This research used a spatial skills test and cognitive-mapping test to examine the effect of GIS learning on the spatial ability and spatial problem solving of college students. A total of 80 participants, undergraduate students at Texas A&M University, completed pre- and post- spatial skills tests administered during the 2003 fall semester. Analysis of changes in the students’ test scores revealed that GIS learning could help students improve their spatial ability. Strong correlations existed between the participants’ spatial ability and their performance in the GIS course. The research also found that spatial ability improvement linked to GIS learning was not significantly related to differences in gender or to academic major (geography majors vs. science and engineering majors). A total of 64 participants, recruited from students enrolled in Introduction to GIS and Computer Cartography at Texas A&M University, completed pre- and post- cognitive-mapping tests administered during the 2003 fall semester. Students’ performance on the cognitive-mapping test was used to measure their spatial problem solving. The study assumed that the analysis of the individual map-drawing strategies would reveal information about the cognitive processes participants used to solve their spatial tasks. The participants were requested to draw a map that could help their best friends find their way to three nearby commercial locations. The map-drawing process was videotaped in order to allow the researcher to classify subjects’ map-drawing strategies. The study identified two distinctive map-drawing strategies: hierarchical and regional. Strategies were classified as hierarchical when subjects began by drawing the main road network across the entire map, and as regional when they completed mapping sub-areas before moving on to another sub-area. After completion of a GIS course, a significant number of participants (about half) changed their map-drawing strategies. However, more research is necessary to address why these changes in strategy came about.

This research used a spatial skills test and cognitive-mapping test to examine the effect of GIS learning on the spatial ability and spatial problem solving of college students. A total of 80 participants, undergraduate students at Texas A&M University, completed pre- and post- spatial skills tests administered during the 2003 fall semester. Analysis of changes in the students’ test scores revealed that GIS learning could help students improve their spatial ability. Strong correlations existed between the participants’ spatial ability and their performance in the GIS course. The research also found that spatial ability improvement linked to GIS learning was not significantly related to differences in gender or to academic major (geography majors vs. science and engineering majors). A total of 64 participants, recruited from students enrolled in Introduction to GIS and Computer Cartography at Texas A&M University, completed pre- and post- cognitive-mapping tests administered during the 2003 fall semester. Students’ performance on the cognitive-mapping test was used to measure their spatial problem solving. The study assumed that the analysis of the individual map-drawing strategies would reveal information about the cognitive processes participants used to solve their spatial tasks. The participants were requested to draw a map that could help their best friends find their way to three nearby commercial locations. The map-drawing process was videotaped in order to allow the researcher to classify subjects’ map-drawing strategies. The study identified two distinctive map-drawing strategies: hierarchical and regional. Strategies were classified as hierarchical when subjects began by drawing the main road network across the entire map, and as regional when they completed mapping sub-areas before moving on to another sub-area. After completion of a GIS course, a significant number of participants (about half) changed their map-drawing strategies. However, more research is necessary to address why these changes in strategy came about.

Computer hardware and algorithm design have seen significant progress over the years. It is also seen that there are several domains in which humans are more efficient than computers. For example in image recognition, image tagging, natural language understanding and processing, humans often find complicated algorithms quite easy to grasp. This thesis presents the different case studies to learn human mapping strategy to solve the mapping problem in the area of coarse-grained reconfigurable architectures (CGRAs). To achieve optimum level performance and consume less energy in CGRAs, place and route problem has always been a major concern. Making use of human characteristics can be helpful in problems as such, through pattern recognition and experience. Therefore to conduct the case studies a computer mapping game called UNTANGLED was analyzed as a medium to convey insights of human mapping strategies in a variety of architectures. The purpose of this research was to learn from humans so that we can come up with better algorithms to outperform the existing algorithms. We observed how human strategies vary as we present them with different architectures, different architectures with constraints, different visualization as well as how the quality of solution changes with experience. In this work all the case studies obtained from exploiting human strategies provide useful feedback that can improve upon existing algorithms. These insights can be adapted to find the best architectural solution for a particular domain and for future research directions for mapping onto mesh-and- stripe based CGRAs.