Using clouds in teaching
While our explorations of clouds for CEOHP have been focused on research, we are delighted at the potential for teaching. On this page, we have included an introduction of two different types of clouds: Word Clouds and Tag Clouds. We provide examples of clouds being used to analyze different interviews as well as to analyze the content of two reports about CEOHP.
What is a word cloud?
“Word clouds” are a whimsical approach to representing the meaning and themes in a body of text. The ones we present have been produced with a simple web-based application called Wordle. As explained in the Working Group report from ITiCSE 2008 [“Computing Educators Oral History Project: Seeking the Trends”; full reference available on the CEOHP cited works page]:
Wordle is a tool that generates “word clouds” from a piece of text. The cloud-generation algorithm represents relative frequencies by displaying words that occur more frequently using a larger-sized font. The resulting word cloud gives a good notion of which ideas from the text are prominent.
A key disadvantage of word clouds is that, while they create a visually interesting display of frequencies, the result is an image that is impossible for individuals with limited sight or who are blind. Because of this limitation, we have now started to explore representing the themes from a piece of text using word tags.
What is a tag cloud?
Definition of “Tag clouds” from wikipedia:
A tag cloud or word cloud (or weighted list in visual design) is a visual depiction of user-generated tags, or simply the word content of a site, typically used to describe the content of web sites. Tags are usually single words and are normally listed alphabetically, and the importance of a tag is shown with font size or color. Thus, it is possible to find a tag alphabetically and by popularity. The tags are usually hyperlinks that lead to a collection of items that are associated with a tag.
Tag clouds can be used in many ways. For example, they are often used on blogs to highlight frequently occurring terms and show relative frequencies. A key point is that tag clouds can be read and interpreted meaningfully by screen readers such as JAWS, which are used by individuals who are blind or have low vision. For the early work, we used the tool tagCrowd to produce the tag clouds, then edited the resulting HTML to produce the final image.