Microcomputers in Education: Cognitive and Social Design Principles Report of a conference * Edited by Thomas W. Malone Cognitive and Instructional Sciences Group Xerox PaIo Alto Research Cemer and James Levin Labommo, of Comparative Human Cognition University of Californic~ San Diego The successful use of microcomputers in education depends critically on the cognitive and motivational processes in learning and the social structure of the educational setting. A number of different groups concerned with these issues have recently tried to specify explicit design principles for using computers successfully in different educational environments, This repmt summarizes a workshop that brought together people from some of these groups to describe the current state of their groups' efforts and to work toward integrating these efforts into a larger scale statement. The first part of this report summarizes the short inff)rmal presentations made by the workshop participants in orcler of presentation; the second part describes some examples of well-designed instructional games and articulates several general themes that ran through the conference, The primary goal of this conference was to specify principles that are actually useful in designing instructional environments. As such, many of the principles discussed here are rough heuristics or rules-of-thumb rather than precisely defined scientific laws. Experienced workers in this field may find many of the principles obvious or well-known, but, in fact, some of the principles that seem the most obvious are the most often violated. It is our hope that this summary will serve both as an introduction to the important issues for those who are not yet familiar with them, and as a stepping stone from which experienced workers can move toward a more powerful set of design principles. *This is the first part of a two-part report of a conference hedl March 12-14, 1981, at the University of California, San Diego, sponsored by the Carnegie Corporation. Part 2 will appear in the next issue of the Bulletin. -6-
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M i c r o c o m p u t e r s in E d u c a t i o n :
Cogni t ive and Socia l Des ign Pr inc ip les
Report of a conference *
Edited by
Thomas W. Malone Cognitive and Instructional Sciences Group
Xerox PaIo Alto Research Cemer
and
James Levin Labommo, of Comparative Human Cognition
University of Californic~ San Diego
The successful use of microcomputers in education depends critically on the cognitive and
motivational processes in learning and the social structure of the educational setting. A number of
different groups concerned with these issues have recently tried to specify explicit design principles
for using computers successfully in different educational environments, This repmt summarizes a
workshop that brought together people from some of these groups to describe the current state of
their groups' efforts and to work toward integrating these efforts into a larger scale statement.
The first part of this report summarizes the short inff)rmal presentations made by the workshop
participants in orcler of presentation; the second part describes some examples of well-designed
instructional games and articulates several general themes that ran through the conference,
The primary goal of this conference was to specify principles that are actually useful in
designing instructional environments. As such, many of the principles discussed here are rough
heuristics or rules-of-thumb rather than precisely defined scientific laws. Experienced workers in
this field may find many of the principles obvious or well-known, but, in fact, some of the
principles that seem the most obvious are the most often violated. It is our hope that this summary
will serve both as an introduction to the important issues for those who are not yet familiar with
them, and as a stepping stone from which experienced workers can move toward a more powerful set of design principles.
*This is the f i r s t part of a two-part report of a conference hedl March 12-14, 1981, at the University of Cal i forn ia, San Diego, sponsored by the Carnegie Corporation. Part 2 w i l l appear in the next issue of the Bu l le t in .
-6 -
List of Participants Organizers James Levin
Laboratory of Comparative Human Cognition (D003)
University of California,, San Diego La Joll& CA 92093
Thornm" Malone Cognitive and Instructional Sciences Group Xerox Pato Alto Research Center 3333 Coyote Hill Road Pato Alto, CA 94304
Invitees John Seely Brown
Cognitive and Instructional Sciences Group Xerox Palo Alto Research Center 3333 Coyote Hill Road Palo Alto, CA 94304
Michael Cote Laboratory of Comparative Human Cognition, D003 University of California, San Diego La Jolla, CA 92093
Allan Collins Bolt Beranek and Newman, Inc. 50 Moutton Street Cambridge, MA 02138
Robert Davis PLATO Project College of Education, Curriculum Laboratory University of Illinois at Urbana-Champaign 1212 West Springfield Urbana, Illinois 61801
Andrea diSessa LOGO Project Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, Massachusetts 02139
Sharon Dugdale PLATO Project Computer-based Education Research Laboratory 252 Engineering Research Laboratory 103 S. Mathews Ave. University of Illinois at Urbana-Champaign Urbana, Illinois 61801
Gerhard Fischer Azenbergstr. 12 University of Stuttgart, Dept. of Computer Science D-7000-Stuttgart 1 West Germany
l.aura Gould [ .earning Research Croup Xerox Pato Alto Research Center 3333 Coyote Hill Road Palo Alto, CA 9,,1304
James Hollan Naval Personnel Research and Development Center (Code 304) San Diego, CA 92152
Edwin Hulchins Naval Personnel Research and Development Center (Code 304) San Diego, CA 92152
Ted Eahn Atari, Inc. 1265 Borregas Avenue Sunnyvale, California 94086
Next Brown discussed a detailed set of principles for "coaching" students in informal learning
environments. These principles are explicitly encoded in a computer-based coaching system for an
arithmetic game (see Burton & Brown, 1979). They assume that the student takes turns playing the
game against another student or against the computer. "IRe computer constructs a model of the
student's skills and weaknesses by observing when the student misses good moves in the game.
This student model is based on a set of Issues which students can learn about from playing the
The principles include the following (for a more detailed discussion, see Burton & Brown, game.
1979):
(1) (2)
Before giving advice, be sure the Issue used is one in which me student is weak.
When illustrating an Issue, only use an Example (an alternative move) in which the result
or outcome of that move is dramatically superior to the move made by the student.
(3) If a student is about to lose, interrupt and tutor him only with moves that will keep him
from losing.
(4) i)o not tutor on two consecutive moves, no matter what.
(5) Do not tutor befi~re the student has a chance to discover the game for himself.
(6) Do not provide only criticism when the Tutor breaks in! If the student makes an
exceptional move, identify why it is g(~)d and congJatulate him.
15
(7)
him to,
(8) (9) (lO) (11)
commentary in case il was not just careless.
After giving ad,,ice t<~ i.hc :si~de~:~t, offer him a chance to retake his turn, but do not force
Always have the Comphter Expert play an optimal game.
tf the student asks tbr help, provide several levels of hints.
If the student is losing consistently, adjust the level of play.
If the student makes a potentially careless error, be forgiving, But provide explicit
Laura Gould
Learning Research Group
Xerox Palo Alto Research Center
I_aura Gould described a system named TRIP for animating algebra word problems (see Gould
and Finzer, 1981). TRIP is intended for students who have mastered the mechanics of algebra but
have difficulty translating the English text of the problem into suitable algebraic expressions. TRIP
provides an environment where students can develop an intuitive grasp of time-rate-distance
problems and their algebraic representations. The system supplies a helpful graphical interface by
means of which students construct a diagram of file problem using high-resolution pictures of
places, travellers, speedometers, odometers, and clocks (see Figure 2). Once the diagram is judged
by the system to be correct, the system asks the student to make a rough guess of the answer. Then
the travellers, meters, and clocks all move together producing an animated representation of the
problem. When the state specified by the student's guess is reached, the action stops, and the
student gets to see the result of the guess. A record of each successive guess and its consequences is
kept in a table from which students induce algebraic expressions and finally an equation for
computing the answer.
Gould pointed out some of the successful and unsuccessful aspects of the system in an attempt
to discover the underlying design guidelines. The user interface for the system, although apparently
quite complicated, was successfully and easily controlled even by students with low confidence
levels. ]'his seemed to be due to (1) the extensive help facility (accessed by a large "Help" button
always visible on the screen), (2) the fact that students started with a nearly blank screen and built
up for themselves a complex representation of the problem, and (3) the consistent use of the same
functions in different parts of the system. ]'RIP was also succesfully integrated into an existing
classroom curriculum. This was aided by (1) involving teachers in the early design phases, (2)
tailoring the computer curriculum to mesh well with what was going on in the class, (3)
individualizing the problems by choosing easy or hard numbers based on each student's ability, and
(4) collecting feedback from the students using a "gripe" facility.
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