Learning experiences can be categorised on a spectrum of those that only motivate surface learning, to those that encourage deeper learning (Säljö. & Marton, 1976).
Surface learning is characterised by:
- Learning facts and information in order to repeat them (e.g. in assessment)
- Making use of rote learning
- A narrow concentration on detail
- A failure to distinguish principles from scenarios, applications, or examples
- A tendency to stick closely to the course requirements, rather than passionately exploring or researching the topic further
In contrast, deeper learning involves the critical analysis of new ideas and experiences, linking them to already known concepts and principles, the synthesis of new concepts, and longer-term retention. Deep learning has been shown to be facilitated by fostering interest and providing intrinsic motivation driven by enjoyment, interest, empowerment and autonomy within the experience (Schiefele, 1991).
Deeper learning also:
- builds transferrable skills that can be used for problem solving in unfamiliar contexts,
- increases the likelihood of building a passion for the topic, and
- ultimately encourages a practice of life-long learning.
OpenLearning believes that good teaching is the encouragement of a deep approach to learning.
OpenLearning designs motivational mechanics that produce intrinsic motivation whenever they are linked to learning experiences. This ensures that we are always encouraging deep learning wherever possible. OpenLearning is constantly under development and focuses on how each change and update to the learning platform’s mechanics affects both individuals and the community as a whole to enhance this effect.
If implementing extrinsic motivational mechanics, it is likely that students will inevitably try to maximise any rewards which have extrinsic value, and bypass the underlying meaning in the experience. On an educational platform this is a problem because much of the learning stems from the users’ online experiences. While extrinsic motivators are sometimes used on OpenLearning to give students a small push in the right direction, intrinsic motivation is always preferable. Furthermore, as demonstrated by many institutional teaching policies which uses grades as an extrinsic reward, the negative impact of extrinsic motivation is compounded by how easily the value of an extrinsic reward can be transferred to other power structures. For this reason we discourage teachers from using OpenLearning student metrics to influence a course’s grading scheme, or the results issued in an educational institution.
Learning experiences can instead be made more intrinsically rewarding by adding a narrative arc, making an experience beautiful visually, in sound, or feel, by adding a fantasy element, being subversive, providing opportunities for ownership, allowing self expression, encouraging innovation, adding elements of discovery, encouraging rapport building amongst peers, and in many more creative ways which ultimately add to the learning community as a whole.