There is a large gap between the ability of experts and
students in grasping spatial concepts and representations.
Engineering and the geosciences require the highest expertise
in spatial thinking, and weak spatial skills are a significant
barrier to success for many students [1]. Spatial skills are also
highly malleable [2]; therefore, a current challenge is to
identify how to promote students’ spatial thinking.
Interdisciplinary research on how students think about
spatially-demanding problems in the geosciences has
identified several major barriers for students and interventions
to help scaffold learning at a variety of levels from high
school through upper level undergraduate majors. The
Geoscience Education Transdisciplinary Spatial Learning
Network (GET-Spatial; http://serc.carleton.edu/getspatial/) is
an NSF-funded collaboration between geoscientists, cognitive
psychologists, and education researchers. Our goal is to help
students overcome initial hurdles in reasoning about spatial
problems in an effort to diversify the geoscience workforce.
Examples of spatial problems in the fields of
geochemistry include scaling, both in size and time;
penetrative thinking to make inferences about internal
structures from surface properties; and graph-reading,
especially ternary diagrams. Understanding scales outside of
direct human experience, both very large (e.g.
cosmochemistry, deep time) and very small (e.g. mineralogy,
nanoparticles) can be acutely difficult for students. However,
interventions have successfully resulted in improvements to
scale estimations and improve exam performance [3].
We will discuss best practices for developing effective
interdisciplinary teams, and how to overcome challenges of
working across disciplines and across grade levels. We will
provide examples of spatial interventions in scaling and
penetrative thinking.
[1] Hegarty et al. (2010) in Spatial Cognition VII 6222, 85-
94. [2] Uttal et al. (2012) Psychology of Learning and
Motivation 57, 147-181. [3] Resnick et al. (2016)
Educational Psychology Review, 1-15.
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Using an engagement lens to model active learning in the geosciences
Active learning research emerged from the undergraduate STEM education communities of practice, some of whom identify as discipline-based education researchers (DBER). Consequently, current frameworks of active learning are largely inductive and based on emergent patterns observed in undergraduate teaching and learning. Alternatively, classic learning theories historically originate from the educational psychology community, which often takes a theory-driven, or deductive research approach. The broader transdisciplinary education research community is now struggling to reconcile the two. That is, how is a theory of active learning distinct from other theories of knowledge construction? We discuss the underpinnings of active learning in the geosciences, drawing upon extant literature from the educational psychology community on engagement. Based on Sinatra et al. engagement framework, we propose a model for active learning in the geosciences with four dimensions: behavioral, emotional, cognitive, and agentic. We then connect
existing literature from the geoscience education community to the model to demonstrate the current gaps in our literature base and opportunities to move the active learning geoscience education research (GER) forward. We propose the following recommendations for future investigation of active learning in the geosciences: (1) connect future GER to our model of active learning in the geosciences, (2) measure more than content learning, (3) document research methods and outcomes with effect sizes to accumulate evidence, and (4) prioritize research on dimensions of active learning essential to the geosciences.
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- NSF-PAR ID:
- 10295405
- Editor(s):
- Hannula, K.
- Date Published:
- Journal Name:
- Journal of Geoscience Education
- ISSN:
- 1089-9995
- Page Range / eLocation ID:
- 1 to 33
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1080/10899995.2021.1913715
