On Friday 17th August 2018 Mr. Godfrey Onyiat defended his doctoral thesis - A Model for Personalizing Learning in an E-Learning System supervised by Prof. Gilbert Maiga and Prof. Jude Lubega.
Prior to the paradigm shift to learner-centred learning, instructor-centred learning and mass education dominated the education system. This worked because the numbers of learners, their diversity and demands were closely related. With the increasing demand for higher education, diversity of learners and their varying learner needs, this approach is no longer satisfactory. This has caused dissatisfaction among the learners, leading to learner unrest, increasing learner drop-out and failure rates. Hence, a model for personalizing learning in an e-learning system is necessary to address the learner diversity, varying learner needs.
The study was set to come up with a model for personalizing learning in an e-learning system. This was done by identifying the factors for institutional readiness for e-learning, the requirements for personalized learning, propose a model that supports personalizing learning, and to evaluate it. A survey was conducted to gather requirements for the model using questionnaire and interview methods. Four hundred (400) second and third year Information Technology students and their corresponding lecturers were purposively selected from both public and private universities in Uganda. The data was analysed using SPSS and the results were used to extend the model for personalizing learning. Seventy (70) Information Technology Instructors from the study sample evaluated the model using a questionnaire and expert opinions to establish the relationship between personalized learning and institutional readiness for e-learning; and its applicability in the real world.
The results indicate that the extended model is suitable for personalizing learning in an e-learning system. The study identified two (2) themes for personalizing learning in an e-learning system: institutional readiness for e-learning and personalized learning. The following factors were established for determining personalized learning: commitment, motivation, engagement, and experience; while for institutional readiness for e-learning are: awareness, institutional culture, management support, feedback, technology, human resource, and reliability. These are linked to both improved e-learning implementation and successful personalized learning. From a practical point of view, it provides a generic model that can guide practitioners in personalizing and implementing e-learning.
After close scrutiny of his research and addressing several open-ended questions, the examination committee that comprised of Assoc. Prof. Rwashana, Dr. Agaba, Dr. Kivunike, Dr. Kahiigi, Dr. Bagarukayo and Assoc. Prof. Owiny accepted Mr. Onyiat’s research with major revisions in content and format (with one committee member responsible for overseeing and approving the major revisions before the final copies are submitted).