Is what you measure what you get?

How can we evaluate the value proposition of information technology in management education? Although learning technologies are often sold as sources of cost savings, can it be demonstrated that corporate clients buy into these technologies because they are more productive? Although few topics related to IT in recent years have been more largely discussed than the effectiveness of e-education, the question is still open to debate. To address the larger question of learning efficacy we must gauge both what students are trying to learn through management education, and how different delivery strategies influence learning content.    This raises a new twist in the productivity paradox: learning technologies won’t contribute to management education until we understand what exactly we trying to learn.

In contrast to the fairly passionate opinions of both students and professors, published studies on learning have provided little conclusive evidence of the differences between the traditional and “virtual” classroom. In an often cited review, Thomas Russell, on the basis of several hundred research studies, found no meaningful difference in grades, satisfaction, or effectiveness among training conducted in classrooms, by postal correspondence, or through Web-based training.[1][4] Although these conclusions need to filter out potential variance caused by the learners’ profiles, subject matter and targeted learning outcomes, they suggest that e-education has a much brighter future than many current clients would suggest. Are the arguments being raised by the critics of learning technologies tied to information technology itself, or tied to the challenges of the meaning of management education today?

The impact of information technology on learning efficacy depends largely what objectives have been set for management education, and which activities are deployed to set those goals. Marc Prensky, in his work on digital learning , points out that students and organizations put under the general concept of “learning” a complex and somewhat contrasting set of  behaviours, activities and objectives.[2] Management education can attempt to teach facts through questions, exercises, and associations. On a different level, management education can seek to develop skills through imitation, feedback and repetition. On a still a different level, educators can attempt students to focus on best practices and processes through analysis, deconstruction and practice. Finally, it can be argued that management education itself should focus on influencing its participants’ mindsets through inquiry, immersion, and narrative management.

Improving learning efficacy also implies assumptions of what we mean by improving the productivity of learning organizations. In their work, Bransford, Brown, and Cocking (1999) argue convincingly that effective learning is either learner-centred, knowledge-centred, assessment-centred, or community-centred. By learner-centred the authors suggest that content delivery will be effective only if it brings to light the unique cognitive structures and understandings of the targeted participants.[3] By knowledge-centred, learning specialists like McPeck (1990) argue that delivery mechanisms must be grounded in the specificities and constraints of particular disciplines and knowledge domains (i.e. teaching mathematics can be quite different from teaching management).[4] Assessment centred learning stresses the importance of delivery mechanisms that facilitate formative evaluation to motivate, inform, and provide feedback to both learners and teachers. Finally, community centred learning implies that delivery mechanisms must mirror the social dynamics of community in which learning is to take place. In short, the role of information technology isn’t to mimic the classroom, but to mirror our vision of the nature of management education.

A third aspect of learning efficacy deals with the relationship between learning content and the context in which we are trying to learn. “Productivity” is a concept embedded in the second industrial revolution in which organizations were essentially factories that integrated technology to produce physical goods as quickly and as cheaply as possible. How relevant is such a concept of “productivity” in describing how universities, business schools and corporate learning centres elaborate their products and services? Is the goal of management education to shorten learning cycles and produce programs more inexpensively? Productivity in management education probably has less to do with the efficiency of its internal processes than the quality, innovation, and effectiveness of the students it “produces”. How can learning technologies best be deployed to enhance these types of value propositions?

Management education has rarely been viewed as essentially disseminating content, but largely viewed as pedagogy in which content is endowed with both vision and meaning. Traditional models of face to face interaction highlight this inevitable link between context and content:  apprenticeships and workshops offer forums to gauge the trade, the language and the vision that are integral parts of knowledge. The current debate over the Semantic Web recognizes the need to link content and context: how can the patterns, visions and mindsets of disciplines, industries and work be reflected directly in way we structure our information architecture. In a similar vein, how can we structure learning technologies to allow a variety of autonomous human agents (students, instructors and communities) to make sense of management education?

Information technologies can improve management education only if we can develop metrics that shed light not just on pedagogical activities and processes but on learning outcomes. Defining those measures may in itself pay by helping organizational change to emerge—rethinking business processes, rethinking organization structures of management education to focus on meeting client demands for quality, timeliness, trust, effectiveness, and so on. To contradict a well known maxim: what you measure isn’t exactly what you get.

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[1] Thomas L. Russell, No Significant Difference Phenomenon, 1999, North Carolina State University, Raleigh

[2] Prensky, M. (2000). Digital game-based learning. New York: McGraw-Hill.

[3] Bransford, J., Brown, A., & Cocking, R. (1999). How people learn: Brain, mind experience and school. Retrieved June 6, 2003, from the National Academy of Sciences Web site: http://www.nap.edu/html/howpeople1

[4] McPeck, J. (1990). Teaching critical thinking. New York: Routledge.

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