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- 1. Introduction to Information Science, Technology and Arts: The Great Ideas of the Information Age Paul Cohen 805 Gould Simpson cohen@cs.arizona.edu
- 2. Welcome!
- 3. SISTA’s Mission To provide expertise and promote research in computational methods and thinking across disciplines; and to teach students to understand the computational aspects of any discipline.
- 4. SISTA’s Mission To provide expertise and promote research in computational methods and thinking across disciplines; and to teach students to understand the computational aspects of any discipline. What this should mean to you: You are a new kind of student. Computer scientists don’t understand the computational aspects of all disciplines Students from other disciplines often don’t understand computation I wish I could think of a name for this new kind of person!
- 5. Your Mission (today and as term proceeds) What should we call someone who, after some discussion and thought, understands the computational aspects of any problem? What should we call students who study to be this kind of person? Surely this is a great extra credit problem! (Why do names matter?)
- 6. Is Computing the “New Math”? • Mathematics is recognized as a foundation for all disciplines • Computer Science probably isn’t • But Computational Thinking probably is
- 7. What is Computational Thinking? • Computational thinking is a fundamental skill for everyone • This course is not “Ways to Think Like a Computer Scientist” • Why? Computational thinking is a fundamental skill for everyone, not just for computer scientists. To reading, writing, and arithmetic, we should add computational thinking to every child’s analytical ability. ...Computational thinking involves solving problems, designing systems, and understanding human behavior, by drawing on the concepts fundamental to computer science. Computational thinking includes a range of mental tools that reflect the breadth of the field of computer science. ... Professors of computer science should teach a course called “Ways to Think Like a Computer Scientist” to college freshmen, making it available to non-majors, not just to computer science majors. We should expose pre-college students to computational methods and models. – Prof. Jeanette Wing, CMU and NSF
- 8. What is Computational Thinking Why it isn’t Computer Science • Computational thinking is broader than what Computer Scientists do, borrowing from – probability and statistics, economics, game theory, neuroscience, decision theory, physics, psychology... • Computer Scientists, like other experts, “go deep” in their work: important and valuable, but rarely interdisciplinary
- 9. What is Computational Thinking? My definition • Thinking about problems as if computers will solve them • Thinking about problems in terms of computational concepts – Computer Scientists do this, but so do many others • 100 computational concepts: The ISTA 100 (more about this later)
- 10. Examples of Computational Thinking Atkinson and Shiffrin’s 1968 model of human memory • Modeled after computer memory
- 11. Examples of Computational Thinking Henry Ford’s Assembly line (c. 1913) • decompose complex systems into components: Hierarchy • work on them in parallel: Workflow • assemble the parts
- 12. Examples of Computational Thinking Jacquard’s Loom Controlling work through stored programs
- 13. Examples of Computational Thinking Harold Cohen’s Art
- 14. Examples of Computational Thinking Harold Cohen’s Art
- 15. Examples of Computational Thinking Harold Cohen’s Art
- 16. An Artist Who Thinks Algorithmically
- 17. What is Computational Thinking? • Thinking about problems as if computers will solve them (and sometimes, programming computers to solve them) • Thinking about problems in terms of computational concepts – Computer Scientists do this, but so do many others – Some great ideas of the Information Age predate computers – Some were developed in fields other than Computer Science – All are used widely
- 18. The ISTA 100 • One hundred concepts that matter to practitioners in the Information Age • Wait! That’s only 77 concepts! How come? abstraction, algorithm, alignmnent, association, bandwidth, bit, class, classification, clustering, code, commonsense, complexity, conditional probability, control, correlation, DAG, data, data mining, data scales, decision, distribution, entity, entropy, estimation, event, evidence, expert system, frequency, functionalism, game, generalization, goal, grammar, graph, hierarchy, histogram, independence, induction, inference, information, knowledge, learning, logic, marginal probability, Markov, mean, meaning, median, model, Monte Carlo, mutual information, network, ngram, ontology, optimization, parallelism, prediction, probability, random variable, regression, reinforcement, relation, representation, search space, semantics, sequence, similarity, simulation, state space, structure-function, syntax, taxonomy, tree, utility, variance
- 19. Concepts, Abstractions • Many ISTA concepts are abstractions . What is an abstraction?
- 20. Abstraction • Um, ok, whatever... Abstraction is a conceptual process by which higher, more abstract concepts are derived from the usage and classification of literal (ie. "real" or "concrete") concepts. An "abstraction" (noun) is a concept that acts as super-categorical noun for all subordinate concepts, and connects any related concepts as a group, field, or category. – Wikipedia
- 21. Abstraction
- 22. Abstraction
- 23. Abstraction – Everyone Does It "I have been continuously aware that in painting, I am always dealing with . . . a relational structure. Which in turn makes permission 'to be abstract' no problem at all." Robert Motherwell, American artist, 1915 - 1991 "I have been continuously aware that in programming, I am always dealing with . . . a relational structure. Which in turn makes permission 'to be abstract' no problem at all.”
- 24. ISTA 100: Learning the Abstractions • Some abstractions pay big dividends!
- 25. ISTA 100 and its Requirements • sista.arizona.edu/courses • 3 assignments – 15 points each • one midterm – 25 points • one cumulative final – 30 points • probably one activity that can substitute for an assignment • assignments give you practice with the 100 concepts • exams test familiarity with and understanding of the concepts • late assignments lose one point per day up to seven days; after that, they are worthless

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