TABLE 1 - uploaded by Christo A Bisschoff
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NUMBER OF CRITERIA IN ACCORDANCE TO R 2
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... scaling had no effect on this research since the same scale is used in all variables. Table 1 shows the step-wise analysis and reduction of the number of criteria in the regression model in context with the correlation coefficient (R 2 ). A total of 34 criteria were eliminated, leaving 8 identified criteria which explains a satisfactory correlation coefficient of 0,657 at a confidence level of 98 % (p<0,02). ...
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... The research by Bisschoff (1998Bisschoff ( , 2000 is employed to measure individual service criteria. Parasuraman, Zeithaml & Berry (1985) (in Nel,, and especially the so-called Gap 5, serves as another measuring tool to determine the performance and gap between performance and expectations relating to the five service criteria, namely: tangibility, responsiveness, empathy, reliability and assurance. ...
The Potchefstroom University for Christian Higher Education embarked on the telematic learning systems route in 1995, introducing an instructional model whereby students would benefit from having access to learning facilitators with both academic and field-related expertise in addition to educational technology applications. Facilitation is regarded to be an important component of the learning model, and hence, a forecasting model with the purpose to predict success in facilitation was developed during 2000. This article deals with the empirical evaluation of the forecasting model to ensure that managerial predictions are validated before it is implemented in practice. The forecasting model identified 8 key attributes for facilitation success based on performance measures from the 1999 Facilitator Customer Service Survey. During 2000 the annual Facilitator Customer Satisfaction Survey was employed to validate the findings of the forecasting model. A total of 1910 questionnaires were distributed in a mail survey to MBA telematic learning students of the PU for CHE. A total of 249 returned questionnaires suitably completed, were returned that resulted in a response rate of 13%. The objectives of the article are to: test the model for practical managerial implementation.
The value of the research is practically significant. The empirical evaluation accredited the forecasting model partially whilst also highlighting its weaknesses. In addition, the evaluation also directed research into new horizons in the forecasting of facilitation success. The research concluded that: the model could not be employed to forecast academic success as a function of facilitation; the definition of success in facilitation is too conservative and should be extended towards other human behavioural characteristics; and $ academic success by facilitators not necessarily implies a high level of customer satisfaction.
The initial purpose of the research to enable the managerial approach to move from a retrospective to pro-active approach whereby corrective measures should be taken before not during courses or after the course, is partially successful because of its limited ability to predict facilitator success. Although already beneficial to the university as agent of quality education, the research should continue in a new direction, namely that of human behaviour to incorporate other influences than just the performance measurements of facilitators as academic expansion of the lecturer. Ultimately, the students deserve the best education possible to contribute to the maximisation of the country's human capital. South African Journal of Higher Education Vol.16(2) 2002: 104-111
