Academic journal article Journal of Geoscience Education

Student Learning of Complex Earth Systems: Conceptual Frameworks of Earth Systems and Instructional Design

Academic journal article Journal of Geoscience Education

Student Learning of Complex Earth Systems: Conceptual Frameworks of Earth Systems and Instructional Design

Article excerpt


The importance of an Earth systems approach to education (Mayer, 1991; Ireton et al., 1997) has been well documented for K-12 science education (NGSS Lead States, 2013; Orion and Libarkin, 2014; The College Board, 2016), geoscience literacy (Earth Science Literacy Initiative, 2009), and geoscience workforce expertise (U.S. Bureau of Labor Statistics, 2015). An inherent feature in this approach is the idea of learners' systems thinking abilities (Orion and Libarkin, 2014). Previous review papers have identified common systems thinking challenges that students face when attempting to learn about Earth systems, such as:

* developing accurate mental models of near-surface Earth systems (Herbert, 2006);

* seeing the Earth system as a whole instead of as disconnected parts (Orion and Ault, 2007);

* encountering "sophisticated, initially counterintuitive conceptions of causality and mechanism" (Stillings, 2012, 104); and

* recognizing that Earth is a dynamic system (Orion and Libarkin, 2014).

Significant progress has been made in curriculum development and assessment of systems thinking skills in the context of Earth systems education at the K-12 level (summarized by Orion and Libarkin, 2014), but studies that explicitly address complex systems ideas such as feedback loops and emergence are sparse (Stillings, 2012; Orion and Libarkin, 2014). This is an active area of education research in other disciplines, and there is significant potential for collaboration in teaching complex systems ideas across the curriculum (Stillings, 2012). Additionally, considering the role of humans in the Earth system is of increasing importance in designing educational interventions in the Earth sciences (Manduca and Kastens, 2012; Orion and Libarkin, 2014; InTeGrate Program, 2015b).

In this systematic literature review, we identified four conceptual frameworks that illuminate how teaching and learning of Earth systems have been presented in the geoscience education research literature. These frameworks can be utilized to guide future research, inform instructional design decisions, and serve as entry points into other disciplines to foster interdisciplinary collaborations. Our findings will be of interest to a broad range of educators in Earth and environmental sciences and scholars interested in discipline-based education research related to student development of systems thinking abilities. This paper is part of a related series of two review papers. The companion paper (Holder et al., this volume) presents a review of problem solving in the geosciences and a model for engaging learners in authentic problem solving about complex near-surface Earth systems.

"Complexity" in the Earth Sciences

There have been multiple calls over the past decade to incorporate ideas from the complexity sciences into the teaching of Earth Sciences (e.g., Herbert, 2006; Turcotte, 2006; Raia, 2012). Complexity sciences have origins in both the systems science ideas developed by members of the general systems community, principally an interdisciplinary and antireductionist approach to science that emphasizes the whole system and its interactions with the environment (Hammond, 2002, 2003), and the field of cybernetics, which is concerned with the flow of information in systems (Castellani and Hafferty, 2009). The landscape of complexity sciences is in itself an intricate network of intersecting and evolving disciplines and subdisciplines (for a comprehensive graphic, see Castellani, 2013) that generally seek to understand complex systems, i.e., those in which the behavior of the system as a whole is not easily predictable from looking at the individual components (Mitchell, 2009). Such emergent behavior is only apparent at the level of the whole system (i.e., it emerges from interactions between components in often surprising ways), and a system may be self-organizing in that the system's behavior is organized, but the mechanisms controlling this behavior are not centralized (Mitchell, 2009). …

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