To develop competency in science practices, such as data analysis and interpretation, chemistry learners must develop an understanding of what makes an analysis and interpretation "good" (i.e., the criteria for success). One way that individuals extract the criteria for success in a novel situation is through making social comparisons,…

Authentic, "messy data" contain variability that comes from many sources, such as natural variation in nature, chance occurrences during research, and human error. It is this messiness that both deters potential users of authentic data and gives data the power to create unique learning opportunities that reveal the nature of science…

The study examined the effects of two different instructional interventions as support for scientific discovery learning using computer simulations. In two well-known categories of difficulty, data interpretation and self-regulation, instructional interventions for learning with computer simulations on the topic "ecosystem water" were developed…

Cognitive and conceptual uncertainties are critical elements in geology from the earliest data collection stage to concluding interpretations. How a geologist conceptually weighs the importance of various data greatly influences final interpretations. In order for the process of data selection and interpretation to be transparent and repeatable,…

Analysis of a sample of 100 pupil scripts from a British Assessment of Performance Unit survey suggests that ability to read and interpret graphical data should not be seen as an independent process skill. Instead, hidden cognitive demands of assessment items require integrated understanding based on a sophisticated procedural model. (SK)

Noting that understanding how science students respond to anomalous data is essential to understanding knowledge acquisition in science classrooms, this paper presents a detailed analysis of the ways in which scientists and science students respond to anomalous data. The paper postulates seven distinct forms of response to anomalous data: ignoring…