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Abstract

The rapid advancement of information technology (IT) is making it difficult for organizations to maintain end user knowledge and skills, and poor user performance negatively impacts the return on investment (ROI) for IT. Conventional training fails to meet the rapidly emerging learning needs of users, costs too much to provide the “just-in-time” learning that is needed, and fails to establish necessary contextual ties between learning and work processes. A solution to this challenge is proposed in the form of embedded learning events that are integrated with IT software tools and made available to users during the conduct of required job tasks. This approach reduces the cost of learning by precluding formal training and increasing the contextual relevance of learning activities. Certain IT capabilities and the learning strategies they afford are identified, mapped to “ROI Factors” and used to estimate the impact of different types of embedded IT learning on the return on investment for information technology.

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References

Britton

B. K.

Tidwell

(1995). Cognitive structure testing: A computer system for diagnosis of expert-novice differences. In Nichols

P. D.

Chipman

S. F.

Brennan

R. L.

(Eds.), Cognitive diagnostic assessment (pp. 251–278). Hillsdale, NJ: Lawrence Erlbaum.

Hammer

Champy

(1993). Reengineering the corporation. New York: HarperCollins.

Goldsmith

T. E.

Kraiger

(1997). Applications of structural knowledge assessment to training evaluation (pp. 73–96). In Ford

J. K.

(Ed.) Improving training effectiveness in work organizations. Mahwah, NJ: Lawrence Erlbaum.

Marquardt

Reynolds

(1994). The global learning organization. New York: Richard D. Irwin, Inc.

Mattoon

J. S.

(1994). Designing instructional simulations: Effects of instructional control and type of training task on developing display-interpretation skills. The International Journal of Aviation Psychology, 4(3), 189–209.

Mattoon

J. S.

(1996). Modeling and simulation: A rationale for implementing new technologies. Educational Technology, 36(4), 17–26.

Mattoon

J. S.

, (1999). Achieving an acceptable return on investment from training technology. In Proceedings of the 19th Interservice/Industry Training Systems and Education Conference. Orlando, FL: The National Training Systems Association.

Mayer

R. E.

(1998). A split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology, 90(2), 312–320.

Mayer

R. E.

Sims

V. K.

(1994). For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning. Journal of Educational Psychology, 86(3), 389–401.

10.

Murray

W. R.

(1990). A blackboard-based dynamic instructional planner. Proceedings of the 8th National Conference on Artificial Intelligence (pp. 434–441). Menlo Park, CA: AAAI Press.

11.

Paivio

Linde

(1982). Imagery, memory, and the brain. Canadian Journal of Psychology, 36(2), 243–272.

12.

Rifkin

(1995). The end of work. New York: G. P. Putnam's Sons.

13.

Schnitt

D. L.

(1993). Reengineering the organization using information technology. Journal of Systems Management, 44(1), 14–20, 41–42.

14.

Steffe

L. P.

Gale

, (Eds.) (1995). Constructivism in education. Hillsdale, NJ: Lawrence Erlbaum Associates.

Metrics for Assessing Return on Investment from Information Technology

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