Computational thinking and the corresponding way of thinking were first proposed by George Polya(2004). After my study of this module in the first two weeks, I take the view that computational thinking is that people use a variety of tools in computers to create a fixed standard and form a way of knowing how to solve a problem. Nevertheless, it can be used out of the computer. As introduced in the first session, computational thinking is used in many areas such as buying, housework, class, exercise, working etc.

Although different people have different explanations about it, there is no acknowledging that it can be applied in various fields as well as our daily life.

In the past, guided by the idea of computational thinking, biology has made substantial progress such as the discovery of DNA. David Baltimore (2001), winner of the Nobel Prize in Physiology or Medicine, considered biology as information science. That is to say, without computational thinking, it is difficult to explore on their own. In physics, computational models and computational methods have contributed to many theoretical discoveries in modern physics, most notably the quantum computational model(Voogt et al.2015). Therefore, computational thinking is being widely used in every area and plays an indispensable part among them.

The idea of computational thinking will continue to be present in our following courses and in our future work. This is because although computational thinking is independent, it can be one of the significant weapons to discover what people have not discovered in all fields and as a result a large number of algorithms and models are built to solve problems.Though computational thinking is probably not originate from computer science as most computer scientists have taken some inspiration from other fields in the last decade, they have continued to advance the development of computational science(David et al,2017). Therefore, computational thinking is a core subject for us, and we will never be able to do any course or get a job without it.

For me, I prefer Python to JavaScript at the moment after studying in the week3 and week4, so my current goal is to utmost my effort to learn more as much knowledge as I can during this period and to work a programmer related to Python in the future. One of the reasons is that other friends have recommended it and I am quite fond of it because of its convenience. It is important to have a computational mindset to study it, so I need to study current courses carefully in order to feel comfortable after learning new knowledge in the future.

I genuinely think that the biggest challenge at the moment is how to apply computational thinking to each course and whether I can come up with my own new ideas about it. Because the concept of computational thinking is so abstract that there are different solutions in different scenarios and although the previous scientists have been able to study and analyse the approach in specific examples, what we should do is to think about whether there is a comparatively better way to approach these problems as well as create ideas to solve those don't have models, so that is something I should considerate and learn in future courses.

Reference

Balitimore, D. 2001. How biology became an information science. In: P. Denning,ed. In The Invisible Future:The Seamless Integration of Technology into Everyday Life[M]. New York: McGraw-Hill, pp. 43-46.

David,B. et al. 2017. Mastering the game of Go without human knowledge[EB/OL]. Avaliable at: https://deepmind.com/documents/119/agz_unformatted_nature.pdf.

George,P. 2004. How to solve it: A New Aspect of Mathematical Method[M]. Princeton University Press.

Voogt,J. et al. 2015. Computational thinking in compulsory education:Towards an agenda for research and practice[J]. Education and Information Technologies, 20 pp.715-728. doi:10.1007/s10639-015-9412-6.