Lessons are often being taught in a long length of information, which leads to the concern of holding and capturing considerable attention from the students’ and having them to engage throughout the lesson. This project looks into the development of microlearning application in a multimedia
environment built within microlearning dimensions and outlined by Gagne’s Nine Events of Instruction to enhance learning understanding amongst undergraduate students. Student feedback was gathered and indicated a positive response towards the microlearning approach found within the multimedia-rich platform. Students’ motivation, understanding were enhanced in the learning environment, which supports the use of microlearning application through web and mobile devices access in a technology integrated classroom in higher education institutions.

nordiana.ludin@mmu.edu.my

This project deals with the development and implementation of mobile Augmented Reality (AR) applications for Science learning. This application is built with a different way to present information to the students in the form of three-dimensional modeling and animation images by using a tracking device through a smartphone& and digital camera. The mobile Augmented Reality (AR) technology will be developed that could potentially enhance the user experience for all users especially focus on individual learning experiences with self-study product and making Science subject learning easier.
Note: Only for full-time candidates

junita.shariza@mmu.edu.my

This project will study how universities can design an effective student leadership development programme for the students that opt for online learning.

zakiah.melatu@mmu.edu.my

This project can be applied to Master or PhD students as well. The primary data (questionnaire) will be use as data source. For the methodology, the Partial Least Square-Structural Equation Model (PLS-SEM) will be employed as model development and prediction. Also, machine learning algorithms eg. Random Forest, Support Vector Machines (SVM), Artificial Neural Networks or any Artificial Intelligent assessment approaches will be used to enhance predictive accuracy and uncover hidden patterns in the data. This project also currently in grant application.

Note: Student can register as soonest. Required for both full time or part time (priority for full time).

nurbalqishanis@mmu.edu.my