Concept learning - investigating the possibilities for a human-machine dialogue
Everyone around us learns. As a flower needs to adapt to the light, an animal to its environment, we people need to adjust to our complex social or personal conditions of life. Because of that we definitely learn during our entirely life. So, we could say that is better to start learning anytime. We could say that learning process is one of the most important parts of our existence. For examples teenagers are more likely to be receptive to the learning environment than older people. Then, what needs to be done for a more productive approach of society development, if not supporting young students and children to improve the learning methods? If we accept the learning process as defined by the acquisition of concepts or of competences, then we will have to reformulate the general question: how to support youth in learning concepts?
Not a long time ago, education was a filling process. Students were supposed to acquire knowledge and learn it by heart. Well, education is more than this. Furthermore, how about the ability to recognize and explain what is learned? That means to understand new learned concepts and be able to use them in contexts. A good teacher recognizes the potential and supports the students to develop and learn new competences and new concepts. Nowadays, technology is used to help people learn faster by providing them all the necessary support for the communication in the educational process: distant resources access, enabling access to other human resources (oral dialogue is a major component of human learning process).
What is above represents the premises of our research. Before this, we need to mention that we will focus on learning from examples. Why? Because this is the way young people develop: by imitating the adults. That is why it’s very important to know what examples to offer, how to present them and how to support the learning from examples. Children are required to learn concepts; concepts are met in everyday life and the curricula ask them to learn as well. Sometimes concepts are quite complex; can we take a simple case like the green colour and claim that we know everything about it? Maybe, the RGB numerical representation of the colour is accessible (#00FF00 is the RGB representation of green). But, “green” can also be defined as an attribute for life, or metaphorically as hope. What about poetry? Can we identify precisely the mind role during this process? Definitely there are a lot of questions to be answered. As we see, it is not so easy to define a concept unless we are at least familiar with the context. So, if we intend to use technology in supporting the learning of concepts, we wonder: why not using AI to support the learning from examples?
After this small journey through some general questions concerning the learning process, it’s time to introduce the aim of this report: to investigate the potential of machine learning algorithms in supporting the human learning of concepts starting from a particular set of examples: images. But, first let us introduce our problem.
Part of the probation report (11th December 2008): “Intelligent support for learning concepts from examples”