{"id":{"repo_id":"de-montfort","oai_identifier":"oai:dora.dmu.ac.uk:2086/8237"},"canonical_url":"https://search.dev.ndltd.org/etd/de-montfort/oai:dora.dmu.ac.uk:2086/8237","repository":{"repo_id":"de-montfort","name":"De Montfort University","base_url":"https://dora.dmu.ac.uk/server/oai/request"},"display":{"title":"Policy-based Runtime Tracking for E-learning Environments","abstract":"The Virtual Learning Environment (VLE) is a form of e-learning environment that is becoming widely adopted in higher educational institutions and universities. The term “Tracking” in relation to an e-learning context is the learner’s observation process of any possible interaction with learning activities. Learning activities are a collection of objects designed within e-learning environments to support learners in better understanding and fulfilling the learning objectives during the learning process. A tracking tool is an essential tool fixed within e- learning environments. Most current VLEs (e.g. MOODLE and Blackboard) have utilized similar tracking functions, which aim at recording statistical data for each learner. The current e-learning environments are unable to track individual learning activities where the tracked information can be used to support and guide learners. In this thesis, we propose a policy-based runtime tracking system. Such a tracking system is implemented as an integral part of an e-learning environment (e.g. MOODLE). Our proposed approach does the following: 1) keeps track of and captures the learning activity events and learner interaction events within a learning activity; 2) enforces a set of policies at runtime that specify how to manage the learning activities and the way the learners behave during them; and 3) provides the learners with supportive feedback in a timely manner. We present a computational model which defines the behaviour of the system’s components and describes the tracking mechanism applied in our proposed approach. We designed architecture for our proposed approach with respect to the computational model. We present learning activity policies based on the ECA model to be enforced at runtime; this is done in response to the captured events about either the learning activities or the interactions of learners within the learning activities. A policy-based enforcement mechanism is proposed where learning activity policies are specified to support and guide learners to achieve the learning objective and thus to meet such requirements. Finally, we present a case study based on a current e-learning environment to evaluate our approach.","abstract_html":"The Virtual Learning Environment (VLE) is a form of e-learning environment that is becoming widely adopted in higher educational institutions and universities. The term “Tracking” in relation to an e-learning context is the learner’s observation process of any possible interaction with learning activities. Learning activities are a collection of objects designed within e-learning environments to support learners in better understanding and fulfilling the learning objectives during the learning process. A tracking tool is an essential tool fixed within e- learning environments. Most current VLEs (e.g. MOODLE and Blackboard) have utilized similar tracking functions, which aim at recording statistical data for each learner. The current e-learning environments are unable to track individual learning activities where the tracked information can be used to support and guide learners. In this thesis, we propose a policy-based runtime tracking system. Such a tracking system is implemented as an integral part of an e-learning environment (e.g. MOODLE). Our proposed approach does the following: 1) keeps track of and captures the learning activity events and learner interaction events within a learning activity; 2) enforces a set of policies at runtime that specify how to manage the learning activities and the way the learners behave during them; and 3) provides the learners with supportive feedback in a timely manner. We present a computational model which defines the behaviour of the system’s components and describes the tracking mechanism applied in our proposed approach. We designed architecture for our proposed approach with respect to the computational model. We present learning activity policies based on the ECA model to be enforced at runtime; this is done in response to the captured events about either the learning activities or the interactions of learners within the learning activities. A policy-based enforcement mechanism is proposed where learning activity policies are specified to support and guide learners to achieve the learning objective and thus to meet such requirements. 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