Data Visualization with AI Tools – Charts & Insights Practice

Enhance your understanding of data visualization and AI by using this comprehensive, easily accessible 38-page student workbook and teacher resource kit! This guide is ideal for 21st century classrooms as it teaches you how to turn raw data into graphic visual stories through analytical charting principles, ethical practices for the creation of visual materials, and hands-on worksheets that help you understand how to create visual stories from data.

You will learn how to identify common types of charting (bar charts, line charts, scatter plots, histograms, stacked bar charts, etc.), create charts that do not mislead viewers, extract actionable insights from data, and leverage computational and/or AI platforms to analyze real life data sets such as urban heat islands, microplastic pollution, butterfly migration patterns and school nutrition.

The following materials are included with each workbook:

- Theoretical foundation on methodology, Gestalt principles, and the "So What?" (i.e., why is this important?) framework for visual storytelling;

- 10 engaging worksheet activities with real world scenarios (i.e., ecology, agriculture, urban design, ethics);

- Instructional visuals, chart selection matrices, and epistemic workflow diagrams;

- Complete teacher answer keys, or rubrics for use with the worksheets provided in the workbook (Part 3); and

- Designed to improve data literacy, critical thinking and AI-assisted analysis skills - you can print or digitally create the materials needed; perfect for teaching data science, statistics, STEM, computer science or environmental studies. Use visuals that are of professional quality to increase the engagement of students and ultimately prepare them for future success as a professional in a data-dominated world.

Keywords : Data visualization workbooks, AI-based charting tools, practice with student data analysis, resources for creating data literacy worksheets, ethical data visualization resources, teacher resources for creating charts, and development of scatter plot and histogram practice materials are all included in the high school data science curriculum.

Reasons Parents/Schools Like It:

*) Developing Skills for the Future: Learn to utilise AI to visualise data in a way that is ethical and can be used to assist with making informed decisions (i.e., college admission requirements and job applications).

*) No Prep/High Student Engagement: The student workbook has been pre-completed and includes keys/rubrics for teachers to save them hours of prep time while providing the students with relevant work experience.

*) Teaching Analytical Reasoning and Ethics: More than just a nice colourful chart, this course will help students comprehend how to variable

*) Social Studies/Math/Science/Tech all use these lessons to create detailed and real-world examples (Ex: Eco- Planning, Urban Planning, Nutrition, and Immigration) that all students can relate to.

*) Diverse Learning Levels/Access: All students will receive support through scaffolding, pictures, and fill-ins throughout the course, while advanced students will be sufficiently challenged.

Levels for which this content is appropriate (Full PDF Analysis):

*) This material is aimed at 8-12th grade (MIDDLE SCHOOL - ADVANCED) – Graduation Year - 9-12 - Level HS

*) The material is evenly divided into the high school level classes; Data Science, Statistics, AP Statistics, Computer Science, or STEM and Environmental Sciences. Level HS - Graduation Year - 9-12 - Level MS - Grades 7-8

*) The language and real-world scenarios associated with these materials are well within the cognitive abilities of adolescents, as noted in the teacher resources. (see More Detail 10 - Adolescent - Grade 7-8)

Copyright / Terms of Usage

Syed Hammad Rizvi has obtained copyright on this book and this document is intended only for single personal and classroom use. You cannot alter, sell or redistribute anything associated with this document. This means to not put it up on the internet and available publicly.

If you would like to share this document with others you need to go through Teachsimple to buy additional licenses.

Thank you for adhering to the terms above.

Syed Hammad Rizvi is the proud owner of this product.