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Part 14: The Future of Teaching Machines
Emeritus Professor of Education
University of Oregon
Historically, the elementary school has been
Tomorrow's elementary school will be heavily capital-intensive. (Peter
Drucker; Austrian writer and management consultant, and self-described
social ecologist; 1909–2005.)
Nothing could be more absurd than an experiment in which computers are
placed in a classroom where nothing else is changed. (Seymour Papert;
South African/American mathematician, computer scientist, and educator;
Written materials—along with knowledge and skills in reading and
writing—were the first general purpose teaching machines. What a great
technological breakthrough! Teach students the rudiments of reading and
writing, and then provide them with books and writing implements. The
book, as a teaching machine, could both help students gain a steadily
increasing level of literacy and could also help in gaining knowledge
and skills in any area that could be represented in written form.
Moreover, writing is a powerful aid to the human brain in both
communication and problem solving.
The advent of Information and Communications Technology (ICT) over the
past 60 years has made possible the development of teaching machines
that include all of the capabilities of book-based reading-assisted
instruction and writing-assisted problem solving and communication, and
also greatly extend these capabilities.
Isaac Asimov’s Vision of a Teaching Machine
Science fiction writers have long considered the possibility of
teaching machines that were better than books. Isaac Asimov
, one of the leading science fiction
writers of the 20th century, addressed this topic in a 1976 short
story, The New Teachers. In his essay of the future, each student
had access to a teaching machine that included access to a global
library. Quoting from the essay:
We can reasonably hope that the teaching machine will be sufficiently
intricate and flexible to be capable of modifying its own program (that
is, “learning”) as a result of the student’s input.
In other words, the student will ask questions, answer questions, make
statements, offer opinions, and from all of this, the machine will be
able to gauge the student well enough to
adjust the speed and intensity of its course of instruction and, what’s
more, shift it in the direction of the student interest displayed.
All teaching machines would be plugged into [a] planetary library and
each could then have at its disposal any book, periodical, document,
recording, or videocassette encoded there. [Bold added for emphasis.]
Our technological progress during the 38 years since 1976, now allows
us to build teaching machines that surpass Asimov’s fictional
futuristic teaching machine.
Beginning in the late 1950s, the United States and Canada built
an “early warning” system of radar and computers that could detect and
report on missiles being launched over the North Pole toward their
countries. Operators viewed a computerized TV display screen and could
act on the data they were receiving. The same display screen could show
simulated (previously recorded or computer generated) data. So, system
operators could be trained/educated using quite authentic simulations.
The integration of a problem-solving tool with a teaching tool was a
huge breakthrough in teaching machines.
In 1960 the first PLATO
(Programmed Logic for Automatic Teaching
Operations) system became operational on a computer at the University
of Illinois. Like any well-conceived teaching machine project, PLATO’s
capabilities grew over time as better hardware became available, as
data was gathered from users, as research progresses occurred in
theories of teaching and learning, and as the content developers and
programmers became more adapt at their tasks.
One of great powers of teaching machines is that they can gather data
as they interact with students. As Asimov forecast, this data can be
used to individualize instruction. In addition, it can be used in
research into the areas of teaching and learning.
The results of this research can be incorporated into the software of
teaching machines. Compare this easy upgrade of the machine’s
capabilities to the task of “upgrading” hundreds of thousands of
human teachers. This ease of updating teaching machines is one reason
they will gradually play a larger and larger role in lifelong informal
and formal education.
My “Near Future” Teaching Machine
Of course, my teaching machine will be small and portable. It
will have a high-resolution color display touch screen, long battery
life, fast connectivity to the Internet, voice input, voice output, and
automatic translation among languages from both text and voice. Using
its built-in intelligence, compute power, and connectivity, it will be
able to solve or help greatly in solving a huge range of problems of
the types that people encounter in school, in their everyday lives, and
on the job. This teaching machine will be aware of its user’s location,
will act as a GPS
and will access and process the visual and sound information that its
user is receiving from both the physical and electronic environments.
It will always be available, and it will facilitate “just in time”
Here are some details elaborating the previous paragraph.
- You are probably familiar with a computer named Big Blue that defeated the reining world chess champion Garry Kasparov in 1997, and a computer named Watson that defeated two of the best human players of the TV game Jeopardy in 2011. IBM’s work with its computer system named Watson
captures the flavor of progress in using powerful computers to help
solve a wide range of human problems in healthcare, research, and a
number of other areas.
My “near future” teaching machine not only provides students with ready
access to such systems but also integrates use of such systems into the
everyday curriculum. See my IAE-pedia article Two Brains are Better Than One.
- Here is a recent personal story. I had a question about some details of Piaget’s four-stages
of human cognitive development, and I was unable to find an answer via
an hour of Web searches. So I sent my question to a Piaget distribution
list. A couple of the responses cited references in Spanish and French.
Another then noted that he was unable to find an English translation of
the French citation that he felt contains an answer. That led to a
response from another person who said roughly, “That’s not a problem.
Simply copy the French text into the free Google Translate system on the Web.”
We already have relatively good voice input systems that translate
speech to text. We have good voice output systems that translate text
into voice. The combination of these capabilities with language
translation capabilities means that students throughout the world will
be able to easily communicate orally and by text with each other.
- We know a considerable amount about individual differences among
learners, the value of individualization of instruction, the value of human tutors,
and the value of computer tutors. My teaching machine will
respectfully accommodate our understanding that there are many aspects
of teaching and learning in which human teachers and student-human
interactions are both absolutely necessary, and are much more
effective, than our current computer teaching machines.
However, it will also reflect that there are already many things that a
teaching machine can do better than human teachers, and there are many
things that a human teacher plus a computer teaching machine working
together can do better than either working alone. A student’s computer
teaching machine will gradually learn which of these three approaches
works best in a particular learning area for a student it is serving.
- We know that there are considerable differences in beliefs and
understandings among people of different nationalities, cultures, and
religions. Many years ago, one of my students exposed me to the idea of
the imperialism of one country inflicting its educational system and
curriculum content on another country. This might be acceptable to both
countries in the discipline of math, but quite unacceptable in global
and national history, politics, and in many other disciplines. For
example, some of the curriculum content of the fine and performing arts
that is broadly accepted in many areas of the world may not be at all
acceptable in other areas. Add to this the need for students to learn
to communicate in their native language and culture, and that inherent
to a language is a great deal of culture and history.
This means that the teaching machine needs to have a great deal of
content and teaching methodology that is specific to the huge number of
different sects living throughout the world. In education, one size
does not fit all at the individual student level, the family level, and
larger groupings. The document List of Wikipedias presents information about how the Wikipedia is currently addressing this problem.
- The first Massive Open Online Courses (MOOCs)
were developed in 2011. By making use of data about the performance of
all students enrolled in such a course, we are gradually improving
MOOCs. My forecast is that eventually such courses will have the
characteristics of today’s Highly-interactive Intelligent
Computer-assisted Learning (HIICAL)
courses. My teaching machine will provide students throughout the world
with free access to a huge number of HIICAL courses they learn from at
a time and place of their choosing.
- Some of our best success stories with teaching machines involve
developing and using computer simulations. A good teaching/learning
simulation engages a student in actually solving problems and
accomplishing tasks. The simulated versions of the problems and tasks
need to be close enough (authentic enough) to the “real thing” that
there is very easy transfer from the learning to the use of the
learning. We are making good progress toward creating Star Trek’s Holodeck simulations. Simulations will be an important facility provided by my teaching machine.
- My teaching machine will be quite portable, thus largely
obviating the need for students to have individual walking/talking
robots. When helpful to students, the teaching machine will be wearable technology and include a future version of Google Glass.
Thus, for example, a student will be able to glance at a person and the
computer system will display the person’s name and identification
information via the glasses. (Is the person is someone I have met
before, I want my teaching machine to retrieve information about
previous meetings and conversations.) Similarly, students will be able
to quickly retrieve information about almost anything (including
people) they see, hear, or think about.
The design, production, and distribution of teaching machines
needs to take into consideration both the educational needs of today’s
students and the changing educational needs of future students. We
humans now have the knowledge, skills, and production capabilities to
provide every person on earth with a quite good teaching machine. Once
this approach to education is widely accepted, the capabilities of the
teaching machines will increase rapidly as more and more materials are
developed to facilitate this type of aid to teaching, learning,
communication, and problem solving.
Human teachers and teaching machines working together can make
education a lifelong endeavor and provide all people with an education
that rivals the best education that currently is available to only a
limited number of students.
We can overcome the technological and manufacturing challenges. But,
can we overcome the acceptance, distribution, and other human
challenges? I wish each of you a long life so that you can participate
in and witness the outcomes of this endeavor.
Asimov, I. (1976). The new teachers. In Robot visions
. London: Orion.
Kaku, M. (2014). The future of the mind
. New York: Random House.
David Moursund earned his doctorate in mathematics from the
University of Wisconsin-Madison. 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.
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
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 http://iae-pedia.org/Main_Page#IAE_in_a_Nutshell.
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