The area of sustainable green smart computing highlights key challenges towards reducing cost and carbon dioxide emissions due to the high-energy consumption of Cloud data centres. Here, we focus on the Cloud virtual machine (VM) scheduling that is usually based on simple algorithms, e.g. VM place

The quality of students' learning experiences is a critical concern for all higher education institutions. With the assistance of modern technological advances, educational establishments have the capability to better understand the strengths and weaknesses of their learning programs. Developing Effective Educational Experiences through Learning Analytics is a pivotal reference source that focuses on the adoption of data mining and analysis techniques in academic institutions, examining how this collected information is utilized to improve the outcome of student learning.

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This research investigates the extent to which the practical application of robotics affects undergraduate computing students' engagement in learning the Java programming language. Current literature suggests that the practical application of objects enables students to engage and understand concepts within engineering, robotics and computing disciplines easier than purely theoretical teaching methods. This research measures student engagement based on affective, behavioural, cognitive and performance engagement factors. Questionnaires, interviews and observations were exercised in order to explore the reasons that student engagement is affected. The findings suggest that the LEGO® MINDSTORMS® robotics are positively engaging students to learn the Java programming language at an undergraduate level. Negative aspects, of limitations and non-participation, may be explained through external factors including the structure of the module and peer and social pressure.

Research and experimentation is uncovering forms of best practice and possible factors on which to centre the analysis of students in an effective way, however learning analytics has yet to be comprehensively implemented country-wide in the United Kingdom. The chapter explores the current impact of learning analytics in higher education at mome discusses and observes the current vacancies with which a framework enabled to function with data visualisation could be utilised. The deliverable seeks to design an initial framework that has the potential to be utilised in a higher education setting for more effective and insightful decision making with regards to learner retention and engagement. This framework will combine the theory and scientific action of predictive analytics with a comparison of the most suitable data visualisation toolsets that are currently available in open-source software.