Deep, Surface and Strategic. Evaluate These Approaches to Learning

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  • Topic: Learning, 1920, 1921
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  • Published : June 26, 2011
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Deep, surface and strategic. Evaluate these approaches to learning

Nowadays, approaches to learning (deep, surface and strategic learning) are increasingly popular in the contemporary world. But in the meantime, which approach is the most effective has become a highly debated issue. Some students adopt a surface approach to their studies (Lublin, 2006) and others adopt a deep approach (Morgan, 1993). Therefore, this essay will analyze deep, surface and strategic learning, and show that these three approaches are equally important. The surface learning will be considered first, followed by the deep learning and strategic learning.

Firstly, surface learning is to cope with course requirements (Moon, 2005).In the first place, surface learning can focus on detailed information (Woodall & Winstanley, 1998). Specifically, student digests information showed at face value (Wittmann & Godshall, 2009). For another, it drives the student’s fear of failing (Study skill 1, 2010). In the other word, surface learners’ aim is pass the exam and they just memorize the information in sequence (Woodall & Winstanley, 1998). However, there are some drawbacks exist. For instance, surface learner accept ideas without understand them when they have a surface approach (Hogan, 2006). Also, it is bad for students’ long-term success (Kaplan, 2010).

In contrast, deep learners try to understand ideas by themselves (Moon, 2005). The benefits of deep learning, for instance, they can relate new information to precious knowledge (Lublin, 2006), because they will spend time to think about what they learnt. Also, it is created from the students’ interest (Hogan, 2006), because they want to take deep learning not force to. The disadvantages are deep learner spend too much time on research the deep meaning of knowledge, it might be effect their other course result, because they cannot interested in all of the subjects. In the other words, deep learning is may not suitable for everybody....
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