Scaffolds and design factors to increase creative outcomes in teaching Software Design and Testing

Graduates are expected to be able to provide holistic solutions, capable of meeting diverse objectives simultaneously. We aim to investigate how students would conceptualize, make sense, desire to know, find solutions and subsequently progress to collaborate, communicate and create new artefacts. We hypothesize that there would be a higher likelihood of better quality design process, explanations as well as modelling outcomes if first, students can relate between the ability to analyse problems with the ability to conceptualize/model and second, the design of the task focuses on not only functional but more importantly sustaining positive user experience. Findings highlight the importance of key design factors contributing to more creative outcomes

Collaborative Tag-Based Context-Aware Recommendation Of Learning Resource

The primary motivation of this thesis is to devise an enhanced collaborative social hypermedia learning resource recommendation techniques. This thesis aims to address how collaborative tagging can be enhanced for personalized learning resource recommendation algorithm to predict and recommend relevant and good learning resources

New Directions in Pedagogy: Design, Playfulness, and STEAM (Editorial)

Massive technological, social and pedagogical changes are reshaping the nature of learning in the 21st Century. In this session at ICCE, researchers and scholars suggest new directions for education that take into account these innovations and that draw upon the latest theoretical developments about learning

Joint Cell Activation and User Association for Backhaul Load Balancing in Green HetNets

This letter proposes a joint cell activation and user association scheme to address the power consumption and backhaul load balancing issues in green dense heterogeneous networks (HetNets). In this scheme, an optimization problem is formulated for jointly minimizing power consumption and optimizing backhaul load balance of dense HetNets, subject to diverse quality of service (QoS) requirements and heterogeneous backhaul capacities. To solve this problem, a Q-learning-based algorithm is developed. Results show that the proposed scheme achieves substantial performance improvements over several baseline schemes in terms of fairness, QoS and energy efficiency