Model-based teaching and learning about inheritance in third-grade science

ABSTRACT

Research suggests that it is challenging for elementary students to develop conceptual understanding of trait variation, inheritance of traits, and life cycles. In this study, we report on an effort to promote elementary students’ learning of hereditary-related concepts through scientific modelling, which affords opportunities for elementary students to generate visual representations of structure and function associated with heredity. This study is part of a four-year design-based research project aimed at supporting students’ learning about life science concepts using corn as a model organism. Study data were collected during the implementation of a project-developed, multi-week, model-based curriculum module in eight third-grade classrooms located in the Midwestern United States. Through mixed methods research, we analysed video recorded observations of curriculum implementation, student artefacts, and student interviews. Results illustrate epistemic dimensions of model-based explanations (MBEs) for heredity that students prioritised, as well as significant variation in students’ MBEs in 2 of the 8 classrooms. While findings show neither students’ content knowledge nor model-based instruction associated with their MBEs, qualitative differences in teachers’ curriculum enactment, and more general approaches to science instruction, may help explain observed differences. Implications are discussed for curriculum and instruction in support of students’ MBE for heredity-related concepts.     

A Hypothetical Learning Progression for Quantifying Phenomena in Science

In this article, we report on a three-pronged effort to create a hypothetical learning progression for quantification in science. First, we drew from history and philosophy of science to define the quantification competency and develop hypothetical levels of the learning progression. More specifically, the quantification competency refers to the ability to analyze phenomena through (a) abstracting relevant measurable variables from phenomena and observations, (b) investigating the mathematical relationships among the variables, and (c) conceptualizing scientific ideas that explain the mathematical relationships. The quantification learning progression contains four levels of increasing sophistication: level 1, holistic observation; level 2, attributes; level 3, measurable variables; and level 4, relational complexity. Second, we analyzed the practices in the Next Generation Science Standards for current, largely tacit, assumptions about how quantification develops (or ought to develop) through K-12 education. While several pieces of evidence support the learning progression, we found that quantification was described inconsistently across practices. Third, we used empirical student data from a field test of items in physical and life sciences to illustrate qualitative differences in student thinking that align with levels in the hypothetical learning progression for quantification. By generating a hypothetical learning progression for quantification, we lay the groundwork for future standards development efforts to include this key practice and provide guidance for curriculum developers and instructors in helping students develop robust scientific understanding.