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Bahasa Indonesia: Modul ini adalah Panduan untuk pengajar program "Reading Wikipedia in the Classroom" yang telah dilokalkan ke bahasa Indonesia menjadi "Menggunakan Wikipedia dalam Pembelajaran" (Modul 1). "Reading Wikipedia in the Classroom" adalah program pengembangan profesional untuk guru sekolah menengah yang diinisiasi oleh tim ...
Computer-supported collaborative learning (CSCL) is a pedagogical approach wherein learning takes place via social interaction using a computer or through the Internet. This kind of learning is characterized by the sharing and construction of knowledge among participants using technology as their primary means of communication or as a common resource. [1]
Macrochelys temminckii luring. Lingual luring is a form of aggressive mimicry in which a predator (typically a snake or turtle) uses its tongue to fool potential prey into approaching close to what appears to be a small wriggling worm. Lingual lures are very well developed in young alligator snapping turtles which wait underwater with their ...
Competency-based learning or competency-based education is a framework for teaching and assessment of learning. It is also described as a type of education based on predetermined "competencies," which focuses on outcomes and real-world performance. [1]
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.
In the Leitner system, correctly answered cards are advanced to the next, less frequent box, while incorrectly answered cards will return to the first box.
Ensemble learning, including both regression and classification tasks, can be explained using a geometric framework. [15] Within this framework, the output of each individual classifier or regressor for the entire dataset can be viewed as a point in a multi-dimensional space.
Learning to rank [1] or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. [2]