How Science Learning Activation Enables Success for Youth in Science Learning Experiences

Main Article Content

Rena Dorph
Matthew A Cannady
Christian D Schunn

Abstract

Expanding on recent advances in science education, cognitive and social psychology, and socio-cultural studies, the paper explores a construct called science learning activation and a theoretical framework that describes the characteristics, function, and impact of this construct. Authors define science learning activation as a set of dispositions, skills, and knowledge that commonly enable success in proximal science learning experiences and are in turn influenced by these successes. This study investigated the relationship between four dimensions of science learning activation (fascination, values, competency beliefs, and scientific sensemaking) and three indicators of success (choice, emotional and cognitive/behavioral engagement, and learning) in temporally proximal science learning experiences. Science learning activation, preferences to choose optional science experiences, engagement ratings, and learning outcomes were collected over multiple time points from diverse group of 681 fifth and sixth grade students from two different regions of the United States. Regression analyses, and hierarchical linear models controlling for demographic characteristics, revealed that: choice preferences were predicted by fascination, values, and sensemaking; engagement levels were predicted by competency believes, fascination, and values; and learning outcomes were predicted by scientific sensemaking. Further, successes themselves predicted further growth in activation: growth in fascination, values, and competency belief themselves were predicted by choice preferences and engagement levels; and growth in sensemaking was predicted by content learning.  Thus, science learning activation provides a theory (and corresponding set of measurement tools) for proximal outcomes of early science learning interventions that can produce positive long-term outcomes through a reoccurring reinforcement process wherein the effects of an early intervention can lead toward additional positive effects from subsequent interventions. Conversely, poor experiences can lead to negative attitudes that hinder the next learning experience and eventually away from seeking future science learning opportunities. These findings have implications for theory, practice, and research.

Article Details

Section
Research / Empirical
Author Biographies

Rena Dorph, The Lawrence Hall of Science; University of California, Berkeley

Dr. Rena Dorph is the Director for The Research Group at the University of California, Berkeley's Lawrence Hall of Science.

Matthew A Cannady, The Lawrence Hall of Science; University of California, Berkeley

Dr. Matthew A. Cannady is the Director for Quantitative Studies of The Research Group at the University of California, Berkeley's Lawrence Hall of Science.

Christian D Schunn, Learning Research and Development Center; University of Pittsburgh

Dr. Christian D. Schunn is a Senior Scientist at the Learning Research and Development Center and a Professor of Psychology, Learning Sciences and Policy, and Intelligent Systems at the University of Pittsburgh