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Journal of Education for Business

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Assessing Students' Accounting Knowledge: A
Structural Approach
Margaret N. Boldt
To cite this article: Margaret N. Boldt (2001) Assessing Students' Accounting Knowledge:
A Structural Approach, Journal of Education for Business, 76:5, 262-269, DOI:
10.1080/08832320109599646
To link to this article: http://dx.doi.org/10.1080/08832320109599646

Published online: 31 Mar 2010.

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Assessing Students’ Accounting
Knowledge:
A Structural Approach
MARGARET N. BOLDT
Murray State University
Murray, Kentucky

ABSTRACT. This study explored a
structural approach to assessing students’ accounting knowledge. An
“expertise” knowledge structure of

basic financial accounting concepts
was constructed, and students’ knowledge structures of the same concepts
were then compared with the “expertise” knowledge structure. Data were
collected from respondents at a large
public university to demonstrate the
procedure and method of analysis.
The procedure has the potential for
providing accounting programs with
valuable information regarding their
students’ knowledge after completing
a course or program of study.

I

n recent years, formal outcomes
assessment of student learning has
become increasingly important for
accounting programs. It is no longer
sufficient to evaluate student learning as
measured by the subjective experience

of the instructor in the classroom or
even by student performance on classroom examinations. Rather, most institutions and accounting programs are
required to have a formal outcomes
assessment program. For example, any
school desiring accreditation by the
American Assembly of Collegiate
Schools of Business-The International
Association for Management Education
(AACSB) must comply with this organization’s requirement for outcomes
assessment.
In a recent article, Barbara Apostolou
(1999) discussed four common outcome
measurements: standardized tests, performance assessment, alumni surveys,
and employer surveys. Certainly, all of
these measures provide accounting programs with valuable data about student
preparedness for employment, satisfaction with their education, ability to “perform” on standardized tests, and so
forth. However, none of these measures
adequately addresses the question of
whether students possess the necessary
accounting knowledge to become

accounting experts. Of course, accounting knowledge is only one capability of

262

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Furthermore, the approach is relatively
easy to implement and can be used to
assess knowledge in various areas of
accounting (e.g., auditing, taxation).

Assessing Knowledge Structures
Goldsmith, Johnson, and Acton
(1991) outlined a three-step process for
implementing a structural approach to
capturing knowledge in a specific
domain. The first step in this process is
knowledge elicitation, essentially the
accessing of participants’ organization
of memory for a set of concepts relevant to the domain being investigated.
Although there are several models for

memory structures in the literature (e.g.,
network models, feature models), all of
them rely on the idea that concepts
vary along some continuum of psychological proximity, or relatedness, in
memory (Schvaneveldt, Durso, Goldsmith, et al., 1985). For the present
study, I used participants’ pairwise ratings of relatedness among concepts in
financial accounting to access participants’ memory structures.
The second step in the structural
approach is defining a representation for
the knowledge elicited from participants
(Goldsmith et al., 1991).There are several procedures available for representing
knowledge elicited in the form of pairwise relatedness ratings. Network mod-

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several mentioned by the Accounting
Education Change Commission ( 1 990).
Importantly, accounting knowledge is
the one capability that accounting programs must address internally. Other
aspects of the collegiate experience are
unlikely to make significant contributions to students’ accounting knowledge. Hence, the onus is on accounting

programs to assess whether students
have the necessary knowledge when
completing courses or programs.
In the present study, I assessed students’ accounting knowledge by using
an “expertise,” or benchmark, knowledge structure that can be compared
with students’ knowledge structures.
The procedure may provide accounting
programs with important information
concerning students’ knowledge gaps.

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els depict local relationships by connecting nodes (representing concepts) with
weighted links (representing relationships between concepts; Schvanaveldt et
al., 1985). Importantly, network models
do not limit the relationships that can be

represented, The present study focused
primarily on identifying the necessary
relationships between financial statement
items that are necessary for expertise and
the extent to which two student groups
have these relationships in their organization of memory. As a result, elicited
knowledge is via linkweighted network
models.
The final step in Goldsmith and colleagues’ (1991) structural approach is
evaluating the knowledge representations relative to some standard. Hence,
students’ knowledge structures are evaluated relative to an “expertise” structure. Additionally, concepts that are not
well defined are classified as being
over-, under-, or misdefined based on
the presence or absence of idiosyncratic
and critical links.

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statements to select 20 concepts that
would be familiar to all groups of participants. Participants rated the 20 concepts by judging the degree of “relatedness” between two items in a given pair

on a scale of 1 (not related) to 9 (very
related). Each participant completed all
possible painvise ratings for the 20 concepts, totaling 190 pairs. (See Table 1
for a list of the 20 items.) Application of
the Pathfinder’ algorithm to respondents’ painvise ratings produced linkweighted network models.

Results and Discussion
Pearson product-moment correlations
were computed for each participant’s
ratings with every other participant’s rat-

ings. The mean correlations of the ratings
are shown in Table 2. These results show
that the master’s degree students had a
relatively high level of agreement with
teachers, whereas the financial accounting students disagreed with both
advanced students and teachers.
I performed Pathfinder analyses on
the educators’ networks to identify separately the links for educators with practical experience and the links for those
without practical experience. The

resulting networks are displayed in Figures 1 and 2. A composite “expertise”
knowledge structure was then compiled
by overlaying the two networks (see
Figure 3).*The dashed lines in Figure 3
represent “flexible” links. For example,
educators did not agree on which group
of concepts inventory should be linked
to, but they all agreed that inventory
should not be linked to interest income.
Next I performed Pathfnder analysis
on the ratings of the master’s degree students and generated a network (see Fig3
ure 4). Then I erformed an overlap
procedure to igntify the “expertise”
links present in the master’s students’
structure. Bold lines in Figure 5 represent these links. Visual inspection
shows that the master’s students had
acquired a majority of the “expertise”
critical links by the time they graduated.
In fact, the master’s degree students’
structure lacked critical links for only

four concepts (cash, cash flow, accounts
payable, and cost of goods sold).
Finally, the financial accounting student network was compared with the
“expertise” structure to identify the
links learned in 1 semester of instruction. In Figure 6, I displayed the

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TABLE 1. Financial Statement
Items Used in Participants’
Relatedness Ratings

Sales
Interest income
Cost of goods sold
Selling and administrative expenses
Interest expense
Net operating income

Cash
Merchandise inventory
Accounts receivable
Property plant & equipment
Accounts payable
Accrued payrolls and other liabilities
Long-term debt
Deferred income taxes

Knowledge Representationsfor
Teachers and Students

Seven accounting teachers at a large
public university in the southwestern
United States served as experts. ’ h o of
these participants had no practical experience in either public accounting or
private industry. However, both of them
had over 15 years of teaching experience
at the college level and had presumably
spent several thousand hours solving
accounting problems. These two participants, then, could be considered
experts at accounting problem solving
even though they lacked practitioner
experience. The remaining five educators all had some practical experience.
Eleven students enrolled in the capstone course for the master’s of accountancy degree served as one group of student participants. None of these
students had ever been employed as an
accountant, but all had completed the
courses required in an undergraduate
accounting major. The final group of
participants consisted of 8 students who
had completed an introductory financial
accounting course satisfactorily (i.e.,
received a grade of C or better).
I reviewed examples of financial

Common stock
Retained earnings

Accumulated depreciation
Dividends paid
Net cash provided from operations
Extraordinary gain

TABLE 2. Mean Correlations of Relatedness Ratings Between Participant
Groups

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Educators
Students
Practical Master’s
Introductory
experience experience degree Financial Accounting

No practical

I

Educators
No practical experience
Practical experience
Students
Master’s degree
Introductory Financial
Accounting

3 9

.so5
.so1

.481

.200

.454

.167

.431

,171
,107

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FIGURE 1. Pathfinder Network for InstructorsWith Practical Experience

I

Extraordinary gain

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inventory

I

7-

Net operating

Accounts payable

administrative expenses
Cash flow

interest income

Accrued liabilities

-4,
interest expense

Property, plant, and equipment
/

I

/

Accrued depreciation

I

FIGURE 2. Pathfinder Network for InstructorsWithout Practical Experience

Accounts receivable

zyxw
HLz-

\

\

/

Selling and
administrative expenses

inventory

1

Net operating

Deferredtaxes

Dividends
interest expense
Retained earnings

Stock

Accrued liabilities
/

I
I

Property, plant, and equipment

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Debt

Accrued depreciation

264

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FIGURE 3. “Expertise” Knowledge Structure for Selected Financial Accounting Concepts

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I Accounts receivable I

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,
Selling and
administrative expenses

I Interest income f

I

Cash flow

t--l Cost of goods sold I

I Extraordinarygain I

j

1 Accrued’liabliities
I
...
j

,*’

,.’1

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4Dividends

Stock

I

Retained earnings

I

1

I

Debt

I

I

Property, plant, and
eaulment

..

{Accumulated depreciation

1

I

1

I

I

FIGURE 4. Pathfinder Network for Master’s Students

I Accounts receivableI
Cost of goods sold

Selling and
administrative expenses

Inventory
Net operating

I

1 Retained earnings

interest income

incomes

HAccounts payableHAccrued liabilities

I

I

I Deferredtaxes

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Dividends

[

Cash flow

I Cash I

I

\

Interest expense

I

I Property, plant, and equipment I

&
Accrued depreciation

I

zyx

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FIGURE 5. “Expertise”-Master’s

Students’ Overlay Depicting Critical Links

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Accounts receivable
Accounts payable

Selling and
administrative expenses

I Interest income
Cash

Cash flow

Cost of goods sold

I

Debt

Pathfinder network for the financial
accounting students’ ratings, and in Figure 7 I show the overlap with the
“expertise” structure. The results
demonstrate that the financial accounting students had not acquired many of
the critical links necessary for expertlevel problem solving. In fact, critical
links were absent for nine of the items.
However, one of the critical links that
was missing in the master’s students’
network was present in the financial
accounting students’ network, implying
that that relationship somehow degrades
and/or decays with time.
To quantify the similarity and identify the specific differences between the
student structures and the “expertise”
structure, I analyzed and classified each
concept as either well-defined, misdefined, overdefined, or underdefined.
This classification was based on the
presence or absence of idiosyncratic
links (i.e,, links present only in the student structure) and the presence or
absence in the student structure of all
critical links (i.e., links present in the
“expertise” structure). Items with all of
266

Accumulated depreciation

the critical links and no spurious links
are well-defined. Misdefined items do
not have all of the critical links but do
have some idiosyncratic links. Overdefined concepts have extraneous links but
also have all of the critical links, whereas underdefined concepts lack spurious
links but also are missing some critical
links. The data in Table 3 show the classification for each of the items by group.
The results are consistent with the mean
correlations presented earlier. As
expected, the master’s students had
many well-defined concepts and only a
few mis-, over-, and underdefined items.
The financial accounting students, on
the other hand, had very few welldefined items compared with the master’s students.
A closer examination of the specific
items that were not well defined by the
master’s students yields some interesting insights. First, it is perhaps not surprising that cash was a misdefined item.
Knowledge of the subtle interrelationships that cash has with other accounts
probably may be acquired only through
solving many problems involving sever-

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al periods. That is, routinized knowledge for this item may come from experience with complete cash cycles, rather
than through isolated transactions.
Although master’s students would certainly have been exposed to some multiperiod problems, the vast majority of
problems in accounting courses deal
with only one effect on cash at a time.
Two of the underdefined items
(accounts payable and cost of goods
sold) deal explicitly with the product
cycle. A possible explanation for this
result is that students generally take relatively few (only two) courses that deal
with product costing and the manufacturing cycle. The overdefined items, in
contrast, are both related to financing
activities and receive a great deal of
exposure over many courses. However,
the coverage is generally indirect in that
these accounts are related to the items
actually being taught (e.g., debt and
stock). Additionally, the related accounts
are covered frequently because of the
complexity involved in accounting for
transactions affecting these accounts.
Possibly, the master’s students have

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FIGURE 6. Pathfinder Network for Financial Accounting Students

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I Cost of goods sold I
Retained earnings 1
\
/
\

/

7
1
administrative exDenses

Interest expense

Accrued depreciation

Dividends

FIGURE 7. “Expertise”-Financial

I

zy

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Accounting Overlay Depicting Critical Links
Accounts receivable

I Accounts payable
I
. I

I

I

I Interest income I

I

inventory

Accrued liabilities

J

I

Dividends

Stock

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zyx
.*... ,,**
I

,

Deferred taxes

I

interest expense

I

Debt

Property, plant, and
equipment

Accumulated depreciation

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TABLE 3. Item Classificationsfor Financial Statement Items
Item
classification

Master’s degree students

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Introductory Financial
Accounting students

Well-defined

Sales
Interest income
Selling and administrative
expenses
Net income
Inventory
Accounts receivable
Property
Accrued liabilities
Debt
Deferred taxes
Stock
Retained earnings
Accumulated depreciation
Extraordinary gain

Inventory
Property
Debt
Deferred taxes
Stock
Accumulated depreciation
Extraordinary gain

Misdefined

Cash

Sales
Cash flow
Interest income
Interest expense
Accounts receivable
Dividends
Debt

Overdefined

Interest expense
Dividends

Selling and administrative
expenses
Accounts payable
Cash
Accrued liabilities

Underdefined

Accounts payable
Costs of goods sold
Cash flow

Costs of goods sold
Net income
Retained earnings

Importantly, this approach provides little information about what students can
do with the knowledge (i.e., practical
skills) and would be used most effectively in conjunction with other assessment procedures.
This exploratory study’s results indicate that beginning students at the particular institution under investigation are
not obtaining a complete understanding
of accrual-basis accounting, a primary
goal of the course. Additional research is
needed to determine exactly how this
knowledge gap can be filled earlier in
the degree program. A possible starting
point for this research might be the use
of a pre- and posttest procedure to identify precisely which relationships currently are being acquired in the course.
This study also provides encouraging
feedback regarding graduating students,
who seem to have acquired most of the
essential links for expertise.
Finally, this study had several limitations that could be addressed in future
research. First, results could be more
generalizable with participants from
several institutions. Additionally, a longitudinal study in which participants
provide ratings after several courses
would help identify when and how
“expertise” knowledge is acquired.
NOTES

erroneously attributed the complexity of
accounting for related items to the
overdefined items. Last, cash flow is
underdefined. Discussions with teachers
at the institution revealed that cash flow
is generally covered at the end of courses in a somewhat cursory fashion.
Unlike the master’s students’ classifications, the results of the financial
accounting students did not seem to have
underlying themes related to the type of
activity. Rather, six of the seven welldefined items were located on one financial statement, the balance sheet. The
seventh item, extraordinary gain, usually
was related to transactions that affect the
balance sheet. The other 13 items that
were not well defined all were related to
one of two types of transactions: infrequent transactions and accruals. Items
related with infrequent transactions (dividends and debt) have many rules associated with them and probably require
268

more than 1 semester of experience to
transfer into routinized knowledge. The
remaining 11 mis-, under-, and overdefined items all relate in some way to
accrual accounting. Obviously, introductory students do not have a good understanding of accrual-basis accounting
after 1 semester of instruction.

General Discussion and
Concluding Remarks

1. The information provided on Pathfinder
relies heavily on Schvanaveldt, Durso, and
Dearholt (1989). For further information on
Pathfinder, consult that article or the documentation available with the software (KNOT PC software).
2. I adapted this procedure from the analysis in
Schvanaveldt et al. (1985) to arrive at the “right
stuff’ for expertise.
3. This overlap procedure differs from the
overlay in that it identifies only the links shared
between the two structures. In contrast, the overlay procedure depicts the links that are in either
structure.

ACKNOWLEDGMENT

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Journal of Education for Business

In this study, I explored the use of a
structural approach for assessing students’ knowledge structures for financial accounting concepts. This approach
provides a more complete picture of the
knowledge gained from a course or program of study. That is, the structural
approach simultaneously provides
information about the concepts or relationships that students do not understand and those they do understand.

This article benefited greatly from comments
provided by Stephen Butler, Francis Durso, and
participants of the University of Tulsa Accounting
Research Symposium and the Sixth Annual Meeting of the American Society of Business and
Behavioral Sciences.

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Accounting Education Change Commission
(AECC). (1990, Fall). Objectives of education
for accountants: Position Statement No. I .
Issues in Accounting Education. 307-3 12.
Apostolou, B. (1999). Outcomes assessment.

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Issues in Accounting Education, 14(I ) ,
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Goldsmith, T., Johnson, P., & Acton, W. (1991).
Assessing structural knowledge. Journal of
Educational Psychology, 83,88-96.
KNOT PC Software. (1990). KNOT-PC: Knowl-

edge network organizing toolfor IBM PC cornpatibles. Las Cruces, NM: Interlink, Inc.
Schvanaveldt, R., Durso, F., & Dearholt, D.
(1989). Network structures in proximity data.
The Psychology of Learning and Motivation,
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Schvanaveldt, R.. Durso, E, Goldsmith, T., Breen,
T., Cooke, N., Tucker, R., & De Maio, J.
(1985). Measuring the structure of expertise.
International Journal of Man-Machine Studies,
23,699-728.

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