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Title: Use of tracking to support individual learning in a real-time process
Author: Lubega, Jude Thaddeus
ISNI:       0000 0001 3613 608X
Awarding Body: University of Reading
Current Institution: University of Reading
Date of Award: 2006
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There is a growing interest in higher education institutions in the use of e-Iearning environments to support learning ubiquitously. E-Iearning environments such as Blackboard are designed to aid learners during the knowledge construction process (learning) through numerous functions. The tracking (monitoring) function can be used to support learners in their individual learning experience. The statistics generated from the tracking function can be processed and used in offering feecib~ck to stakeholders (learner, tutor and instructional designer). The potential future' use of e-Iearning environments leads to an investigation into how these can be improved to . . ~ support stakeholders (h~arner, tutor and instructional designer) in real-time. Thus in this thesis a Knowledge Discovery and Data Mining (KDDM) process is used to show the significance of tracked information in studying learner behaviours within an elearning environment. A tracking method that uses KDDM techniques and personalisation is designed to support stakeholders in real-time as an improvement to the current tracking methods used in e-Iearning environments. Current e-Iearning environments are not designed to offer personalised real-time feedback to stakeholders. The information that is tracked is related to how the modules are accessed (module-oriented) but not how the users interact with the personalised learning activities (leamer-oriented). The KDDM process used to extract hidden knowledge about learner behaviours illustrated the usefulness of tracked information in feedback generation. This extracted knowledge suggests to 'stakeholders how to improve content delivery and quality but does not indicate the '' attainment of learning objectives. Feedback generated from the KDDM process can not facilitate personalised knowledge construction for the learners. This challenging issue highlights the difficulty faced by current tracking methods within e-Iearning environments. In order to allow personalised support in real-time, KDDM techniques and personalisation are adopted within tracking methods. The personalised support in real-time requires extraction of feedback for improvements from the leamer's knowledge p'!th (learning history). Current tracking methods within e-Iearning environments are unable to offer such feedback. Lack of real-time feedback prevents stakeholders from making decisions for improving knowledge construction. This research work adopts Constructivism as the fundamental theory in supporting stakeholders during personalised knowledge construction. The learner and educational requirement are considered during the creation of a learning profile. The learning profile manages the personalised learning activities during knowledge construction. Interactions with the personalised learning activities generate information that can be used to improve knowledge construction. A designed Method for Personalised Tracking in Knowledge Construction (MPTKC) is presented and used to track the interactions with learning activities. This method that contains KDDM techniques monitors personalised learning activities, analyses the ,,- learning activity information and generate~ real-time feedback for the stakeholders. The MPTKC contains Components that are: External (User Profile, Learning Activities, and Stakeholders) and Internal (Monitoring Learning Activities, Analysing Learning Activity Information, and Generating Feedback). These Components interact to generate the real-time feedback. The stakeholders can use this real-time feedback to make appropriate decisions on how to improve knowledge construction.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available