The Little and Often Principle
Timely and Iterative Feedback in Management Learning:
An Empirical Analysis
Bryan Jones, Mammed Bagher, Dearne Valley Business
School, Doncaster, UK.
This paper considers/proposes a learning framework that might apply to
both study and to work. The framework focuses on the nature and timeliness of
feedback mechanisms. Key to the efficacy of this approach is understanding whether
reflexive learning, e.g. like learning how to ride a bike, is transferable to study and to
management contexts. If we consider that we learn how to ride a bike by continuously
avoiding falling off, then the key mechanism operating is continuous feedback: i.e.
reflexiveness (instantaneous assessment); and iterativeness (an increased frequency of
assessment). Thus the individual framework, once established, is continuously revised and
updated through practice and evaluation.
In asking managers whether they can explain how they learn, there are some common answers:
by experience, by questioning and No. Very few
managers articulate a conscious definition of how they, as an individual, think that they
learn. More significantly, whilst Business Schools and learning organisations
encourage more use of management learning frameworks, there are limitations in predicting
the value of such frameworks for a manager over time. It is not clear whether an
individuals ability to articulate learning, as defined by their work as a student,
is a precursor to success as a manager.
In order to achieve the above consideration, the paper utilises both qualitative and
quantitative data in a form of semi-structured interviews and questionnaires from Business
schools management students, both under and post graduate. Management consultancy clients
of the business school, together with the academic staff at Dearne Valley Business School.
A particular contribution of this paper is the consideration of parallel between the
theory and practice.
Key Words: Learning, Learning styles, Retention, Management, Continuous, Learning Methods,
learning environment