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Differentiated instruction and assessment, also known as differentiated learning or, in education, simply, differentiation, is a framework or philosophy for effective teaching that involves providing all students within their diverse classroom community of learners a range of different avenues for understanding new information (often in the same classroom) in terms of: acquiring content ...
The blog articles are written pro bono by major educational writers who advocate for the paradigm shift to Deeper Learning as well as by a balance of school leaders, teachers, professional learning specialists and others who are incorporating deeper learning practices into their curricula, instruction, assessment and system change plans.
Instructional scaffolding is the support given to a student by an instructor throughout the learning process. This support is specifically tailored to each student; this instructional approach allows students to experience student-centered learning, which tends to facilitate more efficient learning than teacher-centered learning.
Lesson planning is a thinking process, not the filling in of a lesson plan template. A lesson plan is envisaged as a blue print, guide map for action, a comprehensive chart of classroom teaching-learning activities, an elastic but systematic approach for the teaching of concepts, skills and attitudes.
Teachers adopt classroom-management strategies and incorporate instructional approaches which promote independence, discipline, and a positive learning mindset. A teacher's classroom-management style influences many aspects of the learning environment. The four general styles of classroom management are authoritarian, authoritative, permissive ...
Emphasis on the student's role in the learning experience has been shown in research to be crucial to a productive learning experience. [1] The Individual Learning Plan can also be used by an individual on their own or as part of a community of interest, a team or an organization to manage learning over the course of their life.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.