I am very proud to have graduated from Ulster University with a PhD from the Faculty of Computing and Engineering.
PhD Title: Intelligent Assessment and Learner Personalisation in Adaptive Educational Systems for STEM Education
PhD Abstract: The work presented in this thesis focuses on the design, development, implementation and evaluation of an Adaptive Educational Systems (AES) named IPAL. Drawing on fields of education, psychology and computer science IPAL is introduced as a supplementary and complementary course tool in higher education, which facilitates teaching and learning in STEM education. This thesis addresses associated challenges with AES and specifically investigates dynamic user modelling by offering a two-step approach in determining learning styles. An initial primary learning style is first established explicitly, addressing the cold start issue which occurs when the information required to determine a student’s learning style is not available (Popescu, 2009), (Buncle, Anane, & Nakayama, 2013). A secondary learning style is then determined implicitly from student engagement, using educational data mining. In addition, the thesis extends the personalisation of theoretical content by supporting complex, practical STEM education, by extending the two-step learning style approach within IPAL to an integrated Game Based Learning (GBL) environment. GBL aims to present, complex concepts or theories in new and innovative ways, providing highly engaging learning experiences through, for example 3D and avatar-based interactions. This approach explores learning style adaption in GBL for STEM education.
A mixed method research approach was employed whereby quantitative and qualitative data was obtained from over 100 participants using STEM content to determine the effectiveness of IPAL. The results in this thesis demonstrate that IPAL is an effective AES in STEM education which improves the learning outcomes of students.