Fundations of Deep Teaching and Deep Learning

In this research, we will answer: Compared with shallow rote teaching and learning, what are the characteristics of deep teaching and learning in brain activities and behavior, both during and after learning. That is, whether deep learning helps to reduce the cognitive and emotional burdens of learning, improve the ability of transfer learning and transfer creation, and improve the ability to identify and solve problems, and whether evidence of brain activity can be found to support these differences.

1. Comparison of deep learning and shallow learning, brain activity, learning cost and effect.

• Choose a typical logic strucutre (for example, if-then or analogy), and then contrast of brain activity of participants in answering questions sharing the same chosen logic structure but close to or far away from everyday life experience. The aim is to identify characteristic brain activities of the chosen logic structure via comparing the brain activities of logical decision-making against decision-making based on everyday experience.
• Choose a knowlege and learn it rotely or meaningfully (for example, the rote learning and meaningful/generative learning of multiplication table, or of Chinese characters), and then compare brain activities during the learning and application of the knowledge the above two ways of learning. The aim is to discover the characteristic brain activities of meaningful/generative learning compared with rote learning.
• In terms of learning costs, we need to consider the measurement of emotional burden and cognitive burden in the learning process.
• In terms of learning effects, in addition to the performance of direct learning tasks, we need to consider the ability of transfer learning and transfer creation before and after learning, in short or learning terms.
• After identifying characteristic brain activities of deep learning, we need to check if they are also activated in subsequent high-level tasks such as transfer learning and transfer creation, and we should even further study the correlation between activation in learning and activation in high-level tasks, and also the correlation between activation of the characteristic brain area and the abilities to complete high-level tasks.

2. Is the distance from knowing to applying, that is, knowing knowledge but not being able to use this knowledge to solve problems, related to the level of teaching and learning?
3. Is the suppression and removal of misconcepts is related to the level of teaching and learning?
4. Multi-brain (teacher-student, student-student) synchronization research of deep teaching and learning: whether deep teaching and learning promotes the brain synchronization, whether the higher the degree of teacher and student brain synchronization is related to the better learning outcomes.

Researches in this direction is mainly carried out on the individual level of specific knowledge in a Lab setting. Of course knowledge that is closely related to the learning target and needed in meaningful learning will also be considered. In the future, we might need to consider the influence of the learning orders on teaching and learning caused by the up-down and left-right connections between knowledge on the entire knowledge network, the impact of personalized learning guidance based on diagnostic test algorithms on teaching and learning. Those will be the topic of other researches, see for example Course-level Experimental Studies of Meaningful Learning.