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A Puzzle to Entertain You

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A Puzzle to Entertain You I have a bag that holds one marble, with equal probability that it is white or black. I add a second marble to the bag, that is white. – PowerPoint PPT presentation

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Title: A Puzzle to Entertain You


1
A Puzzle to Entertain You
  • I have a bag that holds one marble, with equal
    probability that it is white or black.
  • I add a second marble to the bag, that is white.
    I then shake the bag, and take one marble out.
    It is white.
  • What is the probability that the remaining marble
    is black?

2
A Puzzle to Entertain You
  • I have three cards. The first card is blue on
    both sides. The second card is red on one side
    and blue on the other. The third card is red on
    both sides.
  • Now, I show you one side of a card, and it is
    red. What is the probability that the color on
    the other side is red?

3
How Can We TeachProblem Solving?
  • Clifford A. Shaffer
  • Department of Computer Science
  • Virginia Tech
  • shaffer_at_cs.vt.edu

4
Talk Overview
  • Problem Solving
  • What it means to teach PS
  • How I teach PS, and variants
  • Computational Thinking and the CS Principles
    initiative

5
NOT Problem-Based Learning
  • PBL is about a way to present content
  • Students learn content in the context of
    addressing real-world (or at least bigger)
    problems.
  • By Problem Solving I mean fundamental
    skills/strategies that people apply to solve
    problems of any type.

6
Motivation Why We Care
  • Many students are not good at debugging
  • Deduction vs. Random Walk
  • Many students are not good at design
  • Many students are not good at analysis
  • Algorithm Analysis, systems analysis
  • These deficiencies motivated the course, and
    overcoming them is therefore the goal.

7
How CAN we teach PS?
  • An old problem for teachers.
  • Polya 1940s
  • Heuristics

8
What Does It Mean to Teach Problem Solving?
  • Fundamental Hypothesis
  • Problem Solving is a skill, not an ability.
  • Otherwise, we cannot do anything.
  • Secondary Hypothesis
  • Being good at problem solving correlates to being
    good at Computer Science.
  • Skill(PS) Skill(CS)
  • Otherwise, why bother?

9
A Student Comment
  • We are already good at this.
  • Implied hypothesis
  • If you are good at Computer Science, you are good
    at PS.
  • Skill(PS) gt Skill(CS)
  • There does appear to be a lot of truth to this.
  • Correlated? PS is a prereq for CS capability?

10
Fundamental Challenge
  • We want to improve the capability of the weaker
    students to do CS
  • The hypothesis
  • We can do that by improving their PS skills
  • Increased Skill(PS) gt Increased Capability (CS)

11
Observation
  • Many people enjoy doing puzzles.
  • Maybe an interest in puzzles correlates to an
    interest in CS?
  • Irony When a student tunes out my lecture on PS
    because they are working on a Sodoku!

12
History of our PS Course
  • 2006, our Undergraduate Program Committee
    developed major changes in undergraduate
    curriculum
  • Teaching PS not my idea, but I ended up
    developing the course
  • I found textbooks to make a course

13
Pedagogical Approach
  • Weekly homeworks
  • Wide variety including self assessment tests,
    problem sets (individual or in pairs)
  • Key Pedagogical Technique
  • Many classes involve students working problems
    (come to board and demonstrate)
  • Goal is to make visible the problem-solving
    process
  • Failure illustrates more than success

14
What I Actually Teach (1)
  • PS diagnostic, self understanding tests
  • Myers-Briggs, Learning Styles Inventory, Conflict
    resolution
  • Technique Thinking aloud, working in pairs,
    engaging a problem
  • Verbal reasoning/logic, Analogy problems
  • Jack is slower than Phil but faster than Val.
    Val is slower than Jack but faster than Pete.
    Write the names in order of speed.

15
What I Actually Teach (2)
  • Heuristics (about 1/3 of the course)
  • Externalize
  • Visualize
  • Special Features
  • Look at Extremes
  • Simplify
  • Sleep on It
  • Penultimate Step
  • Symmetry
  • Invariants

16
What I Actually Teach (3)
  • Lateral Thinking
  • Deductive and Hypothetical Reasoning
  • Today is Saturday. What is the day after 4 days
    before tomorrow? These are hard!
  • Making an argument proof styles
  • Problem Solving and Programming
  • Succeeding as a student

17
What I Actually Teach (4)
  • Problem Solving in-the-large
  • Problem Definition
  • Generating Potential Solutions
  • Deciding Course of Action
  • Implementing Solution
  • Evaluation
  • Computational Thinking
  • Simulation, Optimization, and Statistics
  • Interpersonal Problem Solving

18
Sources
  • Effective Problem Solving, Second Edition, Marvin
    Levine Heuristics
  • Problem Solving Comprehension, Sixth Edition,
    Whimbey and Lochhead careful deductive
    reasoning
  • The Art and Craft of Problem Solving, Paul Zeitz
    Proofs, Math problems (sparingly)
  • Strategies for Creative Problem Solving, Second
    Edition, Fogler and LeBlanc PS in-the-large
  • I also actively collect sample problems
  • Michalewicz Puzzle Based Learning

19
Variant Math Olympiad Approach
  • Could make the class more math oriented
  • I don't want to make my class too math heavy.
  • Exactly the people that I want to reach (weaker
    CS students) have less capability at math (or are
    even math-phobic)
  • I dont need math to find hard problems!

20
Other Variants
  • CS topics vs. CS relevant examples
  • Finite state and other machines
  • Algorithms
  • Big project for group to work on (or PBL)
  • Computational Thinking
  • Puzzle-based Learning

21
Challenges
  • Student reaction is not strongly positive
  • Our students tend to focus on programming and
    obvious CS content
  • CS Programming
  • Can mitigate by tying more closely to CS content.
    Debugging?
  • Need to maintain faculty support
  • If viewed as non-critical, lower division
    courses get pushed out.

22
Major Positive (to Students)
  • Gives students a framework and a terminology for
    discussing the process of problem solving.

23
The state of Computer Science Education in the US
  • Boom and Bust cycle (15-year cycle)
  • We are coming out of a bust
  • NSF reports 70 reduction in CS majors (80 drop
    among women)
  • We are starting to recover numbers
  • Predictions are for a huge deficit in CS-related
    workers
  • Claims of all the new jobs related to CS

24
Computation Thinking
  • Proposed Solution Teach CS in K12!
  • NSF
  • Jeanette Wing
  • CE21 program
  • CS Principles initiative
  • Google
  • Alice, Scratch, etc.
  • Universities giving summer workshops for
    middle/high school teachers

25
Harsh Realities in US K12 Education
  • CS is not part of the core
  • Few K12 teachers trained to teach CS
  • Lowered interest among students for taking high
    school CS
  • Recently lost our advanced AP exam

26
NSFs CE21 Program
  • Goals
  • Train more teachers to teach CS (10,000?)
  • Teach K12 students to think computationally
  • (We already teach computer literacy in primary
    school)
  • Includes a push to teach CS topics in middle
    schools (6-8)
  • This is where most kids decide their career

27
CS Principles (csprinciples.org)
  • NSF Funded Project College Board
  • PI Owen Astrachan at Duke
  • Goal Define a new AP course
  • Teach it at High School and College Intro

28
CS Principles (csprinciples.org)
  • NSF Funded Project College Board
  • PI Owen Astrachan at Duke
  • Goal Define a new AP course
  • Teach it at High School and College Intro
  • Not a classic programming course
  • Teach a broader introduction to the concepts of CS

29
CS Principles (csprinciples.org)
  • NSF Funded Project College Board
  • PI Owen Astrachan at Duke
  • Goal Define a new AP course
  • Teach it at High School and College Intro
  • Not a classic programming course
  • Teach a broader introduction to the concepts of
    CS
  • Computational Thinking!

30
CS Principles (csprinciples.org)
  • NSF Funded Project College Board
  • PI Owen Astrachan at Duke
  • Goal Define a new AP course
  • Teach it at High School and College Intro
  • Not a classic programming course
  • Teach a broader introduction to the concepts of
    CS
  • Computational Thinking!
  • Pilot Sites

31
CS Principles Big Ideas
  1. Computing is a creative human activity that
    engenders innovation and promotes exploration
  2. Abstraction reduces information detail to focus
    on concepts relevant to understanding and solving
    problems
  3. Data and information facilitate the creation of
    knowledge
  4. Algorithms are tools for developing and
    expressing solutions to computational problems
  5. Programming is a creative process that produces
    computational artifacts
  6. Digital devices, systems, networks enable and
    foster computational approaches to solving
    problems
  7. Computing enables innovation in other fields

32
Computational Thinking Practices
  1. Analyzing effects of computation
  2. Creating computational artifacts
  3. Using abstractions and models
  4. Analyzing problems and artifacts
  5. Communicating processes and results
  6. Working effectively in teams

33
(Almost) The End
  • Thank you for listening!
  • What are your experiences with teaching
  • Problem Solving?
  • Computational Thinking?

34
A Closing Puzzle
  • A man is driving his car on a shopping trip
    around town. Shortly after he starts out, he
    notices that his odometer (which has six digits)
    is showing a palindrome. An hour or so later, as
    he is nearly finished with his shopping trip, he
    looks at his odometer again. He notices that it
    is showing a different palindrome.
  • How far did he drive?

35
A Closing Puzzle
  • On 24 January 1993, Ms. Green celebrated her
    birthday. This was a special day because the
    number of years she had now completed was equal
    to the sum of the digits for the year when she
    was born. How old was Mrs. Green that day?
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