CAREER: The Role of Self-Directed Learning in Facilitating Concept Acquisition: Advancing Research and Training in the Cognitive Science of Learning

New York University, New York NY

Investigators

Abstract

NSF Summary Statement Humans, particularly children, are often likened to sponges, soaking up patterns and regularities in their environment as they learn new concepts and skills. However, unlike a passive sponge, human learners are able to alter their experience in important ways by interacting with the world. For example, when studying for a test, learners can decide how to allocate study effort across materials. Any complete account of human learning must explain not only what is learned from the information we experience, but also the capacity for our actions and choices to expose that information. Many laboratory studies of learning used in cognitive psychology are silent on this issue because they limit participants' control over the flow information (emphasizing instead a type of "passive" learning where the learner does not have control over which information is experienced). This tends to create a blind spot in our theories for how people gather information, when they decide to stop, and for how these ongoing decisions impact learning. The research in this proposal seeks to address this gap by extending theories of human learning to account for self-directed learning behaviors (i.e., situations where learners can control of the flow information they experience by way of their ongoing decisions). The proposed research addresses two specific questions relevant to the cognitive science of learning. First, how do people decide what information will be useful to know when learning? Second, what impact does self-directed learning have on the acquisition of novel concepts? In answer these questions, a computational theory of human learning is tested which attempts to explain how people make decisions to gather more information. A novel aspect of the theory is that it can account for the differences in learning resulting from either self-directed or passive learning. Understanding self-directed learning is a core issue in cognitive psychology which has potential implications for education policy. In addition, the principles identified in this research may translate into assistive learning technologies which may shorten the time required to develop expertise in a domain by tailoring training to the capabilities of individual learners. Alongside this research objective, an overarching goal of this proposal is to integrate research and training activities in computational cognitive science. An innovative training plan will prepare the next generation of psychological scientists for a field that is increasingly organized around computational approaches to the study of the mind.