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Stem display master visualizer12/16/2023 ![]() Here we show: (1) creating explanations of STEM phenomena improves learning without additional teaching and (2) creating visual explanations is superior to creating verbal ones. Uncovering cognitive principles for effective teaching and learning is a central application of cognitive psychology. Together, the findings provide support for the use of learner-generated visual explanations as a powerful learning tool. The benefits should generalize to other domains like the social sciences, history, and archeology where important information can be visualized. The greater effectiveness of visual explanations appears attributable to the checks they provide for completeness and coherence as well as to their roles as platforms for inference. Visual explanations often included crucial yet invisible features. Creating a visual explanation was superior and benefitted participants of both high and low spatial ability. For the chemical system, creating both visual and verbal explanations improved learning without new teaching. For the mechanical system, creating a visual explanation increased understanding particularly for participants of low spatial ability. Both kinds of explanations were analyzed for content and learning assess by a post-test. We compared learning from creating visual or verbal explanations for two STEM domains, a mechanical system (bicycle pump) and a chemical system (bonding). Because visual explanations can show parts and processes of complex systems directly, creating them should have benefits beyond creating verbal explanations. While instruction typically involves visualizations, students usually explain in words. ![]() Mechanisms and processes outside student experience present particular challenges. Students are expected to have had experience coding in JavaScript, HTML, CSS, and jQuery before enrolling in this course.Many topics in science are notoriously difficult for students to learn. This course is not an introductory course to web development. The course will include 4 class projects for you to complete, which will give you the opportunity to practice your D3 skills with real data:Ī simple bar chart to display the revenue growth of a small coffee chain.Īn updating bubble chart, cloning a famous visualization from Gapminder.Īn interactive line chart, showing historical cryptocurrency prices over time.Ī data dashboard for a large conglomerate company.Įach of the projects will gradually become more complex as the course progresses.ĭ3 is an incredibly powerful library to use, with a strong community of developers which is growing every day. Students should take this class if they want to get a rigorous introduction to D3, which covers a wide range of different topics. You'll also learn how to use brushes in D3 to select areas on the chart with the drag of a mouse. You will be able to create visualizations that can communicate with one another, allowing you to link user interactions between multiple different graphs. In the final phase of the course, I will be showing you the proper file structure to use for managing multiple visualizations on the page at once. This part of the course will also teach you the skill of finding new visualizations by yourself, adapting open source code to fit with your own data. I'll introduce you to D3 layouts, and I will be showing you how to build each of these visualizations in D3: You will gain a wide breadth of knowledge in D3, as I will be walking you through pre-written code from members of the D3 community. In the second phase of the course, I will be taking you on a crash course through 12 new visualizations. You will learn how to select the right visual channels for the data that you're working with to create completely unique visualizations. The course will also focus on data visualization design, helping you to make better decisions about how to structure your code, and teaching you to justify the decisions that you make to others. Handle user interactions by adding events to the page.Īdd legends, tooltips, and sliders to your visualizations. Use the D3 update pattern to shift the position of SVGs as our data changes. Write scales, axes, and labels to make some basic visualizations. Understand what SVGs are and how to they work with D3.ĭiscover how D3 associates shapes with pieces of data. In the first phase of the course, I will be building up your knowledge of D3 and introducing you to some of the most foundational topics in data visualization. The course will teach you to program in the latest version of D3 - version 6.x. ![]() This course will take you from a beginner level in D3 to the point where you can build virtually any visualization that you can imagine. Welcome to Mastering data visualization in D3.js!
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