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The English Outdoor Council, an umbrella body, defines outdoor education as a way for students and teachers to be fully engaged in a lesson, all the while embracing the outdoors. The EOC deems outdoor education as "providing depth to the curriculum and makes an important contribution to students' physical, personal and social education.".
Adventure centered experiences can include a wide variety of activities, due to the different ways people experience adventure. Outdoor sports, challenge courses, races, and even indoor activities can be used in adventure education. Adventure education relates to adventure programming, adventure therapy, and outdoor education.
Visual chat rooms add graphics to the chat experience, in either 2D or 3D (employing virtual reality technology). These are characterized by using a graphic representation of the user, an avatar virtual elements such as games (in particular massively multiplayer online games) and educational material most often developed by individual site owners, who in general are simply more advanced users ...
Image source: Getty images. Zscaler. Zscaler (NASDAQ: ZS) is a cybersecurity company whose Zero Trust Exchange platform protects its customers from cyberattacks and data loss. With more ...
Classroom teaching. Active learning is "a method of learning in which students are actively or experientially involved in the learning process and where there are different levels of active learning, depending on student involvement."
Google Classroom is a free blended learning platform developed by Google for educational institutions that aims to simplify creating, distributing, and grading assignments. . The primary purpose of Google Classroom is to streamline the process of sharing files between teachers and students.
WhatsApp (officially WhatsApp Messenger) is an instant messaging (IM) and voice-over-IP (VoIP) service owned by technology conglomerate Meta. [14] It allows users to send text , voice messages and video messages, [ 15 ] make voice and video calls, and share images, documents, user locations, and other content.
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.