@article{kaber_perry_segall_sheik-nainar_2007, title={Workload state classification with automation during simulated air traffic control}, volume={17}, ISSN={["1532-7108"]}, DOI={10.1080/10508410701527860}, abstractNote={Real-time operator workload assessment and state classification may be useful for decisions about when and how to dynamically apply automation to information processing functions in aviation systems. This research examined multiple cognitive workload measures, including secondary task performance and physiological (cardiac) measures, as inputs to a neural network for operator functional state classification during a simulated air traffic control (ATC) task. Twenty-five participants performed a low-fidelity simulation under manual control or 1 of 4 different forms of automation. Traffic volume was either low (3 aircraft) or high (7 aircraft). Participants also performed a secondary (gauge) monitoring task. Results demonstrated significant effects of traffic volume (workload) on aircraft clearances (p < .01) and trajectory conflicts (p < .01), secondary task performance (p < .01), and subjective ratings of task workload (p < .01). The form of ATC automation affected the number of aircraft collisions (p < .05), secondary task performance (p < .01), and heart rate (HR; p < .01). However, heart rate and heart rate variability measures were not sensitive to the traffic manipulation. Neural network models of controller workload (defined in terms of traffic volume) were developed using the secondary task performance and simple heart rate measure as inputs. The best workload classification accuracy using a genetic algorithm (across all forms of ATC automation) was 64%, comparable to prior work. Additional neural network models of workload for each mode of ATC automation revealed substantial variability in predictive accuracy, based on the characteristics of the automation. Secondary task performance was a highly sensitive indicator of ATC workload, whereas the heart rate measure appeared to operate as a more global indicator of workload. A limited range of cardiac response might be sufficient for the demands of the brain in ATC. The results have applicability to design of future adaptive systems integrating neural-network-based workload state classifiers for multiple forms of automation.}, number={4}, journal={INTERNATIONAL JOURNAL OF AVIATION PSYCHOLOGY}, author={Kaber, David B. and Perry, Carlene M. and Segall, Noa and Sheik-Nainar, Mohamed A.}, year={2007}, pages={371–390} }
 @article{kaber_perry_segall_mcclernon_prinzel_2006, title={Situation awareness implications of adaptive automation for information processing in an air traffic control-related task}, volume={36}, ISSN={0169-8141}, url={http://dx.doi.org/10.1016/j.ergon.2006.01.008}, DOI={10.1016/j.ergon.2006.01.008}, abstractNote={The objective of this research was to assess the effectiveness of adaptive automation (AA) for supporting information processing (IP) in a complex, dynamic control task by defining a measure of situation awareness (SA) sensitive to differences in the forms of automation. The task was an air traffic control (ATC)-related simulation and was developed to present four different modes of automation of IP functions, including information acquisition, information analysis, decision making and action implementation automation, as well as a completely manual control mode. A total of 16 participants were recruited for a pilot study and primary experiment. The pilot assessed the sensitivity and reliability of the Situation Awareness Global Assessment Technique (SAGAT) for describing AA support of the IP functions. Half of the participants were used in the primary experiment, which refined the SA measure and described the implications of AA for IP on SA using the ATC-like simulation. Participants were exposed to all forms of automation and manual control. AA conditions matched operator workload states to dynamic control allocations in the primary task. The pilot did not reveal significant differences in SA among the various AA conditions. In the primary experiment, participant recall of aircraft was cued and relevance weights were assigned to aircraft at the time of simulation freezes. The modified measure of SA revealed operator perception and Total SA to improve when automation was applied to the information acquisition function. In both experiments, performance in the ATC-related task simulation was significantly superior when automation was applied to information acquisition and action implementation (sensory and motor processing), as compared to automation of cognitive functions, specifically information analysis. The primary experiment revealed information analysis and decision-making automation to cause higher workload, attributable to visual demands of displays. The results of this research may serve as a general guide for the design of adaptive automation functionality in the aviation industry, particularly for information processing support in air traffic control tasks.}, number={5}, journal={International Journal of Industrial Ergonomics}, publisher={Elsevier BV}, author={Kaber, David B. and Perry, Carlene M. and Segall, Noa and McClernon, Christopher K. and Prinzel, Lawrence J., III}, year={2006}, month={May}, pages={447–462} }
 @article{segall_doolen_porter_2005, title={A usability comparison of PDA-based quizzes and paper-and-pencil quizzes}, volume={45}, ISSN={["1873-782X"]}, DOI={10.1016/j.compedu.2004.05.004}, abstractNote={In the last few years, schools and universities have incorporated personal digital assistants (PDAs) into their teaching curricula in an attempt to enhance students’ learning experience and reduce instructors’ workload. One of the most common uses of PDAs in the classroom is as a test administrator. This study compared the usability effectiveness, efficiency, and satisfaction of a PDA-based quiz application to that of standard paper-and-pencil quizzes in a university course. Effectiveness was measured as students’ quiz scores and through a mental workload questionnaire; efficiency was the time it took students to complete each quiz; and satisfaction was evaluated using a subjective user satisfaction questionnaire. The study showed the PDA-based quiz to be more efficient, that is, students completed it in less time than they needed to complete the paper-and-pencil quiz. No differences in effectiveness and satisfaction were found between the two quiz types. Computer anxiety was not affected by the quiz type. For these reasons, as well as other advantages to both students (e.g., real-time scoring) and teachers (e.g., less time spent on grading), PDAs are an attractive test administration option for schools and universities.}, number={4}, journal={COMPUTERS & EDUCATION}, author={Segall, N and Doolen, TL and Porter, JD}, year={2005}, month={Dec}, pages={417–432} }