Using an adaptive expertise lens to understand the quality of teachers’ classroom implementation of computer-supported complex systems curricula in high school science

Abstract

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention.

Purpose: We propose a model of adaptive expertise to better understand teachers’ classroom practices as they attempt to navigate myriad variables in the implementation of biology units that include working with computer simulations, and learning about and teaching through complex systems ideas.

Sample: Research participants were three high school biology teachers, two females and one male, ranging in teaching experience from six to 16 years. Their teaching contexts also ranged in student achievement from 14–47% advanced science proficiency.

Design and methods: We used a holistic multiple case study methodology and collected data during the 2011–2012 school year. Data sources include classroom observations, teacher and student surveys, and interviews. Data analyses and trustworthiness measures were conducted through qualitative mining of data sources and triangulation of findings.

Results: We illustrate the characteristics of adaptive expertise of more or less successful teaching and learning when implementing complex systems curricula. We also demonstrate differences between case study teachers in terms of particular variables associated with adaptive expertise.

Conclusions: This research contributes to scholarship on practices and professional development needed to better support teachers to teach through a complex systems pedagogical and curricular approach.

Keywords:

• complex systems
• teaching
• adaptive expertise
• professional development
• science education

Acknowledgements

We would like to thank Josh Sheldon, Ilana Schoenfeld, Daniel Wendel, Hal Scheintaub, and David Reider for their work on various aspects of this project.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was funded by a grant from the US National Science Foundation [DRL 1019228].