The Fold Analysis Challenge: A virtual globe-based educational resource. (April 2016)

• Record Type: Journal Article
• Authors: De Paor, Declan G.; Dordevic, Mladen M.; Karabinos, Paul; Tewksbury, Barbara J.; Whitmeyer, Steven J.
• Is Part Of: Journal of structural geology. Volume 85(2016:Apr.)
• Page Start: 85
• Page End: 94
• Publication Date: 2016-04
• Subjects: Google Earth -- Cesium -- Geological education -- Educational games -- Sheep Mountain WY; Geology, Structural -- Periodicals; Géomorphologie structurale -- Périodiques; Geology, Structural; Periodicals; 551.805
• DOI: 10.1016/j.jsg.2016.02.005
• Languages: English
• ISSNs: 0191-8141

Abstract

Abstract: We present an undergraduate structural geology laboratory exercise using the Google Earth virtual globe with COLLADA models, optionally including an interactive stereographic projection and JavaScript controls. The learning resource challenges students to identify bedding traces and estimate bedding orientation at several locations on a fold, to fit the fold axis and axial plane to stereographic projection data, and to fit a doubly-plunging fold model to the large-scale structure. The chosen fold is the Sheep Mountain Anticline, a Laramide uplift in the Big Horn Basin of Wyoming. We take an education research-based approach, guiding students through three levels of difficulty. The exercise aims to counter common student misconceptions and stumbling blocks regarding penetrative structures. It can be used in preparation for an in-person field trip, for post-trip reinforcement, or as a virtual field experience in an online-only course. Our KML scripts can be easily transferred to other fold structures around the globe. Graphical abstract: Highlights: We created a fold analysis lab exercise using Google Earth and COLLADA models. Students are challenged to fit a semi-transparent plane to inclined bedding planes. An inset interactive stereographic net responds to changes in planes on the map. Students must best–fit a fold axis and axial plane to the bedding data. In one version, the computer auto-scores student work and awards medallions based on stored data.