Achievements and Challenges of Modeling-based Instruction (ACMI) in Science Education: from 1980 to 2009

This project will synthesize existing literature on modeling-based instruction (MBI) in K-12 science education over the last three decades. It will rigorously code and examine the literature to conceptualize the landscape of the theoretical frameworks of MBI approaches, identify the effective design features of modeling-based learning environments with an emphasis on technology-enhanced ones, and identify the most effective MBI practices that are associated with successful student learning through a meta-analysis.

Full Description

The University of Georgia will carry out a two-year Synthesis Project that aims to provide a comprehensive review of the research and practices for modeling-based instruction (MBI) in K-12 science education. The project will synthesize existing literature on MBI in K-12 science education over the last three decades. It will rigorously code and examine the literature to conceptualize the landscape of the theoretical frameworks of MBI approaches, identify the effective design features of modeling-based learning environments with an emphasis on technology-enhanced ones, and identify the most effective MBI practices that are associated with successful student learning through a meta-analysis.

The project will build a systematic and analytic framework to conceptualize MBI, recommend best design strategies of technology-based modeling environments, evaluate MBI teacher professional development strategies associated with improved student learning, and propose appropriate assessment strategies created to evaluate and inform MBI. In addition to the comprehensive analysis of the theory and design of MBI, a meta-analysis will study the four components of student learning: theory, design, implementation, and assessment. Based on qualified quantitative studies, an examination of the four components will be made to evaluate how different empirical studies have established their effectiveness, examine the correlations among key components, and chart the impact of associated factors on student learning.

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