Information Age Education
   Issue Number 209
May 16, 2017   

This free Information Age Education Newsletter is edited by Dave Moursund 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, six free books based on the newsletters are available: Joy of Learning; Validity and Credibility of Information; Education for Students’ Futures; 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.

Transfer of Learning Revisited

David Moursund
Professor Emeritus, College of Education
University of Oregon

“If I have seen further it is by standing on the shoulders of giants.” (Isaac Newton; English mathematician and physicist; 1642-1726.)

The traditional view of transfer of learning is one of learning in a manner that facilitates applying one’s increasing knowledge and skills both to somewhat similar settings and to new, unfamiliar settings. The goal is to transfer some of one’s current expertise in one area to other areas (Moursund, 2016b).

In schooling, we want and expect that students will learn in a manner that facilitates applying their learning both in and outside of school. Moreover, we want students to be able to make use of their learning (increased expertise) both immediately and for years to come.

The following subsections present two widely used educational approaches to transfer of learning. A subsequent section discusses expertise.

1. Specifically Teach for Transfer

The low-road, high-road theory of Perkins and Solomon covers rote memory (low road) approaches and deeper understanding (high road) approaches to transfer of learning (Perkins & Soloway, 1988).

In low-road transfer, we want students to be able to apply what they are learning to closely similar situations. If a child learns to tie a shoe using a bowknot, we expect the child to use this learned skill on both left and right shoes and on a different pair of shoes. From my own childhood, I found that transferring shoe tying to tying a bowknot in apron strings behind my back was not an easy transfer to make. Tying a bowknot behind my back was considerably different from tying a shoestring that I could see.

In high-road transfer, we want students to learn to recognize situations that may be somewhat related to the understanding, knowledge, and skills they have previously gained. We then want them to apply their understanding, knowledge, and skills to the new situations. It tends to take a relatively high level of expertise in a specific area for this type of transfer to occur.

There are two related parts to this high-road transfer situation. First there is the problem itself. To understand a problem may require considerable knowledge about the disciplines the problem is embedded in. Suppose, for example you are thinking about the problem of how long it takes for an object to fall to the ground when dropped off the top of a tall building. The physics of this falling body includes both the action of gravity and friction with the air. If you happened to know about Newton’s Laws of Motion, you would have a good start. Isaac Newton had to learn about both gravity and friction to deal with this problem.

Second, it can be a considerable challenge to transfer (apply) one’s current understanding, knowledge, and skills to the problem. It is not an easy task for a student who is progressing through a beginning calculus course to actually apply calculus to solve the problem. Indeed, many students find it difficult to transfer math expertise gained in a math class to problems in other disciplines.

2. Teach for Building on the Accumulated Knowledge of the Human Race

Below are four major aspects of building on the work of others:

Teach “standing on the shoulders of giants.” The quote from Isaac Newton given above has been reiterated by many others, for example by Albert Einstein.
“A hundred times every day I remind myself that my inner and outer life are based on the labors of other men [people], living and dead, and that I must exert myself in order to give in the same measure as I have received and am still receiving.” (Albert Einstein; German-born theoretical physicist and 1921 Nobel Prize winner; 1879-1955.)
As a child, you learned the 3Rs, Reading, wRiting, and aRithmetic. You did not invent these tools, nor did you invent paper, pencils, and ballpoint pens. When you were learning the 3Rs you were standing on the shoulders of those who did, as well as on the shoulders of researchers and practitioners in the teaching of the 3Rs. Similarly—as Einstein’s statement suggests—Einstein did not invent either the math or much of the physics he built on as he developed his theory of relativity.
Teach the use of tools specifically designed to help solve a particular category of problems. Consider the hand tools that carpenters use. Each such tool has a type of built-in, inherent knowledge and skill. For example, the metal claw hammer dates back more than 500 years. It is designed for pounding and pulling nails. The claw hammer you can currently purchase represents hundreds of years of experimentation in producing a hammer with an appropriate weight, handle and balance, a nail-pulling claw, and durability. In some sense, the knowledge and skills of the experimenters are incorporated into the tool. A person gaining nail-pounding and nail-pulling expertise in using such a hammer is building on the knowledge and skills of its developers. A crosscut saw is designed to solve a considerably different type of problem, and the skills required are substantially different than those needed to use a hammer.

A carpenter’s hand tools lend themselves to an apprenticeship type of instruction and learning. Each tool is an embodiment of some knowledge, but it takes both instruction and considerable practice to develop a contemporary level of expertise in using such tools.
Teach the use of general-purpose tools designed to aid one’s physical and cognitive capabilities. Study skills provide a good example. For another example, help students learn about capabilities and limitations of robots and general-purpose computers as an aid to solving the problems in each discipline that students study in school.
Teach Computational Thinking (CT)–thinking and problem-solving that make use of both human and computer brains, a relatively new idea (Moursund, 2016a; Pappano, 4/4/2017). Quoting from the abstract of a report by Lockwood and Mooney (March, 2017):
Computational Thinking (CT) has been described as an essential skill which everyone should learn and can therefore include in their skill set. Seymour Papert is credited as concretizing Computational Thinking in 1980 but since [Jeannette] Wing popularized the term in 2006 and brought it to the international community’s attention, more and more research has been conducted on CT in education. The aim of this systematic literary review is to give educators and education researchers an overview of what work has been carried out in the domain, as well as potential gaps and opportunities that still exist.

Quoting from an article by Jeannette Wing (March, 2006):

Computational thinking builds on the power and limits of computing processes, whether they are executed by a human or by a machine. Computational methods and models give us the courage to solve problems and design systems that no one of us would be capable of tackling alone. Computational thinking confronts the riddle of machine intelligence: What can humans do better than computers, and what can computers do better than humans?

In A-D above, Computational Thinking is “the new kid on the block” and a major change agent. Combining the use of our human brain power with computer brain power and artificial intelligence is now a routine part of our lives, but we tend to not be aware of this. For example, when we use a search engine to look up something on the Web, the search engine is making use of artificial intelligence. When we invest in stock funds, the stock funds are likely making use of artificial intelligence as an aid to the human who is deciding what specific stocks the fund should purchase. Some new cellphones are using artificial intelligence and considerable computer power for face recognition in the log-on process. When you talk to your computer or cell phone, artificial intelligence is being used to translate your voice into text.

Gaining Expertise

“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.)

Informal and formal education lead to increasing levels of expertise. Expertise in any particular area refers to a person’s level of knowledge, skills, and experience in that area. In this section, we are especially interested in cognitive expertise in dealing with problems that involve the use of data, information, knowledge, wisdom, and foresight.

A computer is a tool designed for the input, storage, processing, and output of information. In this definition, the term information has gradually grown from meaning data (early computers were called data processing machines) to including data, information, and knowledge. Indeed, as progress continues to occur in Artificial Intelligence, researchers are striving to develop computers that also have wisdom and foresight. The following diagram builds on the above quote from Arthur C. Clarke.

Arthur C. Clarke’s scale of increasing

Arthur C. Clarke’s scale of increasing understanding.

A computer system is a combination of hardware, software, connectivity, and accumulated information. As we steadily develop faster and more compact/portable hardware, more and better computer software, more and better connectivity, and more information stored in computers, we steadily increase the capabilities of computers. In many problem-solving areas, computers have a high level of expertise. Progress in artificial intelligence provides a foundation for developing expert systems. Quoting from the Wikipedia:

An artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, represented mainly as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of artificial intelligence (AI) software.

The steady increase in the areas and levels of expertise of computers presents a major challenge and a major opportunity for our informal and formal educational systems. My 4/5/2017 Google search of the expression "so much to learn so little time" returned more than 150 thousand results. How should the limited and very valuable time in school be spent? The totality of collected knowledge is huge and is growing very rapidly. No human learner can keep up with this pace of new things to learn. Some summary data about publication of scientific, technical, and medical articles in presented in a report by Ware and Mabe (2015):

There were about 28,100 active scholarly peer-reviewed English-language journals in late 2014 (plus a further 6,450 non-English-language journals), collectively publishing about 2.5 million articles a year. The number of articles published each year and the number of journals have both grown steadily for over two centuries, by about 3% and 3.5% per year respectively, though there are some indications that growth has accelerated in recent years.

IBM is deeply involved in using a combination of artificial intelligence and fast computers in the field of medicine. Quoting from an article by Danny Vena (3/21/2017):

IBM Watson for Drug Discovery and Pfizer Inc. (NYSE:PFE) are collaborating in the area of immunotherapy, which uses the body's own immune system to help fight cancer. Watson ingested 25 million Medline abstracts, over one million medical journal articles, data from 4 million patients, and every drug patent since 1861. The companies believe that the ability to recognize previously hidden patterns in the data will provide the next generation of targeted drug uses, while also discovering new uses for existing medications. [Bold added for emphasis.]

Historically, transfer of learning has referred to people learning to transfer their current knowledge to similar or new problems. We have long had simple tools that in some sense contained a limited amount of knowledge and skill. Such tools are an aid to transfer of learning. We now have computer systems and robots that have a considerable (and steadily growing) level of knowledge and skills, and that can learn on their own.

Final Remarks

Information and Communication Technology (ICT) now offers our informal and formal educational systems a very powerful and rapidly changing tool and aid to transfer of learning. I like to think about this situation as one in which a computer can serve both as a teacher and as a problem-solving tool.

Some aspects of ICT tools can be mastered by a child who is learning from a peer or others in a type of apprenticeship mode. For example, a preschool child can learn to play a variety of computer games. Some of these games are carefully designed to provide and integrate teaching, learning, and entertainment.

There are also powerful computer tools that provide only a modest amount of instruction or feedback, but that a young child can learn to use. A digital camera is an excellent example. Feedback from a peer or older person can stress the idea of a “good” picture or video, and how to improve one’s photographic efforts.

Other aspects of ICT tools require the reading (or reading and writing) skills typically taught in schools. However, the same computer system that requires the use of reading and writing can also provide instruction in reading and writing. The tool is both a teacher and a tool! Of course, this isn’t exactly a new idea. Schools have long made use of the idea of learning to read and then using reading as a tool and as an aid to learning.

Still other aspects of ICT tools require specific instruction within existing specialization areas. Each academic area of study has some uses of computer hardware, software, connectivity, and databases of collected information that are quite specific to the discipline. In essence, this suggests that every higher education faculty member needs to have some reasonable level of expertise in the use of ICT in their specialization areas.

I have recently published The Fourth R, a book available free on the Web (Moursund, 12/23/2016). This book presents the idea of Reasoning/Computational Thinking as a 4th R, an extension of the traditional 3 Rs. It proposes that Information and Communication Technology be thoroughly integrated throughout the PreK-12 curriculum, much in the same manner as are the 3 Rs of Reading, wRiting, and aRithmetic (Math). I strongly believe that all students should learn to use computers and to do Reasoning/Computational Thinking, just as all students learn the traditional 3 Rs (Moursund, 12/23/2016). Thus, by starting early and integrating ICT throughout the curriculum, all students will gain a significant level of skill in using the capabilities of computers as an aid to representing and solving problems, and as an aid to learning.

References and Resources

Lockwood, J., & Mooney, A. (March, 2017). Computational thinking in education: Where does it fit? A systematic literary review. Retrieved 4/3/2017 from

Moursund, D. (12/23/2016). The Fourth R. Eugene, OR: Information Age Education. Download the Microsoft Word file from Download the PDF file from Access the book online at

Moursund, D. (10/29/2016). Good curriculum, instruction, and assessment. IAE-Blog. Retrieved 3/27/2017 from

Moursund, D. (2016a). Computational thinking. IAE-pedia. Retrieved 4/3/2017 from

Moursund, D. (2016b). Transfer of learning. IAE-pedia. Retrieved 3/27/2017 from

Pappano, L. (4/4/2017). Learning to think like a computer. The New York Times. Retrieved 4/7/2017 from

Perkins, D.N., & Solomon, G. (1988). Teaching for transfer. Educational Leadership. Retrieved 3/27/2017 from

Vena, D. (3/21/2017). IBM's Watson is tackling medicine's most complex problems. Retrieved 4/5/2017 from

Ware, M., & Mabe, M. (2015). The STM report: An overview of scientific and scholarly journal publishing. International Association of Scientific, Technical and Medical Publishers. Retrieved 4/5/2017 from

Wing, J.M. (March, 2006). Computational thinking. Communications of the Association for Computing Machinery. Retrieved 4/5/2017 from

Free Educational Resources from IAE

IAE publishes and makes available four free online resources:


David Moursund is an Emeritus Professor of Education at the University of Oregon, and editor of the IAE Newsletter. His professional career includes founding the International Society for Technology in Education (ISTE) in 1979, serving as ISTE’s executive officer for 19 years, and establishing ISTE’s flagship publication, Learning and Leading with Technology. He was the major professor or co-major professor for 82 doctoral students. He has presented hundreds of professional talks and workshops. He has authored or coauthored more than 60 academic books and hundreds of articles. Many of these books are available free online. See

In 2007, Moursund founded Information Age Education (IAE). IAE provides free online educational materials via its IAE-pedia, IAE Newsletter, IAE Blog, and books. See Information Age Education is now fully integrated into the 501(C)(3) non-profit corporation, Advancement of Globally Appropriate Technology and Education (AGATE) that was established in 2016. David Moursund is the Chief Executuve Officer of AGATE.


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