Challenges in Understanding Human Learning Physiology
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 15672
Special Issue Editor
Special Issue Information
Dear Colleagues,
Learning is the fundament of human life in the most profound sense. Since very ancient times, it has been evident that teaching and learning are the key factors literally building our society and ultimately defining our life quality. The relevance of understanding the mechanisms of human learning is quite obvious: An effective and efficient teaching must comply with the capabilities, the limits, and all the factors driving human learning. It is also evident that the mechanisms of human learning have not been fully described, and controlling all the factors affecting learning is a great challenge for a teacher or an educator. In modern times, it is acknowledged that learning resides in brain mechanisms, but there is a huge gap between knowledge of cellular mechanisms and the “emergent properties” of the brain (i.e., behavior). Thus, learning is a topic addressed by lot of disciplines with different approaches and different points of view, like cellular biology, neurobiology, brain physiology, computational sciences, cognitive psychology, behavioral psychology, and pedagogy. There is a huge amount of different information, and a synthesis is still lacking. Such a synthesis is a challenge in itself. Different disciplines use different language; words like stimulus, response, motivation, reward, reinforcement, incentive, memory, notion, knowledge, and skill can be found in different contexts with different meanings, and there are also different models, theories, conclusions, and recommendations. Nevertheless, all disciplines offer a contribution in trying to optimize teaching and learning methods, and a route toward a possible synthesis is highly advisable or even necessary. If such a route is possible, the starting point should be a summary of the state of the art. This Special Issue is a challenge in collecting a summary of information, models, and theories from all those different disciplines addressing human learning.
Prof. Andrea Viggiano
Guest Editor
Manuscript Submission Information
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Keywords
- Learning
- Memory
- Teaching
- Education
- Pedagogy
- Conditioning
- Reinforcement
- Reward
- Incentive
- Motivation
- Neural plasticity
- Synaptic plasticity
- Neural networks
- Computational models
- Long-term potentiation
- Hippocampus
- Basal ganglia
- Cerebellum
