Information Age Education
   Issue Number 150
November, 2014   

This free Information Age Education Newsletter is written by Dave Moursund and Bob Sylwester, and produced by Ken Loge. The newsletter is one component of the Information Age Education (IAE) publications.

All back issues of the newsletter and subscription information are available online. In addition, four free books based on the newsletters are available: Understanding and Mastering Complexity; Consciousness and Morality: Recent Research Developments; Creating an Appropriate 21st Century Education; and Common Core State Standards for Education in America.

This is the third IAE Newsletter in a new series devoted to the educational issue of credibility and validity of information.

Credibility and Validity of Information
Part 3: Information Overload and Underload

David Moursund
Emeritus Professor of Education
University of Oregon

“What is the use of having countless books and libraries, whose titles their owners can scarcely read through in a whole lifetime?” (Lucius Annaeus Seneca; Roman Stoic philosopher, statesman, dramatist; 4 BC-65 AD.)

The previous two articles in this series suggested that future students will need to become much more personally responsible for determining the credibility and validity of information that they use. Quoting from the first of these newsletters:

Credibility focuses on a belief that the person who made an allegation about a phenomenon is believable and can indeed be trusted. It is common to talk about a person and what the person writes/says as being credible and believable.

Validity is an important component of educational research. The word tends to be used in two somewhat different ways:
  1. Validity is the quality of being logically or factually sound. Validity is the extent to which a concept, conclusion, or measurement is well-founded.

  2. A research instrument or test is valid if it measures what it is purported to measure. 
In brief summary, one can think of credibility having a subjective base and validity having an objective base.

This IAE Newsletter discusses information overload and underload (Moursund, 2014). The quote given at the beginning of this newsletter indicates that the concept of information overload is a couple of thousand years old. My 11/2/2014 Google search of information overload underload produced over 54 thousand hits.

A Digital Camera Example

I have a relatively inexpensive 16-megapixel camera. I use it to take a picture. The result is approximately 32 million bytes (256 million bits) of data. In one click of my camera I produce about 256 million zeros and ones. If my camera happens to be in video mode and I take five seconds of 24 frames/second video, I produce over 30 billion bits of data.

You have probably heard the statement, “A picture is worth a thousand words.” Actually, the text in a 250-page novel requires less than a million bytes of computer storage. So, in some sense a color picture is worth 32 books!

If those numbers don’t completely overwhelm you, then consider the Large Hadron Collider (LHC). When an experiment is being run, the equipment takes about 40 million pictures per second. One second of data from the LCD is roughly equivalent to 13 years of high definition television or several hundred million books. That is a lot of data!

Data, Information, Knowledge, Wisdom, and Foresight

“Before you become too entranced with gorgeous gadgets and mesmerizing video displays, let me remind you that information is not knowledge, knowledge is not wisdom, and wisdom is not foresight. Each grows out of the other, and we need them all.” (Arthur C. Clarke; British science fiction author, inventor, and futurist; 1917-2008.)

The following diagram expands on Clarke’s statement and provides some short definitions.

People often use the term information to include all five of the categories data, information, knowledge, wisdom, and foresight. Within any discipline of study we can inquire about the credibility and validity of its information.

The digital camera example of the previous section certainly indicates that we have data overload. Fortunately, we can use computers and other automated machines to process data. My digital camera snapshot can be made into a printed color photograph for about 15 to 20  cents or so. Then I can view and appreciate the picture, share it with friends, and save it in a photograph album. I am dealing with one printed photograph, rather than with 32 million bytes of data.

A Tidbit of Computer History

The first commercially-produced electronic digital computer was named the UNIVAC and became available in June, 1951. In those days, computers were considered to be data processing machines. Gradually, computers began to be regarded as information processing machines. In my early studies in Computer Science, I learned that “A computer is a machine for the input, storage, processing, and output of information.” Over time, the discipline of Computer Science was renamed Computer and Information Science.

The field of computer and information science has grown substantially as computers have steadily become more capable. You may be surprised to learn that the Association for Computing Machinery held its 20th annual meeting on Knowledge and Data Mining August 27, 2014. The 2011 success of IBM’s computer named Watson in defeating human players of the TV game Jeopardy has made it clear that computers are now quite powerful knowledge processing machines.

We now think of a computer as a machine for the input, storage, processing, and output of data, information, and knowledge. The wisdom and foresight still must come from its users. Computer scientists and others continue to struggle with the nature and extent of current computer intelligence and the idea that eventually computers may (will) surpass humans in intelligence.

Information Overload

"Everybody gets so much information all day long that they lose their common sense." (Gertrude Stein; American writer, poet and feminist; 1874-1946.)

I remember the “good old days” when my wife and I bought the Encyclopedia Britannica. This seemed like a large investment at the time, and I built a special bookcase just to house this collection.

Now, the Wikipedia is available free on the Web. Quoting from the Wikipedia (Try not to laugh. I am quoting the Wikipedia about itself. Is this information credible and valid?):

The English Wikipedia alone has over 2.6 billion words, over 100 times as many as the next largest English-language encyclopedia, Encyclopædia Britannica.

I routinely use Google to search the Web. Quoting from John Koetsier (11/1/2013):

[A Google] search starts, of course, with crawling and indexing, and Google says that the web now has 30 trillion unique individual pages. That is up an astonishing 30 times in five years: Google reported in 2008 that the web had just one trillion pages.

Google says that it stores information about those 30 trillion pages in the Google Index, which is now at 100 million gigabytes. That’s about a thousand terabytes, and you’d need over three million 32GB USB thumb drives to store all that data.

When you search, Google tries to figure out not just what you’re typing into the box, but what you mean. So algorithms for spelling, autocompletion, synonyms, and query understanding jump into action. When Google thinks it knows what you want, it pulls results from those 30 trillion pages and 100 million gigabytes, but it doesn’t just give you what it finds.

First, a ranking procedure uses over 200 closely guarded secret factors that look at the freshness of the results, quality of the website, age of the domain, safety and appropriateness of the content, and user context like location, prior searches, Google+ history and connections, and much more.

This last sentence is particularly important. In essence, it says that Google “screens” the hits it provides you so that the ones it considers will be most useful to you are at the top of the list. As Google learns more about you, it uses this knowledge in the screening process.

Information Underload

You might think that a Web search will answer any question you can think of and locate any information that you desired to find. But, that is not the case. Information underload is usually used to describe the situation in which a person cannot gain access to desired information that is known to exist. But, how does a person know what information exists?

I think it is better to think of information underload in terms of a combination of:
  • Not knowing what information exists. When I pose a question or problem to the Web, it would be nice if the Web had enough intelligence to be able to tell me if, as of yet, there is no known answer to the question or problem. The information retrieval system could then go on to explain promising areas of research and development that are making progress in this area, and provide me with access to information about this progress.

  • Not being able to retrieve some of the information that is known to exist. Much of the accumulated knowledge of the human race is not (yet) online, and much that is online is only available for a fee. In addition, there is much information that is proprietary or “secret.” I want the information retrieval system to inform me about such situations and why I cannot have access to the information that I want.

  • Not having the knowledge and skills to make effective use of the information that one retrieves. A good information retrieval system would have provisions for me to tell it my informal and formal educational background, my interests, and other information that would help the system to provide me with information at a level I can understand. (If I have just a high school education, I likely don’t want an answer designed for Ph.D. research Biologists!) In the future, a good information retrieval system will also be a teaching machine. When I am exploring a topic, the system will apprise me of online instructional materials designed to help me learn more about the topic I am exploring.

Final Remarks

The total accumulation of information is huge and is growing rapidly. We suffer from both information overload and information underload. Broad-based browsers such as Google do not screen websites for content credibility and validity. Indeed, they don’t even carry a warning, sign such as: Readers beware! This browser does not assume responsibility for the correctness of the website information it helps you locate.

Here are some important points to consider:
  1. As we search for needed information, we are faced by the problem of “Garbage in, garbage out” (GIGO). Much incorrect and/or very biased information is integrated into the total collection of information available to us. Even an expert in a particular small domain can have trouble separating the wheat from the chaff in his or her domain of expertise. It is not at all surprising that ordinary people often are so easily mislead by what they read on the Web. Our educational system is weak in helping students learn to assess the credibility and validity of information sources and the information they provide.

  2. It takes substantial education and experience to make effective use of much of the accumulated information that is available. Contrast the current Web with a “smart” Web-of-the-future that provides answers suitable to the knowledge, experience, and contextual situation of the individual posing a question or problem. We have a very long way to go to provide this level of individualization.

  3. Think about the difficulty of communicating a problem or question to a computer so that it retrieves just a quite limited number of good, useful answers. When I do a Web search, I am quite displeased when I get thousands or millions of hits. This problem can be addresses in two ways. One way is to provide students with substantial instruction and practice in communicating problems and questions to a computer system, and in refining their communication if it does not produce results that meet their needs. A second way is to make the information retrieval systems smarter. Progress in artificial intelligence is gradually doing this.


Koetsier, J. (3/1/2013). How Google searches 30 trillion web pages, 100 billion times a month. VB News. Retrieved 11/1/2014 from

Moursund, D. (2014). Information underload and overload. IAE-pedia. Retrieved 11/1/2014 from


David Moursund earned his doctorate in mathematics from the University of Wisconsin-Madison. He taught in the departments of Mathematics, Computer Science, and Teacher Education at the University of Oregon. A few highlights of his professional career include founding the International Society for Technology in Education (ISTE), serving as ISTE’s executive officer for 19 years, and establishing ISTE’s flagship publication, Learning and Leading with Technology (now named Entrsekt). He was a major professor or co-major professor of 82 doctoral students. He has authored or coauthored more than 60 academic books and hundreds of articles. He has presented hundreds of professional talks and workshops.

In 2007, he founded Information Age Education (IAE), a non-profit company dedicated to improving teaching and learning by people of all ages throughout the world. See Contact information:

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