|When considering the general issue of
training future managers in statistics, it might be useful to make a distinction
between those who will work in industry and those who will work in general
Indeed, most managers do not deal with complex statistical issues in person.
Yet, they must master the core concepts of statistics and be familiar with
the main objectives of statistical methods. They should be in a position
to 1- raise the right questions, and 2- analyse and interpret the solutions
proposed by statisticians.
Thus, devising a training program for future managers is complex for
the following reasons:
- It proves impossible to teach the theoretical bases of the statistical
methods used in businesses, since most French management students do not
master the necessary math. That can only amplify the "epistemological
anxiety" (Wilenski, 1997) which students feel in front of concepts
whose legitimacy they question.
- Moreover, it does not suffice to present examples of how statistical
problems are solved in businesses to elicit the students' interest and
allow them to become familiar with the concepts. It has long been known
that it is difficult to bridge the gap between theory and realities in
the field (Boaler, 1994, Hahn, 2000, Lave, 1998, Nunes, 1993).
- Lastly, the use of new technologies (Galbraith & Haines, 1998) adds
to legitimacy-related concerns. Yet, these tools must be used in statistics.
Under specific conditions, though, it has been observed that they do motivate
students (Kulik, 1994).
Given the above-mentioned difficulties, some institutions of higher learning
are content with presenting a few recipes which will hopefully allow students
to interpret the output of "technological black boxes" (Keitel
et al., 1993).
Even though the authors of this paper believe strongly that it is not
necessary for future managers to master the mathematical aspects of statistics,
they are convinced that it is not enough to teach students how to manage
this relation of " input/output " (Keitel et al., 1993). Training
in statistics must be adapted to the students' needs, in particular to
help them make the right decisions in their future corporate environment.
Besides, the authors of this paper think it is necessary to implement
new pedagogical approaches which address each student's difficulties and
In the course of their presentation, the authors first show a few examples
of the types of on-the-job problems future managers are likely to meet
in such fields as marketing and strategy which illustrate how poor knowledge
of statistical concepts and an inability to analyse statistical data can
lead to grave mistakes.
Then, they explain how a field survey has led them to adjust the spirit
and the contents of the program they offer, which stresses data analysis
more than the fundamentals of the statistical inference.
They also review the difficulties which are specific to the teaching of
statistics in schools of management. Over the past few years, these difficulties
have led them to experiment with several systems which are based on information
and communication technologies (Dassonville, 1997, Dassonville & Hahn,
Lastly, they present an assessment of the latest system they have devised
and experimented with: an e-learning platform which in particular involves
collective and individual synchronous tutoring
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