Building Future Fit Teams: Creating a Good Learning Experience
What Makes for a Good Learning Experience?
Learning experiences are like journeys. The journey starts where the learning is now, and ends when the learner is successful. The end of the journey isn’t knowing more, it’s doing more. — Julie Dirksen
10 Learning Startegiesfor modern Pedagogy
- Cross over learning – Learning in informal settings, such as museums and after-school clubs, can link educational content with issues that matter to learners in their lives.
- Learning through argumentation – Argumentation helps students attend to contrasting ideas, which can deepen their learning
- Incidental learning – Incidental learning is unplanned or unintentional learning. It may occur while carrying out an activity that is seemingly unrelated to what is learned.
- Context- based learning – Context enables us to learn from experience. By interpreting new information in the context of where and when it occurs and relating it to what we already
know, we come to understand its relevance and meaning
- Computational Thinking – Computational thinking is a powerful approach to thinking and problem solving. It involves breaking large problems down into smaller ones
(decomposition), recognizing how these relate to problems that have been solved in the past (pattern recognition), setting aside unimportant details (abstraction), identifying and
developing the steps that will be necessary to reach a solution (algorithms) and refining these steps (debugging)
- Learning by doing science – Engaging with authentic scientific tools and practices such as controlling remote laboratory experiments or telescopes can build science inquiry skills,
improve conceptual understanding, and increase motivation.
- Embodied Learning – Embodied learning involves self-awareness of the body interacting with a real or simulated world to support the learning process
- Adaptive Learning – Adaptive teaching systems recommend the best places to start new content and when to review old content. They also provide various tools for monitoring
one’s progress. They build on longstanding learning practices, such as textbook reading, and add a layer of computer-guided support.
- Analytics of Emotions – Automated methods of eye tracking and facial recognition can analyze how students learn, then respond differently to their emotional and cognitive states
- Stealth Assessment -The automatic data collection that goes on in the background when students work with rich digital environments can be applied to unobtrusive, ‘stealth’,
assessment of their learning processes.