Meditating Role of Cognitive Load on the Relationship Between
Navigation Structure, Prior Knowledge, and Performance in Accounting Case
Analyses
Abstract: Accounting case analysis is an important part of accounting curriculum.
Instructors encourage students to complete cases independently in order to learn from
them. With availability of web technologies inside and outside the classroom, it is
important to understand how self-directed learning can be promoted by using web
technologies like hypertext. When web-based case studies are used, there is one common
technological component: use of hypertext. Use of hypertexts can aid self-directed
learning. However, hypertexts can facilitate learning only when properly structured,
otherwise they cause disorientation (lost in space). Thus, it is imperative that we
understand how navigation structure of hypertext allows for improved learning during
accounting case analysis.
One potential effect of hypertext is increasing the extraneous cognitive load,
which distracts students from the core learning activity. Hypertexts arranged in different
navigation structures, might affect extraneous cognitive load differently. In this paper I
suggest a study to explore which hypertext navigation structure leads to decrease in
cognitive load, and how cognitive load impedes learning from a case study. I also suggest
how prior knowledge can moderate the effect of navigation structure on cognitive load.
1
INTRODUCTION
Web-based learning is becoming popular. Many universities have started offering
online accounting courses and these are becoming popular among employed students. For
these online courses, instructors interact with students only via Internet. Even instructors
teaching in conventional classrooms use Internet technologies (e.g. WebCT, Blackboard,
customized websites) extensively to improve their instructional delivery.
Accounting case analysis is an important part of any accounting curriculum and
accounting educators advocate the benefits of these case materials (Gobeil and Philips,
2001). Accounting educators can encourage independent case-based learning by placing
these case materials on the web. However, it is important to present these cases in a
manner that extracts maximum leverage from web technology.
One important component of web technology is hypertext. Hypertexts have the
potential to be used as a tool for improving independent learning from accounting cases.
For example, Crandall and Philips (2002) suggested that accounting hypertext-based case
studies could be used from concept knowledge to applications to improve learning. But,
the dilemma is how to present these cases because certain studies have exhibited the
problem of disorientation because of the use of hypertext (e.g. Bible, Graham, and
Rosman, 2005). Thus, we need to find ways to improve learning from hypertext-based
cases in a way that causes least disorientation.
Hypertexts can have different navigation structures and one pertinent question is
how hypertext navigation structures affect learning from cases. This will allow educators
to use the right navigation structure for imparting learning from hypertext-based case
studies.
2
This paper outlines a model to study the impact of different hypertext navigation
structures, and prior knowledge, on cognitive load of students when they attempt to learn
from an accounting case. In particular, it studies two navigation structure: 1) hierarchical
structures, where a node at one level can access another node directly at a level above or
below, thus forming a hierarchy, 2) network structures, which allow a node to be
connected to any other node in the hypertext forming a complex structure with many
links. The paper also explores the moderating impact of prior knowledge on cognitive
load. Case studies are also used as a training tool in auditing firms. Compared to students,
auditors have well developed prior knowledge structures. Their prior knowledge has the
potential to moderate the influence of navigation structures on cognitive load. Further, I
outline a research method to validate this model.
THEORY
Cognitive load theory explains the linkage between instructional design and
cognitive processes (Paas, Renkl et al. 2003). When new knowledge is to be acquired, the
learning takes place through working memory. Working memory is a location “where
current mental activity takes place and is a cognitive structure that is very limited in both
capacity and duration” (Carlson, Chandler and Sweller, 2003; p.629). While short-term
memory has been conceived as a passive storage buffer, working memory is assumed to
have both processing as well as storage functions (Daneman and Carpenter, 1980).
Working memory processes information, and stores the products of that processing for a
short duration. After new information has been processed through working memory,
schema formation in the long term memory can occur. Thus, the processing of new
3
information depends on both the existing schema as well as the learners’ processing
capacity (Leidner and Jarvenpaa, 1995).
Cognitive load theory suggests that learning occurs through a limited working
memory. When information is presented to learners, working-memory will be critical in
determining the effectiveness of learning (Carlson et al., 2003; Sweller et al. 1998).
When learners’ limited working memory is exceeded, cognitive overload occurs. This
impedes learning (Pierce et al., 1993).
There are three components to cognitive load: intrinsic cognitive load, extraneous
cognitive load, and germane cognitive load (Paas, Renkl et al. 2003). Intrinsic cognitive
load is inherent to the level of complexity of the task. If a task is broken down into
elements, then complex tasks require higher element interaction for overall understanding
of the task as compared to simpler tasks. The elements of the concept to be learned
cannot be understood in isolation. This high element interactivity imposes demands on
working memory capacity and thus increases cognitive load. Learning vocabulary is an
example of low element interaction, whereas learning a language is an example of high
element interactivity.
For example, learning from an accounting case analysis can be considered as a
complex task. To understand the case requires high interactivity between the elements
and simultaneous processing. For a risk-based auditing case, students must understand
the client’s business strategy, the business processes to achieve the strategy, and the key
indicators necessary to monitor performance of business processes in achieving the
strategy. They must also find the linkages between the business environment, business
strategy and the business processed. Subsequently, they decide how these interactions
4
affect the risk judgment at the transaction level. The intrinsic cognitive load for case
analysis would be high because of this complexity. Intrinsic cognitive load is difficult to
change with instructional designs.
Extraneous cognitive load occurs because of instructional techniques that require
learners to engage in activities that are not directed towards learning (Sweller 1994;
Gerjets and Scheiter 2003). Evidence suggests that instructional designs that decrease
extraneous cognitive load improve learning (e.g. Carlson et al., 2003; Brunken et al.,
2002; Kirschner, 2002). Thus, using specific features in the computerized aids that
decrease the cognitive capacity needed for activities extraneous to learning can improve
learning from decision aids (Paas, 1992; Rose, 1998). For example, using a particular
hypertext navigation structure might lead to increase or decrease in cognitive load.
Germane cognitive load is related to processes that contribute to the schema
development (Paas, Tuovinen et al. 2003). Unlike intrinsic and extraneous cognitive load,
germane cognitive load contributes to learning. Germane cognitive load occurs when the
task is simple enough to leave sufficient working memory available so that learners may
devote more effort to processes that are directly relevant for learning (Sweller, van
Merrienboer et al. 1998). Thus, when the task is highly complex, germane cognitive load
does not occur.
These three components of cognitive load are additive, i.e. the sum of intrinsic
cognitive load, extrinsic cognitive load, and germane cognitive load form overall
cognitive load, which must stay within the limits of working memory to promote
learning.
5
PRIOR LITERATURE
Hypertext-based learning
Hypertexts can be effective in self-directed learning because they allow users to
choose which links to follow and allow users to work their way through the material
along various paths of their own (Muller-Kaltoff and Moller, 2003). Researchers posit
that hypertexts are suited for learning in complex domains (Mao et al., 1996; Spiro et al.,
1998). They suggest that when a complex domain is presented in a flexible way such that
it is possible to revisit the same material through different hypertexts at different times
and in rearranged contexts, hypertexts improve learning (Balcytiene, 1999; Spiro and
Jehng, 1990).
Some evidence suggests that hypertexts can enhance learning. For example,
research shows that hypertexts effectively encourage contextualized access to knowledge
within a decision aid (Mao and Benbasat, 1998). Further, educational researchers suggest
that hypertexts facilitate learning with a task that includes a specific goal (Last and
O’Donnell, 2001). However, researchers also contend that hypertexts can impair learning.
The impairment in learning can occur if users have become disoriented because of
confusion regarding search for information (Conklin, 1987; McKnight et al., 1991).
Within accounting, there is little hypertext-related research (Dull et al., 2003).
The few studies in accounting show mixed results. Crandall and Phillips (2002) suggest
that the use of hypertext-based instructional materials produce greater knowledge
application than identical instructional material that does not include hypertexts. In
contrast, Hodge (2001) states that participants who use hypertext-based financial
statements are more prone to grouping unaudited information with audited information,
6
as compared to participants who view the paper materials. Similarly, Bible et al. (2005)
find that auditors using an electronic hypertext system were less able to identify seeded
errors as compared to auditors in the traditional audit paper environment.
Navigation Structures and hypertext:
Though hypertexts are useful for learning, they might cause disorientation
(Conklin, 1987; Foss, 1989; McKnight et al., 1991) because some hypertext navigation
structure can affect an individual’s ability to locate and extract information (Van Dyke
Parunak, 1989; Batra et al., 1993). However, McDonald and Stevenson (1996) suggested
that disorientation (getting lost in space) can be minimized by use of right navigation
structures. Shin et al. (1994) assessed that the most popular navigational structures for
hypertext are hierarchical and network structures. In hierarchical structures, a node at one
level can access another node directly at a level above or below, thus forming a
hierarchy. On the other hand, network structures allow a node to be connected to any
other node in the hypertext forming a complex structure with many links (McDonald and
Stevenson, 1996). This study focuses on these two navigation structures.
Prior knowledge and learning
Auditing research studies comprise a vast literature exploring the effect of prior
knowledge on auditing judgments. I illustrate two studies, rather than exhaustively
review this literature. Libby and Luft (1993) proposed a model to study the effect of
experience and knowledge on auditing performance (See Figure 1). Further, they
conducted an experimental study based on this model. They find that professionals with
7
more domain knowledge make better decisions than professionals with less domain
knowledge. Recently, O’Donnell, Koch and Boone (2005) examined how prior
procedural knowledge interacts with task complexity when tax professionals develop
client recommendations. They find that the prior knowledge of tax professionals
influences their recommendations when the task complexity is high, but has no influence
when the task complexity is low1.
Researchers studying the effectiveness of the use of hypertexts in computerized
aids considered the effect of prior knowledge (Hoffman and Oostendorp, 1999; Fang,
2001). Kelly (1993) found that users with little prior knowledge tend to get lost in the
maze of hypertext easily. Similarly, Akanabi and Dwyer (1989) noted the importance of
prior knowledge while studying the effect of hypertext structure on learning performance.
They find that students with prior knowledge benefit more in less structured and
inductive learning environment and students without prior knowledge benefit more in
highly structured and deductive environment.
HYPOTHESES DEVELOPMENT
Based on Cognitive Load theory and prior literature, the overall model for the research
study is as shown in figure 2.
Effect of navigation structure
Poorly designed hypertext may increase cognitive load, if users must remember
their location in the network, make decisions about where to go next, and keep track of
1 These studies focused on schema that matched with the information to be learned. However, these results might
change when information to be acquired significantly differs from the existing schema of auditors, i.e. there is a
mismatch of information to be learned versus existing schema.
8
pages previously visited (Rouet et al., 1996; Wright, 1991).
Network hypertext
navigation structure provides more number of choices to the user, in terms of the
different routes they may follow. The user must use additional effort and concentration to
perform the tasks needed for navigation as the user is presented with an abundance of
navigational alternatives. Thus, the limited working memory capacity is used for
processing the decision on which route to follow, and the location in the network. This
leads to an increase in extraneous cognitive load. Thus,
H1: Participants who are presented with an accounting case having network
navigation hypertext structure will experience more extraneous cognitive load
than will participants who are presented with an accounting case having
horizontal navigation hypertext structure.
Effect of prior knowledge on learning from a hypertext-based computerized aid
Learning occurs by mapping the concept to be learned to existing knowledge
structures. The person with prior knowledge decreases the complexity of the task by his
or her ability to link to the existing knowledge structures. Thus, intrinsic cognitive load,
which is related to the complexity of the task, decreases leading to an overall decrease in
cognitive load.
So, I hypothesize:
H2a: Participants with prior knowledge will have less cognitive load as compared to
participants without prior knowledge when they are presented with an hypertextbased accounting case.
9
As intrinsic cognitive load decreases, participants have more working memory
space to accommodate the demands of any presentation style. So, when these participants
are presented with a network navigation structure, they are impacted less as compared to
participants without prior knowledge with regard to cognitive load.
H2b: Prior knowledge will moderate the impact of navigation structure on
cognitive load.
Effect of cognitive load on learning
To facilitate learning, the web presentation structure should decrease this
cognitive load so that cognitive resources are devoted to learning. With low cognitive
load navigation structure, participants can take advantage of the flexibility provided by
hypertext to foster learning. Thus,
H3: Participants who experience low cognitive load will learn more from an
accounting case analysis.
RESEARCH DESIGN
I will conduct an experiment with a 2x2 between-participants design. The 2x2
between-participants manipulations will be “navigation structure” and “prior knowledge”
Prior knowledge has two levels: (1) Students who have taken the class related to the case
study (2) Students who did not take that class yet. The variable “navigation structure” has
two levels: 1) Hierarchical, and 2) Network.
Masters level accounting students will be randomly assigned to one of the four
groups in the 2x2 factorial designs. Participants have to go through an auditing case
adapted from an auditing textbook that is a part of the curriculum. The case is related to
10
auditing the revenue cycle. Participants will be requested to participate either before or
after the class on auditing the revenue cycle. Participants will go through the case using
either hierarchical navigational structure or network navigational structure.
The study will be conducted in a controlled environment, although the
computerized aid will be accessed over the Internet. The universities would participate I
this study will have similar computing facilities and they would have followed the same
textbook for instruction. GMAT scores will be compared to find uniformity among
participants’ ability.
I choose Masters student participants for specific reasons in this project. First my
study needs to be generalized to accounting student learning. So, student participants are
appropriate. Second, case analysis is more prevalent with Masters program as compared
to undergraduate programs. Third, the complexity of the task is best suited for Masters
students. The task would have confused undergraduate students.
MEASURING DEPENDENT VARIABLES
There are two dependent variables: cognitive load and learning performance.
Researchers measured cognitive load with either analytical methods, physiological
techniques or rating scale techniques (Paas, Tuovinen, Tabbers, and Van Gervan, 2003).
Researchers have also used NASA-TLX (Task Load Index) to capture cognitive
load2(Gerjets and Scheiter, 2004; Morris, Speier, and Hoffer, 1999). I will use NASATLX. I have chosen this measure for two reasons. First, it has been extensively validated.
Second, it is easy to administer as compared to other measurements.
2
For a detailed description of the NASA-TLX, please refer to Hart and Staveland (1988)
11
As stated by ACT theory (Anderson, 1982), learning occurs in two stages. First
the learner acquires the relevant facts and second the learner applies the relevant facts to
different situations. Thus, I measure learning in terms of 1) Acquisition of relevant facts
in the accounting case 2) Application of relevant facts in the accounting case. A similar
measure has been used and validated by Gobeil and Philips (2001).
CONTRIBUTIONS AND LIMITATIONS
This paper suggests a model for exploring the impact of hypertext navigation
structure, and prior knowledge on learning in accounting case analysis. The study can
contribute to the research on learning using web-based case analysis in several ways.
The proposed research addresses an emerging accounting education issue: in
recent years, web-based learning is becoming popular. In spite of pervasive use of
hypertext in web-based learning, we don’t know yet how to structure hypertexts in a way
that facilitates learning from accounting cases. This study will guide us in that direction.
Second, the study will assist in finding how level of knowledge affects the effect of
different navigation structures on learning from an accounting case. Someone who is
more knowledgeable will more probably need a network structure as compared to
someone who is less knowledgeable who will need a hierarchy structure. Third, the study
improves our understanding about the effect of navigation structures on learning based on
cognitive load theory. Fourth, the study may assist auditing firms in their training and in
knowledge acquisition. Web-based auditing software and computerized aids are
increasingly popular in auditing firms as knowledge acquisition tools. For example
KPMG uses a web-based software called KRisk(SM) for strategic systems auditing (Bell
12
et al., 2002). Auditing teams of Ernst & Young use a web-based portfolio of audit tools
called EY/NexGen. Similarly, Delloitte & Touche use web-based audit systems ACL
Web (Krasss, 2002). Our study will be a preliminary stdu that can be replicated with
auditors to understand impact of navigation structures on performance in auditing
settings.
In this study, I will limit the number of hypertext links per page to maximum 10
because I want to keep the study simple. However, the results might differ when more
number of links is used. Further research needs to be done by varying the number of
hypertext links. One possible study is to find out how the number of hypertext links
provided in web-based cases affects cognitive load, and how that affects learning.
This study attempts to explore prior knowledge that matches with existing
knowledge structures. Future studies can also explore the effect of prior knowledge that is
disparate and does not match with existing knowledge structure. That may have a
negative
effect
on
learning
from
13
hypertext
based
case
analysis.
Experience
Knowledge
Performance
Ability
Figure 1: Libby and Luft Model of the Effect of Experience, Knowledge, and Ability on
Performance (1993)
Navigational
Structure
Cognitive Load
Learning from
Accounting
Case Analysis
Prior accounting
Knowledge
Figure2: Suggested Research model for hypertext-based accounting case learning
14
REFERENCES
Anderson, J. R. (1982). "Acquisition of Cognitive Style," Psychological Review, 89, p.
369.
Balcytiene, Aukse (1999). “Exploring Individual Processes of Knowledge Construction
with Hypertext,” Instructional Science, 27, p. 303.
Bell, T. B., Bedard, J. C., Johnstone, K. M., & Smith, E. F. (2002). “KRisk(SM): A
computerized decision aid for client acceptance and continuance risk assessments,”
Auditing: A Journal of Practice and Theory, 21, p. 97.
Brunken, R., Steinbacher, S., Plass, J.L., Leutner, D. (2002). “Assessment of cognitive
load in multimedia learning using dual-task methodology,” Experimental Psychology, 49,
p. 109.
Carlson, R., Chandler, P., and Sweller, J. (2003). “Learning and understanding science
instructional material,” Journal of Educational Psychology, 95, p. 629.
Conklin, J. (1987). “Hypertext: An introduction and Survey,” IEEE Computer, 20, p. 17.
Crandall, D., and Phillips, F. (2002). “Using Hypertext in Instructional Material: Helping
Students Link Accounting Concept Knowledge to Case Applications,” Issues in
Accounting Education p, 163-183.
Daneman, M. and Carpenter, P.A., (1980), “Individual Differences in Working Memory
and Reading”, Journal of Verbal Learning and Verbal Behavior, 19, p.450.
Dull, R.B., Graham, A.W. and Baldwin, A.A. (2003) “Web-based financial statements:
hypertext links to footnotes and their effect on decisions,” International Journal of
Accounting Information Systems, 4, p.185.
Fang, X. (2001). Web site design factors and usability: A navigation structure
experiment, Ph.D. Dissertation, University of Kentucky.
Foss, C L (1989), "Tools for reading and browsing hypertext," Information Processing
and Management, 25, p. 407-418.
Gerjets P. and K. Scheiter (2003). “Goal Configurations and Processing Strategies as
Moderators between Instructional Design and Cognitive Load: Evidence from HypertextBased Instruction.” Educational Psychologist, 38, p. 33.
Gerjets P. and K. Scheiter (2004). “Designing Instructional Examples to Reduce Intrinsic
Cognitive Load: Molar versus Modular Presentation of Solution Procedures.”
Instructional Science, 32, p. 33.
Hodge, F.D. (2001). “Hyperlinking unaudited information to audited financial
statements: Effects on investor judgments,” The Accounting Review, 76, p. 675.
15
Hoffman, R. & van Oostendorp, H. (1999). “Cognitive effects of a structural overview
in a hypertext,” British Journal of Educational Technology, 30, p. 129.
Kirschner, P.A. (2002). “Cognitive load theory: implications of cognitive load theory on
the design of learning,” Learning and Instruction, 12, p.1.
Krasss, P. (2002). “The Never-ending Audit: Can software prevent future Enrons?,” CFO
Asia, 2002(Nov); http://www.cfoasia.com/archives/200211-08.htm (Accessed: 14th
March, 2004).
Libby, R. (1981). Accounting and Human Information Processing: Theory and
Applications, Prentice Hall.
Libby. R., R. Bloomfield and M. W. Nelson (2002). "Experimental Research in Financial
Accounting," Accounting Organizations and Society, p. 775.
Last, D.A., O’Donnell, A.M. (2001). “The effects of prior knowledge and goal strength
on the use of hypertext,” Journal of Educational Multimedia and Hypermedia, 10, p. 3.
Leidner, D.E., Jarvenpaa, S.L. (1995). “The use of Information Technology to enhance
Management School Education: A theoretical view,” MIS Quarterly, 19, p. 24.
Mao, J., and Benbasat, I. (1998). "Contextualized Access to Knowledge in Knowledgebased Systems: A Process Tracing Study," Information Systems Journal, 8, p. 217.
McKnight C., Dillon A. & Richardson J., (1991). Hypertext in Context, Cambridge
University Press.
Muller-Kaltoff, T. and Moller, J. (2003). “The effects of graphical overviews, prior
knowledge, and self-concept on hypertext disorientation and learning environment,”
Journal of Educational Multimedia and Hypermedia, 12, p.117.
Paas, F. (1992). “Training strategies for attaining transfer of problem-solving skills in
statistics: A cognitive-load approach,” Journal of Educational Psychology, 84, p. 429.
Paas, F., J. E. Tuovinen, et al. (2003), “Cognitive Load Measurement as a Means to
Advance Cognitive Load Theory,” Educational Psychologist,” 38, p. 63.
Paas, F., A. Renkl, et al. (2003). “Cognitive Load Theory and Instructional Design:
Recent Developments,” Educational Psychologist, 38, p. 1.
Pierce, K.A., Duncan, M.K., Gholson, B., Ray, G.E. and Kamhi, A.G. (1993). “Cognitive
Load, Schema acquisition, and procedural adaptation in non-isomorphic analogical
transfer,” Journal of Educational Psychology, 85, p. 66.
16
Rouet, J.-F., Levonen J. J., Dillon, A. & Spiro, R. J. (eds.), Hypertext and cognition.
Mahwah, NJ. et al.: Erlbaum.
Sweller, J., Chandler, P., Tierney, P. & Cooper, M. (1990). “Cognitive load as a factor in
the structuring of technical material,” Journal of Experimental Psychology, 119, p. 176.
Sweller, J. (1994). "Cognitive load theory, learning difficulty, and instructional design,"
Learning and Instruction, 4, p. 295.
Sweller, J., van Merrienboer, J.J.G., and Paas, F.G.W.C. (1998). “Cognitive architecture
and instructional design,” Educational Psychology Review, 10, p. 251.
Tuovinen, J.E. and Sweller, J. (1999). “A comparison of cognitive load associated with
discovery learning and worked examples”, Journal of Educational Psychology, 91, p.
334.
17