Using educational technology as an institutional teaching and learning improvement strategy?
Increasingly, educational technology is identified as crucial to addressing many scale issues around higher education learning and teaching. However, such projects are often run with the technical project goals achieved but the educational goals unrealised. Further, in an age of austerity, all investments must be closely scrutinised as to their efficacy in meeting their intended goals. To what extent can educational technology be used as a management tool to enable and promote institution-level change in learning and teaching as a strategic goal? This paper reports on use of the Resources, Activity, Support and Evaluation (RASE) model at an Australian university in its move from an incumbent to a new ‘learning management system’ coupled with judicious use of inflection points introduced to drive educational change across a whole institution and to model and report on that change.
A system dynamic model of student enrolment at the private higher education sector in Syria
ABSTRACT This paper investigates the dynamics of student enrolment in the Syrian private higher education sector. The paper adopts a system dynamics approach, to construct suitable simulation models that could be used to examine the complex and dynamic interactions between student flows, staff ratios and investments in plant and facilities. The study involved interviews with key university personnel, focus groups with university staff, a survey of student perceptions and personal observations of key departments at the university selected for the study. Further interviews were held with members of staff of all the other private universities in Syria. The simulation model developed in this study has provided insightful and meaningful exploration of data whose practical applicability is not necessarily restricted to the Syrian university, but broadly encompasses all educational sectors, whether private or public. The model designed in this research is a decision support system, one that is a flexible tool to design measures that might help to improve student enrolments. University management can use the simulation model to create different future scenarios, involving changes in student numbers, staff–student ratios or investment in plant and facilities.
The parallel waveform relaxation stochastic Runge–Kutta method for stochastic differential equations
For large-scale non-autonomous Stratonovich stochastic differential equations, we study a very general parallel waveform relaxation process which is on the basis of stochastic Runge–Kutta (SRK) method of mean-square order 1.0 in this literature. The convergence of the whole parallel numerical iterative scheme can be guaranteed and the scheme provides better properties in terms of decreasing the load of the computation and operating speed. At the same time, the related limit method is also introduced as the continuous approximation derived from the iterative scheme. In the approximation interval, it is worth noting that the mean-square order of the parallel numerical iterative scheme can be kept consistent with the previous SRK method at any arbitrary time point, not just at discrete points. Some numerical simulations are presented to elaborate the computing efficiency of the parallel numerical iterative scheme.