An intelligent model for quality service in open distance electronic learning
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Authors
Amoako, Prince Yaw Owusu
Issue Date
2023-02-15
Type
Thesis
Language
en
Keywords
Quality of service , Open Distance Electronic Learning , Fused multimodal biometric , Authentication , Online examination , Bandwidth , Normalization , Learning management , Smart education , Smart conflict management , SDG 4 Quality Education
Alternative Title
Abstract
Quality of service (QoS) in the open distance electronic learning (ODeL) environment, in general, becomes a part of the entire assessment of all services provided by the institution. High-quality service delivery in a virtual environment is one of the most significant challenges, as it is required to become the primary competitive institutional strategy in service-oriented organizations. However, critical quality of service elements in ODeL are not optimal in providing high quality requirements. Authentication as a critical QoS element in ODeL has been considered in numerous research but an optimal cheating-free, non-venue-based assessment has not yet been realized. Bandwidth resource, another critical QoS element in the ODeL platform, is scarce when services performed by many users contend for bandwidth, causing congestion in the network. Through intelligent systems ODeL can be made smarter to achieve QoS; however, the challenge is that many conflicting issues affect the implementation of smart education in ODeL.
This research proposes an intelligent QoS framework capable of reorganizing and adapting to changes within ODeL to provide smart education. The framework constitutes a fused multimodal biometric authentication model based on facial recognition, voice recognition, and keystroke dynamics to provide cheating-free examination in ODeL. It is a predictive framework of bandwidth management, which integrates a sustainable hidden Markov model (HMM) and a normalization policy coupled with SolarWinds technology for prior network data feeder, is incorporated. It is a model that relies on the classified critical conflict factors in the smart education environment and the possible resolution strategies. The QoS elements modeled in the research are validated with a confirmatory factor analysis on a survey of the research participants. The framework will benefit open distant electronic learning institutions, examination agencies, organizations with limited network bandwidth, and quality assurance agencies.