CPResearch conducts a wide variety of behavioral research to support the development of command performance.
CPResearch uses a combination of behavioral research and educational program evaluation findings to optimally fit instructional designs to learner need and provider readiness.
CPResearch has been involved in educational program evaluation since its founding, investigating ways to conceptualize and measure the adult learning process.
Today's professionals must learn more in less time than ever before. Perhaps most importantly, they must learn how to learn in order to keep pace with a rapidly changing work environment. Technology-assisted instruction must be carefully designed to promote critical, flexible thinking and greater attunement to the outside world in order to support what professionals must do every day.
We conduct the applied behavioral research that drives this creative design process. Specifically, we examine work environments to determine exactly what expert performance “looks like;” we reach back to learning theory and instructional design practices to identify the optimal methods for promoting skill acquisition; and we explore the organizational characteristics that have implications for how to implement training and education effectively.
Learner Performance Analysis is the examination of the operational performance requirements that must be met via training or education. Rather than targeting knowledge, skills, and abilities, learner performance analysis focuses on the behaviors that enable individuals or groups to adapt to (or shape) the environment in which they work. Specifying operational performance requirements enables more precisely defined learning objectives, better selection of instructional strategies, and enhanced design of educational technologies, all of which promote the transfer of learning to work performance.
Of particular interest in a global knowledge economy are the operational performance requirements associated with solving persistent, complex problems via diverse groups of experts, many of whom are not located in the same physical place. In recent years, our research has explored the operational performance requirements of:
The methods we use allow us to generalize our findings from one context to others such that our analyses build on one another and enable cost-effective research studies.
Cianciolo, A. T., Evans, K. M., DeCostanza, A. H., & Pierce, L. G. (in press). Trust in distributed military operations. To appear in N. Stanton (Ed.), Trust in Military Teams. Surrey, England: Ashgate Publishing, Ltd.
Evans, K. M., Cianciolo, A. T., Hunter A. E., & Pierce, L. G. (2010). Modeling interpersonal trust in distributed command and control teams. Proceedings of the 15th International Command and Control Research & Technology Symposium. Santa Monica, CA.
Cianciolo, A. T., LaVoie, N., Foltz, P., & Pierce, L. G. (2009). Augmented performance environment for enhancing interagency coordination in stability, security, transition, and reconstruction (SSTR) operations (Tech. Rep. 1246). Arlington, VA: U. S. Army Research Institute for the Behavioral and Social Sciences.
Cianciolo, A. T., LaVoie, N., Lauper, U., & Foltz, P. (2008). Emerging concepts in interagency coordination training. Proceedings of the Interservice/Industry Training, Simulation, & Education Conference (I/ITSEC). Orlando, FL.
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Instructional design is the application of learning theory to the selection of instructional strategies and learning environments, which drive the development of training and educational content. When linked to operational performance requirements,sound instructional design promotes rapid skill acquisition that transfers to the work environment. Founding instructional design on theory produces generalizable approaches that may be applied to different operational performance requirements or work environments.
The design of technology-assisted instruction must take into account the full range of environments in which adults learn, including virtual classrooms, online discussion forums, and even on the job. In recent years, we have explored instructional designs that include:
Cianciolo, A. T. & Evans, K. M. (in press). Distributed communities of practice. To appear in J. Lee & A. Kirlik (Eds.), Oxford Handbook of Cognitive Engineering. New York: Oxford University Press.
Cianciolo, A. T., LaVoie, N., Foltz, P., & Pierce, L. G. (2009). Augmented performance environment for enhancing interagency coordination in stability, security, transition, and reconstruction (SSTR) operations (Tech. Rep. 1246). Arlington, VA: U. S. Army Research Institute for the Behavioral and Social Sciences.
Cianciolo, A. T., LaVoie, N., Lauper, U., & Foltz, P. (2008). Emerging concepts in interagency coordination training. Proceedings of the Interservice/Industry Training, Simulation, & Education Conference (I/ITSEC). Orlando, FL.
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Cianciolo, A. T., Cianciolo, D., Prevou, M. I., & Morris, R. F. (2007). Using digital storytelling to stimulate discussion in Army professional forums. Proceedings of the Interservice/Industry Training, Education, & Simulation Conference (I/ITSEC). Orlando, FL. Best Paper Nominee
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Organizational characteristics arguably have the greatest impact on the success or failure of professional development initiatives. Successfully implementing training and education involves specifying the chain of events that lead to achieving expected program outcomes and ensuring that each link in the chain is sound. Such links include resources, facilities, instructor preparation, and learner readiness. To implement technology-assisted instruction, the organization also must consider the technical capabilities required to support and engage in learning.
In recent years, we have supported organizational implementation by investigating:
Although each analysis is different, we have produced a generalizable framework for investigating organizational readiness to implement technology-assisted professional development.
Cianciolo, A. T., Grover, J., Bickley, W. R., & Manning, D. (2011). Problem-based learning: Instructor characteristics, competencies, and professional development (Research Report No. 1936). Arlington, VA: U. S. Army Research Institute for the Behavioral and Social Sciences.
Cianciolo, A. T. (2008). Program Evaluation Metrics for U.S. Army Lifelong Learning Centers (LLCs): Extension to Military Operational Specialty (MOS)-Based LLCs (Study Report No. 2008-05). Arlington, VA: U.S. Army Research Institute for the Behavioral and Social Sciences.
Cianciolo, A. T. (2008). Further investigations of Army Lifelong Learning: An enhanced assessment framework. Proceedings of the Interservice/Industry Training, Simulation, & Education Conference (I/ITSEC). Orlando, FL.
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Cianciolo, A. T. (2007). Program evaluation metrics for U.S. Army Lifelong Learning Centers (Technical Report No. 1196). Alexandria, VA: U.S. Army Research Institute for the Behavioral and Social Sciences.
Cianciolo, A. T. (2007). U.S. Army lifelong learning: Program assessment metrics and initial results. Proceedings of the Interservice/Industry Training, Education, & Simulation Conference (I/ITSEC). Orlando, FL.
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