oa Interim : Interdisciplinary Journal - Selling higher education to the highest bidder : corporatising learning

Volume 3 Number 2
  • ISSN : 1684-498X



A typical example how quasi academics and politicians prefer to use HEIS success ratesis the term "throughput" which is remarkably similar to the conveyer belt syndrome of a factory. This kind of terminology, based on input and output jargon tends to create the "revolving door" for learners to move through as fast as they can. This often contributes to the unnecessary failure rate of learners who are still in the articulation phase. Whether it is vertical or horizontal articulation or mobility from one institution to another, these ambitions clash with the term "throughput". It merely becomes another direction for the "revolving door" phenomenon to take. <br>Academic pass rates, achievement and lifelong learning are eminently more suitable for investigation. The real causes of failure rates and the factors that affect learner success may be discovered. It may also lead to enhancing learner successes by redesigning institutional management styles. The learner should not be regarded as an industrial product but as a human being. In this regard, therefore, it is a first priority to investigate how learners cope with academic failure, especially those learners who were previously disadvantaged in developing countries. Finally, it is not fair to discriminate against learners by characterising them as "at risk" but, instead, it may be more correct to refer to risk courses such as mathematics, science and technology. <br>It is so often debated in conferences all over the world that HEIS cannot willy-nilly adapt industrial approaches to monitor course delivery in their quality assurance evaluations. In short, universities are not factories. One good example is staff-learner ratios. How does one analyse the so called throughput for a science lecturer vis-à-vis a ceramic arts teacher? The philosophical debate around the world to extend the theory and practice of academic development has shown that it is far too complex to compare numerical output and statistical figures only.

Loading full text...

Full text loading...


Article metrics loading...


This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error