What Do Life Science Graduates Do? Suzanne Creeber Careers Consultant
Suzanne Westbrook, PhD School of Information: Science, Technology, & Arts Computer Science Dept, UA.
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Transcript of Suzanne Westbrook, PhD School of Information: Science, Technology, & Arts Computer Science Dept, UA.
What is Computational Thinking (CT)?(Wing) “Computational thinking involves solving
problems, designing systems, and understanding human behavior, by drawing on the concepts fundamental to computer science.”
(NSF program solicitation for Cyber-Enabled Discovery and Innovation) “Computational thinking is defined comprehensively to encompass computational concepts, methods, models, algorithms, and tools. … [it] promises a profound impact on the Nation’s ability to generate and apply new knowledge.”
What else?
Is CT new? Who thinks this way already?
CountingFollowing directionsUsing abstraction – building things (small or
complex)Solving problems by decompositionOther examples?
We all use it every day!
So why isn’t everyone a computer scientist? What computer scientists do:Learn to solve all sorts of problems
using:• Problem abstraction• Problem decomposition• Data structures• Algorithms
Study “theory of computation”What is computable?How long does something take to solve?How can we model a solution to a problem?
“What computer scientists do” cont’dUse computers to implement our solutionsUnderstand how computers work and how
to make them work better, faster, more efficiently, (more computer engineering area)
Work with people in other areas to solve interesting problems which often have large amounts of data to be stored and analyzed
Computing concepts can be applied to problems in other areasScheduling issues – who gets to go next?
For how long?Pipelining and pre-fetching – having info
when you need itDeadlock – what if everything is waiting
for each other? Who “gives”?“working set” – fast access to data;
keeping frequently used things close by
More computing conceptsData representation (structures)RecursionDivide and conquerBacktrackingHeuristics
Data StructuresExamples
ListsStacksQueuesTreesHash tables
Choice based on use – tradeoff of time versus space
AlgorithmsThe really creative part! Is an algorithm
“elegant”? Is one algorithm faster than another that does the same thing? Is it correct? How does it operate when the amount of data (size n) gets really large?
Algorithms and data structures go hand in hand…Storing data – search, modify, insertion,
deletion
Why might non-CS people want to know more about CT?
To recognize how they use it alreadyTo stimulate “out of the box” ideas for
solutions to their problemsTo more easily work with computer
scientists in new ways – on multi-disciplinary teams
You might find that you want to be a computer/computing scientist – the world needs more!
UA’s SISTASchool of Information Sciences, Technology, and
ArtsCore set of 5 classes: Great Ideas in the
Information Age, Computational Thinking and Doing, Dealing With Data, Ethics in a Digital World, Statistics
Thematic courses: networks, sequences, othersOpportunities for students to develop common
understanding of CT and relationships across disciplines
Increased opportunities for faculty to collaborate
Cool tech stuff for society– not just for Computer Scientists!
Smart phones – do we still need PCs?Tablet PCs – making computers easier to
useRobots – aerial robotics, medical robots,
domestic robots…Computer visionCAVE – 3D immersive environmentSurface computing – for example
Microsoft’s Surface: http://www.microsoft.com/surface/
What else?