Introduction to the Digital Age
Reaction Papers: Instructions and Rubric
REACTION PAPERS
DUE: The week of your choice between LW2-5 (cannot be same weeks as you post a
podcast)
You will submit one reaction paper during LW2- LW5. You will be required to write about the
reading for that week (not including references). The paper should be no less than four doublespaced pages and no more than five pages double-spaced (not including references). I will enforce
the page limit and will not read past the fifth page. Please treat this paper as a mini-research brief ?
the purpose is for you to gain some practice for your final paper. The papers should be in three
sections, as detailed below. Please use APA headings. You do not need an abstract, but please
include an APA-formatted title page and reference list. The reaction paper is worth 40 points.
Grading details are in the grading rubric.
Papers should be uploaded to Turnitin via our Blackboard course site on the ?Assignment
Guidelines? page.
The grading rubric for this assignment is attached below.
?
Introduction: Introduce what the topic is and let your reader know what he/she can expect in
this paper. This section should set the context through which your reader should interpret
the information you present in your study summaries.
?
Summarize: In section one you should summarize three of the readings (if there are more than
3 that week, you may choose). Dedicate one paragraph to each study. In your own words
and without using quotations, please explain the studies. Begin the paragraph by explaining
how the researchers conducted the study and then tell me what the results were. Do not
include information on the hypotheses or literature review. Tell me what the researchers did
and what they found. Use transitions between studies to show how they relate to each other.
?
Analyze: In the second section tell me what YOU think about the readings. You should try
to pull together a main theme for the readings as a whole. Do NOT re-summarize the
studies. You only have to pick one or two things to write about. This section should be no
more than one or two paragraphs. Link these observations back to the topic ? what is the
significance of these observations in relation to the topic? What implications do your main
ideas have for communication practitioners? The main purpose of this section is to see if
you can take the research findings and translate them into implications and practical
recommendations for communication practitioners.
Your assignment should include the following:
? APA style title page
? Your 4-5 double spaced pages of main text
? Reference list in APA style
Introduction to the Digital Age
Reaction Papers: Instructions and Rubric
Reaction Paper Rubric
Name _________________________
Criteria for Grading (Overall quality
and coherence of the paper will affect the
number of points earned in each category)
Introduction: The introduction provides
an introduction to the topic and describes
why it is important. The introduction also
provides a roadmap for what the reader
can expect.
The summary section uses at least 3 texts,
and accurately and succinctly summarizes
the important points of each. Overall, the
section demonstrates the student?s
understanding & command of the week?s
topic. For empirical studies, the paper
brings out the salient points of the
method & findings only. For chapters &
articles that survey readings or provide
background, or for theoretical articles, the
paper summarizes the key concepts and
the author?s arguments.
The analysis section provides insight,
observations, & conclusions about the
readings as a whole, but doesn?t continue
to summarize them. Provides a thoughtful
discussion of the implications of the
research findings for communication
practice and practitioners, and offers
specific recommendations for
practitioners. The student supports his or
her statements with reasoning and
evidence drawn from the readings.
Paper correctly uses APA style.
Writing is free of errors in grammar and
syntax, is concise, and can be readily
understood by readers without their
having to re-read.
TOTAL
Topic______________________________
Points Possible
3 points
15 points
15 points
2 points
5 points
40
Points Earned
Introduction to the Digital Age
Reaction Papers: Instructions and Rubric
Received February 10, 2020, accepted March 16, 2020, date of publication March 19, 2020, date of current version March 30, 2020.
Digital Object Identifier 10.1109/ACCESS.2020.2981892
Usability of Mobile Applications: A Systematic
Literature Study
PAWE? WEICHBROTH
Department of Software Engineering, Faculty of Electronics, Telecommunications and Informatics, Gda?sk University of Technology, 80-233 Gda?sk, Poland
e-mail: [email protected]
ABSTRACT Since the release of the first mobile devices, the usability of on-board applications has been the
concern not only of software vendors but hardware manufacturers as well. The academia community later
willingly joined the discussion on usability in terms of theory and empirical measurement, having experience
and knowledge in desktop settings. At first sight, such a background should guarantee a solid foundation
to conduct research on software usability in a new setting. However, a preliminary study on the subject
matter revealed methodological disorder in contemporary literature. As a matter of fact, a need emerged to
review existing usability definitions, attributes and measures to recognize all associated aspects. In order
to fill this void, we conducted a systematic literature review on usability studies indexed by the Scopus
database and devoted to mobile applications. The input volume covers 790 documents from 2001 to 2018.
The data analysis shows that the ISO 9241-11 usability definition has been adopted in an unchanged form
and popularized as the standard by the HCI community. Secondly, in total, 75 attributes were identified and
analysed. The most frequent are efficiency (70%), satisfaction (66%) and effectiveness (58%), which directly
originate from the above definition. Subsequently, the less frequent are learnability (45%), memorability
(23%), cognitive load (19%) and errors (17%). The last two concern simplicity (13%) and ease of use (9%).
Thirdly, in the evaluation of usability, controlled observation and surveys are two major research methods
applied, while eye-tracking, thinking aloud and interview are hardly used and serve as complementary to
collect additional data. Moreover, usability evaluations are often confused with user experience dimensions,
covering not only application quality characteristics, but also user beliefs, emotions and preferences. All these
results indicate the need for further research on the usability of mobile applications, aiming to establish a
consensus in the theory and practice among all interested parties.
INDEX TERMS Mobile applications, usability, attributes, measures, usability evaluation methods, systematic literature review.
I. INTRODUCTION
Amobile application is defined as ??a software application
developed specifically for use on small, wireless computing
devices, such as smartphones and tablets, rather than desktop or laptop computers?? [1]. A recent Statista report shows
that in 2017 smartphones had a share of 77% of the global
mobile device market [2], and more than 32% of the global
population used a smartphone [3].
Although technological progress has been made regarding mobile devices equipped with computing power, leading
to a shift from desktop computers, many limitations and
The associate editor coordinating the review of this manuscript and
approving it for publication was Mario Luca Bernardi
VOLUME 8, 2020
.
challenges still remain [4]. From the many identified, usability has been the main concern, since the users of an
application, and their judgment, ultimately decide on its
success or failure [5]?[7]. Since the inception of the first
smartphones, the subject of mobile application usability has
gained attention both in academia communities and in the
software vendors industry. While researchers are focused
on formulating theories [8], modelling frameworks [9], and
constructing methods and techniques [10], [11] for new settings, manufacturers simply desire to deliver high quality
products [12].
Despite the abundance of research devoted to studies of
mobile application usability on the one hand, and design
patterns, prototyping tools and software frameworks on the
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
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P. Weichbroth: Usability of Mobile Applications: Systematic Literature Study
other, the term tends to be vague and loose, weakening the
ability to capture its real facets and impeding the construction of measures. As a consequence, such methodological
disorder violates the core assumptions and principles laying
beneath the foundations of the usability notion. Therefore,
considering the need for the emergence of a usability definition, its attributes and measures, along with evaluation
methods, valid for mobile applications, in this paper we made
an attempt to find reliable answers by conducting a systematic
literature review. We expect that the obtained results can be
used not only by researchers to perform further studies in this
area, but also for practitioners engaged in mobile application
development and quality-in-use evaluation to better understand the characteristics and measures of the notion.
The main contributions of this study include: (i) an
evidence-based discussion of the usability definition, its
attributes and measures, (ii) and an up-to-date map of the state
of the art in usability evaluation methods (UEMs), adopted
for and adapted to mobile applications, covering publications
from 2001 to 2018.
The rest of the paper unfolds as follows. Section 2 provides
the background on the subject addressed, and related work.
Section 3 describes the research methodology. The definition
and execution of the literature review are respectively presented in Sections 4 and 5. Section 6 provides an analysis
of the extracted data, while the results are further discussed
in Section 7, along with the future research directions. The
conclusions are raised in Section 8.
II. BACKGROUND
Most people tend to use products that are easy to understand,
work as expected, and eventually deliver value. In the context
of the software engineering, system usability plays the crucial
role in shaping perceived quality in use by its users [13], [14].
Usability is the study of the intersection of between systems and users, tasks and expectations in the context of
use. Since many software products have been determined to
be insufficient to meet user needs, several comprehensive
studies have been conducted so far under the term usability,
which move towards a better understanding and relevant
measurement, aiming to cover all valid phenomena in one
framework or model [15]?[17].
The results of the study, introduced by Weichbroth
[18], show that over time the definition of usability has
evolved. In 1991 the Organization for Standardization (ISO),
in response to the emergence of the need of the software
community to standardize some facets of software products,
publicized the 9126 standard, which defines usability as ??a
set of attributes of software which bear on the effort needed
for use, and on an individual assessment of such use, by a
stated or implied set of users?? [19].
Then, in 1998, ISO refashioned the usability definition in
the ISO 9241-11 norm, which actually states that usability
is ??the extent to which a product can be used by specified
users to achieve specified goals with effectiveness, efficiency
and satisfaction in a specified context of use?? [20], [21].
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While some argue that it is the most recognizable definition [18], others maintain that ??a generally accepted usability
definition still does not exist, as its complex nature is hard to
describe in one definition?? [22], [23].
The other usability definition can be found in ISO/IEC
25010 [24], which replaced the ISO/IEC 9126 standard from
2001 [25], and specifies usability as the ??degree to which a
product or system can be used by specified users to achieve
specified goals with effectiveness, efficiency and satisfaction
in a specified context of use??. Here, it is worth noting that
these two latest paraphrased definitions, however differently
particularized, still share exactly the same three virtues which
affect the user?s ability to achieve specified goals.
Since the inception of the first official usability definition,
one might argue that a great plethora of usability attributes
have been taken into consideration regarding the ability to
use particular software products, ranging from monolithic
systems to lightweight web pages. Having said that, based
on the literature search and analysis, in view of usability
attributes that contribute to the quality in use of the desktop
software, the latest study [18] shows that the most frequent
are efficiency, satisfaction, learnability and effectiveness. The
least frequent are understandability and operability, memorability, errors, attractiveness and accessibility.
To collect all necessary data in order to improve the quality
of particular software facets, a variety of usability evaluation methods (UEMs) have been developed and empirically
tested. One of the most recognized UEMs concern the family
of user testing methods [26]?[28], in particular think-aloud
protocol [29]?[31], question-asking protocol [32]?[34], performance measurement [35]?[37], log analysis [38]?[40], eye
tracking [41]?[43], and remote testing [44]?[46]. Secondly,
inspection methods, intended to be used by experts [47],
refers to heuristic evaluation [48]?[50], cognitive walkthrough [51]?[53], perspective-based inspection [54]?[56],
and guideline reviews [57]?[59]. Thirdly, inquiry methods,
designed to gathering subjective data from users, utilize both
quantitative (questionnaires [60]?[62]) and qualitative (interviews [63]?[65] and focus groups [66]?[68]) techniques.
Furthermore, some authors also distinguish analytical modelling methods such as cognitive task analysis [69]?[71], task
environment analysis [72]?[74] and GOMS analysis (Goals,
Operators, Methods and Selection rules) [75]?[77].
Regarding the context of this study, Zhang and Adipat
(2005) propose a generic framework for conducting usability
tests for mobile applications through discussing existing
methodologies and usability attributes [78]. As challenges,
they point to the unique features of mobile devices and
wireless networks which influence the usability of mobile
applications, including mobile context, multimodality, connectivity, small screen size, different display resolutions,
limited processing capability and power, and restrictive data
entry methods. In the case of research methodologies for
usability testing, they point to controlled laboratory experiments and field studies. While former limitations are ignorance of the mobile context and the preservation of reliable
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P. Weichbroth: Usability of Mobile Applications: Systematic Literature Study
network conditions and other environmental factors, then
later, the lack of sufficient control over participants in a study,
and dealing with issues such as the selection of environmental conditions, evaluation performance, data collection and
condition control. They also identify nine generic usability
attributes: learnability (ease of use), efficiency, memorability,
errors, user satisfaction, effectiveness, simplicity, comprehensibility (readability) and learning performance.
Hussain and Kutar (2009) introduce a hierarchical GQM
(Goal Question Metric) model to evaluate mobile usability [79]. On the top level, they place three quality characteristics: effectiveness, efficiency and satisfaction. On the middle
level, six guidelines are conceptualized: simplicity, accuracy,
time taken, features, safety and attractiveness. Eventually,
on the bottom, there is a mapping between questions and
metrics, which enables the collection of quantitative data in
order to evaluate usability.
Kronbauer et al. (2012) propose a hybrid model for the
evaluation of smartphone application usability [80]. In this
study, the hybrid approach blends two methods for data
capture, namely, Logging and ESM (Experience Sampling
Method). The first one is based on data collection related to
user interaction with an application. Using sensors available
in smartphones for contextual data collection, such as luminosity intensity and the device?s position, allows the performance of statistical analysis regarding usability. The second
one is based on the collection of users? feelings towards a
specific product through questions. These two methods are
respectively used to measure efficiency, effectiveness and
satisfaction.
Harrison et al. (2013) developed the PACMAD (People
At the Centre of Mobile Application Development) usability
model, which identifies three major dimensions affecting the
overall usability of a mobile application: the user, the task
and the context of use [81]. However, the last one plays a
crucial role, as an application may be used in multiple and
very different contexts (e.g. environment, physical location,
user?s state or activity performed). The model encompasses
seven attributes, which together reflect the usability of an
application: effectiveness, efficiency, satisfaction, learnability, memorability, errors and cognitive load. In some studies
the model has been adopted to set up testing and evaluation
frameworks [82], [83]. The novelty of the model concerns
cognitive load as a new usability attribute. The authors claim
that it can be observed that users of mobile applications
often perform additional tasks, such as walking, while using
the mobile device. For this reason, these additional tasks
impact the user?s performance, arguing by example of a
walking user who in the same time is texting a message
which reduces walking speed as s/he is concentrating on
typing (sending) the message. More recently, cognitive load
has been acknowledged [84], or disregarded [85], as one of
the usability notions.
Actual usability, located in the frames of the quality-in-use
model by Lew and Olsina (2013), comprises effectiveness,
efficiency, learnability in use, and communicability [86].
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They also emphasize the difference between the context of
mobile applications and traditional, desktop or web applications. The context does not only concern hardware limitations
(e.g. size of the screen), but also other factors, such as: user
activity, day/time of day, location, user profile, device and
network performance.
Obviously, there are many more usability models, individually applicable to particular domains, such as mobile
banking [87], or healthcare [88]; however, they were excluded
from the discussion due to their specific attributes, classified
as superior with respect to the others.
III. RESEARCH METHODOLOGY
A systematic literature review (SLR) in its nature differs from
traditional narrative reviews by adopting a replicable, scientific and transparent process methodology. By design, it aims
to reduce cognitive bias by providing an audit trail of the
associated assumptions and procedures, reviewers decisions
and conclusions on the one hand, and by identifying and
documenting key scientific contributions to a field or question
on the other.
In order to provide a body of knowledge on the usability
of mobile applications, we performed a systematic literature
review by adopting and adapting the approach provided by
Kitchenham and Charters [89], [90], since a large majority of
the reported SLRs in software engineering has been carried
out in respect to their guidelines [91].
According to the research design employed, this study
consists of three steps, performed in a fixed sequence. Interdependency is revealed in the one-way output/input relations.
Step 1 in the research methodology involves defining the
research questions and the review protocol, which encompasses the data source and search strategy, the inclusion and
exclusion criteria and the definition of the search string. The
outcome of this step is described in Section 4. Step 2 in the
research methodology involves executing the search string
carried out on the database engine. Next, the obtained results
are extracted and further processed. The outcome of this step
is given in Section 5. Step 3 in the research methodology
involves reviewing, analysing and reporting each data record,
in order to consequently find and document answers for a
defined set of the research questions. The outcome of this step
is described in Section 6.
IV. SYSTEMATIC LITERATURE REVIEW DEFINITION
A. RESEARCH QUESTIONS DEFINITION
Investigating the gap in usability between desktop and mobile
settings, the following three questions arose:
RQ1. How has usability for mobile applications been
defined?
RQ2. What are the usability attributes for mobile applications?
RQ3. How have usability attributes for mobile applications
been defined, and which measures and evaluation methods
have been used?
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P. Weichbroth: Usability of Mobile Applications: Systematic Literature Study
TABLE 1. The general search query criteria.
TABLE 3. The exclusion criteria (EXCLUDE) to the subject area
(SUBJAREA).
TABLE 2. The inclusion criteria (LIMIT-TO) to the subject area (SUBJAREA).
These three interrogative statements provide the overall
framework for conducting this study, by giving direction and
setting up boundaries.
B. DATA SOURCE AND SEARCH STRATEGY
In line with the research methodology, step 1 involves
a systematic search of the scientific literature on the
topic of mobile application usability. Performed on Scopus,
the largest abstract and citation database of peer-reviewed
literature, counting over 71 million records [92], the search
strategy aims at identifying indexed publications. A key issue
when formulating a search strategy is to define the period of
time to set up time boundaries. Being in our interest to obtain
reliable and concise answers to the questions, we determined
the closing date in December 2018.
TABLE 4. The inclusion criteria (LIMIT-TO) for the document
type (DOCTYPE).
TABLE 5. The inclusion (LIMIT-TO) and exclusion (EXCLUDE) criteria for
the language.
C. SEARCH QUERY DEFINITION
The search query was defined by the presence of ??usability??
and the string ??mobile application?? in titles, abstracts and
keywords. These unique and specific terms, joined together
in that order and in the extent of such meta-data, embody the
authors? common declaration of their research objectives and
the adopted context of their performed studies. The summary,
in terms of the search query construct, is given in Table 1.
D. INCLUSION AND EXCLUSION CRITERIA
In accordance with our research objective and questions,
the first applied inclusion criterion relates to the subject
area, which alternatively includes: computer science, engineering, mathematics, social sciences, or decision sciences.
Table 2 presents the summary of the search query construct
in this scope.
In this study, usability is considered in the context of
software, which is a concern of computer science and is also
closely associated with the other abovementioned disciplines.
In this line of thinking, we exclude irrelevant subject areas
(e.g. Medicine, Health Professions, Chemistry and others).
Table 3 depicts the summary of the search query construct in
this scope.
The second inclusion (exclusion) criterion was the document type which alternatively encompasses: conference proceedings, journal articles or book chapters. On the other
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hand, we did not take into account conference reviews and
other reviews, which present non-scientific contributions.
Table 4 outlines the summary of the search query in this
scope.
Not all scientists regard conference proceedings as a reliable and valuable source of knowledge. However, from our
point of view, our judgement was not solely based on the
document type, but on scrupulous reading and conscientious
content analysis.
The third inclusion (exclusion) criterion was the language, exclusively limited to English. Therefore, two other
(Portuguese and French) were excluded. Table 5 depicts the
summary of the search query construct in this regard.
English has become the modern lingua franca in the modern world. The major international standardization bodies
publish norms and standards in English, and communication
channels between experts and communities follow the same
rule as well.
V. SEARCH EXECUTION
A. SEARCH AND SELECTION
In the first run, the search query (Table 1) produced
1,615 document results. To this volume, the inclusion
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P. Weichbroth: Usability of Mobile Applications: Systematic Literature Study
FIGURE 1. The distribution of the number of publications per year.
and exclusion criteria were applied, defined respectively
in Tables 2?5. The search strings, given in all these tables,
were eventually combined by the relevant Boolean operators.
The final search query construct, which entirely fulfils all the
requirements, is given below.
TITLE-ABS-KEY (usability AND ??mobile application??) AND (LIMIT-TO (SUBJAREA, ??comp??) OR
LIMIT-TO (SUBJAREA, ??engi??) OR LIMIT-TO (SUBJAREA, ??math??) OR LIMIT-TO (SUBJAREA, ??soci??) OR
LIMIT-TO (SUBJAREA, ??deci??) OR EXCLUDE (SUBJAREA, ??medi??) OR EXCLUDE (SUBJAREA, ??heal??) OR
EXCLUDE (SUBJAREA, ??ceng??) OR EXCLUDE (SUBJAREA, ??envi??) OR EXCLUDE (SUBJAREA, ??phys??) OR
EXCLUDE (SUBJAREA, ??mate??) OR EXCLUDE (SUBJAREA, ??bioc??) OR EXCLUDE (SUBJAREA, ??ener??)
OR EXCLUDE (SUBJAREA, ??psyc??) OR EXCLUDE
(SUBJAREA, ??arts??) OR EXCLUDE (SUBJAREA, ??eart??)
OR EXCLUDE (SUBJAREA, ??nurs??) OR EXCLUDE
(SUBJAREA, ??chem??) OR EXCLUDE (SUBJAREA,
??neur??) OR EXCLUDE (SUBJAREA, ??econ??) OR
EXCLUDE (SUBJAREA, ??agri??) OR EXCLUDE (SUBJAREA, ??immu??) OR EXCLUDE (SUBJAREA, ??phar??))
AND (LIMIT-TO (DOCTYPE, ??cp??) OR LIMIT-TO (DOCTYPE, ??ar??) OR LIMIT-TO (DOCTYPE, ??ch??)) AND
(EXCLUDE (PUBYEAR, 2019)) AND (LIMIT-TO (LANGUAGE, ??English??)) AND (EXCLUDE (LANGUAGE,
??Portuguese??) OR EXCLUDE (LANGUAGE, ??French??))
The results summary was checked in order to verify
whether all the criteria were successfully applied. In total,
the final search query eventually produced 887 documents,
published between 2001 and 2018. The details of the volume
data are as follows, while the numbers in brackets indicate the
total number of publications: (a) published in English (887),
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(b) the subject area is from: computer science (803), decision sciences (40), engineering (198), mathematics (197)
and social sciences (103), and (c) the document type is:
conference proceedings (666), journal articles (196) or book
chapters (25). The peak year is 2017 (140), followed by
the years 2015 (110), 2018 (104) and 2016 (101), with an
average of 74 documents published annually between 20082018 (Figure 1).
The distribution of the number of publications increases in
linear. However, in 2018 a fall was observed in comparison to
the previous year, but still above the year 2016. The majority
of documents were published by Springer in Lecture Notes
in Computer Science, including sub-series Lecture Notes
in Artificial Intelligence and Lecture Notes in Bioinformatics (148), while the largest contributor among journals is
the Journal of Telecommunication, Electronic and Computer
Engineering (12). The top three countries, the USA (136),
Germany (81) and Malaysia (66), accounted for over 31% of
the countries the authors were affiliated to.
B. DATA EXTRACTION
Having imported the reference data (authors, document
title, year, and digital object identifier) to an external
spreadsheet, we systematically searched for each record
in full-text databases hosted by particular publishers and
indicated as the source of the document. From the list
of 887 records, in total 790 (89%) documents were fully
available, while using a HAN system licensed account.
To extract the data, three independent reviewing procedures
were prepared and executed, respectively for each research
question.
In the first run, each available document was screened
with the aim to identify and recognize a usability definition
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P. Weichbroth: Usability of Mobile Applications: Systematic Literature Study
TABLE 6. The list of adopted usability definitions for mobile settings.
TABLE 7. The shares of adopted usability definitions for mobile settings.
referenced by the author(s). The document was classified as
relevant if: (a) usability, as a term, was explicitly defined
and (b) correctly referenced. If the authors provided more
than one definition and did not indicate a particular one as
valid, then the first one given was assumed to be adopted.
Eventually, 66 (8%) documents were classified as relevant as
the input for analysis, with the aim of formulating an answer
to the first research question.
In the second run, each document was screened again to
determine the overall quality and its relevance. A document
was classified as relevant if: (a) the subject of the research
was addressed to the usability of mobile applications, and
(b) was not biased by a context of the research, such as:
(i) application type or (ii) user-specific properties, such as:
age, occupation, sex or (iii) system-specific support features,
like visually impaired or disability. The review of the list
produced 53 (7%) documents as relevant as the input for
analysis with the aim of formulating an answer to the second
research question.
In the third run, the above list was reviewed and examined
again with the aim of extracting attribute definitions, measures and UEMs. The document was classified as relevant
if: (a) usability attributes being the subject of the study were
explicitly defined, whereas a measure was valid if it captures
the quantitative data which accurately describes one particular usability attribute. Ultimately, 39 (5%) documents were
classified as relevant as the input for analysis with the aim of
formulating an answer to the third research question.
VI. DATA ANALYSIS
This section addresses the analysis of the data extracted
from the studies in accordance with the three defined
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research questions. We used a qualitative content analysis, which focuses on the characteristics of language
as a communication channel, with attention to the specific subjects, narrowed and directed by particular research
questions.
RQ1. How has usability for mobile applications been
defined?
To this day, none of the authors have introduced any
formal definition of usability associated with an application (system) running on a mobile device. Therefore, all identified and recognized definitions have been
adopted from the existing general norms, standards and
definitions.
The great majority of authors (88%) have defined usability
solely in terms of the ISO 9241-11 norm, while others have
also made reference to ISO 25010 (4,5%) and ISO 9126 (3%)
norms, as well as to the IEEE Glossary (1,5%), the Nielsen
(1,5%) and Bevan (1,5%) definitions. Table 6 includes the
full text of these six definitions, whereas Table 7 depicts
findings of the shares of adopted usability definitions for
mobile settings.
RQ2. What are the usability attributes for mobile applications?
In total, 75 usability attributes were identified and analysed. Among them, the most frequent are efficiency (70%),
satisfaction (66%) and effectiveness (58%). Less frequent
are learnability (45%), memorability (23%), cognitive load
(19%) and errors (17%). The last two concern simplicity (13%) and ease of use (9%). The remaining attributes
occurred four times or less. Table 8 outlines the details in
this regard (the attributes which occurred only once are not
included).
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P. Weichbroth: Usability of Mobile Applications: Systematic Literature Study
TABLE 8. The list of adopted usability attributes for mobile settings.
RQ3. How have usability attributes for mobile applications been defined, and which measures and evaluation
methods have been used?
The foremost attribute, efficiency is the ability of a user
to complete a task with speed and accuracy. Efficiency is
measured in a number of ways, such as the duration spent
on each screen, the duration to complete a given task (a set of
tasks), and the user?s error rate. Two evaluation methods are
used: controlled observation and survey.
Satisfaction is a user?s perceived level of comfort and
pleasure, or a us