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The American Biology Teacher

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Algorithms, Abstractions, and Iterations: Teaching Computational Thinking Using Protein Synthesis Translation
Amanda Peel, Patricia Friedrichsen
The American Biology Teacher, Vol. 80 No. 1, January 2018; (pp. 21-28) DOI: 10.1525/abt.2018.80.1.21
Amanda Peel
AMANDA PEEL is a PhD student in science education in the Department of Learning, Teaching, and Curriculum at the University of Missouri; email: anpn98@mail.missouri.edu.
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Patricia Friedrichsen
PATRICIA FRIEDRICHSEN is an associate professor jointly appointed in the Department of Learning, Teaching, and Curriculum and the Division of Biological Sciences at the University of Missouri; email: friedrichsenp@missouri.edu
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Article Figures & Data

Figures

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  • Figure 1.
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    Figure 1.

    Lightbot game.

  • Figure 2.
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    Figure 2.

    Abstraction (left) and Iteration (right).

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    Figure 3.

    Two examples of student-generated algorithms.

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    Figure 4.

    Scratch layout and vocabulary.

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    Figure 5.

    How to create blocks.

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    Figure 6.

    Scratch and CT connections.

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    Figure 7.

    Example mRNA to amino acid sequence algorithm.

Tables

  • Figures
  • Table 1. CT concept definitions.
    CT ConceptDefinitionExample
    AlgorithmA sequence of steps to solve a problemA recipe is an algorithm for how to make a particular food.
    AbstractionSimplifying information; displaying only the information that is neededWhen someone asks you what you did yesterday, you tell them you stayed at home and watched Netflix, not that you woke up, took a shower, got dresses, ate breakfast, fed your dog…, etc.
    IterationRepeating a sequence of steps until a condition is metWhen you eat a meal, you put food in your mouth, chew, swallow, and repeat until the food is gone.
    BranchingChoosing a path, if/then/else statementsDriving through traffic lights: IF the light is green, THEN you go, ELSE you slow down and stop.
    VariableA value that can change; used in programming to make programs universalIf you were writing an algorithm for your morning routine, you would write: wake up, get out of bed, shower, put on clothes, eat breakfast. In this algorithm, “clothes” is a variable, and its value (what you actually wear each day) changes. Maybe on Monday, clothes = a dress, and on Tuesday, clothes = a shirt and jeans.
  • Table 2. Lesson outline.
    DayLearning ActivityObjective
    1Introduction to CT Using LightbotStudents will problem-solve in a programming game to explore basic CT concepts.
    2Applying CT: Writing Translation AlgorithmsStudents will write an algorithm to simulate how the system of the translation process functions.
    3Extending CT: Programming Translation with Scratch (optional)Students will design a program to simulate the patterns associated with the translation process.
  • Table 3. CT concept examples for student notes.
    CT ConceptExamples
    AlgorithmGame example (MAIN blocks): In every level you build an algorithm to light the colored squares.
    Real life example: When someone asks you for directions to your house, you give them an algorithm.
    AbstractionGame example (Procedure): The procedures were abstractions of the steps in the main program
    Real life example: When someone asks you what you are doing tonight, you tell them you're going to eat spaghetti, not that you are going to boil water, put the noodles in for 10 minutes, heat the sauce, brown the meat…, etc.
    IterationGame example (loops): The loops in the games were examples of iteration. They repeated the sequence until all the squares were lit.
    Real life example: Each day is an iteration, each week, each month, each year.
    BranchingReal life example: Choosing what to wear each day: if it is cold outside, then wear a sweater, else don't wear a sweater.
    VariableReal life example:
    Set variable1 = 5 (program user decides each time they run the program)
    Set variable2 = 6 (program user decides each time they run the program)
    Program: variable1 + variable2 = 11 (the sum of the two values set by the program user)
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Vol. 80 No. 1, January 2018

The American Biology Teacher: 80 (1)
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Algorithms, Abstractions, and Iterations: Teaching Computational Thinking Using Protein Synthesis Translation
Amanda Peel, Patricia Friedrichsen
The American Biology Teacher, Vol. 80 No. 1, January 2018; (pp. 21-28) DOI: 10.1525/abt.2018.80.1.21
Amanda Peel
AMANDA PEEL is a PhD student in science education in the Department of Learning, Teaching, and Curriculum at the University of Missouri; email: anpn98@mail.missouri.edu.
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Patricia Friedrichsen
PATRICIA FRIEDRICHSEN is an associate professor jointly appointed in the Department of Learning, Teaching, and Curriculum and the Division of Biological Sciences at the University of Missouri; email: friedrichsenp@missouri.edu
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Algorithms, Abstractions, and Iterations: Teaching Computational Thinking Using Protein Synthesis Translation
Amanda Peel, Patricia Friedrichsen
The American Biology Teacher, Vol. 80 No. 1, January 2018; (pp. 21-28) DOI: 10.1525/abt.2018.80.1.21
Amanda Peel
AMANDA PEEL is a PhD student in science education in the Department of Learning, Teaching, and Curriculum at the University of Missouri; email: anpn98@mail.missouri.edu.
  • Find this author on Google Scholar
  • Search for this author on this site
  • View author's works on this site
Patricia Friedrichsen
PATRICIA FRIEDRICHSEN is an associate professor jointly appointed in the Department of Learning, Teaching, and Curriculum and the Division of Biological Sciences at the University of Missouri; email: friedrichsenp@missouri.edu
  • Find this author on Google Scholar
  • Search for this author on this site
  • View author's works on this site
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