A NATURALISTIC COMPUTATIONAL MODEL OF HUMAN BEHAVIOR IN NAVIGATION AND SEARCH TASKS

Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.

Understanding "Just Enough" Computer Users: Motivation Style and Proficiency

Among daily computer users who are proficient, some are flexible at accomplishing unfamiliar tasks on their own and others have difficulty. Software designers and evaluators involved with Human Computer Interaction (HCI) should account for any group of proficient daily users that are shown to stumble over unfamiliar tasks. We define "Just Enough" (JE) users as proficient daily computer users with predominantly extrinsic motivation style who know just enough to get what they want or need from the computer. We hypothesize that JE users have difficulty with unfamiliar computer tasks and skill transfer, whereas intrinsically motivated daily users accomplish unfamiliar tasks readily. Intrinsic motivation can be characterized by interest, enjoyment, and choice and extrinsic motivation is externally regulated. In our study we identified users by motivation style and then did ethnographic observations. Our results confirm that JE users do have difficulty accomplishing unfamiliar tasks on their own but had fewer problems with near skill transfer. In contrast, intrinsically motivated users had no trouble with unfamiliar tasks nor with near skill transfer. This supports our assertion that JE users know enough to get routine tasks done and can transfer that knowledge, but become unproductive when faced with unfamiliar tasks. This study combines quantitative and qualitative methods. We identified 66 daily users by motivation style using an inventory adapted from Deci and Ryan (Ryan and Deci 2000) and from Guay, Vallerand, and Blanchard (Guay et al. 2000). We used qualitative ethnographic methods with a think aloud protocol to observe nine extrinsic users and seven intrinsic users. Observation sessions had three customized phases where the researcher directed the participant to: 1) confirm the participant's proficiency; 2) test the participant accomplishing unfamiliar tasks; and 3) test transfer of existing skills to unfamiliar software.

Driver Safety in Far-side and Far-oblique Crashes: A Study of Patrol Vehicles in the United States of America

The dissertation titled "Driver Safety in Far-side and Far-oblique Crashes" presents a novel approach to assessing vehicle cockpit safety by integrating Human Factors and Applied Mechanics. The methodology of this approach is aimed at improving safety in compact mobile workspaces such as patrol vehicle cockpits. A statistical analysis performed using Michigan state's traffic crash data to assess various contributing factors that affect the risk of severe driver injuries showed that the risk was greater for unrestrained drivers (OR=3.38, p<0.0001) and for incidents involving front and far-side crashes without seatbelts (OR=8.0 and 23.0 respectively, p<0.005). Statistics also showed that near-side and far-side crashes pose similar threat to driver injury severity. A Human Factor survey was conducted to assess various Human-Machine/Human-Computer Interaction aspects in patrol vehicle cockpits. Results showed that tasks requiring manual operation, especially the usage of laptop, would require more attention and potentially cause more distraction. A vehicle survey conducted to evaluate ergonomics-related issues revealed that some of the equipment was in airbag deployment zones. In addition, experiments were conducted to assess the effects on driver distraction caused by changing the position of in-car accessories. A driving simulator study was conducted to mimic HMI/HCI in a patrol vehicle cockpit (20 subjects, average driving experience = 5.35 years, s.d. = 1.8). It was found that the mounting locations of manual tasks did not result in a significant change in response times. Visual displays resulted in response times less than 1.5sec. It can also be concluded that the manual task was equally distracting regardless of mounting positions (average response time was 15 secs). Average speeds and lane deviations did not show any significant results. Data from 13 full-scale sled tests conducted to simulate far-side impacts at 70 PDOF and 40 PDOF was used to analyze head injuries and HIC/AIS values. It was found that accelerations generated by the vehicle deceleration alone were high enough to cause AIS 3 - AIS 6 injuries. Pretensioners could mitigated injuries only in 40 PDOF (oblique) impacts but are useless in 70 PDOF impacts. Seat belts were ineffective in protecting the driver's head from injuries. Head would come in contact with the laptop during a far-oblique (40 PDOF) crash and far-side door for an angle-type crash (70 PDOF). Finite Element analysis head-laptop impact interaction showed that the contact velocity was the most crucial factor in causing a severe (and potentially fatal) head injury. Results indicate that no equipment may be mounted in driver trajectory envelopes. A very narrow band of space is left in patrol vehicles for installation of manual-task equipment to be both safe and ergonomic. In case of a contact, the material stiffness and damping properties play a very significant role in determining the injury outcome. Future work may be done on improving the interiors' material properties to better absorb and dissipate kinetic energy of the head. The design of seat belts and pretensioners may also be seen as an essential aspect to be further improved.

An Experience-Driven Pedagogy for the Instruction of Software Testing in Computer Science

In the realm of computer programming, the experience of writing a program is used to reinforce concepts and evaluate ability. This research uses three case studies to evaluate the introduction of testing through Kolb's Experiential Learning Model (ELM). We then analyze the impact of those testing experiences to determine methods for improving future courses. The first testing experience that students encounter are unit test reports in their early courses. This course demonstrates that automating and improving feedback can provide more ELM iterations. The JUnit Generation (JUG) tool also provided a positive experience for the instructor by reducing the overall workload. Later, undergraduate and graduate students have the opportunity to work together in a multi-role Human-Computer Interaction (HCI) course. The interactions use usability analysis techniques with graduate students as usability experts and undergraduate students as design engineers. Students get experience testing the user experience of their product prototypes using methods varying from heuristic analysis to user testing. From this course, we learned the importance of the instructors role in the ELM. As more roles were added to the HCI course, a desire arose to provide more complete, quality assured software. This inspired the addition of unit testing experiences to the course. However, we learned that significant preparations must be made to apply the ELM when students are resistant. The research presented through these courses was driven by the recognition of a need for testing in a Computer Science curriculum. Our understanding of the ELM suggests the need for student experience when being introduced to testing concepts. We learned that experiential learning, when appropriately implemented, can provide benefits to the Computer Science classroom. When examined together, these course-based research projects provided insight into building strong testing practices into a curriculum.