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Unit 23: Quality Management in Education: Challenges

Manpower or human resources measures include the number of personal of different types, often Notes
expressed as ratios in relation to student numbers at each level. They also include background
information about these personal such as educational qualifications, experience, and perhaps
knowledge competencies and attitudes.
Educational outputs refer to the consequences of the educational process as reflected in measures
such as the levels of knowledge, skills and values acquired by students, and the later careers of
graduating students in terms of, for example, educational accomplishments assessed by the proportion
of students participating in post-secondary education.
There is abundant empirical evidence to demonstrate that these inputs, outputs, and processes are
related in the sense that the use of different inputs and processes should affect the outputs of the
educational system. But, while we acknowledge that these important causal linkages exist, it is
important to recognize that the availability on information describing these three areas is no guarantee
that we will be able to improve the quality of education that is, the availability of information by
itself often restricts our knowledge of the education system to an assessment of current status.
For this reason, educational status indicators constitute a passive information system rather one
that leads directly to a strategy for raising the quality of education. At one’s best, one might use the
information generated by such a system to develop hypotheses that may be explored for their utility
in improving the quality of education.
The testing of such hypotheses might even draw upon some of the input process measures in
explaining outcomes. But, even this extension of a system of educational status indicators requires
some assumptions about the connections between the use of information and strategies to raise
quality; educational status indicators are, therefore, best used for their heuristic value rather than
their deterministic implications for improving quality.
In order for information to be used to improve the quality of education through better decision-
making, there must exists a sound theoretical or conceptual framework that ties decisions that use
this information to higher quality. Such theories need to go beyond description to the realm of
prescriptive or predictive relations that will guide that adoption of strategic actions. That is, one
needs to tie the various policies, processes, and inputs to the outputs that are being produced. Only
in this way can one convert information into sound strategies for raising the quality of education.
Unfortunately, more than twenty-five years of work on educational production functions has revealed
just how elusive these relations can be. They seem to vary from study to study and to depend upon
the sample of schools, the specification measures of inputs, and the techniques of estimation. This
is not to argue that such relations do not exist, but that they are difficult to measure and use a basis
for a strategy that will improve quality in a predictable manner (Heyneman. 1983).
The problem seems to be that many measures of inputs and processes are extremely difficult to
measure in a reliable and valid fashion. For example, calculating the number of library books that
are available per student might make input measures of “access to school library facilities”. However,
this measure would not address the issue of precisely how many books, of which kind, of what level
of excellence, etc, are being used by each student. Some schools with very large libraries may have
low levels of library access because of a very poor selection of books, or they may have restrictive
borrowing rules, or there may be little encouragement given to students to use the library facilities.
Similarly, a range of “teacher behavior” variables may be measured on the basis of observations
gathered for a few hours of teaching. These observations may be unreliable and/or invalid because
the few hours selected for measurement may not be representative of the general of the teacher’s
behaviors.
Despite the lack of a solid knowledge base that would permit the use of educational information to
set out strategies of manipulating inputs and processes in order to improve educational outcomes,
the production function framework is the dominant conceptual one for building educational
information systems. While experience with this approach has yielded some guidelines for

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