By Jason Moll, Office of Corporate Communications, National Geospatial-Intelligence Agency (www.nga.mil), Bethesda, Md.
The National Geospatial-Intelligence Agency (NGA) and Penn State University entered into the fourth of a five-year partnership in January 2014 designed to improve how geospatial analysts learn and practice their craft. Researchers from the two organizations involved in the cooperative research and development agreement (CRADA) are studying how to improve analysts’ training and education.
The goal has led Penn State to study how the mind works, or “makes sense,” when processing geospatial information, said Todd Bacastow, director of the geospatial intelligence program at Penn State. Bacastow’s disappointment with college-level geospatial intelligence courses caused him to approach NGA about a CRADA.
“I realized that universities were teaching people how to do analysis the way we teach someone to use geospatial software,” explained Bacastow. “We never considered what it takes to make someone a good geospatial intelligence analyst.”
The academic outreach team at NGA’s National Geospatial-Intelligence College (NGC) also saw an opportunity to enhance course design, according to Kristin Anderson, the college’s academic outreach program manager. The industry outreach division of NGA’s InnoVision directorate is partnering with NGC to manage the CRADA.
“We were interested, because whatever makes Penn State’s program better is likely to make our program better,” said Anderson.
CRADA partnerships don’t involve monetary exchanges, which also benefits NGA during the currently austere fiscal times, according to Anderson.
The CRADA gave Bacastow an opportunity to sit with NGA geospatial analysts for several days in January 2013 to understand how analysts think on the job. Bacastow made a note of everything analysts did when they worked alone and in a group. One of the first things he realized is that analysts do their jobs without fully understanding the thought processes that drove them to their conclusions.
“When we asked people about their work, most of our conversations revolved around what they did and not what they thought about,” said Bacastow. “The metacognitive aspect, or how they think about their thinking, is a missing component, even though it’s sorely needed.”
Bacastow and his colleagues came to appreciate that spatial analysis is “sense making,” or the process by which humans are able to develop explanations from data that are sparse, noisy and uncertain, he said. This is a core ability of geospatial analysts.
“The analytic process starts with discovering and builds to describing, explaining, interpreting and anticipating geospatial phenomena,” explained Bacastow. “But not every analyst will be called upon to work at all levels, nor will the analyst be able to perform skillfully at a level without preparation. The question is how do we train and educate analysts to incorporate the appropriate aspects of sense making into this hierarchy of analysis when they’re solving problems?”
Individual experience dictates how analysts navigate the sense-making process, according to Bacastow. Experience is so important that clinical education should be seen as a key part of “trade-craft,” because hands-on experience also is required if one is to become an expert craftsman.
“Experience is one of the key factors that separates the very best analysts from their peers,” said Bacastow. “Since you can’t go to a reference guide and learn how to do analysis well, a lot of what you learn must be based on your experience.”
Disciplines that require hands-on learning, like the study of medicine, may have the best models for teaching geospatial analysis.
“Medicine uses clinical education, where you’re actually learning on the job while performing under the guidance of a trained and skilled clinical educator who helps you learn the craft,” noted Bacastow. “You really wouldn’t want someone to operate on you unless they’ve actually done it successfully
before—perhaps many times before—under the guidance of an expert practitioner. The same should be true for geospatial analysis.”
Instructional designers at NGC also are interested in how clinical education might be applied to training at NGA, according to Anderson. Bacastow and his Penn State colleagues are also researching different educational aids to help the learner.
“We’re looking at applications, such as mind exercises, that help the learner identify the key spatial elements of a problem, the analyst’s spatial biases, and then place these into a sense-making paradigm,” said Bacastow.
Although it is too early to tell how the CRADA’s findings will affect NGC’s programs, “anything is on the table,” said Arthur Cobb, a project scientist with NGA’s InnoVision directorate. “Whatever works and helps us produce the best analysis I’m sure would be implemented,” added Cobb.
For more information on NGA
CRADAs, contact firstname.lastname@example.org.