Another dot in the blogosphere?

Video source

The video above is actually about how programmers get artificial intelligence (AI) to learn. It provides insights on human teaching and learning.

The methods range from reinforced learning of models to novelty or incentive-based learning. Reinforcement learning is relatively easy and limited by the models that humans provide AI. This also  results in low-level AI. Providing novelty is not always productive either. AI can get “bored” of this. 

These insights might serve as reminders of how we teach our learners. My message is not that teaching by reinforcement or novelty/incentive is not always bad. It is that these methods should be contextual. 

Reinforcement or drilling is good for honing fine or gross motor skills. It might also provide a foundation for socialisation, e.g., saying please or thank you. Novelty might grab attention but it cannot maintain it. However, if it is linked to cognitive dissonance and problem-solving, then the initial effort to engage is a good strategy.

Teaching by reinforcement and providing novelty are easy, which might be why teachers reach for them so often. But these are not sufficient or effective in the long run. Anything worth learning takes time and effort. Shortcuts are not going to get us there.