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Big data technologies, like business intelligence, cloud computing, and databases; Visualization, such as charts, graphs, and other displays of the data; Multidimensional big data can also be represented as OLAP data cubes or, mathematically, tensors. Array database systems have set out to provide storage and high-level query support on this ...
While the analysis of educational data is not itself a new practice, recent advances in educational technology, including the increase in computing power and the ability to log fine-grained data about students' use of a computer-based learning environment, have led to an increased interest in developing techniques for analyzing the large amounts of data generated in educational settings.
Dr. Wolfgang Greller and Dr. Hendrik Drachsler defined learning analytics holistically as a framework. They proposed that it is a generic design framework that can act as a useful guide for setting up analytics services in support of educational practice and learner guidance, in quality assurance, curriculum development, and in improving teacher effectiveness and efficiency.
Educational technology is an inclusive term for both the material tools and processes, and the theoretical foundations for supporting learning and teaching. Educational technology is not restricted to advanced technology but is anything that enhances classroom learning in the utilization of blended, face-to-face, or online learning. [12]
Data-intensive computing is intended to address this need. Parallel processing approaches can be generally classified as either compute-intensive, or data-intensive. [6] [7] [8] Compute-intensive is used to describe application programs that are compute-bound. Such applications devote most of their execution time to computational requirements ...
Data-informed decision-making (DIDM) gives reference to the collection and analysis of data to guide decisions that improve success. [1] Another form of this process is referred to as data-driven decision-making, "which is defined similarly as making decisions based on hard data as opposed to intuition, observation, or guesswork."
Example for the usefulness of exploratory data analysis as demonstrated using the Datasaurus dozen data set Data science is at the intersection of mathematics, computer science and domain expertise. Data science and data analysis are both important disciplines in the field of data management and analysis, but they differ in several key ways.
Education 3.0 is an umbrella term used by educational theorists to describe a variety of ways to integrate technology into learning. According to Jeff Borden, Education 3.0 entails a confluence of neuroscience, cognitive psychology, and education technology, using web-based digital and mobile technology , including apps, hardware and software ...