A COGNITIVE-SCIENCE AND GEOSCIENCE-EDUCATION COLLABORATION: ENHANCING THE TEACHING OF ROCK IDENTIFICATION
We illustrate the application of the models in a variety of highly controlled laboratory experiments in which novice students are trained to identify different sets of igneous, metamorphic and sedimentary rocks. The models are used to provide detailed quantitative accounts of the students’ learning trajectories and their ability to generalize correctly to novel samples from the trained rock types. As a prerequisite for applying the models in this manner, an initial step is to derive a high-dimensional “feature space” in which the numerous rock samples are embedded. We describe a variety of complementary methods for achieving this initial goal, including similarity-scaling studies, direct dimension-rating studies, and application of modern “deep-learning” technologies.
Finally, we describe a variety of recommendations that the models make for enhancing the teaching of rock identification; and we describe the preliminary support that we have gathered for these recommendations in our laboratory experiments.