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Measuring the effectiveness of a continuous quality improvement cycle in education is a cumbersome and sophisticated process. This article contributes a comprehensive self-assessment instrument for identifying the strengths and weaknesses of all phases of a continuous quality improvement cycle, including planning, data collection, analysis and reporting, and implementation of improvements. To this end, a four round Delphi study soliciting a total of 23 program quality experts from four universities was conducted. The produced survey instrument contains a total of 50 questions. The instrument may be used by quality experts in education to judge the quality of their continuous quality improvement cycle that endeavours to assess the attainment of learning outcomes in various undergraduate educational programs. Moreover, the instrument could be exploited to infer relevant user and system requirements and guide the development of an automated self-assessment tool aimed at identifying the shortcomings in educational continuous quality improvement cycles.

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Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS’ QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50–60%, 30–40%, and 10–20% for high, normal, and low traffic loads respectively.