Search results
Results from the WOW.Com Content Network
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.
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."
The Outdoor Education Group (OEG) was founded by Tony Pammer in 1984. For many private schools, OEG offered a third-party alternative to programs such as Geelong Grammar 's Timbertop . By 2008, The Age reported that OEG at least partially ran over 80 schools' outdoor education programs, 42 of which were in Victoria .
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.
A classroom in Norway. Learning theory describes how students receive, process, and retain knowledge during learning.Cognitive, emotional, and environmental influences, as well as prior experience, all play a part in how understanding, or a worldview, is acquired or changed and knowledge and skills retained.
In the Leitner system, correctly answered cards are advanced to the next, less frequent box, while incorrectly answered cards return to the first box.
A wide range of supervised learning algorithms are available, each with its strengths and weaknesses. There is no single learning algorithm that works best on all supervised learning problems (see the No free lunch theorem).