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Teaching and Mentoring

Lesson Plan

Topic: Data Abstractions with the CORGIS Visualizer

Author: Austin Cory Bart acbart@udel.edu

Version: 0.1.1

Duration: 40-50 minutes

Overview

In this lesson, students interact with an online platform for creating visualizations of a wide variety of datasets (including health, energy, books, law, and more). In doing so, they must confront the limitations of the abstraction inherent in the models presented.

  1. Students will select a dataset from the CORGIS Visualizer, suggest possible concrete abstractions, and identify the kinds of questions that could be answered with those abstractions.
  2. Students will analyze the actual data abstraction that they choose, develop a question related to the dataset, and then create a visualization that answers the question.
  3. Students will identify limitations of the abstraction with regards to the questions it can answer.

Purpose

Visualizations are a powerful way to summarize data into a medium accessible by a wider audience. Computational tools like Excel or Python’s MatPlotLib can be used to quickly produce these visualizations. The result can then be analyzed and interpreted to draw conclusions. Increasingly, data is collected and used to answer important real-world questions by generating these visualizations. However, the collection of data is a design process with trade-offs and decisions. While a computational tool can make it easy to interact with a rich data abstraction, there are still limitations inherent by the process of formalizing an abstraction. In particular, the details that are removed by the process make it impossible to answer other kinds of questions.

Learning Objectives

By the end of this lesson, learners will be able to…

  1. Given a real world entity or idea, identify possible data abstractions and the questions answerable with that abstraction.
  2. Given a tool that provides access to a large dataset, describe the abstraction represented by the data.
  3. Given a tool that provides access to a large dataset, explain the kinds of questions such a tool could and could not answer.

You may also cover:

  1. Given a graph, students will evaluate the graph for its accuracy, validity, and reasonableness.

Standards Alignment

Relevant Computer Science Principles:

Assessment

To assess/verify the learning objectives:

  1. Learners will show the instructors their completed graphs.
  2. Learners will answer instructor questions in the Post-discussion.

Prior Knowledge

Prior to this lesson, learners will already be able to:

  1. Interpret histograms, line plots, scatter plots, and bar charts
  2. Define the concept of a data abstraction (e.g., a dataset)

Learners and Contexts

This lesson was designed for:

Age: Grades 9-12

Size: Any reasonably-sized class should work, probably in 10-50 range works best.

Instructors: No additional instructors are necessary. More instructors can help guide discussion.

Formality: Suitable for formal and informal settings.

Computers:

External Tool: https://think.cs.vt.edu/corgis/visualizer/

Activities

Most of this lesson will be:

1. Warm-up

Strategy: Present Content

Duration: 5 minutes

Content:

Delivery:

2. Show CORGIS Datasets

Strategy: Provide Guidance

Duration: 2 minutes

Instructions:

Rules:

3. Dataset Discussion

Strategy: Support Practice

Duration: 10 minutes

Instructions:

Engagement:

Goals:

3.5. Visualization Misconceptions (Potentially)

Strategy: Present Content

Duration: 10 minutes

Content:

4. Demo Visualizer

Strategy: Provide Guidance

Duration: 5 minutes

Instructions:

Notes:

5. Dataset Exploration

Strategy: Support Practice

Duration: 10 minutes

Instructions:

Engagement:

Goals:

Progress:

Correction:

Rules:

6. Wrap-up

Strategy: Wrap-up

Duration: 8 minutes

Alert:

Instructions:

Summary:

Next:

Contingency Planning

Lack of Devices

Internet Issues

Projectors

Staff Numbers

De-motivated Learners

Struggling Learners

Advanced Learners

Instructional Materials