“A man coming into a strange country without knowledge of the language is uncertain where to get his ticket at the station or the harbor, where to put his boxes, how to make use of the telephone in the telephone box, where to go in the post office. But if he sees pictures by the side of the strange words, they will put him on the right path.“
(Otto Neurath 1980, as cited in Sonvilla-Weiss, 2008: p. 30 et seq.)
This is only one of many situations in which communication through visuals is very helpful or even necessary. However, it doesn‘t have to be such a specific situation to show the strengths of visualization— pictures help us in communicating certain kinds of information in our everyday life. They can make it much easier and faster to tell about facts or situations than a verbal description could. They help to communicate, even in situations when speaking would be inappropriate. Taking a photo and sending it via mobile phone is often less effort than writing an explanation (see Rantavuo, 2008: p. 83 et seq.).
Pictures can make complex data constructions simple and almost self-explanatory, help you to see what others think and make it easier for you to understand, connect and remember information.
I. Isotype and Pictograms
The problem described in the quote above about being in a strange country not knowing the language and trying to find one‘s way around is a typical situation that has to be solved in a visual way. One possibility would be to use a special kind of signs called pictogram, invented by Otto Neurath and designed by Gerd Arntz, who developed a visual language called “Isotype” (International System of Typographic Picture Education). Isotype is a collection of standardized signs that are meant to be understandable for everyone and that “became the visual code of picturing knowledge” (Sonvilla-Weiss, 2008: p. 33 et seqq.). The video below by “The Noun Project“, which is a project to expand the collection of Isotype with new pictograms in order to develop a global visual language for everyone, explains the principle and the aim of those icons very briefly.
Pictograms may have the power to unite people all over the world by creating a visual language everyone can understand. However, even those signs call for previous knowledge to connect to: In order to understand what is being said, you have to know the real situation the symbol is referring to, like working on a computer or making coffee using a coffee machine. This might sound obvious, but is being neglected very often.
In the case of “The Noun Project“, for example, the information system is created for a western understanding of knowledge, while other ways of knowing, that might be completely different, are being ignored (see Van der Velden, 2001: p. 165 et seqq.). Different cultures may have different symbols, different art or technology and a completely different perception of the world, and therefore might not be able to understand many of those signs. As „The Noun Project“ tries to develop a language for everyone, this is an aspect they should pay attention to.
II. Connectivism and Constructivism
The thought of different cultures and different ways of knowing leads to an important theory for visual knowledge building called Connectivism. Connectivism deals with the question of how to help people to connect and to learn.
Connecting to each other and to existing networks is the key, because knowledge rests in networks from which a learner might benefit. As the real and digital world is flooded with information and new knowledge every day, it is impossible to know it all — therefore knowing where to find information is more important (see Siemens, n.d.).
Furthermore, a diversity of opinions and all kinds of information can help to choose what is most effective and what to learn (see Siemens, n.d.).
Connectivism is not to be confused with Constructivism, which also is a learning theory. Constructivism says that people create meaning through individual constructs, their own understanding and knowledge of the world through experiences. This is done actively by the recipient, who aligns new situations and information with their concepts, which might affect their opinions or lead to declining the new information (see Dougiamas, 1998).
III. Understanding Images
As stated above, pictures can explain a situation or some facts very quickly, while describing with words would make much more effort. Especially when describing something visual, like the new car or a certain hair-do, words would never be able to explain all the exact details, colors and shapes, while a picture can do this in less than a second. However, you usually need words that tell you what the picture is about, unless you know the context through the situation or previous communication.
In order to “read” the information and knowledge carried by a picture, you need the knowledge and the skills to identify them (see Collier 2001: p. 35 et seq.). There are several approaches to read a picture as well as theories like Gestalt and Semiotics that can assist in discovering the meaning of an image. However, there can often be more than one suitable interpretation and it might be hard to tell what meaning the picture is supposed to deliver.
When images are used to visualize and assist the understanding of a particular information, this uncertainty about the actual meaning has to be avoided and the meaning should be clear in order to not confuse the recipient.
IV. Information Design
Visual knowledge building is not only about understanding certain signs in order to find one‘s way around, although signs like the pictograms mentioned above can be necessary and helpful in all learning situations. Visual knowledge building goes further: It is about learning and achieving knowledge and skills through and with visuals, to understand relations and big amounts of abstract data.
Just as design is about solving problems, information design is about solving information problems like information overload, missing trust, reliability transparency or even to simply interest us. It is a form of knowledge-compression, the information is turned into a visual landscape that you can explore with your eyes. This can make the information, no matter how complicated and abstract it might be, effortless, even beautiful, so observing it feels like a relieve in the jungle of information, especially on the internet (see McCandless, 2010).
„From flight plans to forecast maps, from tomography to robot simulations, from global info maps to artistic data sculpture, this digital information can only be fully understood if information visualization, data mining and graphic design are jointly employed“ (Sonvilla-Weiss 2008: p. 61). Visualized, these facts, connections and data can even reveal additional information: specific patterns, new connections or ideas can be developed.
A popular way to visualize data is to create an infographic that shows, through visuals and text, all the important facts, connections at first glance and, at second glance, further information and details (see Neurath, Otto, cited in Sonvilla-Weiss 2008: p. 33). There are many ways to do this, depending on the content that is being explained. The examples below can give some inspiration, but while exploring the internet you can find many more, for example on pages like informationisbeautiful.net, dailyinfographic.com or visualcomplexity.com.
The video below is an infographic about information, that comes along in the form of a video. The combination of images with written and spoken text makes is even easier and fun to follow and understand the content.
V. Mind Maps
Another very useful way of visualizing information is to create a mind map. In contrast to infographics, mind maps focus on the creative process of thinking about a certain topic. The method was invented by Tony Buzan, who established several laws for most effective mind mapping, which you can see in the video below.
VI. Bloom‘s Taxonomy
In 1956 Benjamin Bloom developed a taxonomy of learning that divides the aim of the learning process into three aspects: cognitive (knowing), affective (attitude) and psychomotor (skills) (see Clark, n.d.). For Visual Knowledge Building especially the cognitive aspect is very interesting, as it gives us a concept about how to improve the learning effect for recipients.
Bloom separates the cognitive learning aspect into six steps, from the lowest level at the bottom to the highest level at the top:
6. Creating: create a new product or point of view by combining information
5. Evaluating: arguing and defending information, judging and making decisions
4. Analyzing: identifying and examining information and logic
3. Applying: using the information for solving problems etc.
2. Understanding: being able to explain in own words
1. Remembering (Knowledge): memorizing information(see Overbaugh, n.d.).
This means that the learning effect for the recipient will be higher, the more they are involved in the learning situation and the more they have the chance to interact and create something on their own. How these levels can be achieved always depends on the learning object itself, but this model gives us a guideline on what aspects to focus on.
VII. E-Learning and Digital Natives
The term „e-learning“ summarizes all kinds of learning that are supported electronically. That means, the information or knowledge is delivered in an electronic way, for example via internet, audio or TV and can include text, pictures, videos and sounds. A high advantage of e-learning, especially when using a computer, is not only the fact that text, images and sounds can be combined very easily to create an effective multimedial learning object, but also the possibilities to create simulations and include interactivity (as in the examples below).
“Cyberspace… enables its audience not merely to observe a reality, but to enter it and experience it as if it were real…. Whereas film is used to show a reality to an audience, cyberspace is used to give a virtual body, and a role, to everyone in the audience. Print and radio tell; stage and film show; cyberspace embodies”
(R. Walser, 1990, cited in Sonvilla-Weiss, 2006: p. 4)
However, not everybody feels comfortable with using the computer, particularly in learning situations. Some people might not be used to work with the computer at all, some may have some experience but still have difficulties with understanding all the complex and interactive possibilities, while others navigate through the virtual environment intuitionally without having any problems.
Basically, you can devide the population today in two main groups called the „digital natives“ and the „digital immigrants“. The digital natives are, as the name indicates, those that have grown up with computers and internet and learned how to use them at a very young age. Therefore, they find their way very quickly and have developed a certain way of learning and thinking, which is completely different from the one the other main group, the digital immigrants, have (see Prensky 2001: p. 1 et seq.).
The group of the digital immigrants consists of the older generations, those that didn‘t grow up with digital media all around them but learned (or tried to learn) how to use them at a later point in their life. As if they were learning a new foreign language, they tried to adopt all the things they need to know about getting along in digital environments; however, most of them will never get rid of their „digital immigrant accent“, which means they might tend to print emails or read manuals instead of learning by doing (see Prensky 2001: p. 1 et seq.).
This is something we always have to keep in mind when creating learning objects, especially when using the computer. If our target group is a younger genereration, we can expect them to be able to use the virtual learning object without problems and being able to explore the information given without difficulties, and might even find it easier and more exciting to learn in a playful way, through computer games and interactive visualized data to explore theirselves. When adressing older target groups, that we expect to belong to the digital immigrants, we have to make sure they are well guided and don‘t get lost in the big, wide virtual space.
Clark, D.R. (n.d.): Bloom‘s Taxonomy of Learning Domains. http://www.nwlink.com/~donclark/hrd/bloom.html, accessed on 2012-10-30.
Collier, Malcolm (2001): Approaches to Analysis in Visual Anthropology. In: Van Leeuwen, Theo / Carey Jewitt (2001): Handbook of Visual Analysis. London: SAGE Publications Ltd, p. 35-60.
Dougiamas, Martin (1998): A journey into Constructivism. http://dougiamas.com/writing/constructivism.html, accessed on 2012-10-30.
McCandless, David (2010): The beauty of data visualization. http://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.html, accessed on 2012-10-28.
Prensky, Marc (2001): Digital Natives, Digital Immigrants. In: On the Horizon, Vol. 9 No. 5. NCB University Press.
Rantavuo, Heli (2008): Connecting Photos: A Qualitative Study Of Cameraphone Photo Use. Helsinki: University of Art and Design Helsinki.
Siemens, George (n.d.): Connectivism. A learning theory for today‘s learner. About: Description of Connectivism. http://www.connectivism.ca/about.html, accessed on 2012-10-30.
Sonvilla-Weiss, Stefan (2006): Art / Science and Education. We have to know what we want to know before we can start looking for it. Helsinki.
Sonvilla-Weiss, Stefan (2008): (In)visible. Learning to Act in the Metaverse. Vienna: SpringerWienNewYork.
The Noun Project (2012): About – Creating, Sharing and Celebrating the World‘s Visual Language. http://thenounproject.com/about/, accessed on 2012-10-30.
Overbaugh, Richard C. / Lynn Schultz (n.d.): Bloom‘s Taxonomy. http://ww2.odu.edu/educ/roverbau/Bloom/blooms_taxonomy.htm, accessed on 2012-10-30.
Van der Velden, Maja (2001): Cognitive Justice: Cultivating the Diversity of Knowledge. In: Lovink, Geert / Soenke Zehle (2005): Incommunicado reader. Amsterdam: Institute of Network Cultures, p. 164-170.
-  The Conversation Prism by Brian Solis. http://www.briansolis.com/2008/08/introducing-conversation-prism/
-  VW Käfer. http://automarken.net/modelle/vwkaefer.shtml
-  Starbucks and McDonalds. http://www.princeton.edu/~ina/infographics/starbucks.html
-  Bloom’s Taxonomy. http://www.learningandteaching.info/learning/bloomtax.htm
- Sources of images in galleries/slideshows are mentioned in each image’s caption