Some topics seem systematically extremely difficult for students, and conventional methods of teaching usually fail. Topics like this are found at all age levels, including, in physics; matter and density, Newtonian mechanics, electricity, and relativity; in biology: Evolution and genetics. These topics are difficult to learn, because learning them requires students to undergo a conceptual change. Conceptual change contrasts with less problematic learning, such as skill acquisition (learning a physical skill or an algorithm for long division) and acquisition of facts (such as "basic number facts" for addition or multiplication). If there are difficulties in these areas, they are for more apparent reasons such as sheer mass of learning or the necessity of practice to produce quick, error-free performance. The name "conceptual change" embodies a first approximation of the primary difficulty: Students must build new ideas in the context of old ones, hence the emphasis on "change" rather than on simple accumulation or (tabula rasa, or "blank slate") acquisition. Evidence strongly suggests that prior ideas constrain learning in many areas. The "conceptual" part of the conceptual change label must be treated less literally. Various theories locate the difficulty in such entities as "beliefs," "theories," or "ontologies," in addition to "concepts."

This work uses microgenetic study of classroom learning to illuminate (1) the role of pre-instructional student knowledge in the construction of normative scientific knowledge, and (2) the learning mechanisms that drive change. Three enactments of an instructional sequence designed to lead to a scientific understanding of thermal equilibration are used as data sources. Only data from a scaffolded student inquiry preceding introduction of a normative model were used. Hence, the study involves nearly autonomous student learning. In two classes, students developed stable and socially shared explanations ("causal schemes") for understanding thermal equilibration. One case resulted in a near-normative understanding, while the other resulted in a non-normative "alternative conception." The near-normative case seems to be a particularly clear example wherein the constructed causal scheme is a composition of previously documented naïve conceptions. Detailed prior description of these naive elements allows a much better than usual view of the corresponding details of change during construction of the new scheme. A list of candidate mechanisms that can account for observed change is presented. The non-normative construction seems also to be a composition, albeit of a different structural form, using a different (although similar) set of naïve elements. This article provides one of very few high-resolution process analyses showing the productive use of naïve knowledge in learning.

This article examines a remarkable learning event where a high school class developed, on its own, a stable, normative view of thermal equilibration. The event is also notable because the intuitive ideas that students bootstrapped into their model of equilibration have been thoroughly documented in prior research. Therefore, the process of changing prior conceptions is well delineated. The main point of the article is to review what happened in this microcosm of learning from multiple perspectives to examine how well each perspective can account for the learning that took place. We use three competing views of conceptual change: Knowledge in Pieces, the Theory Theory, and the Ontological View. We argue that Knowledge in Pieces provides a more detailed and more adequate account of the learning that took place, whereas that learning contradicts core commitments of the Theory Theory and of the Ontological View.

This article reviews Giyoo Hatano's ground-breaking theoretical, empirical, and methodological contributions to conceptual change research. In particular, his discovery of 'vitalism' as part of children's legitimate and distinctive biology at early ages stands as a landmark. In addition, his work reinterpreted childhood 'personification,' changing it from an indicator of deficient intellect, to a creative and often insightful strategy for coming to understand biology. Copyright © 2007 S. Karger AG.

Clinical interviewing is viewed here as a social interactional pattern in order to examine the nature and limits of the technique as a means of scientific data acquisition. I defend the technique against criticisms that it is ecologically suspect and prone to systematic biases, mainly due to influence of the interviewer on the interviewee or to unnatural and biasing interactional patterns. The Central Hypothesis of this work is that at least some forms of clinical interviewing are derivative of naturally occurring patterns of activity and interaction. As such, they do not warrant unnecessary a priori suspicion. More importantly, this view leads to avenues of empirical examination that allow determination and checking of the character of the clinical interaction, which bears directly on how and when data extracted in clinical contexts are scientifically valid. Data from an extensive corpus involving a single subject are used to illustrate and substantiate claims. Copyright © 2007, Lawrence Erlbaum Associates, Inc.

This article develops some ideas concerning the “big picture” of how using computers might fundamentally change learning, with an emphasis on mathematics (and, more generally, STEM education). I develop the big-picture model of computation as a new literacy in some detail and with concrete examples of sixth grade students learning the mathematics of motion. The principles that define computational literacy also serve as an analytical framework to examine competitive big pictures, and I use them to consider the plausibility, power, and limitations of other important contemporary trends in computationally centered education, notably computational thinking and coding as a social movement. While both of these trends have much to recommend them, my analysis uncovers some implausible assumptions and counterproductive elements of those trends. I close my essay with some more practical and action-oriented advice to mathematics educators on how best to orient to the long-term trajectory (big picture) of improving mathematics education with computation.

This article provides an empirical analysis of a single classroom episode in which students reveal difficulties with the concept of proper time in special relativity but slowly make progress in improving their understanding. The theoretical framework used is “coordination class theory,” which is an evolving model of concepts and conceptual change. The paper will focus on showing to what extent and in what sense most of the conditions and events in the data corpus seem understandable from the point of view of coordination class theory. In addition, however, some extensions of the theory are implicated, although we argue that they are “natural” extensions, improvements that extend, but do not threaten, the core theory. In particular, we observe students articulately aligning different ways of determining proper time, and we conjecture, more generally, that such a process is strongly consistent with coordination class theory and likely to be productive in other cases of conceptual change. The empirical analysis is explicitly connected to the general issue of theories and theory development in studies of conceptual change.