U.S. patent application number 10/619266 was filed with the patent office on 2004-03-11 for system and method for data entry of cluster analysis.
Invention is credited to Dong, Jianming, Martin, Shirley Lynn.
Application Number | 20040046775 10/619266 |
Document ID | / |
Family ID | 31994506 |
Filed Date | 2004-03-11 |
United States Patent
Application |
20040046775 |
Kind Code |
A1 |
Dong, Jianming ; et
al. |
March 11, 2004 |
System and method for data entry of cluster analysis
Abstract
A graphical user interface for use in a data processing system
for facilitating data entry for cluster analysis. In a preferred
embodiment, the graphical user interface includes a source card
list area, a participants area, a first sort area, and a second
sort area. The source card list area allows entry, display of, and
direct manipulation access to all of a plurality of items to be
sorted. The participants area allows entry and display of
participant names. The first sort area includes a plurality of
first sections that each can contain a set of items dragged from
the source card list area and represents a first-level of grouping
of the items from the source card list area. The second sort area
includes a plurality of second sections. Each of the plurality of
second sections may contain items dragged from at least one of the
first sections and represents a second-level of grouping of the
items from the source card list area.
Inventors: |
Dong, Jianming; (Austin,
TX) ; Martin, Shirley Lynn; (Austin, TX) |
Correspondence
Address: |
DUKE W. YEE
CARSTENS, YEE & CAHOON, L.L.P.
P.O. BOX 802334
DALLAS
TX
75380
US
|
Family ID: |
31994506 |
Appl. No.: |
10/619266 |
Filed: |
July 14, 2003 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
10619266 |
Jul 14, 2003 |
|
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09584593 |
May 31, 2000 |
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Current U.S.
Class: |
715/700 ;
707/E17.091 |
Current CPC
Class: |
G06F 16/355
20190101 |
Class at
Publication: |
345/700 |
International
Class: |
G09G 005/00 |
Claims
What is claimed is:
1. A graphical user interface for use in a data processing system
for facilitating data entry for cluster analysis, the graphical
user interface comprising: a first area containing a plurality of
lists of items; a second area containing a plurality of
participants; and means for corresponding a selected list to a
respective one of the plurality of participants, wherein to
selected list is the one of the plurality of lists selected by the
respective one of the plurality of participants.
2. The graphical user interface as recited in claim 1, further
comprising: means for corresponding groupings of the plurality of
lists to a respective one of the plurality of participants.
3. The graphical user interface as recited in claim 1, wherein the
means for corresponding comprises an array of third areas in which
the items within each list may be displayed in accordance with a
selection made by a respective one of the plurality of
participants.
4. The graphical user interface as recited in claim 1, wherein the
list of items displayed in the first area corresponds to a
highlighted participant in the second area.
5. The graphical user interface as recited in claim 1, wherein the
participants are arranged in a scrollable list in the second
area.
6. The graphical user interface as recited in claim 1, wherein the
first area allows entry, display of, and direct manipulation of the
items in the plurality of lists.
7. The graphical user interface as recited in claim 1, wherein the
means for corresponding comprises a third area having sections and
entries into the sections of the third area are used to calculate
similarity and distance matrices for cluster analysis purposes.
8. A method of providing entry of data into a cluster analysis
program, comprising the steps of: responsive to receiving a first
user input, removing a selected card name from a source card list
area; and responsive to receiving a second user input, placing the
selected card name in a selected one of a plurality of first
grouping area sections.
9. The method as recited in claim 8, further comprising: responsive
to receiving a third user input, entering an identification number
corresponding to a user selected one of the plurality of first
grouping area sections into a user selected one of a plurality of
second grouping area sections.
10. The method as recited in claim 8, wherein the plurality of
first grouping area sections comprises an array of boxes in which
card names from the card sort list area may be placed and
displayed.
11. The method as recited in claim 9, wherein the plurality of
second grouping area sections comprise a plurality of rows wherein
each row contains at least one box configured to display the
identification numbers.
12. A computer program product in computer readable media for use
in a data processing system for providing entry of data into a
cluster analysis program, the computer program product comprising:
first instructions, responsive to receiving a first user input, for
removing a selected card name from a source card list area; and
second instructions, responsive to receiving a second user input,
for placing the selected card name in a selected one of a plurality
of first grouping area sections.
13. The computer program product as recited in claim 12, further
comprising: third instructions, responsive to receiving a third
user input, for entering an identification number corresponding to
a user selected one of the plurality of first grouping area
sections into a user selected one of a plurality of second grouping
area sections.
14. The computer program product as recited in claim 12, wherein
the plurality of first grouping area sections comprises an array of
boxes in which card names from the card sort list area may be
placed and displayed.
15. The computer program product as recited in claim 13, wherein
the plurality of second grouping area sections comprise a plurality
of rows wherein each row contains at least one box configured to
display the identification numbers.
16. A data processing system for providing entry of data into a
cluster analysis program, comprising: means, responsive to
receiving a first user input, for removing a selected card name
from a source card list area; and means, responsive to receiving a
second user input, for placing the selected card name in a selected
one of a plurality of first grouping area sections.
17. The data processing system as recited in claim 16, further
comprising: means, responsive to receiving a third user input, for
entering an identification number corresponding to a user selected
one of the plurality of first grouping area sections into a user
selected one of a plurality of second grouping area sections.
18. The data processing system as recited in claim 16, wherein the
plurality of first grouping area sections comprises an array of
boxes in which card names from the card sort list area may be
placed and displayed.
19. The data processing system as recited in claim 17, wherein the
plurality of second grouping area sections comprise a plurality of
rows wherein each row contains at least one box configured to
display the identification numbers.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Technical Field
[0002] The present invention relates generally to computer software
and, more particularly, to a method and system for data entry for
cluster analysis.
[0003] 2. Description of Related Art
[0004] Cluster analysis is an exploratory data analysis tool for
solving classification problems. Its object is to sort cases
(people, things, events, etc.) into groups, or clusters, so that
the degree of association is strong between members of the same
group and weak between members of different groups. Each such
cluster thus describes, in terms of the data collected, the class
to which its members belong. This description may be abstracted
through use from the particular to the general class or type.
[0005] Cluster analysis is thus a tool of discovery. It may reveal
associations and structure in data which, though not previously
evident, nevertheless are sensible and useful once found. The
results of cluster analysis may contribute to the definition of a
formal classification scheme, such as a taxonomy for related
animals, insects or plants; or suggest statistical models with
which to describe populations; or indicate rules for assigning new
cases to classes for identification and diagnostic purposes; or
provide measures of definition, size and change in what previously
were only broad concepts; or find exemplars to represent
classes.
[0006] One useful application of cluster analysis is to analyze
data from card-sorting exercises. In a card-sorting procedure,
representative users of a product or technology arrange cards
representing data objects into groups on the basis of their
perceived relatedness. Cluster analysis of the resulting groups can
help researchers to understand users' perceptions of the degree of
relatedness of items in data sets.
[0007] Multiple software packages are currently available that
allow developers to utilize cluster analysis to translate user
expectations into a meaningful organization of a web site. However,
currently available cluster analysis software is prohibitively
difficult to use for non-professional statisticians. These software
packages require the user to calculate and construct similarity or
distance matrices from raw data. Only after these matrices have
been painstakingly constructed will the packages perform cluster
analyses. Therefore, it would be advantageous to have a method and
apparatus that provides a simpler user interface and method for
users to enter raw data into a cluster analysis software package.
Furthermore, a cluster analysis software package that does not
require the user to perform numerous calculations or construct
matrices would also be advantageous.
SUMMARY OF THE INVENTION
[0008] The present invention provides a graphical user interface
for use in a data processing system for facilitating data entry for
cluster analysis. In a preferred embodiment, the graphical user
interface includes a source card list area, a participants area, a
first sort area, and a second sort area. The source card list area
allows entry and display of, and direct manipulation access to, all
of a plurality of items to be sorted. The participants area allows
entry, display and editing of participant names. The first sort
area includes a plurality of first sections, each of which may
contain a set of items dragged from the source card list area. Each
of these first sections represents a first-level grouping of the
items from the source card list area. The second sort area includes
a plurality of second sections. Each of the plurality of second
sections may contain items dragged from at least one of the first
sections, and represents a second-level grouping of the items from
the source card list area.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] The novel features believed to be characteristic of the
invention are set forth in the appended claims. The invention
itself, however, as well as a preferred mode of use, and further
objectives and advantages thereof, will best be understood by
reference to the following detailed description of an illustrative
embodiment when read in conjunction with the accompanying drawings,
wherein:
[0010] FIG. 1 depicts a block diagram of a data processing system
in which the present invention may be implemented;
[0011] FIG. 2 depicts a flowchart illustrating a method of
performing a card-sorting test for use in a cluster analysis
program in accordance with the present invention;
[0012] FIG. 3 depicts an example of a "page" card for use in
performing cluster analysis in accordance with the present
invention;
[0013] FIGS. 4-6 depict diagrams illustrating the relationships
between pairs of pages in accordance with the present invention;
and
[0014] FIGS. 7-9 each depict an example of a graphical user
interface for facilitating entry of data into a cluster analysis
program in accordance with the present invention;
[0015] FIG. 10 depicts a flowchart illustrating a method of
allowing data entry into a cluster analysis program using a
graphical user interface in accordance with the present invention;
and
[0016] FIG. 11 depicts a flowchart illustrating an exemplary method
in a data processing system for allowing entry of card sorting
results in accordance with the present invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
[0017] With reference now to the figures, and in particular with
reference to FIG. 1, a block diagram of a data processing system in
which the present invention may be implemented is illustrated. Data
processing system 100 is an example of a client computer. Data
processing system 100 employs a peripheral component interconnect
(PCI) local bus architecture. Although the depicted example employs
a PCI bus, other bus architectures, such as Micro Channel and ISA,
may be used. Processor 102 and main memory 104 are connected to PCI
local bus 106 through PCI bridge 108. PCI bridge 108 may also
include an integrated memory controller and cache memory for
processor 102. Additional connections to PCI local bus 106 may be
made through direct component interconnection or through add-in
boards. In the depicted example, local area network (LAN) adapter
110, SCSI host bus adapter 112, and expansion bus interface 114 are
connected to PCI local bus 106 by direct component connection. In
contrast, audio adapter 116, graphics adapter 118, and audio/video
adapter (A/V) 119 are connected to PCI local bus 106 by add-in
boards inserted into expansion slots. Expansion bus interface 114
provides a connection for a keyboard and mouse adapter 120, modem
122, and additional memory 124. In the depicted example, SCSI host
bus adapter 112 provides a connection for hard disk drive 126, tape
drive 128, CD-ROM drive 130, and digital video disc read only
memory drive (DVD-ROM) 132. Typical PCI local bus implementations
will support three or four PCI expansion slots or add-in
connectors.
[0018] An operating system runs on processor 102 and is used to
coordinate and provide control of various components within data
processing system 100 in FIG. 1. The operating system may be a
commercially available operating system, such as OS/2, which is
available from International Business Machines Corporation. "OS/2"
is a trademark of International Business Machines Corporation. An
object oriented programming system, such as Java, may run in
conjunction with the operating system, providing calls to the
operating system from Java programs or applications executing on
data processing system 100. Instructions for the operating system,
the object-oriented operating system, and applications or programs
are located on a storage device, such as hard disk drive 126, and
may be loaded into main memory 104 for execution by processor
102.
[0019] Those of ordinary skill in the art will appreciate that the
hardware in FIG. 1 may vary depending on the implementation. For
example, other peripheral devices, such as optical disk drives and
the like, may be used in addition to or in place of the hardware
depicted in FIG. 1. The depicted example is not meant to imply
architectural limitations with respect to the present invention.
For example, the processes of the present invention may be applied
to multiprocessor data processing systems.
[0020] The present invention provides a graphical user interface
for data entry into a cluster analysis program to allow users using
card-sorting and cluster analysis to be involved in the
organizational design of Web sites. Members of a site's target
audience sort physical cards representing key pages of a proposed
site into groups. These cards may be images of a sample web page or
may simply be text indicating the content of the web page. Cluster
analysis is then performed across all participants' card groupings
to produce site diagrams. By revealing the perceived relatedness of
the key pages, these diagrams can help guide the navigational
design of the site to meet users' expectations, resulting in a more
usable site.
[0021] The organizational structure of a Web site can have a
profound effect on its ease of use. An ideal structure would allow
users to navigate freely and confidently through the site, while a
less-than-ideal structure can throw obstacles between the users and
their goals. Many corporate Internet sites inherit their structures
from the internal structures of their companies, grouping the pages
of the site according to the divisions that produce them.
Unfortunately, most visitors to these sites are unfamiliar with the
inner workings of the companies, and are unlikely to find this kind
of site easy to navigate.
[0022] A more user-oriented approach to site structure design
requires evaluating users' expectations for organizing a Web site.
One method of collecting data on users' organizational expectations
is card sorting. In a card-sorting test, participants are presented
with randomly ordered cards representing pages of a Web site, and
group the cards as they see fit.
[0023] Learning how users group pages is useful, but how can site
designers reconcile the various groupings that different users
choose? Some Web site designers have "eyeballed" card groupings
created by a few test participants, and somehow divined a central
tendency from the competing sorting structures. This method, if
ever it were manageable, becomes unwieldy very quickly with the
inclusion of more than a handful of topics or users. However,
"eyeballing" groupings becomes much harder as the number of cards
or participant grows. Subjective judgments often cause incorrect
decisions.
[0024] Cluster analysis of card-sorting data is a promising
quantitative method for making sense of multiple participants'
input to the organization of Web site pages. Cluster analysis
quantifies card-sorting data by calculating the strength of the
perceived relationships between pairs of cards, based on how often
and at which level the members of each possible pair appear in a
common group. The cumulative number of times that each pair of
cards is grouped together yields the "raw similarity score". These
raw similarity scores are divided by the maximum possible raw
score.
[0025] The array of these normalized similarity scores forms a
"similarity matrix". The highest possible score in a similarity
matrix is 1, meaning that the corresponding pair of cards is always
grouped together by participants. The lowest score in a similarity
matrix is 0, meaning that the corresponding pair of cards is never
grouped together by any participants. A distance matrix is
constructed by Subtracting each similarity score in the similarity
matrix from 1, resulting in a "distance" from the best possible
similarity.
[0026] The cluster analysis program manipulates the similarity
matrix or the distance matrix and generates output in the form of
tree diagrams, in which the relationship between each pair of cards
is represented graphically by the distance between the origin and
the branching of the lines leading to the two cards. There are
several different algorithms to decide where the joint node of card
clusters are located. (Joint nodes are the points where the tree
structure branches.) These algorithms interpret the input data in
different perspectives and are not mutually exclusive. In most
cases, the tree structures that are generated by different
algorithms have similar patterns, which can be used in cluster
analysis. Researchers choose the algorithm based on the specific
scenario.
[0027] Card sorting is a data collection method that can be
particularly useful for understanding users' perceptions of
relationships between items. In the example described here,
participants sort cards that display contents of a Web site's most
important pages. The strengths of the page relationships are
calculated by assigning similarity points to each pair of cards
each time a participant places them in a common group. The points
are totaled across all participants and converted into a distance
score for each possible pair of cards. Then the distance scores are
compared using a cluster analysis program that arranges pages into
a tree structure.
[0028] Referring now to FIG. 2, a flowchart illustrating a method
of performing a card-sorting test for use in a cluster analysis
program is depicted in accordance with the present invention. As in
any user involvement activity, the first step of a card-sorting
test is to identify the target audience for the site (step 202).
This step is essential and deserves special attention because
different groups of users will expect different arrangements of
site content. An audience description should include all the
qualities that pertain to their interest in the site; for example,
a target audience could be "information technology professionals
whose job responsibilities have included making hardware or
software purchasing decisions." If the site is intended to serve
more than one audience, testing should include representatives of
each user group.
[0029] When the audience descriptions are complete, test
participants who match those descriptions are recruited (step 204).
It is important that the participants have no more familiarity with
the company or organization the site represents than do the target
audience members.
[0030] Next, a test administrator creates several sets of paper or
poster board cards representing information for inclusion in the
Web site (see FIG. 3 for an example of a "page" card 300) (step
206). The information on each card should include a title and a
one-sentence summary of the contents of that page. The cards are
shuffled thoroughly to assure random arrangement within each set.
If users perceive any logical ordering in the cards as initially
presented, that ordering may influence the users' groupings.
[0031] Turning now to the test procedure, it is highly suggested
that each participant be tested in an individual session to assure
independence of grouping strategies (step 208). Although it may
seem economical to have several test participants arrange card sets
in a single session, the results of multiple-user sessions may be
less reliable than those of individual sessions for a couple of
reasons. In a multiple-participant situation, participants may
influence one another's number of card groups or sorting criteria.
Participants also may be reluctant to take as much time as they
need for careful sorting if they see that others have completed the
task. Because these influences can be subliminal, their effects
cannot be avoided through instructions to disregard other
participants.
[0032] Each participant is asked to arrange the cards into logical
groups (step 210). Card 300, illustrated in FIG. 3, is an example
os a sample page card for the card-sorting task. It should be
explained that the groups should contain topics that seem to that
participant to be related. An example instruction reads:
[0033] "Please arrange the cards into groups in a way that makes
sense to you. There are no right or wrong answers; we are
interested in what you perceive to be the most logical arrangement
of the cards."
[0034] When the participant is satisfied with the groupings, each
group of cards is bound together (step 212). The cards are bound in
such a way as to discourage the participant from moving cards from
one group to another. Cluster analysis assumes that participants
are making the groupings independently, without planning further
levels of categorization. The participant is then asked to arrange
the original groups into larger groups if any further logical
groupings are apparent (step 214). When the participant is
satisfied with the second grouping, or has stated that no further
grouping is logical beyond the first pass, each set of groups is
bound with a clip or rubber band (step 216).
[0035] As an option, one can solicit suggestions for names for the
larger groups (step 218). If suggestions for group names are
needed, supply self-adhesive note paper and ask participants to
label the groups they created. As discussed above, participants
should not be forewarned that they will be providing names for the
bundles. They should feel free to group the cards as their "gut"
requires, without concern for how to articulate or explain the
basis of the groupings.
[0036] The test procedure should be explained only incrementally
over the course of testing. The entire procedure should not be
explained to the participants at the beginning of the test;
explaining that they will be arranging topic cards into groups will
suffice. The cluster analysis below is designed to work on the
assumption that participants completed the first sorting without
planning any subsequent bundling of the groups, and both sorting
passes without concern for naming the groups.
[0037] Cluster analysis is rarely applied to card-sorting data,
probably due to the tedious procedures required for getting the
user data into, and interpreting the output of, currently available
statistical packages such as, for example, SAS.TM. or
Statistica.TM.. Both of these popular packages require converting
the raw user data (card groups) into matrices of either distance
scores or similarity scores. This conversion can take several hours
per test participant if performed by hand. The packages' output is
also difficult to manage. The packages produce tree diagrams that
illustrate the relationships users perceived between the cards, but
provide no assistance in visualizing the consequences of choosing
various criteria for grouping the pages.
[0038] Cluster analysis is not by its nature a definitive test to
determine which items belong together. It extracts from
card-sorting data the relative strength of perceived relationships
between pairs of items, allowing site designers to consider these
perceptions when organizing the site.
[0039] The diagrams indicate the strength of the perceived
relationships between pairs of pages by the relative distance from
the origin (0) of the nearest vertical line that connects the
pages' horizontal lines. To find the strength of the perceived
relationship between any two pages, trace a path from one of the
pages to the other, following the branches of the dendogram, and
taking the shortest possible path. The distance from 0 to the
outermost vertical line required by this path represents the
perceived degree of difference in meaning between the two pages.
The maximum distance, 1.00, indicates that no participant grouped
the two cards together; while the minimum distance, 0.00, means
that every participant grouped the two cards together in both
stages of the sorting procedure.
[0040] Referring now to FIG. 4, a diagram illustrating the
relationships between pairs of pages is depicted in accordance with
the present invention. The first sample pair is composed of the
pages labeled Aptiva 402 and Aptiva's ease of use 404. This pair is
connected by a vertical line 412 at approximately 0.22, indicating
that participants perceived these pages as being relatively closely
related. The other highlighted pair in FIG. 4 is Kona Desktop 406
and UI Fundamentals 408. The outermost vertical line 410 required
by the path between these two pages falls at 1.00, indicating that
participants never placed them in a common group. (A 1.00 in a
dissimilarity matrix corresponds to a 0.0 in a similarity
matrix.)
[0041] With reference now to FIG. 5, a diagram illustrating the
relationships between pairs of pages showing the major divisions of
the site is depicted in accordance with the present invention. The
major divisions of the site 502, 504, 506, and 508 (indicated in
FIG. 5 by shading changes) were obtained by drawing a vertical line
at the 0.925 hash mark, and grouping together any pages whose
connecting lines fall to the left of this point. This distance
threshold was chosen by experimenting until a reasonable number of
major divisions (in this example, four) resulted. Though setting
criteria post-hoc is usually frowned upon in statistical analysis,
this type of cluster analysis is an exception. It would be
impractical to establish cutoff values prior to seeing an output
diagram.
[0042] In FIG. 6, a second threshold has been established for the
minor divisions 510, 512, 514, 516, 518, 520, 522, 524, and 526
within the larger groups in FIG. 5. The minor divisions 510, 512,
514, 516, 518, 520, 522, 524, and 526 are distinguished again by
variations in shading. In this example, minor divisions 510 and 512
are part of major division 502; minor divisions 514, 516, and 518
are part of major division 504; minor divisions 520 and 522 are
part of major division 506; and minor divisions 524 and 526 are
part of major division 508. Again, a distance criterion was
established by observing the effects of various placements of the
threshold line until a suitable number of groups resulted.
[0043] Card-sorting tests and cluster analysis can help site
designers understand their target audience's expectations for site
content organization. These procedures provide a method for
quantifying the relationships users perceive between the content
pages of a site. They allow users' expectations to influence a
site's navigational structure. Site designers can use the results
to help determine a structure that their audiences will
understand.
[0044] Referring now to FIG. 7, a pictorial diagram illustrating a
graphical user interface for facilitating entry of data into a
cluster analysis program is depicted in accordance with the present
invention. The example shown discloses a method of data entry as
applied to card-sorting test data, but it will be recognized that
the present invention is applicable to any kind of data appropriate
for cluster analysis. Graphical user interface 700 is an example of
a graphical user interface which may be utilized in conjunction
with a cluster analysis program to facilitate entry of data into
the program. Such a cluster analysis program and graphical user
interface 700 may be implemented in a data processing system such
as, for example, data processing system 100.
[0045] Graphical user interface 700 includes a source card list
area 716, a participants area 722, a first sort area 714, and a
second sort area 712. Source card list area 716 allows entry,
display of, and direct manipulation access to all of the items to
be sorted. Source card list area 716 includes an import cards
button 726 that allows a user to import cards from a file outside
the cluster analysis program. Source card list area 716 also
includes a collection of edit buttons 720 that allow a user to add,
edit or delete a card from the source card list. Manila folder icon
718 indicates that the card name field is currently empty.
[0046] Participants area 722 allows entry and display of
participants' names and includes edit buttons 724 to allow a user
to add, edit, or delete a participant. First sort area 714 includes
a plurality of boxes 704 for storing card names that are dragged
and dropped from source card list 716. Each of the plurality of
boxes 704 is identified by a serial number 702. Second sort area
712 includes a first plurality of boxes 710 for second level
grouping names and a second plurality of boxes 708 for storing
serial numbers of first level groups which form the members of the
second level group. Each of the first plurality of boxes 710
corresponds to a distinct one of the second plurality of boxes 708
and also to a unique identifier 706 for second sort categories.
[0047] Referring now to FIG. 8, graphical user interface 700 is
depicted with entries to the source card list area 716 and
participants area 722.
[0048] Referring now to FIG. 9, graphical user interface 700 is
depicted in which several of the card entries for participant "Paul
Moody" in participant area 722 have been dragged to various ones of
the plurality of boxes 704. Each time a card name from source card
list 716 is dragged and dropped into a one of boxes 704, it
disappears from source card list 716 thus preventing the user from
inadvertently placing a card name into more than one of boxes 704.
Referring briefly to FIG. 8, the card name "Aptiva" appears at the
top of source card list 716. In FIG. 9, the card name "Aptiva" has
been moved to the one of boxes 704 identified by the serial number
"3." The user moves card names from source card list 716 into
various ones of boxes 704 as indicated by how the particular
participant highlighted in participants area 722 had previously
indicated the cards should be grouped. If second order grouping is
applicable for the particular situation, the user then selects a
serial number corresponding to one of boxes 704 and copies that
number into one of boxes 708 corresponding to a second order group.
This process continues until each of the card names in source card
list 716 has been moved to one of boxes 704 for each participant in
participant area 722.
[0049] In the depicted example, the card name "users" is in the
process of being moved from source card list 716 into the one of
boxes 704 identified by serial number "6". The card name
"principles" may be moved, as indicated by the arrow, into the one
of boxes 704 identified by serial number "5" corresponding to the
manner in which the highlighted participant "Paul Moody" in
participant area 722 grouped the cards. Also in the depicted
example in FIG. 9, the one of boxes 704 in first sort area 714
identified by serial number "7" may be copied, as indicated by the
arrow, into the one of boxes 708 in second sort area 712
corresponding to group "E" to correspond to the way the highlighted
participant, "Paul Moody," further grouped the first groups in
first sort area 714. Others of boxes 704 have previously been
copied into one of boxes 708. For example, the one of boxes 708
corresponding to Group B in second sort area 712 has had serial
numbers "2" and "3" from first sort area 714 copied into it. Thus,
the members of group B in second sort area 712 include all card
names placed in the one of boxes 704 identified by serial number
"2" and the one of boxes 704 identified by serial number "3."
[0050] Note that, as an option, the user can enter a name or
identification for each group in second sort area 712. These names
or identifications are entered into ones of boxes 710. Also note
that particular ones of boxes 704, 708, and 710 that are not needed
for a particular cluster analysis remain empty.
[0051] Once the sorted cards are entered for each user, the cluster
analysis program may then compute a similarity matrix and a
distance matrix. Thus, the user is freed from the tedious and
complex task of computing the matrices by hand. Because of the drag
and drop method of moving card names into a particular grouping box
704 that removes the name from source card list area 716 as it is
moved into first sort area 714, the potential for mistakenly
placing a card name in more than one group is removed:
[0052] Referring now to FIG. 10, a flowchart illustrating a method
of allowing data entry into a cluster analysis program using a
graphical user interface is depicted in accordance with the present
invention. First, a card sort with multiple participants must be
performed as described above (step 1002). Next, the test proctor
must enter the name of each participant into the participants area
722 of the graphical user interface 700 (step 1004). The names of
the cards that were used in the card sort exercise must be entered
or imported into the source card list 616 graphical user interface
700 (step 1006). The test proctor then selects the first
participant from the participant list (step 1008), such as, for
example, by highlighting the participants name using a mouse, and
moves the card names from the source card list area 716 to one of
the entry blocks 704 and then, if further grouping has been made,
select and copy entry block reference numbers 602 to the ones of
blocks 608 that correspond to how the participant further grouped
the cards (step 1010). The card names are moved into the entry
blocks 704 that correspond to the way in which the current
participant grouped the cards in the card sort exercise. Once all
the card names have been moved into the appropriate entry blocks
704 for the present participant, then it must be determined if
there is another participant whose card groupings have not been
entered (step 1012). If there is another participant, then the next
participant is selected (step 1014) and the card names are moved
from source card list 716 to entry blocks 704 in accordance with
the manner in which this new participant grouped the cards (step
1010). If there are no more participants, then the process of data
entry ends.
[0053] Referring now to FIG. 11, a flowchart illustrating an
exemplary method in a data processing system for allowing entry of
card sorting results is depicted in accordance with the present
invention. After a user opens the cluster analysis program, the
program waits for user input (step 1102). Once user input has been
received, the cluster analysis program determines whether the user
has requested to end the session (step 1104). If the user has
requested to end the session, then the program is closed (step
1118).
[0054] If the user has not requested to end the program, then the
cluster analysis program determines whether the user has selected a
participant name from participants area 722 (step 1106). If no
participant name has been selected, then the program continues to
wait for user input (step 1102). If a participant name has been
selected, then the program determines if a card name from the
source card list 716 has been selected (step 1108). If a card name
has been selected from the source card list 716, the program
determines whether the user has dragged and dropped the card name
over one of entry area blocks 704 in the first sort area 714 (step
1110). If the user has not dragged and dropped the card name over
one of the entry blocks 704, then the program continues to wait for
further use input (step 1102). If the user has dragged and dropped
the card name over an entry area 704, then the card name if removed
from source card list area 716 and is placed into the user
specified one of entry blocks 704 (step 1112) and the program waits
for further user input (step 1102).
[0055] If the user has not selected a card name from the source
card list, the program determines whether the user has selected,
moved, and dropped an entry block reference number 702 into one of
blocks 708 in the second sort area 712 (step 1114). If a user has
not selected, moved, and dropped an entry block reference number
702 into the second sort area 712, then the program continues to
wait for further user input (step 1102). If the user has selected,
moved, and dropped an entry block reference number 702 into the
second sort area 712, then the number of the entry block reference
number 702 that was moved is entered into the specific one of
blocks 708 chosen by the user (step 1116), at which point the
program continues to wait for further user input (step 1102).
[0056] It is important to note that while the present invention has
been described in the context of a fully functioning data
processing system, those of ordinary skill in the art will
appreciate that the processes of the present invention are capable
of being distributed in a form of a computer readable medium of
instructions and a variety of forms and that the present invention
applies equally regardless of the particular type of signal bearing
media actually used to carry out the distribution. Examples of
computer readable media include recordable-type media such a floppy
disc, a hard disk drive, a RAM, and CD-ROMs and transmission-type
media such as digital and analog communications links.
[0057] The description of the present invention has been presented
for purposes of illustration and description, but is not intended
to be exhaustive or limited to the invention in the form disclosed.
Many modifications and variations will be apparent to those of
ordinary skill in the art. The embodiment was chosen and described
in order to best explain the principles of the invention the
practical application and to enable others of ordinary skill in the
art to understand the invention for various embodiments with
various modifications as are suited to the particular use
contemplated.
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