Nature Of Science

This post proposes the use of a key biological concept - broad classification - to teach the provisional and contested nature of science in school biology curricula. It also examines existing curriculum-related factors which might pose obstacles to implementing such a change. An investigation in South Africa highlights the problems regarding biological classification at the kingdom level of 50 biology students entering one university. Using interviews, questionnaires and document analysis, factors thought to affect learners' ideas were investigated, including the understanding of the changing and contested nature of scientific knowledge of a range of biology educators. The students lacked knowledge of the concept of a biological kingdom, and showed archaic thinking about the number of kingdoms. Many of the teachers held similar views, used outmoded classification systems in their teaching, and were unaware of the history of changes in biological systems. A review of two relevant syllabus and five textbooks revealed insufficient, inaccurate, inconsistent and/or contradictory information about biological classification systems and how they change with time. Three potential problems associated with curriculum innovation are discussed.

The Artificial Intelligence

Artificial intelligence in the future will churn out machines and computers, which are much more sophisticated than the ones that we have today. For example, the speech recognition systems that we see today, will become more sophisticated and it is expected that they will reach the human performance levels in the future. It is also believed that they will be able to communicate with human beings, using both text and voice, in unstructured English in the coming few years. However, will artificial intelligence be able to create machines that are self-aware and even more intelligent than human beings - is a question that nobody has an answer to. Also, even if this is possible, how much time it is going to take, cannot be predicted at present.

It is expected that in the future, such machines will be developed having basic common sense, similar to human beings, although pertaining to specific areas only. It is also expected that the human mind functions, such as learning by experience, learning by rehearsal, cognition and perception will also be performed by future intelligent machines. In fact, research and experiments are being conducted to recreate the human brain. CCortex , a project by Artificial Development Inc., California, and Swiss government's IBM sponsored Blue Brain Project, are two main ventures, whose goal is to simulate the human brain. Whether this brain will have human consciousness incorporated in it - there is still no answer for that. Read more on artificial intelligence and the future of man.

It is expected that the robots in future, will take on everybody's work. Whether it is office work or the work at home, robots will accomplish it even more faster and efficiently than human beings. So if somebody's falling ill, they can obtain a robot nurse who will give periodic medicines to them. How much care, concern and empathy the robot nurse will have towards the patient is anybody's guess. Thus, artificial intelligence is still in its infancy, and artificial intelligence's future depends upon the capability of the scientists to crack the puzzle of the human mind. Will they be able to solve "the problem of the mind" and incorporate all the human, mental, emotional qualities in the machines? Let us Wait for the future!

Neural Networks

The field of neural networks is wide, and the technological advances have made our lives simple. In my opinion, the neural network work field is abandoned by the world. It’s an area that only scientist, engineers and some other enthusiast take into account. During my student years, I had this fascination for this artificial intelligence division. In one occasion, I had to develop a project in which the work environment was crucial. The project consisted on a small car capable of recognize a determined type of terrain for crop development.

I was aware about what to do. however, something important was missing. A neural system needs to be properly trained. My next task was to develop software to train and design the neural network. In reality, this was not necessary, since there is a lot of functional neural network software in the market. To finish my Project, I had to buy software to develop and design the neural network of my car brain. At the end of the story, my project was a complete success. It was acquired by a local company dedicated to sell crop tools. Now, this device is manufactured as a crop inspection robot. Learning to design a neural network is crucial for our projects that require artificial intelligence technology. Therefore, I suggest acquiring all the equipment needed as books and software because in some way they make our life easy.