Program Announcement: Cognition and Student Learning CFDA 84.305A

Program Officers:
Dr. Carol O'Donnell
Carol.ODonnell@ed.gov
(202) 208-3749

Purpose

The purpose of the Cognition and Student Learning (Cognition) research program is to improve student learning by applying recent advances in cognitive science to education practice. The objectives of the Cognition research program are to: (1) explore underlying processes involved in reading, writing, mathematics, or science that are associated with student achievement in the relevant domain, for the purpose of identifying potential targets of intervention; (2) develop innovative interventions—instructional approaches, practices, and curricula—for improving student learning; (3) establish the efficacy of fully developed interventions and approaches for improving student learning with efficacy or replication trials; and (4) develop and/or validate measurement tools that can be used to improve student learning and achievement.

The long-term outcome of this program will be an array of tools and strategies (e.g., instructional approaches, computer tutors) that are based on principles of learning and information processing gained from cognitive science and that have been documented to be efficacious for improving learning in education delivery settings from prekindergarten through high school and for vocational or adult basic education or developmental (remedial)/bride programs for under-prepared college students.

Background

The most important outcome of education is student learning. Recent advances in understanding learning have come from cognitive science, as well as cognitive and developmental psychology, but these advances have not been widely or systematically tapped in education. The Institute intends for the Cognition research program to establish a scientific foundation for education by building on these theoretical and empirical advances and applying them to education practice with the goal of improving student learning and academic achievement. The Institute is supporting research on this topic to bridge basic cognitive science and education.

Cognitive science has shown explosive growth in the last 30 years. Basic laboratory research in cognitive science within disciplines such as psychology, linguistics, and neuroscience has generated new and important fundamental knowledge on how people learn. Cognitive scientists have identified a number of basic principles of learning that are supported by a solid research base (for examples, see Carver and Klahr 2001). For the most part, however, these research principles have not been incorporated into education practice, either at the level of instruction or through the creation of materials that support teaching and learning.

Authentic education settings are often quite different from the laboratory. Contrasted with learning in laboratory settings, learning in everyday instructional settings typically involves content of greater complexity and scope, delivered over much longer periods of time, with much greater variability in delivery, and with far more distractions and competitors for student time and effort. Moreover, the parameters that have defined "learning" in laboratory experiments are often not the same as what defines learning in school. For example, in laboratory experiments, learning is typically defined as having occurred if individuals can recall an item a few minutes or hours after presentation; rarely are individuals asked to recall items days, weeks, or months after presentation. In school, however, students are expected to remember information presented in September the following May, and to be able to use that information in subsequent years. Students in school are expected to learn sets of related concepts and facts, and to build on that knowledge over time. Before some principles of learning generated from research in cognitive science can be applied to instruction in classroom settings, we need to understand if the principles generalize beyond well-controlled laboratory settings to the complex cognitive and social conditions of the classroom.

Through the Cognition research program, the Institute supports research that utilizes cognitive science to develop innovative approaches intended to improve teaching and learning in authentic education settings. For typical Cognition projects, researchers begin by identifying a specific learning or instructional problem in schools, consider which findings from the empirical literature might be relevant to tackling the problem, and then propose a research plan for translating those findings into an education strategy that addresses the problem. Researchers should note that the Institute is interested in the development of strategies and materials that involve students learning educationally meaningful or relevant components or units of academic content, such as would be covered in a chapter or multiple chapters addressing a topic or learning goal in a textbook. The Institute strongly encourages cognitive scientists to collaborate with education researchers who understand teaching and learning in the context of authentic education settings.

Under Goal One (Exploration), the Institute funds projects designed to explore the cognitive processes underlying the acquisition of reading, writing, mathematics knowledge and skills, science knowledge and skills, or general study skills. This is translational research intended to inform the development of innovative programs, practices, or products to improve student outcomes. Such studies might include short-term longitudinal studies in which the objective is to identify the component processes and skills that are: (a) highly correlated with reading, writing, mathematics, or science proficiency in academic settings; and (b) can be improved, accelerated, or advanced through instruction. In order for applications to be competitive, the researcher should make explicit the hypothesized link between the underlying cognitive process and improving academic achievement. That is, it is not sufficient to propose research to simply examine cognitive processes or skills. The objective here is to gain a better understanding of which processes and skills are predictive of subsequent proficiency in reading, writing, mathematics, science, or study skills that would allow researchers to develop interventions (e.g., curricula or instructional approaches) that target these processes and ultimately result in improving academic achievement. For example, a researcher might propose to measure early mathematical skills and correlate differences in the emergence of these skills with measures of academic achievement (e.g., performance on mathematics achievement tests in the elementary grades). Other Cognition Goal One projects might explore the underlying processes that explain learning problems (difficulties) that occur in authentic education settings. In these cases, researchers might begin by identifying a constellation of observed behaviors indicating an academic learning problem, and then propose a research plan to systematically explore possible causal explanations for that problem. For example, a group of first grade students may struggle with mastering addition facts, and repeated practice does not appear to improve the students' mastery of these facts. Researchers could propose to examine whether this problem was associated with a failure to initially learn the facts or a failure to retrieve the facts at the time of testing. If the first experiments indicate that students fail at initial learning, the research team could further examine if that initial failure to learn was explained by attentional patterns or visual spatial processing of the components of equations. As with all Goal One proposals, strong applications would include a rationale that justifies the plausibility of developing interventions that might improve the targeted underlying skills.

In addition, the Institute encourages projects that address how principles and knowledge emerging from research in cognitive science can be used to better understand teacher knowledge and classroom practice, in order to improve teacher instructional practices and ultimately student learning. For example, researchers could identify teachers whose students typically gain more than students of the average teacher, conduct detailed observations to compare the instructional practices of high-gain teachers with average-gain teachers, and use these data to identify instructional approaches or patterns of instructional strategies that distinguish the two groups. The ultimate objective would be to obtain an understanding of the instructional approaches of high-gain teachers that would lead to the development of interventions.

References

Carver, S. M., & Klahr, D. (Eds.). (2001). Cognition and instruction: Twenty-five years of progress. Mahwah, NJ: Lawrence Erlbaum Associates, Publishers.