Surface and Deep Learning

Surface Learning
- Learning to specifically meet course requirements
- Studying unrelated bits of knowledge
- Memorising facts and figures to repeat
- No linking or connection of learning

The surface approach to learning comes from “the intention to get the task out of the way with minimum trouble while appearing to meet course requirements” (Biggs, 2003, p14). This often includes rote learning content, filling an essay with detail rather than discussion and list points rather than providing background or context to the work.

Deep Learning
- Learning that seeks to understand and connect the concepts
- Relates ideas to previous knowledge and experience
- Explores links between evidence and conclusions
- Critiques arguments and examines rationale

The deep approach comes “from a felt need to engage the task appropriately and meaningfully, so the student tries to use the most appropriate cognitive activities for handling it” (Biggs, 2003, p16). Using this approach students make a real effort to connect with and understand what they are learning. This requires a strong base knowledge for students to then build on seeking both detailed information and trying to understand the bigger picture

In reflection of Surface and Deep Learning I’d very much say I was a bit of both learning techniques. On one hand sometimes I only learn what’s specifically required for the course and no more, I’m also very good at memorizing facts and figures but then I don’t study unrelated bits of knowledge which is all included within surface learning. For Deep Learning I also use some of those techniques for example relating ideas to previous knowledge and experience.