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It is a notion that students must master the lower level skills before they can engage in higher-order thinking. However, the United States National Research Council objected to this line of reasoning, saying that cognitive research challenges that assumption, and that higher-order thinking is important even in elementary school.
Technological innovation is the process where an organization (or a group of people working outside a structured organization) embarks in a journey where the importance of technology as a source of innovation has been identified as a critical success factor for increased market competitiveness. [2]
Adaptive learning, also known as adaptive teaching, is an educational method which uses computer algorithms as well as artificial intelligence to orchestrate the interaction with the learner and deliver customized resources and learning activities to address the unique needs of each learner. [1]
The ECIU Executive Board, consisting of the rector or vice rector and a local coordinator of each member institution, meets twice a year. The local coordinator is the contact person for information on activities, projects, and seminars.
Thomas Edison with phonograph in the late 1870s. Edison was one of the most prolific inventors in history, holding 1,093 U.S. patents in his name.. Innovation is the practical implementation of ideas that result in the introduction of new goods or services or improvement in offering goods or services. [1]
Design thinking has a history extending from the 1950s and '60s, with roots in the study of design cognition and design methods.It has also been referred to as "designerly ways of knowing, thinking and acting" [6] and as "designerly thinking". [7]
Lifelong learning is the "ongoing, voluntary, and self-motivated" [1] pursuit of learning for either personal or professional reasons.. Lifelong learning is important for an individual's competitiveness and employability, but also enhances social inclusion, active citizenship, and personal development.
Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. [1] For example, for image classification, knowledge gained while learning to recognize cars could be applied when trying to recognize trucks.