The role of cognitive theory in human-computer interface

Computers in Human Behavior 19 (2003) 593–607
www.elsevier.com/locate/comphumbeh
The role of cognitive theory in
human–computer interface
Patricia A. Chalmers*
Crew System Interface Division, US Air Force, 2255 H Street, Wright-Patterson AFB,
OH 45433-7022, USA
Abstract
Many computer users have trouble learning and remembering information presented on a
computer screen. Based on cognitive theories, part of the reason for lack of retention is hypo-
thesized to be the user’s inability to form a mental picture, or schema, of the information pre-
sented via a computer screen. In order to form a schema, users need to be able to understand
where newly acquired knowledge ?ts into ‘‘the big picture’’. However, computers and the
information on them are so in?nite, users may have trouble thinking in terms of a big picture.
When on a website, for example, how many times have you asked yourself, ‘‘Where am I?’’ or
‘‘Where was I?’’ or ‘‘Where am I going?’’ Likewise, for many learners, there may be little sense
of place when learning with the assistance of a computer. It is proposed that these problems of
the inability to form a schema and disorientation with the human–computer interface are
worth researching, not only for better retention, but also for increased satisfaction among
users. In addition to cognitive theories of learning, retention, organization, and individual
di?erences, human–computer interface guidelines are also addressed. For this paper, the
phrase human–computer interface is also called the ‘‘user interface’’ because of the emphasis on
the end user, or the student. It may also be called simply the interface. Human–computer
interface is de?ned as the point of contact between the computer and the computer user.
# 2003 Published by Elsevier Science Ltd.
Keywords: Human–computer interaction; Human–computer interface; HCI; CHI; Human factors;
Cognition; Cognitive theory; Interface design; Interface development; Software interface; Usability
1. Introduction
In 1951, Univac introduced the ?rst commercial computer. In those early years,
computers were used in only a few areas such as computation, data storage and data
retrieval. However, computers have since been used in a myriad of ?elds including,
but certainly not limited to, business, advertising, entertainment, engineering, law,
* Tel.: +1-937-255-7560; fax: +1-937-255-9198.
E-mail address: patricia.chalmers@wpafb.af.mil (P.A. Chalmers).
0747-5632/03/$ - see front matter # 2003 Published by Elsevier Science Ltd.
doi:10.1016/S0747-5632(02)00086-9

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medicine, training, and education. It is the last of these ?elds, the ?eld of education,
upon which this paper is focused.
Education with the assistance of technology, or educational technology, is
becoming a booming industry, especially in the area of distance education. Learning
institutions around the world are competing for their place in the endeavor to edu-
cate learners who may not be willing to or able to come to a campus for instruction.
In addition to learning institutions, many other entities, medical organizations being
one example, are in the business of educating the public via the World Wide Web,
on topics ranging from abrasions to zygotes. Everyone seems to be eager to educate
the public via computers. Indeed, computers may be the most convenient support to
education our world has ever seen. However, the e?ectiveness of this type of edu-
cation remains to be established.
Human–computer interface is de?ned as ‘‘the point of contact between the application
and the end user’’ (Sheppard & Rou?, 1994, p. 1402). As such, in an educational setting,
the human–computer interface is that which enables the learner to communicate with the
computer, and is that which enables the computer to communicate with the learner.
This interactive communication is accomplished for both the learner and the
computer via the computer hardware interface, by way of such features as the keyboard,
function keys, the mouse, a touch screen, or a stylus. Interactive communication is also
accomplished via the computer software interface. The computer software plays a
role in interactive communication by way of the presentation layout or screen
design, including, among other features, icons, menu bars, dialogue boxes, graphics,
windows and split screens. This paper is focused on software interface.
1.1. The digital divide
One problem with educational technology is the di?culty many learners have
working with computers, including computer software as well as computer hardware.
This problem begs usability questions such as, ‘‘Is quality hardware and software
equally usable to all learners?’’ This problem is so prevalent there is now a coined term,
‘‘the digital divide,’’ to describe the situation of inaccessibility and lack of usability.
‘‘If there is a digital divide, i.e. if computers and other technological advances are
not equally accessible and usable to all learners, who are the people who do not have
access to usable technology? In the United States, older adult learners, women, and
less educated learners are three groups who have less accessibility according to Kerr
(1996, p. 154).
In studying educational technology, we need to consider that women, older adult
learners and those less educated, even if they had equal access to computers, could
still be at a disadvantage because they experience the world di?erently, resulting in
di?erent ways of interacting with computers, thus making computers less usable.
1.2. Usability
With a growing number of organizations and researchers working on behalf of
access for as many as possible, the future should be brighter for those on the other

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side of the digital divide. However, even among people who have do have access,
many say, ‘‘I’m just not good at computers’’. These types of comments have spurred
the growth of usability organizations such as the Human Factors and Ergonomics
Society (HFES), the Usability Professionals’ Association (UPA), the British Com-
puter Society Specialist Group on Human–Computer Interaction (BCS-HCI), the
Association for Computing Machinery (ACM) and its special interest group for
improving computer–human interaction (SIGCHI). These organizations, and those
like them, work toward usability for all computer users.
After answering the questions of the digital divide and usability mentioned above,
we are faced with the more speci?c question, ‘‘What is the solution to the above
problems?’’ In other words, how can we make educational technology more acces-
sible and more usable? Although the lack of accessibility and usability are inter-
twined, this paper addresses usability. It is hoped that better usability will yield
better access to educational technology. In other words, as technology is made more
usable, it may be more accessible to a larger portion of the population.
1.3. Disorientation with the interface
One problem with technology in general is the problem of disorientation. In fact,
disorientation is one of many reasons for computer anxiety and computer related
anxiety, which is estimated to a?ect 30% of the United States work force (Logan,
1994, as cited in Ramsay, 1997, p. 546). Ramsay also noted that computer related
distress in the workplace yields increases in mistakes, debilitating thoughts, self-
deprecating thoughts, irrational beliefs and absenteeism. These, in turn, are sug-
gested to have an impact on decreases in performance, production, motivation, and
morale. These problems may also extend to student computer users.
Designing a usable interface, however, is cumbersome and challenging, which
makes it di?cult to design good user interfaces for computer hardware and soft-
ware. In fact, the code to implement the user interface typically takes up 40–90% of
the code for an entire program (Sheppard & Rou?, 1994, p. 1402).
How easily users, or learners in the case of educational technology, become dis-
oriented in a computerized text may be a function of the user interface. In fact,
many computer users have such a di?cult time with text on a computer screen they
will simply print out a hard copy of whatever is on the screen, rather than orient
themselves to the computer screen. This phenomenon can be related to problems
with font type, font size, screen brightness, or simply the users’ inability to adapt to
text printed on a screen.
One area where disorientation can be a problem is in the use of links. Links may
be a joy for some people but a means to disorientation for others. Links enable users
to expand their knowledge to include thousands of related topics. Although links
create the advantage of exploration, as with explorers through the ages, there is
always the chance that the explorer may get lost. For example, explorers, or learners
in the case of hyperlinked computer tutorial programs, may become so disoriented
they do not know where they were, where they are going, or more importantly,
where they are.

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In summary, there are problems in general with human–computer interaction. Of
these general problems, the one speci?c problem that will be addressed in this paper
is disorientation, since it may be related to schema building.
2. Can we apply learning theory to user interface development?
When designing the software screens for education, we can consider incorporating
traditional learning theories. Learning theories have traditionally been applied to
venues of instruction such as textbook instruction, classroom instruction, and one-
on-one tutoring. It cannot be assumed, however, that learning theories applied to
the above venues can automatically be applied to learning with computers. On the
other hand, it may be a good place to start. For example, we can assume that in
order to use computer-based information, we must incorporate the knowledge into
our cognition, or learn it, and we must retain information if we are to use it.
2.1. Schema theory
Schemas are generally thought of as ways of viewing the world and in a more
speci?c sense, ways of incorporating instruction into our cognition. Schema theory is a
cognitive learning theory that was introduced by Bartlett (1932). Piaget described
schemas as the basic building blocks of knowledge and intellectual development.
Schemas have further been described as ‘‘mental representations of general categories of
objects, events, or people’’ (Bernstein, Roy, Skrull, & Wickens, 1991, p. 321). Satzinger
(1998) more recently described schema theory to include knowledge structures that store
concepts in human memory, including procedural knowledge of how to use the concepts.
For example, the schema of ‘‘bottle feeding’’ is composed of the cognitive organization
of: learning to seeing a shape, recognizing and categorizing it as a bottle, grasping
the bottle, bringing the bottle to the mouth, and sucking on the nipple of the bottle.
Likewise, the schema of ‘‘cleaning an art studio’’ may be composed of the cognitive
organization of: learning the rationale for a clean studio, the cleaning and storing of
paint supplies, as well as the cleaning and replacing of furniture.
Piaget proposed that learning is the result of forming new schemas and building
upon previous schemas. He proposed that two processes guide learning: (1) the
organization of schemas, and (2) adaptation of schemas. He further proposed that
adaptation of schemas involves: (a) the assimilation of new information into existing
schemas, or (b) the accommodation of schemas to new information, which may not
?t into existing schemas.
Organizing a schema for a learner and providing the schema to the learner may be
especially important for novice learners. Novice learners are those who have little or
no knowledge of a topic. At the risk of the learner organizing an incorrect schema, it
may be optimal to provide novice learners with an already organized schema.
In research of the relationship between prior knowledge and interactive overviews
(a method of organization) during hypermedia-aided learning, Shapiro (1999a, p.
143) noted that ‘‘novices may be uniquely challenged in that they have little or no

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prior knowledge to aid in the learning process.’’ In addition, Shapiro found that
novice learners bene?ted more from organization than did learners with prior
knowledge of the subject matter. However, Shapiro noted that a pretest used in her
study might have prompted prior knowledge and a ‘‘redundancy e?ect’’ which is
described as the e?ect, which occurs when unnecessary information is presented, or
when information is repeated (Yeung, 1999, p. 201). The redundancy e?ect has been
described as a possible threat to schema organization (Bobis, Sweller, & Cooper,
1993; Chandler & Sweller, 1991; Sweller & Chandler, as cited in Yeung, 1999). As
such, a redundancy e?ect may act as a confounding variable working against those
with prior knowledge of subject matter.
Organizing a schema also brings up the question of who should organize the
learner’s schema, the learner, or the instructor. McNamara (1995) addressed this
question. She used the term ‘‘generation e?ect’’ to describe the phenomenon that
learners are usually better at retaining information which they generate themselves
than they are at retaining information, which is generated for them. Examples of
information generated for a learner include information read to the learner, and
information presented in text form to the learner. In her study, McNamara com-
pared math learners who simply read math problems and read the solutions with
math learners who read math problems and worked out, or generated, the solutions.
McNamara found that low-prior-knowlege and average-prior-knowledge students
bene?ted more from the generation e?ect (generating the solutions, rather than
simply reading the solutions) than high-prior-knowledge students.
The above ?ndings may also have to do with a redundancy e?ect for the higher-
prior-knowledge learners. That is, it is possible that the tutorial will prompt a
redundancy e?ect if material is presented in text and in the form of an organizer.
Eylon and Reif (1984) found in their research the presentation of a well structured
hierarchical organization was not as essential for high ability students as for low
ability students. Further, they proposed, ‘‘It would clearly be a major educational
challenge contributing signi?cantly to the good of making students better indepen-
dent learners to develop methods for teaching students themselves to reorganize
information into useful hierarchical forms’’ (p. 41).
Larkin and Simon (1987, p. 57), on the other hand, proposed that instructor gen-
erated schema building would be better for learning in that it would make learning
more e?cient and less time consuming, which would expedite cognitive processing.
This debate continues regarding organization and whether learners or instructors
should generate schema building. The answer may lie in individual di?erences and in
situational di?erences, with learner-generated schemas better in some cases, and
instructor-generated schemas better in other cases.
Sca?olding is a term used to describe the process of forming and building upon a
schema. Interface sca?olding refers to a schema support for computer-assisted
learning. A key component of one kind of interface sca?olding is that it can be made
fadeable. That is, interface sca?olding can be faded in or out as needed. This fading
can be a function of the learner or the computer. In learner induced fading, learners
decide whether of not to show the sca?old. The trouble with this idea is that learners
may not make good decisions about which sca?olding to show and which sca?olding

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to hide. In computer induced fading, the computer decides whether or not to fade
the sca?olding, based on a model of the learner’s understanding. The main problem
with this approach is that ‘‘an extensive model of the learner’s knowledge may be
hard to specify or evaluate in more open ended domains’’ (Jackson, Krajcik, &
Soloway, 1998, p. 187). In their study, Jackson and her colleagues developed a
software tool called ‘‘Theory Builder’’ based on guided learner-adaptable sca?old-
ing. This system would o?er the ‘‘best of both worlds’’ in that learners could control
the fading of sca?olding with the help of the system.
2.2. Cognitive load
In addition to schemas, another closely related cognitive learning theory is that of
cognitive load. Cognitive load is a term used to describe the amount of information
processing expected of the learner. Intuitively, it makes sense that the less cognitive
load a learner has to carry, the easier learning should be. In fact, researchers have
proposed that working memory (similar to short-term memory) limitations can have
an adverse e?ect on learning (Sweller, 1993; Sweller and Chandler, 1994; Yeung, 1999).
Yeung (1999) devised a study in which the researchers presented learners with text
that included unfamiliar words. Half of the learners had the de?nitions of the unfa-
miliar words in a traditional glossary. The other half of the learners had short de?-
nitions of the unfamiliar words integrated into the space above the line of text, based
on a method of text writing used in classical Chinese literature. The integrated de?-
nitions in Yeung’s study were in an 8-point font size directly above the de?ned word.
The spacing between the lines of text was such that there was adequate room for
short de?nitions above the de?ned words. The learners with the glossary were pre-
sumed to have a higher cognitive load than the learners with the integrated de?ni-
tions. This was assumed because of the extra e?ort imposed on learners; that is, the
e?ort and time it took learners to leave the text, look up the de?nition in the glos-
sary, incorporate the de?nitions into their schema, remember the de?nitions, ?nd
their way back to the text, and, ?nally, incorporate the de?nitions into the text they
were reading. Intuitively, this does seem to impose a great amount of cognitive e?ort
on the part of the learner. Indeed, Yeung found that 5th and 8th grade students with
the integrated de?nitions had better comprehension scores than the students with the
traditional glossary. However, it was also found that university-age students with the
integrated de?nitions had lower comprehension scores than the students with the
glossary. It was proposed that the university students exhibited a redundancy e?ect,
which interfered with the decreased cognitive load they may have experienced, had
they been younger and less experienced readers. In addition, Yeung’s 5th and 8th
grade students learned to speak English after they learned to speak their native
language (ESL), which could in itself, be a confounding variable.
Although his sample size was low, Yeung’s study is important on which to build
further research. Yeung did conclude that decreasing cognitive load (as measured by
the time it takes to ?nd a de?nition, hold the de?nition in memory, then incorporate
it into the learning material) may or may not help comprehension, depending on
such factors as grade level and ESL status.

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Closely related to the idea of cognitive load is the e?ect of split attention. Split
attention is described as that which occurs when learners have to split their attention
between multiple sources of information (Yeung, 1999, p. 198). In the study described
above, Yeung was not only studying the e?ects of cognitive load, but also the e?ects of
split attention. The idea of learners having to split their attention between a glossary
and text was one reason proposed to have a?ected learners in a negative way.
Redundancy also may have negatively in?uenced cognitive load in Yeung’s study.
For learners who are pro?cient in English, unneeded de?nitions above the text may
simply create redundancy and unneeded split attention. A learner’s use of de?nitions
incorporated into text, may, therefore, show a positive or negative e?ect on learning.
In addition to Yeung’s ?ndings, Reinking and Rickman (1990) found that placing
de?nitions close to unfamiliar words increased comprehension. Additionally, Hess,
Detweiler, and Ellis (1999) found that learners took advantage of physical informa-
tion in software design interface ‘‘to augment and strategically support their cognitive
storage and control resources’’ when performing cognitively demanding tasks.
2.3. Retention theories
In addition to learning, students also need to retain information, if they are to use
their knowledge beyond the learning situation. Retention refers to the amount of
knowledge which can be remembered after a given amount of time. Retention can be
subdivided into two types depending on the amount of time which has elapsed
between the point of learning and the point of recall. These subdivisions are called
short-term retention, or working memory, and long-term retention, or long-term
memory. Working memory can be assessed during or immediately after material has
been presented. Long-term memory, on the other hand, is assessed at least one week
after material has been presented (Tennyson, 1996, as cited in Plomp & Ely, 1996, p. 54).
To enhance retention, a number of techniques have been suggested. One of these
techniques is chunking. It has been shown that the average person can retain
approximately seven (plus or minus two) items of information at a time (Miller,
1956, p. 97). What happens, however, when there are more than seven items of
information to retain? One way to make retention easier is to ‘‘chunk’’ the informa-
tion, that is, group the multiple pieces of information into chunks. In a computer-
assisted learning situation, learners may be presented with, for example, 49 facts. The
instructional designer can simplify the process of retaining all these facts by chunking
the information into as many as nine topics with as many as nine subtopics.
3. How about software screen design theories?
In addition to learning theories, it is hypothesized that designers of computer-
assisted instruction must also consider the importance of good screen design.
Heines (1984, p. 24) noted, ‘‘poorly designed computer screens can hinder
communication’’. However, as Szabo and Kanuka (1998, p. 38) suggest, we cannot
simply avoid poor designs, we must take an active role in producing good designs.

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Szabo and Kanuka suggested that viewing a good screen design enables automatic
processing, whereas viewing poor screen designs encourages a manual and, there-
fore, less e?cient processing. In addition, these researchers found that good design
leads to completing lessons in less time and with a higher completion rate. This,
therefore, encourages instructional technologists and graphic designers to incorpo-
rate good design into educational technology, including attracting and holding the
viewer’s attention and communicating easily (understood information that aims to
have the viewer remember the information’’, p. 25).
3.1. Layout
Sheppard and Rou? (1994) described software layout to include, among other
things, how objects are grouped. For example, menu choices can be grouped in a ver-
tical arrangement, by a one-dimensional branching tree arrangement, or by a three-
dimensional cone tree arrangement (p. 1403). Layout software also will determine
object attributes such as font, font size, colors, and object placement. Finally, layout
software also includes the objects, colors, movement, and sound used in the interface.
3.2. Consistency
Shneiderman (1998) lists consistency as the ?rst of his ‘‘Eight golden rules of
interface design,’’ Shneiderman’s eight golden rules include: (1) strive for consistency,
(2) enable frequent users to use shortcuts, (3) o?er informative feedback, (4) design
dialogs to yield closure, (5) o?er error prevention and simple error handling, (6)
permit easy reversal of actions, (7) support internal locus of control, and (8) reduce
short-term memory load; although he added the caveat that these golden rules should
be ‘‘interpreted, re?ned, and extended for each environment’’ (Shneiderman, 1998, p.
75). In addition, Jones, Farquhar, and Surry (1995) proposed using a consistent for-
mat in the form of keeping similar information in the same part of each screen.
However, Satzinger (1998, p. 3) tested the e?ects of conceptual consistency on user
knowledge, performance, and satisfaction when two integrated work applications
were learned and used by student participants and found no e?ect. Thus, there is
confusion about how, when and where to use consistency in interface design.
3.3. Color
In addition to layout and consistency, color is another factor in software screen
design. The use of color can involve a delicate balance between interest and dis-
traction. In educational technology, the use of color should be used to maintain
interest, but not at the expense of distraction. In addition, certain colors should be
avoided because some users may be colorblind. Because the colors red and green are
the most common colors to be confused with each other, these should not be used
on the same screen. An exception may be made if users are familiar with an object,
for example, the American stoplight. That is, if you were to insert a stop light into
the computer graphics of a computer tutorial, users may know that the top color is

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red and the bottom color is green, not because they can distinguish these colors, but
because they are familiar with the color placement.
The use of familiar colors may also be helpful. For example, when highlighting a
word or phase, yellow may be used for the highlighting because that is a familiar
highlighting color for many learners.
In addition, the use of a single familiar color may be less distracting, would not be
confused with other colors, and would be easily recognized and familiar.
3.4. Spatial display
Regarding placement of objects on a computer screen, Szabo and Kanuka (1998, p.
33) described object placement unity as that which occurs when the ‘‘sum total of the
square inches between the objects is less than the total of the square inches around the
objects as a group’’ and also when the objects are farther from the edge than they are
to each other. In their study, Szabo and Kanuka used the design principles of unity
and proposed a focal point to decrease boredom via isolation and contrast.
3.5. Organizational methods and techniques
The use of organization in text presentations has had its proponents for a very
long time. MacGregor (1999, p. 203) proposed that organized text enables learners
to construct a coherent mental representation of what they learn and can make the
di?erence between deep and super?cial understanding of results. In addition, Sha-
piro (1999a, p. 143) noted that text organizers work because they prompt previous
knowledge and give the learner an ‘‘elaborative tool for new information’’. Robinson
and Skinner (1996) found delayed review facilitated performance for students who
viewed text plus graphic organizers, which will be discussed below. They likened the
brain to an organized library versus a library in which books are either scattered or in
the wrong places. These ideas regarding organization of text hark back to schema
theory and cognitive sca?olding discussed earlier.
Following is a discussion of organizational strategies. These strategies include
advance organizers, outline organizers, post organizers, graphic organizers, and
knowledge maps. Also included is the ‘‘continuous organizer’’, a potential improve-
ment in screen organization.
3.5.1. Advance organizers
The presentation of a structure of what is to be learned was the thrust of much
research by Ausubel (1960, 1968; Asubel & Youssef, 1963).
Ausubel (1963) as cited in Hall, Hall, and Saling (1999, p. 103) believed that the
nature of a learner’s pre-existing knowledge structure, or schema, was a critical factor in
retention. An example of giving a learner an ‘‘advance organizer’’ may be an introduction
to a chapter in a book or an introduction to a class lecture. Another example is a list of
topics on a chapter title page, giving the main topic of the chapter with a list of all
subtopics to be discussed. Ausubel proposed using the advance organizer to give learners
a structure of pre-existing knowledge. In related research, McEneany (1990, p. 93) found

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that those learners who exhibit unfamiliarity with subject matter have more to gain from
advance organizers than those learners who are familiar with subject matter.
Even though advance organizers have been researched heavily with regard to hard
copy and in class presentations, there has been little published research on the e?ects
of advance organizers with computer-assisted instruction (Jones et al., 1995; Shapiro,
1999a, 1999b). It could be assumed that the results of hard copy research would be
transferable to computer-assisted learning. However, that assumed generalization
may or may not hold true. Diaz, Gomes, and Correia, (1999, p. 107) note, quite
understandably, ‘‘the very ?exibility of reading on screen is disorienting for a user
who cannot conceptualize an overview of the structure’’.
Although results from hard copy research do not necessarily generalize to com-
puter-assisted instruction, it is a reasonable point from which to start research. It is
at least intuitive and reasonable to assume that some of the knowledge we have
gained from hard copy research or lecture-setting research (in other words, tradi-
tional teaching methods research) may transfer to computer-assisted instruction.
Jones et al. (1995, p. 19) took the idea of an advance organizer one step further
than the traditional use in textbooks. They suggested not only using advance orga-
nizers in hardcopy text but in softcopy text as well, to help learners ‘‘conceptualize
the organization of the information in the program’’.
Shapiro (1999a, p. 143) noted that advance organizers have been seen as successful
in traditional text-based learning as well as hypermedia-assisted learning. This was
especially noted for novice learners (Shapiro, 1999a, p. 150 in Mannes & Kintsch,
1987). However, she found that advance organizers did not have an e?ect on sub-
jects with prior knowledge of presented material (p. 143).
On the other hand, McEneany (1990, p. 89) found on review of advance organizer
research that the literature was ‘‘equivocal’’ at best. Possible reasons follow.
Advance organizers in the form of chapter outlines, with sub lists of topics to be
covered in the chapter, may not help much if the information in the organizer is
unfamiliar. If an unfamiliar word is used in the advance organizer, the learner may
ignore the word, leading to incomplete understanding. Alternatively, the learner may
make a false impression of what the word means, and the learner’s understanding
may be skewed. Likewise, if unfamiliar concepts are used in the advance organizer,
the same results may occur.
The split attention theory noted previously might also come into play. In this case,
the learner must leave the text, go back to the advance organizer, and then return to
the text and attempt to ?t the text into the schema of the advance organizer.
3.5.2. Outline organizers
Outline organizers may be presented in the form of an ‘‘agenda’’ before a tutorial
or lecture. The presenter may also refer back to the agenda before each main topic is
presented. In textbooks, outline organizers often appear in the form of a chapter
outline. These outlines are usually presented for each chapter and before the chapter
text. They may appear o? to the side, below, or after the chapter title page.
Ausubel (1968) noted that an outline is helpful because it shows how present
knowledge relates to prior knowledge. Westera (1999, p. 94) noted that an important

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Document Outline

• The role of cognitive theory in human-computer interface
  • Introduction
    • The digital divide
    • Usability
    • Disorientation with the interface
  • Can we apply learning theory to user interface development?
    • Schema theory
    • Cognitive load
    • Retention theories
  • How about software screen design theories?
    • Layout
    • Consistency
    • Color
    • Spatial display
    • Organizational methods and techniques
      • Advance organizers
      • Outline organizers
      • Post organizers
      • Graphic organizers
      • Continuous organizers
      • Concept maps
    • Should we consider individual differences in computer users?
      • Age
      • Gender
      • Level of education
      • Affect
      • Motivation
  • Summary
  • References

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