Modeling meaningful learning in chemistry using structural equation modeling

Abstract

Ausubel and Novak's construct of meaningful learning stipulates that substantive connections between new knowledge and what is already known requires the integration of thinking, feeling, and performance (Novak J. D., (2010), Learning, creating, and using knowledge: concept maps as facilitative tools in schools and corporations, New York, NY: Routledge Taylor & Francis Group.). This study explores the integration of these three domains using a structural equation modeling (SEM) framework. A tripartite model was developed to examine meaningful learning through the correlational relationships among thinking, feeling, and performance using student responses regarding Intellectual Accessibility and Emotional Satisfaction on the Attitudes toward the Subject of Chemistry Inventory version 2 (ASCI V2) and performance on the American Chemical Society exam. We compared the primary model to seven alternatives in which correlations were systematically removed in order to represent a lack of interconnectedness among the three domains. The tripartite model had the strongest statistical fit, thereby providing statistical evidence for the construct of meaningful learning. Methodological issues associated with SEM techniques, including problems related to non-normal multivariate distributions (an assumption of traditional SEM techniques), and causal relationships are considered. Additional findings include evidence for weak configural invariance in the pre/post implementation of the ASCI(V2), mainly due to the poor structure of the pretest data. The results are discussed in terms of their implications for teaching and learning.