a qualitative investigation of the impact of graphical user interface (gui) of color palettes on...

7/28/2019 A Qualitative Investigation of the Impact of Graphical User Interface (GUI) of Color Palettes on Perception

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A Qualitative Investigation of the Impact of Graphical User Interface (GUI) of Color Palettes on Perception

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Graphical User Interface, Qualitative, Color, RGB,

The goal of this research is to foster understanding of how GUIs impact the process used to carry outdesign tasks and perceptions associated with its use. Quantitative and qualitative collections andanalyses methods were employed in the study. Two distinct GUI, namely the traditional RGB color paletteand the experimental Hue color palette were used and served as basis for comparison. A qualitativeanalyses was made of four participants’ actional strategies and perceptions in association with a series of fundamental color design tasks, ranging from color matching to color composition design. Assertions werecreated in associated with participants’ use of GUI systems. The data suggests that the GUI of the RGBand Hue palettes impacted the participants’ thinking processes related to design decisions in various ways,and consequently influenced their perceptions associated with the use of those palettes. As the datatriangulation suggested, those perceptions were not always accurate.

Topic: Information systems and communication / digital media

Anais do

4° Congresso Internacional de Design daInformação / 3° InfoDesign Brasil / 4° CongicCarla G. Spinillo, Priscila L. Farias & Romero Tori (orgs.)Sociedade Brasileira de Design da Informação – SBDIRio de Janeiro | Brazil | 2009ISBN

Proceedings of the

4th Information Design InternationalConference/ 3rd InfoDesign Brazil / 3rd CongicCarla G. Spinillo, Priscila L. Farias & Romero Tori (orgs.)Sociedade Brasileira de Design da Informação – SBDIRio de Janeiro | Brazil | 2009ISBN



C. Spinillo, P. Farias & R. Tori | Guidelines for submitting papers | 2

2 Introduction

Taking into consideration that graphical user interface (GUI) are visual representations (or symbolic systems) part of an information systems, or strategy, depending on the task, it can beargued that they can either facilitate or complicate the process. The relationship between

representation and interpretation is articulated by Norman (1990). If one adopts the notion that“artifacts” carry visual messages, as advocated by Norman, it may be argued that when visualrepresentations are poorly designed, they lead to ineffective use by the end-user consequentlyaffecting not only its practical use but also its perception. D. Norman argues that essentiallypoorly designed artifacts “trap the user and thwart the normal process of interpretation andunderstanding” (p. 2). Most GUI designers need to take into consideration the level of accessibility of conceptual models imparted in their designs (Mullet & Sano, 1995; D. Norman,1990). It is only when the designer’s and user’s conceptual models are compatible that thedesign reaches its higher potential of effective use while simultaneously shaping perceptions.

There has been a lack of dialog between designers and computer engineers who havehistorically developed and implemented interface design computer systems (Laurel, 1990). For example, the advent of the Internet prompted the development of color look-up tables that wereincorporated in standard browsers. Weinman (2004) expresses her concerns with that type of palette: “The browser-safe palette was developed by programmers with no design sense(…).That's because a designer would have never picked these colors” (p.3). She believes there is aclear lack of sensitivity to color perception; the colors were chosen mathematically. It is this lackof dialog that produces interfaces without a clear understanding of their impact on design tasks.Expecting that people adapt to poorly designed interfaces is not effective design practice.

Based on this notion, and inspired by a previous study (Schwarz et al., 1987), Douglas andKirkpatrick (1999) tested two methods of visual representations that they termed “low” and “highvisual feedback interfaces” and their impact on speed and accuracy in performing color-relatedtasks on the computer for both RGB and HSV color models. Speed was related to the amountof time needed to perform a task, and accuracy to the level of precision in matching colorsbased on predefined parameters. Their study was guided by the hypothesis that humanperformance on the tasks described in the study is affected more by the visual feedback method

employed in the GUI than by the color model (e.g., RGB, HSV) of choice. They argue, “Visualfeedback and design of the interface may be a more important factor in improving the usabilityof a color selection interface than the particular color model used” (Douglas & Kirkpatrick, 1999,p. 96). Their findings point out that the tests conducted on high and low interface approaches,as defined in the paper, did not have major impact on the speed when participants tried toperform color matching tasks of both RGB and HSV models. On the other hand, theydiscovered that accuracy was greatly influenced by visual feedback integrated in the GUI.

While it is critical to understand the impact that the attributes of GUI (e.g., color palettes) mayhave on thinking processes and the outcome of those processes, it may be beneficial tounderstand how user’ perceptions of those tools are shaped by those attributes. The lack of methods to explore the attributes in GUI that shape user perception contributes to the lack of substantial knowledge that we have “about the factors that underlie motivation, enjoyment, and

satisfaction” (Norman, 1993, p. 32). Therefore, understanding of perceptions may also guidethe design and development of GUI systems.

2 Methodology

This section discusses the materials (e.g., color palettes), procedures, design, and theoreticalframeworks used to conduct the study and to gain insight into the nature of the process andperceptions associated with media attributes, more specifically the symbol systems of two digitalcolor palettes (i.e., RGB and Hue palette).

Anais do 4° Congresso Internacional de Design da Informação / 3° InfoDesign Brasil / 4° CongicProceedings of the 4th Information Design International Conference/ 3rd InfoDesign Brazil / 3rd Congic




Theoretical Framework

Data collection and analysis

This study takes a qualitative approach (Bogdan & Biklen, 1982; Erickson, 1986; Goetz &LeCompte, 1984; Kuniavsky, 2003; Patton, 2002) to investigate the impact of two differentinformation systems in the context of color selection and design. The investigation wasconducted while taking into consideration issues related to color palette configuration and visual

attributes’ impact on color design decisions, thinking processes, and cultivation of thinking skills(Salomon, 1994). In addition, this study also investigated perceptions and views of participants’experiences in association with those palettes as related to color design tasks and how their experiences influence choice when they are asked to perform complex color design tasks.

The research focused on an in-depth study of a microsystem (Savenye & Robinson, 2004); inthe context of this study, this means that the researcher selected six predefined tasks of different cognitive levels that are representative of a wide range of skills central to color designprocesses.

Nonparticipant observation data collection procedures were employed (Goetz & LeCompte,1984)..Video recording, digital screen captures, and questionnaires used in the study are toolscommonly used in nonparticipant observation methods and, as such, were integrated in thisstudy as a means to collect information in an unobtrusive way in order to provide an additional

dimension to the data (e.g., in addition to semistructured interview). Semistructured interviewswere also used at the very end of the data collection process for clarifications of meanings andactions (Patton, 2002; Savenye & Robinson, 2004).

Within- and across-case analysis methods based on purposeful sampling provided anopportunity for in-depth investigation of the phenomena being studied (Patton, 2002) in thetarget population (e.g., art and design students). This was coupled with task analysis methods(Kuniavsky, 2003). The methods used permitted a search for patterns in the data.

Another dimension added to the study was to triangulate (Isaac & Michael, 1995; Patton, 2002)data sources to further substantiate the findings. For example, interviews were triangulated withpatterns in the clicks of the computer mouse to verify and confirm findings. Finally, projectfindings were correlated with theoretical orientations or other findings (Douglas & Kirkpatrick,1999; D. Norman, 1990; Schwarz, et al., 1987) in the literature in order to answer the researchquestions. Triangulation was a critical method used in order to confirm or strengthen findings.

Participants

Four participants were selected based on a survey that was used to determine their qualifications to participate in the study (e.g., overall knowledge of color design process). Thisresearch focused on the use of the palette in an academic setting in the United States(undergraduate students). Participants were students of art and design in the junior of sophomore years. A concern dealt with the number of participants employed in the studies. Theauthor favored a smaller sample size in order to foster in-depth analysis of processes andperceptions. This approach is supported by the literature in studies dealing with color interfacing systems (Douglas and Kirkpatrick, 1999). Patton (2002) points out that “There are norules for sample size in qualitative inquiry” (p. 244). He adds that “The validity, meaningfulness,

and insights generated from qualitative inquiry have more to do with the information richness of the case selected and the observational/analytical capability of the researcher than with samplesize” (p. 224).

Color Palettes

For the purpose of understanding the impact of GUI as an information system has onperception, this study focuses on investigating the impact that two distinct swatch-based color palette configurations, or GUI, and their inherent attributes have on participants’ abilities toperform tasks and their perceptions associated with its use. While the GUI systems used for thisinvestigation are specific (i.e.,color palettes), it is assumed that the findings from this research

may inform and or foster methodologically and theoretically the investigation of other relatedresearches.





Colors produced on the computer screen are, in one way or another, based on the structure of the RGB color model. The RGB color model is a scientific method of generating color on thecomputer screen; however, popular ways to access colors on the computer screen are via color palettes and color pickers.

Two color palettes employed in the study: the Traditional RGB Palette and the ExperimentalHue Palette. The palettes were named by the author solely for the purpose of identification.Both palettes are based on digital color and use RGB color specifications. The colors in both

palettes are identical; the only difference is their GUI design which are representative of twosystems of representations or conceptual models (D. Norman, 1990, 1993; Salomon, 1994).The palettes represent different symbol systems but share similar functions in the study. TheRGB palette is widely found on the market, whereas the Hue palette was developedindependently by the researcher (Bendito, 2005).

Traditional RGB Palette

Figure 1 shows the traditional RGB color palette, which is based on six cuts of the RGB color cube. In this palette colors are displayed based on blending structures. Each of the six paletteshas four different colors on each corner except the first one (top left), which has black in one of the corners, and the last one (bottom right), which has white in one of the corners.

Figure 1: Traditional RGB color palette

The RGB palette is available in many computer graphics software and is used to be the defaultpalette in programs such as FreeHand®; Flash®, and Dreamweaver®. It is pervasively used inart and design educational programs and by professionals. The RGB palette visual organization

has been criticized (Weinman & Heavin, 1997) and widely reinterpreted, such as the VisiBonecolor palette and Lynda Weinman’s hue and value (Weinman, 2004). Therefore, it wasselected because of its controversial nature.

Experimental RGB Hue Palette

The experimental RGB Hue Palette is an attempt to provide access to computer colors basedon value and intensity relationships for each individual hue family (e.g.,reds, yellows, etc.). Thiscontrasts with the configuration of the RGB palette, which is solely based on six parallel cuts of the RGB cube and colors seem to blend together.

As Davis (2000) points out, “The color solids of Ostwald and Munsell provide systems withwhich one can understand and predict color phenomena” (p. 32). It is based on this notion of understanding that the experimental Hue color palette was developed. As opposed to the

traditional RGB Color Palette, in the experimental Hue Color Palette, color families areorganized individually.

On the other hand, even though the experimental RGB Hue Color Palette has the same color set as in the Traditional Hue Color Palette, its layout and visual access method greatly differ from each other, providing a basis for contrast (Bendito, 2005) in terms of their GUI attributes.

From a visual organization standpoint, the experimental RGB Hue Palette allows each individualcolor family (hue) to be systematically compartmentalized for access during the design decisionprocess. This approaches of mapping color structures was influenced by the works of color theorists focusing on hue organizations (Ostwald & Birren, 1987, Itten, 1968, Munsell, 1915)and guided the development of the experimental Hue palette as shown in Figure 2. A fulltechnical description of the experimental palette can be found in Bendito (2005).





Figure 2: Screen capture showing detail of experimental Hue palette.

Materials

The materials used in this study were (1) the traditional RGB color palette and (2) theexperimental Hue color palette. Access to the RGB and Hue palettes during the tasks was fromcustom software. Both the RGB and Hue palettes use the same set of colors; however, eachpalette organizes the colors in different ways (i.e., via different conceptual models).

Instrumentation

A wide range of data collection procedures was involved in the study. This approach allowed





the investigator to conduct an in-depth analysis of the phenomena being observed and toconduct triangulation. Below is a list and description of the instruments used in this study:

Computer station : A dedicated computer station was devoted to the study.

Custom software : The custom software provided access to the RGB and Hue palettes. All tasks were performed in the software. For the color matching task, the softwareautomatically kept track of number of attempts (or clicks) and number of accurate and

inaccurate clicks. For the other tasks, third-party software recorded participants’ activity(see next instrument).

Digital built-in video capture : Digital video capture built into the computer recordedparticipants’ process while completing the tasks. This was performed by usingCamtasia®.

External video recording : Video was recorded (in digital format) of each participantduring the color tasks procedures.

Participants’ collected works : Works produced by the students during the tasks weresaved in the computers via Camtasia® software.

Written Posttasks survey (digital) : Students wrote answers to survey questionsimmediately after completing each task in the RGB and Hue palettes.

Interview questions protocol: A follow-up interview, based on an interview protocol, wasconducted to clarify actions and meanings.

Field notes : Contextual notes were taken during data collection of students’ overallbehavior.

Participants handbook : The handbook assured that all participants had access to thesame set of instructions to perform and record the tasks during data collection.

Preliminary instructional slide show : A predefined slide show set up in PowerPointassured that each participant had access to the same content during preliminaryinstructional activity. The content included color terminology, software demo andpractice, introduction to tasks 1-5 using different color sets, color, and meaning.

NVivo: QSR’s NVivo® software : used to assist data coding and transcripts searching.

Setting

The study took place in the visual communications design classroom located in the artdepartment at a large midwestern university. This was the same classroom where participantsnormally attended their design classes. TFigure 4 shows the classroom where data collectiontook place (left) and a screen close-up (right) of the desktop setup showing the custom softwareand Camtasia®. The flat-screen monitor was color calibrated with the Pantone ColorVisionSpyder2™ system by IT staff before data collection procedures took place.

Figure 3: Setting (left) with dedicated workstation in the foreground and screen close-up (right) of desktop setup.





Color Design Tasks and Procedures

Four participants worked at separate times that did not overlap. They were scheduled in a blockof time in the morning or afternoon. Prior to performing the tasks, preliminary instruction tookplace. After a 15 min break participants were asked to follow directions in the ParticipantsHandbook in order to complete the tasks.

Participants completed six tasks, grouped into four categories. Each task was performed twice

(with the exception of Task 6), each time in a different palette (RGB and Hue palettes). Table 5shows each task (1-6) and the order in which of the color palettes were utilized in the study.Students saved each project and completed a written survey after the end of each task.

Table 1: Order of tasks performed by the students

Tasks Timeline

Participants 1 and 2 Participants 3 and 4

Task 1 RGB Palette Hue Palette

Hue Palette RGB Palette

Task 2 RGB Palette Hue PaletteHue Palette RGB Palette







Task 6 RGB or Hue Palette RGB or Hue Palette

Following completion of all the tasks (1-6), participants were asked to replay the video and to

specifically describe “each step” they took during Task 1 and Task 6. This was also followed bya 15-minute break.

After the break and following the completion of the experimental tasks, an interview wasconducted with each participant using an interview protocol. Questions were asked specificallyand systematically regarding each task (e.g., importance of color matching). Finally, questionswere asked regarding color palette preference.

Figure 4 shows a screen capture of the software used in the study for Task 6. Thecheckerboard (upper left) and palette areas (bottom) were replaced with the appropriate taskinstruments (Tasks 1 through 5) and color palettes (RGB or Hue palettes).

Figure 4: Screen capture of the software used in the study.





Description of tasks and the Issues they address

Six color design tasks were employed that ranged from strictly mechanical to conceptual color design skills. Therefore, the tasks that participants performed ranged from mechanical (e.g.,color mathing) to more complex and conceptual (e.g., create a color palette and produce adesign with it):

Task 1: strictly mechanical, is derivative of other published color matching tasks in the

literature (Douglas & Kirkpatrick, 1999; Schwarz, et al., 1987). Tasks 2 and 3: based on Albers (1963) and explore foundational problem-solving skills.

Task 4: developed by the author, expands the notion of color matching to full color schemes─that is, the student has to find groups of colors as opposed to individualcolors as required in Task 1.

Task 5: based on color skills training dealing with designs based on color properties byMiller (1997).

Task 6: investigates the most complex of the color problems and explores issues of color image or communication.

Task 6 is a critical experiment and was used as a springboard to investigate the issue of choice

and perception. Note that Tasks 1 through 5 were building blocks to Task 6, for they gaveparticipants the opportunity to experience an increasing level of complexity related to color design processes.

Data Analysis

The research used a case study approach while taking into consideration within-case and cross-case analysis (Patton, 2002) of participants’ individual tasks analysis results in order to generatea set of descriptors that derived coding categories to reveal commonalities and differences(Bogdan & Biklen, 1982). During Analytic Induction key assertions were tested against the data

(Erickson, 1986). Data triangulation was constantly performed to either confirm or further question the ongoing findings (Bogdan & Biklen, 1982; Erickson, 1986; Patton, 2002). For example, built-in video capture and posttask survey findings were compared with interview datato substantiate assertions.

An adapted version of Kuniavsky’s task analysis approach was employed (Kuniavsky, 2003).Task analysis was used to search for actional patterns and to pinpoint strategies thatparticipants used to perform the tasks. Task analysis is appropriate in two conditions: the goalis well established and the researcher wants to know how users are reaching that goal by usinga tool.

Derivative diagrams based on the task analysis were created to investigate the differentpatterns in the course of actions. At this point the patterns found in the data were examinedbased on the theoretical framework proposed by Norman (1990) regarding the predictability

impact on a user’s action as a consequence of conceptual models represented in interfacingsystems. Norman argues that when the model (of a system) presented to an end-user isinadequate, users have difficulties using the system. For example, based on this approach, itwas possible to determine which palette’s conceptual model better facilitates color matchingtasks.

The data collected via written survey and interviews (both with open-ended questions) providedinformation regarding the participants’ perceptions of the tasks and overall experience andquestioned the rationale behind the palette selected to perform the final task (task 6).Interviews and surveys brought into QSR’s NVivo to start the coding process and were largelyused during during data triangulation. From the participants’ responses coding categories werederived. Their responses, it was found, either followed coded patterns or not. Participants’responses were also triangulated with field notes and videos, which added another dimension tothe analysis process.





In summary, in order to answer the research questions, data analysis sought to identify anddiscuss patterns in the data as well as account for irregularities in the patterns.

Findings

The data suggests that the GUI of the RGB and Hue palettes impacted the participants’ thinking

processes related to design decisions in various ways, and consequently influenced their perceptions associated with the use of those palettes. As the data triangulation suggested,those perceptions were not always accurate.

Ease of Use

Assertion 1: GUI, in the context of computer-based color palettes, impacted differently the ability to complete color matching and color selection tasks with respect to the amounts of mental elaborations that they allowed or required.

A compilation of the number of clicks recorded via Camptasia software performed by theparticipants shows that there were more observable attempts (clicks) in the traditional RGBpalette than in the experimental HUE palette during color matching tasks (Table 2).

Table 2: For three participants, it was easier to perform color matching in the experimental Hue Color Palette as shown in the pattern of clicks.

Participants Palettes

RGB (# of Clicks) HUE (# of Clicks)

P1 11 7

P2 21 8

P3 7 11

P4 26 16

Total 65 42

The data reveal that three out of the four participants show a cumulative fewer number of clicks(42) to perform the same tasks in the Hue palette versus the RGB palette (65). As the Table 2shows it took much less clicks to perform color matching in the experimental RGB Hue color palette.

During data triangulation Participant 2’s comments of his video performing color matching, for example, illustrate a possible type of experience when performing a prime attempt:

Yeah, got it—first try.

This [i.e., Hue palette] was the easiest one . . . like—I mean—I got it the first try there. It was just a loteasier to see. I mean, you don’t have—like—red right next to the one that you’re trying to find. So, it’sa lot easier to see . . . what color you need.

The quotes above suggest that participants selected an identical color to the target color using a

single correct click. The data suggest that the attribute that mostly impacted performing the taskwas its color arrangement:

“[in the Hue palette] you don’t have—like—red right next to the one that you’re trying to find.”

Predictability

Assertion 2: GUI, in the context of computer-based color palettes, impacted one’s ability to predict the outcome of his/her color matching and color selection decisions. The Hue palettewas the most predictable of the systems.

The concept of predictability adopted in this study is adapted from Norman’s (1990) conceptualmodel approach for designed systems. Norman argues that designed artifacts should simplifythe structure of a task. One of the many ways that this can be accomplished is by assuring thatthe user can comprehend the functionality of the designed artifact and be able to consistentlypredict the effect of their actions when using it.





A summary of the level of predictability categories and subcategories coded during the analysisand the outcome result for each style of attempt are provided in Table 3.

Table 3: Categorization of Levels of Predictability and example of associated quotes.

Continuum-Based Strategies

Category Action Representative Examples from Interview Data Outcome Accuracy

Higher LevelPredictableOutcome

Prime Attempt

“I think this one was probably . . . yeah, got it—first try.” (P2)

Yes

Double-Check

“…I just had to make sure. Then I just clickedon another one just to be sure and then I wassure and then I went back.” (P3)

Yes

Mid-LevelPredictableOutcome

Fine-Tune “…if I wasn’t right the first time, I would go backand look at different shades of the samevalues.” (P2)

Yes

Low-LevelPredictableOutcome

MultipleSteps

Not directly described in the interview. Evidentin the video (Camtasia) and through datatriangulation.

Yes

SuccessfulGuess

“First I would look through the palette and try tosee with my eye which color closely resembledit and then I would guess.” (P1)

Yes

Give Up “I think this is the only one that I didn’t finish, justbecause I gave up and couldn’t find it.” (P2)

No

The data suggest that the Hue palette’s symbol system was the most “predictable” because itincreased the participants’ chance to perform the two Higher Level Predictable Outcome styles,namely prime attempt and double-check (see Table 4).

Table 4: Amount Higher Level Predictable Outcome (HLPO) by palette

Tendency Toward HLPO Attempt by Palette

Participant RGB Palette Hue Palette

P14 5

P2 -- 3

P3 5 5

P4 -- 2

Distorted Perception of Time

Assertion 3: GUI, in the context of computer-based color palettes, impacts one’s judgment inregards to amount of time spent on task. Perception of time will be mostly distorted by arrangement of visual elements and is related to how easy or hard one perceives the system tobe.

There seems to be a contradiction in the data in relationship to reported perception of time





versus actual time spent on a task. When asked why they chose the Hue palette to completethe final task, Participants 2, 3, and 4 reported directly or indirectly that the Hue palette wasmore “time efficient.” When comparing their statements with the time actually spent for eachtask, the data show that only Participant 2 consistently used “less time” to perform the tasks(see Table 5) in the experimental Hue Palette. Everybody else had mixed results. Therefore,the perception of Participant 3 and Participant 4 that the Hue palette is “time efficient” is notsupported by the analysis.

When participants said that a palette was time efficient, they may have actually been alluding toease of use. In fact, the data showed that the Hue palette demanded less time only for color matching tasks (i.e., the lower lever color tasks).

Table 5: Pattern Regularities reveals that only Participant 2 consistently used “less time” to perform thetasks (see Table 5) in the experimental Hue Palette.

P1 P2 P3 P4

Categories RGB Hue RGB Hue RGB Hue RGB Hue

Task 1 - Color Matching 01:25 01:12 03:34 00:56 01:35 01:54 02:07 01:57

Task 2 - Color Transp. 02:13 04:07 03:10 02:59 05:44 03:20 00:26 00:35

Task 3 - Color Interaction 01:49 03:39 02:46 01:32 01:57 03:17 00:45 00:55

Task 4 - Color Interaction 02:42 02:32 04:18 03:11 03:11 02:48 04:05* 03:16

Task 5 - Color Properties 03:06 03:53 03:46 03:05 01:20 01:07 01:19 01:52

Color Palette of Choice

Assertion 3: In the context of computer-based color palettes,a GUI perceived easy of use, the

perception of time spent of task in association with the GUi, and positive or negativeassociations with the experience of using the palette are some of the most impactful featureson choice of one color palette versus another.

One of the most common response types given by the participants in the written and oralinterview reflected on their overall experience. These statements summarize mostlyparticipants’ perceptions of the experience in association with the use of the GUI.

The data suggest that participants’ rationale for choosing the Hue palette relate to their overallexperience and perceptions. These experiences and perceptions were mostly homogeneous, asevidenced in the regularities in the checkerboard pattern shown in Table 6. This indicates thatthere are overall “agreements” among participants regarding their experiences, as suggested bytheir comments both in the survey and interview data.

Table 6: Overall experience: pattern regularities in the data

P1 P2 P3 P4

RGB Hue RGB Hue RGB Hue RGB Hue

Overall Experience

Easier to use(general)

- x - x - x - x

Harder to use(general)

x - x - x - x -

Efficient Use of

Time

x - - x - x - x





TimeConsuming

- x x - x - x -

PositiveCharacterization

x x - x - x - x

NegativeCharacterization

x - x - x - x -

Ease of use

The data show that, in general terms, one of the rationales for selecting the Hue palette for thefinal task was that participants perceived the Hue palette to be easier to use. Terms or statements they used to described this decision-making rationale included: “I thought it waseasiest to use,” “I had the easiest time with it,” “easier to work with in my opinion,” “easier todistinguish [color].”

Perceived time efficiency

As previously discussed the experimental Hue palette was perceived to be more time efficientthan the RGB palette. For example, Participant 2 illustrated his time-based rationale for selecting the Hue palette: “One of them [tasks] was probably two minutes and then when I usedthe Hue palette it only took like thirty seconds or something. It was just a lot quicker to find thecolor that I wanted to use” (emphasis added). He also mentioned, “I was able to create thechange [to make one color look like two] with both palettes, but it was much easier and faster touse the Hue palette.”

Positive vs negative characterizations

all participants referred to emotional aspects of their experiences in both Hue and RGB palettes.These emotional aspects were also used to explicate or suggest participants’ rationale for picking the Hue palette to complete the final task. both palettes triggered or cultivated emotionalresponses in the participants, and those responses were associated with behavior or specificfeatures afforded by the palettes. Furthermore, the pattern shows regularity. The Hue palettewas afforded the highest amount of positive characterization.

The data showed that positive negative characterizations were mostly subjective statementsand were occasionally based on process descriptions. The following excerpts from Participant4’s interview data show participants associating subjective characterizations (e.g.,“comfortable”) with more concrete associations (e.g., less “searching”) reflected by hisexperiences or palette features (underlines are my emphases):

INTERVIEWER: [in the survey]… you’re saying you “had the easiest time with it”… what does it feellike to have this “easiest time”?

PARTICIPANT 4: It’s more comfortable [characterization], you know. I feel like I can make a better

decision without as much searching [direct association]. And I mean it just turns into a more enjoyable[characterization] experience in making my color choice if I feel confident that I’m finally going in theright path [direct association]. If I’m thinking something about a color and looking for a certaincharacteristic [direct association], I found that I felt like I could be more confident and comfortable[characterizations] with the Hue palette. (emphasis added)

When asked how the RGB palette impacted “going in the right path,” the participant responded:

PARTICIPANT 4: Well, I wouldn’t . . . I’d be less comfortable and more frustrated [characterizations] if Icouldn’t find a color as easily [direct associations] as I would have with the Hue palette; however, Imean it’s, uh . . . it would just be a . . . I think it would take longer [direct associations]. I think it wouldbe more difficult to find what I’m looking for [direct association]. (emphasis added).





Conclusion

Rigor was applied in the analysis of the data in order to achieve internal validity, or credibility (Guba &Lincoln, 1989). A strategy used to achieve this validity was to ensure that findings were triangulatedusing multiple data sources. For example, the analysis in this study identified contradictory findingsregarding perceptions and actuals,

These research findings may eventually facilitate informed decisions regarding GUI of color palette and

its appropriateness in order to conduct color design tasks. Gagné, Briggs, & Wager (1992) providesome key questions that should be answered with the purpose of making appropriate media selectionfor instructional purpose. They say that an important aspect of teaching with technology is the onerelated to “affective impact” of the media. The data showed that all participants also related to symbolsystems on an affective level. The findings can help, for example, educators to better understand theemotional impact that the experience afforded by a GUI may have on learners.

The findings here discussed contributes to previous research by suggesting that a system's conceptualmodel affects predictability of task outcome (Norman, 1990). Salomon argues that “processingburdens” (Salomon, 1994, p. 222) are impacted differently by the attributes of media. Both D. Normanand Salomon acknowledge that visual representations are not neutral and affect our cognitive abilities.The findings here presented support such notions.

This study was able to investigate issues related to perception influencing the color palette of choicewhen performing a range of color design tasks. Based on the findings, the following recommendationsare made:

In order to generate guidelines for color palette design, an increased number of participantscould be used, thus generating a more extensive corpus for the purpose of analysis andconsequently enhancing the validity of future related studies.

This study was conducted with art and design students who have had prior training in color design. Another study could investigate the nature of the processes and perceptions across arange of students’ levels of expertise.

In this study, the quest for new knowledge related to GUI in the context of color design tasks waspursued. Similar framework is can be used to investigate other types of GUIs, consequentlystrengthening the body of knowledge of one of the most ubiquitous methods of information access andproduction.

References

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Bendito, P. (2005, March). RGB colour palette based on hue relationships. P roceedings of the10th Congress of the International Colour Association, AIC Color, (Part 2), Granada, Spain.

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