The proposed automatic attention estimation system has a clear potential usage as a tool for automated analytics of the learning process, providing a mechanism for large-scale analytics of student behavior in the classroom by using affordable but very capable hardware.
The experimentation reported in this work contributed mainly to the Large-Scale Analytics (LSA and Aviationn threads of Testbed-12.
This multi-stakeholder interdisciplinary collaborative aims to enhance the value of observational health data by using large-scale analytics.
Large-scale analytics is a key application area for data processing and parallel computing research.
Co-founder Ajay Anand was the Director of Product Management for Hadoop and Cloud Computing at Yahoo, and was responsible for driving the development and adoption of Hadoop based infrastructure for large scale data analytics across Yahoo.
Exemplary large scale implementations of predictive modeling in learning analytics include the Course Signals Project at Purdue University (Arnold and Pistilli 2012) and the Student Success System by Desire2Learn.13.
However, the large scale of data and the critical latency analytics requirement in finance poses a great challenge for current system architecture.
Using a multi scale dataset for climate data, they demonstrated a cloud based large scale data integration and analytics approach where they made use of tools such as RapidMiner and Hadoop to process the data in a hybrid cloud.
A review of the state of the art provides very promising insights about applying cloud computing resources for large scale smart city data analytics.
Table 1 The space of visual learning analytics and open learner models Visualisation type For teachers (and other professional stakeholders) For students (and perhaps teachers, parents, peers) Activity, behaviour, performance score data Inferred learning information Large scale Small scale Learning analytics x x x Open learner models x x x.
