Problem-Solving In the Field: Novice to Expert Geologic Mapping Strategies, Behavior, and Cognition

Learning to create geologic field maps is commonly considered to be a key component in the education of future geoscientists. Little is yet known about how students reason during field mapping, how they solve complex problems in the field, or what knowledge and skills are critical to competent mapping performance. Even less is empirically known about how professional geoscientists approach field mapping. This pilot study investigated the strategies, behaviors, and cognitive processes of novice through expert geologists as they produced bedrock maps of two field sites in Michigan's Upper Peninsula. Seven participants, including undergraduates enrolled in a field mapping course, graduate students, and professional geoscientists, represented a continuum of prior field mapping experience from none to 10+ years. Data collected from all participants included background and novelty space surveys, field maps and notes, and GPS tracks of participant movement during mapping. Additionally, three participants (one novice and two experienced mappers) recorded audio logs during the mapping exercises and participated in a follow-up interview.

Participant-generated maps were digitized and analyzed via comparison of (a) the total number of mapped units and (b) percentage of area mapped as belonging to specific lithological units. Participant GPS tracks were analyzed to determine trends in spatial patterns, identify “hot spots” of activity, and correlate tracks with mapped features. We found that expert mappers spend more time in key areas (such as contact relationships, faults, etc.) than novices, and display more economy of movement by having simpler tracks and less backtracking. Thematic content analysis of audio logs and interviews identified three key aspects of cognition during mapping: (a) navigation and spatial awareness, (b) procedural and declarative knowledge as exemplified by identification of key features, and (c) metacognitive strategies used to synthesize data, produce testable models, and continually evaluate and revise strategies and final maps.