Integrating Adaptation and HCI Concepts to Support Usability

in User Interfaces

A Rule-based Approach

Luisa Fernanda Barrera, Angela Carrillo-Ramos, Leonardo Florez-Valencia,

Jaime Pavlich-Mariscal and Nadia Alejandra Mejia-Molina

Departamento de Ingeniería de Sistemas, Pontificia Universidad Javeriana, Bogotá, Colombia

Keywords: User Interfaces, Adaptation, Usability, HCI.

Abstract: A common problem in information systems development is to provide support for adaptation, to

automatically adjust their services to different users and contexts. User Interfaces (UI) are required to adapt

to those contexts and to satisfy specific criteria and standards to guarantee usability. Several methods have

been created to ensure a degree of usability in UI. However, these methods focus mainly in the design stage

of the development process. The benefits of these methods may be lost during execution time, since they do

not address the necessity to dynamically adapt the interfaces both to context and users. To address this issue

it is necessary to integrate User Interface Design with Adaptation, to ensure that UI usability is preserved at

the execution time, for different users and contexts. This paper proposes the framework Tukuchiy, a rule-

based system that dynamically generates Adaptative User Interfaces, based in HCI precepts. This guarantees

their usability during execution time, while taking into account user preferences and context. This paper

focused in the rule-based system of Tukuchiy. That rule system includes usability criteria commonly used

for web pages, which were mapped to a desktop application.

1 INTRODUCTION

When users interact through a computational system,

they do it through a User Interface (UI). An

adequate user interface design has become a very

important aspect in software development (Stone et

al., 2005). This problem is studied by two areas:

HCI and Adaptation. Human-Computer Interaction

(HCI) is a discipline that utilizes ideas from

Psychology, Ergonomics, and other disciplines, to

improve usability of user interfaces and provide

better interaction between users and systems.

Adaptation considers the heterogeneity of users and

the context in which they utilize computers and

requires that UI could be easily adapted to perform

various tasks.

User interface design in HCI is commonly

performed at the design stage in software

development, but some usability characteristics

defined at the design stage are lost during execution

time. Adaptation, however, does not prescribe ways

to improve usability of information systems. To

address this issue, previous work of the authors

proposed Runa-Kamachiy (Barrera et al., 2013a), a

model to integrate HCI and Adaptation concepts, to

improve the interaction between user and Adaptative

systems, and improve usability. To validate the

Runa-Kamachiy model, a framework, called

Tukuchiy (Barrera et al., 2013c) was created.

Tukuchiy realizes Runa-Kamachiy as an

infrastructure to generate dynamic user interfaces.

Two prototypes were created to validate the model

in two application areas: Idukay (Barrera et al.,

2013c) for education and Midiku for clinic

radiology.

This paper describes a rule-based system utilized

by Tukuchiy to dynamically adapt user interfaces,

and the way Adaptation concepts can be utilized to

improve usability of user interfaces.

The remainder of this paper is organized as

follows. Section 2 explains basic concepts required

to understand Tukuchiy. Section 3 reviews related

work. Section 4 describes Tukuchiy and the way it

addresses the Nielsen criteria. Section 5 details

Tukuchiy's rule-based system for UI generation and

its application in the Midiku prototype. Section 6

describes the validation of the prototype. Section 7

concludes and describes future work.

Barrera L., Carrillo-Ramos A., Florez-Valencia L., Pavlich-Mariscal J. and Mejia-Molina N..

Integrating Adaptation and HCI Concepts to Support Usability in User Interfaces - A Rule-based Approach.

DOI: 10.5220/0004857400820090

In Proceedings of the 10th International Conference on Web Information Systems and Technologies (WEBIST-2014), pages 82-90

ISBN: 978-989-758-024-6

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

2 BACKGROUND

This section describes background concepts required

to understand Tukuchiy.

First HCI concept that we use is the “Five User

Interface Laws”. Hale et al. (Hale, 2011) indicate

that there are five laws that every user interface

designer should know and apply: i) Fitts Law

(Guiard and Beaudouin-Lafon, 2004); ii) Miller Law

(Miller, 1956); iii) Steering Law (Accot and Zhai,

2001); iv) Hicks Law (Seow, 2005); v) Practice Law,

(Roessingh and Hilburn, 2000).

The second HCI concept is “Nielsen's Usability

Heuristics. Nielsen proposes ten heuristics to design

user interfaces (Nielsen, 1994). They are as follows:

i) System state visibility; ii) Coincide real world and

system; iii) User control and freedom; iv)

Consistency and Standards; v) Error prevention; vi)

Recognizing instead of remembering; vii) Flexibility

and efficiency; viii) Static and minimalistic design;

ix) Help the user to recognize, diagnose and recover

from errors; x) Help and Documentation,

documentation should be easy to search, focus in

user task.

In adition, Tukuchiy utilizes two main

Adaptation concepts: User, and Context Profiles.

User profiles represent tastes, necessities, and

preferences of each user in a system, and can be

used to adjust the services provided by the system,

according to individual user aspects. Context

profiles represent the user environment,

characteristics that may affect the system's usability.

Particularly, Tukuchiy takes into account the time of

the day to adjust UI illumination. This adjustment is

based in the Berry criteria (Berry, 2013), which

indicates the way to manage brightness to ensure

that user interface colors are comfortable for the user

and would not reduce his/her perception capabilities.

3 RELATED WORK

Related Work Table 1 shows a comparison between

related work about UI usability and UI generation,

based in our work in (Barrera et al., 2013c) and (L.

F. Barrera et al., 2013a). Columns are the related

works. Rows are the criteria to evaluate each work.

The columns 1-6 are as follows: 1(Moussa et al.,

2000); 2 (Criado et al., 2010); 3 (Zimmermann et al.,

2013); 4 (Namgoong et al., 2006); 5 (Akoumianakis

and Stephanidis, 1997); 6 (England et al., 2009).

The criteria used in Table 1 were chosen to

highlight the deficiencies with respect to interfaces

usability.The evaluation comprises both HCI and

Adaptation. Most works do not focus on improving

usability. Although most take into account user

profile and his/her context, they do not take into

account HCI standards. These works do not take into

account that interfaces change during execution time

and that it is necessary to avoid losing standards

given during design time.

Table 1: Related Work Comparison.

Criterion 1 2 3 4 5 6

Takes into account usability criteria

during Execution (E) time or Design

(D) time.

D E-D D D D E

UI let the user recognize, diagnose, an

recover from errors

- - + - - +

UI include help and documentation + - - - + -

Keeps consistency between the real

world and the system

+ + - + + -

Adapts to different types of users - + - - - +

Takes into account user context aspects - + + + - -

Uses HCI techniques

+ - - - + +

Utilizes a rule-

ased system to

generate UI

- - - - + -

4 TUKUCHIY

Tukuchiy ("Tukuchiy" is a Quechua word that means

"To Transform") is a framework based on the Runa-

Kamachiy model (L. F. Barrera et al., 2013a), to

generate dynamic user interfaces, adjusted to

specific user characteristics, context, and

presentation preferences.

Figure 1: Tukuchiy Base Interface.

Tukuchiy keeps some usability standards at

execution time, so that UI usability can be kept

across the entire life cycle of the system (Figure 1).

The Figure 1 shows some of the usability rules in

Tukuchiy.

The description of Tukuchiy's component and

IntegratingAdaptationandHCIConceptstoSupportUsabilityinUserInterfaces-ARule-basedApproach

Table 2: Usability Criteria and Heuristics.

Usability

Criterion

Heuristic

Learning

User control and freedom. Recognize instead of

Remembering.

Error

prevention

Help the user to recognize, diagnose, and recover

from errors. Help and Documentation.

Memorization

Consistency and Standards. Help and

Documentation.

Efficiency

Flexibility and Efficiency.

Satisfaction

System state visibility.

Efficacy

Static and minimalistic design.

conceptual integration can be found in (Barrera et

al., 2013b). This section focuses in explaining the

way Tukuchiy adapts usability concepts in web

pages to desktop applications. Table 2 shows the

usability criteria addressed by this research and the

heuristics utilized to address them.

4.1 Learning

Learning is related to the capacity of the software to

let users learn to use its components (Carvajal and

Saab, 2010). Tukuchiy uses Practice Law (Section

2.1) to provide different types of help, with various

levels of detail, depending on the user expertise. If

the user is new, help is more detailed (see Figure

2a). As the user gains more experience utilizing the

system, help is reduced (Figure 2b).

(a) Novice

(b) Expert

Figure 2: Learning in Tukuchiy.

4.2 Error Prevention

An error-tolerant interface is designed to assist the

user in recovering from errors (Carvajal and Saab,

2010). Tukuchiy utilizes tooltips with more or less

information, according to the user experience level.

Users with less experience received more detailed

tooltips, while users with more experience received

tooltips with less detail.

Additionally interface buttons are associated to

intentionality and a color that represents that

intentionality. Figure 12 shows the color palette

utilized when one wants to change the color to the

"close" button. Since this button is associated to a

"danger" intentionality, blue and green colors, which

represent "harmony", are not present in the palette.

4.3 Memorization

The memorization aspect enables users to easily

remember how to interact with that system, after a

period without using it (Nielsen, 1995). To address

the memorization aspect, this research utilized the

Miller Law (section 2.1). Tukuchiy groups buttons

according to functionality based in this Miller rule

(see Figure 3). Changes performed by the user in

design (personalization) of the UI persist across

sessions.

Figure 3: Memorization in Tukuchiy.

4.4. Efficiency

Efficiency is associated to the amount of effort

required by the user to achieve a specific goal in

his/her interactions with the system (Carvajal and

Saab, 2010). Tukuchiy enlarges buttons (see Figure

8), based in the Fitts Law. In addition, it reduces in

the amount of colors in palettes. These two strategies

reduce the user efforts to accomplish a task or to

personalize the interface.

4.5 Efficacy

According to ISO 9131-11, efficacy is the degree in

which planned activities are performed and the

planned results are achieved. In other words, can

users do what they need in a precise manner?

The use of tooltips and Fitts Law to enlarge UI

elements, seeks to improve the precision of the

performed tasks. In addition, color transformation

assists people with color blindness to properly

identify colors and avoid mistakes. As seen in Figure

6, for people with Protanopy (red color blindness),

Tukuchiy changes the color palette, discarding red

colors, so that the user may distinguish a broader

range of colors.

4.6 Satisfaction

Satisfaction is the perception of pleasantness and

positive attitude towards the utilization of a product.

That perception is reflected in the physical and

emotional actions of the user when utilizing the

system (Carvajal and Saab, 2010). The system does

not directly address this criterion. However, we

sought to indirectly satisfy the user by integrating all

WEBIST2014-InternationalConferenceonWebInformationSystemsandTechnologies

of the other criteria. For instance, the palette change

for color blind users (Flück, 2006) may be pleasant

for them.

5 RULE SYSTEM

To maintain usability characteristics during

execution time, Tukuchiy utilizes a rule-based

system, which is detailed in this section. To test the

rules, Midiku was built, a clinic radiology

application, to support the diagnostic process and

medical image simulation. To build the system, two

groups of rules were created: HCI rules and

Adaptation rules. Both are detailed in the following

sections.

5.1 HCI Rules

This group of rules realizes a subset of HCI

standards. To build that subset, this research verified

all of the standards that could be kept during

execution time. The rules are the following:

5.1.1 Physical Conditions

The system focuses in assisting two physical

difficulties: color blindness and myopia. Two

processes are performed to assist in these

difficulties: color simulation and polarization and

button enlargement.

Figure 4: Ishihara Test (Flück, 2009).

For color blindness, Tukuchiy changes the palette

using the following rule: i) Color blindness

identification: when entering the system, the user is

shown an image corresponding to the Ishihara Test

(Flück, 2009). This test determines which type of

color blindness the user (see Figure 4); ii) based in

the code of (Duck, 2012), a simulation is performed

in which palette colors are changed, so that they

could be perceived by the person, according to

his/her color blindness type.; ii) base colors are

compared with simulated colors and the difference is

calculated. This is used to change colors that are

visible to the user.

Figure 5 is a fragment of the rule for color

changes. This rule is utilized when the user needs to

use the palette to personalize the interface colors.

Figure 5: Color transformation rule fragment (color

blindness).

The Ishihara test is performed several times, to

mitigate any external factors that could affect the

validity of the user answers (e.g. screen resolution).

Figure 6: Midiku Color Transformation, user with

protanopy (Barrera et al., 2013).

As shown in Figure 6, this rule changes colors both

to the buttons and the medical image being

examined.

The following algorithm is used for button

enlargement: i) Identify the visual problem is

explicitly, asking the user if he/he has myopia, this is

stored in the user profile; iii) button properties are

changed, so that, whenever the user points to the

button, it changes its size. The layout of buttons

within the same functional group is re-arranged.

Figure 7: Button enlargement rule.

Figure 8: Button Enlargement.

Figure 7 describes the way button scale is changed

according to the user profile. This rule is based in

IntegratingAdaptationandHCIConceptstoSupportUsabilityinUserInterfaces-ARule-basedApproach

the Fitts Rule (Guiard and Beaudouin-Lafon, 2004).

Figure 8 shows an exam

ple of button enlargement in

Midiku.

5.1.2 Effective Color Combinations

Wright et al (Wright et al., 1997) indicates that

colors are not visible when they overlap. To ensure

that this rule is enforced during execution, Tukuchiy

performs the following algorithm: i) identify the

color of the element that contains the component

whose color is going to change; ii) identify the color

of the elements contained by the component whose

color is going to change; iii) using the above

information, the color palette is filtered to eliminate

the colors that, according to Wright, do not match

adequately (Wright et al., 1997). Color combinations

are organized in a pessimistic manner, i.e., there is a

list of colors that do not match in the previous steps;

iv) Presentation of the color palette, the filtered

palette is presented to the user.

Figure 9: Color combination rule.

Figure 9 shows the palette change rule according to

color combination.

Figure 10: Color combination example.

Figure 10 is an example of a palette change, in

which the text of the red button contains only the

colors that combine or contrast with the button color.

5.1.3 Widget Intentionality

In a study performed by Bedolla (Bedolla, 2002),

colors are associated to specific psychological states

and have specific intentionality (e.g. red is

associated to danger situations). This is taken into

account to assign to each UI element, an

intentionality associated to a color, to keep each

element's essence. The algorithm for this task is the

following: i) a table is created that maps

intentionality to allowed and forbidden colors, an

XML file is used to store that table. ii) when the user

is going to change a color, it is evaluated whether

the color keeps the same intentionality, according to

the table. Similarly to the color combination rule,

this filter is performed pessimistically and is

presented as a palette to the user

Figure 11: Button intentionality.

Figure 11 is a fragment of the rule that performs the

filter (eliminate colors of the palette) of the colors

that are not allowed, according to the button

intentionality. Figure 12 shows the allowed colors

for the "close" button.

Figure 12: Widget Intentionality in Midiku.

5.1.4 Luminosity

Given the importance of luminosity (see Section

2.3), a rule was created to transform the colors of the

entire interface. The transformation takes context

into account. For instance, illumination is changed

according to the time of the day.

Figure 13: Color brightness.

Figure 14: Brightness palettes in Tukuchiy.

WEBIST2014-InternationalConferenceonWebInformationSystemsandTechnologies

Figure 13 and Figure 14 is an example of the way

illumination is updated according to context. This

rule does not perform changes while the system is

being utilized, to avoid being too intrusive for the

user.

5.2 Adaptation Rules

This section shows the Adaptation rules that

complement the dynamic generation of interfaces,

based in user characteristics and context.

5.2.1 Help

Tukuchiy filters information during the system

startup to evaluate the user experience level and

language preferences. This rule process is as

follows: i) the user profile has an attribute that

indicates the amount of time the user utilizes the

system, which determines the experience level of the

user; ii) when starting the system, the user chooses

his/her language of preference; iii) from the

information in i) and ii), the system changes the

names in its UI elements according to the chosen

language. Tooltips are automatically changed

according to the experience level. Currently, the

system has two tooltips that are more detailed for

novice users than for expert users.

Figure 15: Use level about use level.

Figure 15 illustrates the help rule. Each help has an

XML file that associates UI elements with different

tooltips and names.

5.2.2 Color Preferences

Each user may have different preferences about

colors to display each UI element. To realize this in

the preferences, a rule was created that organizes the

color palette, to show the UI according to the tastes

of the user.

This rule is utilized as follows: i) each time a

user selects a color, a counter is updated, which is

used by the system to find out which the degree of

color preference; ii) based in the degree of color

preference, the color palette is reorganized from

most preferred colors to least preferred colors.

Figure 16: Color preferences rule.

Figure 16 is a code fragment that denotes the way

the palette is organized according to the user

preferences. Figure 17 shows the palette that result

from applying the above rule. In this example, the

preferred color is green.

Figure 17: Color preferences in Midiku.

6 PILOT TEST

The authors are currently developing a functional

prototype called Midiku. Since this is a work in

progress, its initial assessment has only been

performed over the design of Midiku’s User

Interface. This design includes functionality given

by Tukuchiy (see Section 4).

6.1 Evaluation Process

To evaluate the usability of Midiku’s interfaces,

Mock-ups (Soegaard, 2004) were utilized. Mockups

are a digital demonstration of the way the UI will

look like in the final system. Mockups were shown

to three physicians of the San Ignacio Hospital in

Bogotá, Colombia. One of them is an expert

radiologist with several years of experience, who is

not proficient with current computing technologies.

The other two are physicians who are specializing in

radiology and have high proficiency utilizing current

computing technologies. The three physicians

IntegratingAdaptationandHCIConceptstoSupportUsabilityinUserInterfaces-ARule-basedApproach

answered a survey based in QUIS (Questionnaire for

User Interface Satisfaction) (Chin et al., 1988). The

questions answered focused exclusively in

evaluating the UI design.

Table 3: Example questions of the survey.

Criterion Question Scale

1.Interaction

and

Adaptability

Flexibility of the user

interface

Very rigid, Rigid, Flexible or

Very Flexible

Complexity of the user

interface

Very hard, Hard, Easy or

Very easy

2.Screen and

Display

Organization of

information on screen

Very confused, Confused,

Clear or Very clear

Is the screen density:

Very inadequate, Inadequate,

Adequate or Very adequate

3.Presentation

and

Visualization

Are groups of info

demarcated?

Very confused, Confused

Clear or Very clear

Does it provide visually

distinctive data fields?

Very high grade, High grade,

Low grade or Very low

grade

Table 3 shows some of the questions, grouped by

evaluation criteria. The first criterion is the user

appreciation with respect to the interface. The second

criterion is the organization and meaning of graphical

elements in the screen. The third criterion is about the

color utilization and screen zones delimitation.

6.2 Pilot Test Results

Surveyed subjects were divided in two groups:

expert and novice. Three questions from Criterion 1

(Interaction and Adaptability), six from Criterion 2

(Screen and Display), and four from Criterion 3

(Presentation and Visualization). Figure 18 indicates

the results of the survey.

For each criterion, results are shown for the

expert group, the novices group and the expected

value, which is the maximum score that can be

obtained in each criterion.

Figure 18: Survey Results.

The Figure 25 indicates that the expert radiologist

valued the first criterion as 66.7%, emphasizing the

interface flexibility, but he expressed that the

attractiveness of interface has a low level. He valued

the second criterion as 54.2%, emphasizing the

adequate density of elements in the screen, but

indicating the difficulty to understand the meaning

of buttons. He valued the third aspect as 81.3%,

emphasizing the adequate use of colors.

For novice users, the answers were averaged.

The first aspect was valued as 66.7%, emphasizing

the ease of initial interpretation of the interface. The

second aspect was valued as 68.8%, emphasizing the

organization and adequate terminology, but they

expressed the density of elements in the screen are

inadequate. The third aspect was valued as 68.8%,

emphasizing the adequate visual distinction among

screen zones, but indicating the inadequate

utilization of colors.

The users commented that they would want to

have more intuitive and less complex radiology

interfaces. They also commented that there are

“dead spaces” in the screen that could be better

utilized to present information. They indicated that

the survey could be enriched by using videos of the

mockups, to better understand the functionality.

7 CONCLUSIONS AND FUTURE

WORK

This paper presented Tukuchiy, a framework that

integrates several methods and techniques in HCI

with Adaptation concepts to improve user

interaction with systems in changing contexts.

Tukuchiy's rule-based system ensures usability

criteria are preserved at execution time in changing

interfaces.

This paper also presented a functional prototype

(Midiku) that supports radiologists to diagnose

medical images. An initial assessment at this stage

has only been performed over the UI design of

Midiku. This assessment was performed through a

Mockup and a survey that was answered by an

expert and two novice radiologists. The results

emphasize positive aspects, such low UI complixity,

adequate organization of information on the screen

and the ease to visually distinguish data fields.

Negative aspects found are the difficulty to

understand the meaning of buttons, inadequate

characters visualization and inadequate terminology.

Future work includes fully developing the

functionality of Midiku and performing a more

detailed analysis of the capabilities of Tukuchiy in

terms of efficiency, efficacy, and user satisfaction.

In addition, Tukuchiy will be assessment with fully

test (20 observer’s approx.). The assessment

includes an initial perception test and then

interaction atoms test (key functionalities).

WEBIST2014-InternationalConferenceonWebInformationSystemsandTechnologies

ACKNOWLEGEMENTS

The authors want to acknowledge the Systems

Engineering Department and the Systems

Engineering and Computing Master’s program of

the Pontificia Universidad Javeriana, for supporting

the development of Runa-Kamachiy, Tukuchiy and

Midiku. The authors also thank Luis Felipe Uriza

and his team of resident physicians of the San

Ignacio Hospital, for their collaboration in the initial

evaluation of Midiku.

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