Lesson Summary

Summary 

Continuing the focus on data analysis from Unit Five, students will use the browser-based Dataquest learning environment (http://www.dataquest.io) and supplementary materials to explore more ways in which Python can be used to analyze data. For the first week, students will explore Dataquest through the browser-based "missions" on the website. Each lesson begins with a warm-up/journal entry, and students then spend the rest of the time working through the missions at their own pace.  For the second part of the lesson, students will design and implement their own data analysis project in order to prepare them to complete a data-focused Create Performance task.

Outcomes

  • Students will understand how to design a data analysis project
  • Students will have the tools to analyze data in Python
  • Students will have practice reading and understanding datasets

Overview

Week One: Learning Dataquest

  1. Getting Started (5 - 10 min)
  2. Independent Study (40 - 45 min)

Week Two: Data Analysis Project

  1. Students Plan and Implement Data Analysis Program

 

Learning Objectives

CSP Objectives

Big Idea - Creativity
  • EU 1.1 - Creative development can be an essential process for creating computational artifacts.
    • LO 1.1.1 - Apply a creative development process when creating computational artifacts. [P2]
      • EK 1.1.1A - A creative process in the development of a computational artifact can include, but is not limited to, employing nontraditional, nonprescribed techniques; the use of novel combinations of artifacts, tools, and techniques; and the exploration of personal curiosities.
      • EK 1.1.1B - Creating computational artifacts employs an iterative and often exploratory process to translate ideas into tangible form.
  • EU 1.2 - Computing enables people to use creative development processes to create computational artifacts for creative expression or to solve a problem.
    • LO 1.2.2 - Create a computational artifact using computing tools and techniques to solve a problem. [P2]
      • EK 1.2.2A - Computing tools and techniques can enhance the process of finding a solution to a problem.
      • EK 1.2.2B - A creative development process for creating computational artifacts can be used to solve problems when traditional or prescribed computing techniques are not effective.
    • LO 1.2.4 - Collaborate in the creation of computational artifacts. [P6]
      • EK 1.2.4A - A collaboratively created computational artifact reflects effort by more than one person.
      • EK 1.2.4B - Effective collaborative teams consider the use of online collaborative tools.
      • EK 1.2.4C - Effective collaborative teams practice interpersonal communication, consensus building, conflict resolution, and negotiation.
      • EK 1.2.4D - Effective collaboration strategies enhance performance.
      • EK 1.2.4E - Collaboration facilitates the application of multiple perspectives (including sociocultural perspectives) and diverse talents and skills in developing computational artifacts.
Big Idea - Abstraction
  • EU 2.2 - Multiple levels of abstraction are used to write programs or create other computational artifacts.
    • LO 2.2.1 - Develop an abstraction when writing a program or creating other computational artifacts. [P2]
Big Idea - Data
  • EU 3.1 - People use computer programs to process information to gain insight and knowledge.
    • LO 3.1.1 - Find patterns and test hypotheses about digitally processed information to gain insight and knowledge. [P4]
    • LO 3.1.2 - Collaborate when processing information to gain insight and knowledge. [P6]
    • LO 3.1.3 - Explain the insight and knowledge gained from digitally processed data by using appropriate visualizations, notations, and precise language. [P5]
  • EU 3.2 - Computing facilitates exploration and the discovery of connections in information.
    • LO 3.2.1 - Extract information from data to discover and explain connections or trends. [P1]
    • LO 3.2.2 - . Determine how large data sets impact the use of computational processes to discover information and knowledge. [P3]
Big Idea - Algorithms
  • EU 4.1 - Algorithms are precise sequences of instructions for processes that can be executed by a computer and are implemented using programming languages.
    • LO 4.1.1 - Develop an algorithm for implementation in a program. [P2]
      • EK 4.1.1A - Sequencing, selection, and iteration are building blocks of algorithms.
      • EK 4.1.1B - Sequencing is the application of each step of an algorithm in the order in which the statements are given.
      • EK 4.1.1C - Selection uses a Boolean condition to determine which of two parts of an algorithm is used.
      • EK 4.1.1D - Iteration is the repetition of part of an algorithm until a condition is met or for a specified number of times.
      • EK 4.1.1G - Knowledge of standard algorithms can help in constructing new algorithms.
      • EK 4.1.1H - Different algorithms can be developed to solve the same problem.
      • EK 4.1.1I - Developing a new algorithm to solve a problem can yield insight into the problem.
    • LO 4.1.2 - Express an algorithm in a language. [P5]
      • EK 4.1.2A - Languages for algorithms include natural language, pseudocode, and visual and textual programming languages.
      • EK 4.1.2B - Natural language and pseudocode describe algorithms so that humans can understand them.
      • EK 4.1.2C - Algorithms described in programming languages can be executed on a computer.
      • EK 4.1.2G - Every algorithm can be constructed using only sequencing, selection, and iteration.
Big Idea - Programming
  • EU 5.1 - Programs can be developed for creative expression, to satisfy personal curiosity, to create new knowledge, or to solve problems (to help people, organizations, or society).
    • LO 5.1.1 - Develop a program for creative expression, to satisfy personal curiosity, or to create new knowledge. [P2]
      • EK 5.1.1A - Programs are developed and used in a variety of ways by a wide range of people depending on the goals of the programmer.
      • EK 5.1.1B - Programs developed for creative expression, to satisfy personal curiosity, or to create new knowledge may have visual, audible, or tactile inputs and outputs.
      • EK 5.1.1C - Programs developed for creative expression, to satisfy personal curiosity, or to create new knowledge may be developed with different standards or methods than programs developed for widespread distribution.
      • EK 5.1.1D - Additional desired outcomes may be realized independently of the original purpose of the program.
    • LO 5.1.2 - Develop a correct program to solve problems. [P2]
      • EK 5.1.2A - An iterative process of program development helps in developing a correct program to solve problems.
      • EK 5.1.2B - Developing correct program components and then combining them helps in creating correct programs.
      • EK 5.1.2C - Incrementally adding tested program segments to correct working programs helps create large correct programs.
      • EK 5.1.2D - Program documentation helps programmers develop and maintain correct programs to efficiently solve problems.
      • EK 5.1.2E - Documentation about program components, such as code segments and procedures, helps in developing and maintaining programs.
      • EK 5.1.2F - Documentation helps in developing and maintaining programs when working individually or in collaborative programming environments.
      • EK 5.1.2I - A programmer's knowledge and skill affects how a program is developed and how it is used to solve a problem.
      • EK 5.1.2J - A programmer designs, implements, tests, debugs, and maintains programs when solving problems.
    • LO 5.1.3 - Collaborate to develop a program. [P6]
      • EK 5.1.3A - Collaboration can decrease the size and complexity of tasks required of individual programmers.
      • EK 5.1.3B - Collaboration facilitates multiple perspectives in developing ideas for solving problems by programming.
      • EK 5.1.3C - Collaboration in the iterative development of a program requires different skills than developing a program alone.
      • EK 5.1.3D - Collaboration can make it easier to find and correct errors when developing programs.
      • EK 5.1.3E - Collaboration facilitates developing program components independently.
      • EK 5.1.3F - Effective communication between participants is required for successful collaboration when developing programs.
  • EU 5.2 - People write programs to execute algorithms.
    • LO 5.2.1 - Explain how programs implement algorithms. [P3]
      • EK 5.2.1A - Algorithms are implemented using program instructions that are processed during program execution.
      • EK 5.2.1B - Program instructions are executed sequentially.
      • EK 5.2.1C - Program instructions may involve variables that are initialized and updated, read, and written.
      • EK 5.2.1E - Program execution automates processes.
      • EK 5.2.1I - Executable programs increase the scale of problems that can be addressed.
  • EU 5.4 - Programs are developed, maintained, and used by people for different purposes.
    • LO 5.4.1 - Evaluate the correctness of a program. [P4]
      • EK 5.4.1A - Program style can affect the determination of program correctness.
      • EK 5.4.1B - Duplicated code can make it harder to reason about a program.
      • EK 5.4.1C - Meaningful names for variables and procedures help people better understand programs.
      • EK 5.4.1D - Longer code segments are harder to reason about than shorter code segments in a program.
      • EK 5.4.1E - Locating and correcting errors in a program is called debugging the program.
      • EK 5.4.1G - Examples of intended behavior on specific inputs help people understand what a program is supposed to do.
      • EK 5.4.1H - Visual displays (or different modalities) of program state can help in finding errors.
      • EK 5.4.1I - Programmers justify and explain a program’s correctness.
      • EK 5.4.1J - Justification can include a written explanation about how a program meets its specifications.
      • EK 5.4.1K - Correctness of a program depends on correctness of program components, including code segments and procedures.
      • EK 5.4.1L - An explanation of a program helps people understand the functionality and purpose of it.
      • EK 5.4.1M - The functionality of a program is often described by how a user interacts with it.
      • EK 5.4.1N - The functionality of a program is best described at a high level by what the program does, not at the lower level of how the program statements work to accomplish this.
  • EU 5.5 - Programming uses mathematical and logical concepts.
    • LO 5.5.1 - Employ appropriate mathematical and logical concepts in programming. [P1]
      • EK 5.5.1A - Numbers and numerical concepts are fundamental to programming.
      • EK 5.5.1B - Integers may be constrained in the maximum and minimum values that can be represented in a program because of storage limitations.
      • EK 5.5.1C - Real numbers are approximated by floating-point representations that do not necessarily have infinite precision.
      • EK 5.5.1D - Mathematical expressions using arithmetic operators are part of most programming languages.
      • EK 5.5.1E - Logical concepts and Boolean algebra are fundamental to programming.
      • EK 5.5.1F - Compound expressions using and, or, and not are part of most programming languages.
      • EK 5.5.1G - Intuitive and formal reasoning about program components using Boolean concepts helps in developing correct programs.

Teacher Resources

Student computer usage for this lesson is: required

DataQuest.io website: https://www.dataquest.io/learn

Week One Materials: Unit 6 Resources -> DataQuest.io -> Week One Lesson Materials -> Mission #

Week Two Materials:

Datasets: Unit 6 Resources -> Dataquest.io - > Week Two Project Datasets and Materials -> Datasets

Sample Project: Unit 6 Resources -> Dataquest.io - > Week Two Project Datasets and Materials -> Sample Project

Project Rubric: Unit 6 Resources -> Dataquest.io - > Week Two Project Datasets and Materials -> "Data Analysis Project Rubric"

(Quizzes for Week One and Week Two are in the corresponding teacher-only resource folders)

 

 

Lesson Plan

Week One: Learning Dataquest

Note: all worksheets and quizzes can be found in the teacher-only resource folder, Unit Six -> DataQuest.io -> Week One Lesson Materials -> Mission #

Directions for working in Dataquest.io

  1. Each student will first need to create an account on Dataquest.io. This is free, and will help them to keep track of their progress.
  2. Each mission comes with a worksheet with required sections to complete. Students are encouraged to fill out as much as possible. The non-required sections are introductions to basic coding tools. Some students may want to do these if they need a refresher on the concepts. 
    • Note: As of now, sections cannot be skipped on the website. This limitation may change in the future.
  3. Once they have completed the worksheet for the mission, students will use the notes on their worksheets to complete:
    1. concept quiz to test their understanding of the data science concepts.
    2. coding quiz to test their understanding of the Python concepts.

Quizzes should be done in class, and should take a minimum of 10-20 minutes to complete. It is advisable to not give a quiz out in the last ten minutes of class. If there are only a few minutes left, the student can use the time to add to their notes.

If a student fails one of the quizzes, they may be given the chance to go back and add to their worksheet before attempting the quiz again. (Multiple versions of all coding quizzes are available.)

There are a total of four Missions for the Introduction to Python track. Students are only required to do the first three. The fourth Mission has worksheets/quizzes for those students who get to it, and can be counted as extra credit/normal grade at the teacher’s discretion. Two additional optional missions are available: one on data visualization, and one on working with statistics.

Getting Started (5 - 10 min)

Day 1

Show the first two minutes of the introductory video in Mission 1 on the Dataquest.io website. Students will discuss their reactions and thoughts about Data Science.

Day 2

Pull up d3js.org on the projector. This is the webpage for a data visualization library in Javascript that has many great examples of ways to make connections from data. You can explore by clicking on one of the tiles on the front page. Explore the D3 front page with the class and discuss reactions.

Day 3

This warm-up time is used for class discussion on progress through the missions. You can use this time to gauge the students' comfort with Python concepts by having students vote with their heads down. If enough students are having trouble, you may want to have a separate review session during the class.

Day 4

This warm-up time can be used for reviewing a Python concept (such as Dictionaries) or looking at a current news article involving data analysis (any article about a topic of interest to the students that uses statistics would be appropriate). Students should think-pair-share on additional ways in which data could be used.

Day 5

Students should do a show of hands to see where everyone is in the missions. The class should have a general discussion about progress.

 

Week Two: Data Analysis Project

Note: All materials for this section can be found in Unit 6 Resources -> Dataquest.io - > Week Two Project Datasets and Materials

Directions: 

For this week, students will be pairing up to create and implement a data analysis program of their own design.

  • Teachers start out the first day by presenting the PowerPoint "Project Introduction," which goes through the steps to creating a data analysis project. Teachers then review the "Data Analysis Project Directions" document.
  • The class splits up into groups of two (with up to one group of three) and each group chooses a dataset to work with. It is preferable if each group chooses a different dataset.

For the rest of the week, students should work on their projects in their groups. At the end, teachers can optionally have them present their PowerPoints to the class, exchange presentations in pairs, or merely turn everything in.


Evidence of Learning

Formative Assessment

  • Week One quizzes
  • Check for understanding at the beginning of each day of week one.

Summative Assessment

Week two project.