mental picture or representative physical system of a phenomenon. 11 These statements contain the terms: “theory,” “evidence,” “phenomena,” “observation,” “data,” “measurement,” “hypothesis,” “model,” and “explanation.” The statements suggest that the terms are grouped as follows: Data — Evidence about phenomena obtained by observation or instrumentation; Phenomena — The