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Thematic teaching (also known as thematic instruction) is the selecting and highlighting of a theme through an instructional unit or module, course, or multiple courses. It is often interdisciplinary, highlighting the relationship of knowledge across academic disciplines and everyday life. Themes can be topics or take the form of overarching ...
Ensemble learning trains two or more Machine Learning algorithms to a specific classification or regression task. The algorithms within the ensemble learning model are generally referred as “base models”, “base learners” or “weak learners” in literature. The base models can be constructed using a single modelling algorithm or ...
Learning styles. Learning styles refer to a range of theories that aim to account for differences in individuals' learning. [1] Although there is ample evidence that individuals express personal preferences on how they prefer to receive information, [2] : 108 few studies have found validity in using learning styles in education.
Dialogic learning at Shimer College. Dialogic learning is learning that takes place through dialogue. It is typically the result of egalitarian dialogue; in other words, the consequence of a dialogue in which different people provide arguments based on validity claims and not on power claims. [1] The concept of dialogic learning is not a new one.
Understanding by Design, or UbD, is an educational theory for curriculum design of a school subject, where planners look at the desired outcomes at the end of the study in order to design curriculum units, performance assessments, and classroom instruction. [1] UbD is an example of backward design, the practice of looking at the outcomes first ...
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Outcome-based education or outcomes-based education ( OBE) is an educational theory that bases each part of an educational system around goals (outcomes). By the end of the educational experience, each student should have achieved the goal. There is no single specified style of teaching or assessment in OBE; instead, classes, opportunities, and ...
Double-loop learning entails the modification of goals or decision-making rules in the light of experience. The first loop uses the goals or decision-making rules, the second loop enables their modification, hence "double-loop". Double-loop learning recognises that the way a problem is defined and solved can be a source of the problem. [1]