User Interface Factors of Mobile UX: A Study with an Incident

Reporting Application

Lasse Einfeldt

and Auriol Degbelo

2 a

xdot GmbH, M

unster, Germany

Institute for Geoinformatics, University of M

unster, M

unster, Germany

Keywords:

Mobile UX, Mobile Form Design, Map UX, Environmental Monitoring.

Abstract:

Smartphones are now ubiquitous, yet our understanding of user interface factors that maximize mobile user

experience (UX), is still limited. This work presents a controlled experiment, which investigated factors that

affect the usability and UX of a mobile incident reporting app. The results indicate that sequence of user

interface elements matters while striving to increase UX, and that there is no difference between tab and

scrolling as navigation modalities in short forms. These ﬁndings can serve as building blocks for empirically-

derived guidelines for mobile incident reporting.

1 INTRODUCTION

User experience (UX) has gained attention from many

sides since the turn of the millennium. Although

many authors mentioned the lack of clear deﬁnitions

of user experience and no clear understanding of it

in early research (Forlizzi and Ford, 2000; McCarthy

and Wright, 2004; Hassenzahl, 2005; Wright et al.,

2005), there has been a lot of research dealing with

user experience since then. There has been reviews

of UX in human-computer interaction (e.g. Bargas-

Avila and Hornbæk (2011); Pettersson et al. (2018);

Kieffer et al. (2019)) and work investigating factors

of mobile UX in general (e.g. Wigelius and V

(2009); Arhippainen and T

ahti (2003)). Nonetheless,

our understanding of user interface factors which

maximize mobile user experience is still limited. In-

vestigating these factors is important for at least two

reasons. First, mobile devices are peculiar by virtue

of their size, their (still) relatively reduced process-

ing power, and input modalities (e.g. post-WIMP in-

teraction). That is, insights gathered while assessing

user experience on desktop (or other devices) are not

readily portable to the world of mobile UX. Second,

an understanding of these factors is important to de-

velop design heuristics, which can then be integrated

as constraints during computer-generated user inter-

face design (Oulasvirta, 2017).

https://orcid.org/0000-0001-5087-8776

This work is primarily concerned with the im-

pact of positioning and type of navigation modality

on the overall usability and user experience of mobile

geospatial applications. Incident reporting apps (of

which maps are a central component) are of interest

here for two reasons. From the theoretical point of

view (and as mentioned in Kray et al. (2017); Roth

(2013)), there are currently no consolidated set of

guidelines that have emerged as to how to design in-

teractions with maps. A few works (Sch

oning et al.,

2014; Arhippainen, 2013; Kraak et al., 2018) made

some useful recommendations, but these do not ad-

dress the UX of mobile geospatial apps (i.e. maps)

directly. Thus, research in this area must remain ac-

tive for study outcomes to crystallize into empirically-

derived guidelines in the future. From the practi-

cal point of view, maximizing UX in the context of

incident reporting is a catalyst for uptake and pro-

longed use. Put differently, a positive user experience

is crucial to guarantee prolonged contributions by cit-

izens. As a starting point for the work, the mobile

app “Meine Umwelt” was used. The rationale for its

choice is introduced next.

Reports of ecological data are an important data

source for German federal agencies dealing with the

preservation of the environment. Reported data can

have several topics including ﬁndings of neophytes,

illegally disposed waste, or endangered animals. This

information can be used to ﬁnd items of interest in

the wild easily, instead of searching for them. A

system used for reporting this data is the mobile

Einfeldt, L. and Degbelo, A.

User Interface Factors of Mobile UX: A Study with an Incident Reporting Application.

DOI: 10.5220/0010325302450254

In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 2: HUCAPP, pages

245-254

ISBN: 978-989-758-488-6

245

app “Meine Umwelt” (Kooperation-Umweltportale,

2019). “Meine Umwelt” was created by the “Kooper-

ation Umweltportale”, a cooperation of German fed-

eral states for the development of environment-related

apps. More than 10.000 downloads in the Google

Play Store, more than 3000 active users on Android,

in addition to more than 2.250 unique downloads on

iOS build the current user base. Since the app is de-

veloped for federal agencies in Germany, means for

measuring the interactions (e.g. interaction logs) with

the application cannot be implemented into the live

app in the app stores. An assessment of the interaction

with the app to identify possibilities for improvement

can only happen through a lab-based study ofﬂine.

The contributions of this work are twofold: (i)

an investigation of the effect of map placements on

the user experience within a mobile app for reporting

ecological data: a takeaway from the experiment is

that sequence of UI elements matters while trying to

maximize mobile UX; (ii) a comparison of tab-based

and scrolling navigation for short forms on mobile de-

vices: contrary to Harms et al. (2015) who found that

scrolling performs worse than tab for the interaction

with long forms on smartphones, the difference be-

tween both interaction modalities for short forms was

not signiﬁcant in this work.

2 RELATED WORK

As indicated in (Ricker and Roth, 2018), mobile de-

vices enable users to volunteer their local knowl-

edge and experience while situated in place, provid-

ing timely and unstructured information about chang-

ing geographic conditions. Since “Meine Umwelt” is

dedicated to the reporting of environmental data, re-

lated work on reporting systems is brieﬂy presented in

this section. In addition, research on factors of mobile

UX is brieﬂy introduced, followed by work on form

design on mobile devices, and interactive maps.

Reporting Systems. Winckler et al. (2016) focused

on the UX dimensions important for incident report-

ing systems. Interviews with participants were used

to gain insights into the users’ perception of the in-

vestigated app. They found users to prefer a selection

of reportable items from a menu. This provides an

overview of all items and avoids generic forms trying

to ﬁt all items at once. Moreover, an interactive map

was clearly demanded by the users. Another require-

ment found in their interviews was the necessity to

provide an identiﬁcation, to avoid fake reports. Pic-

tures and videos of the item should also be included

in the report. Related to incident reporting are citizen

observatories, deﬁned as “the participation of citizens

in monitoring the quality of the environment they live

in” (Liu et al., 2014). Here, no recent incident or event

is present as a motivation for the report. Instead, ob-

servatories are more focused on ecological data and

observations than on incidents in an urban context.

The acquired data should be used by the government

and if possible made available to the public as data

and/or service (Liu et al., 2014). Citizens’ observa-

tories are described as a cheap and easy way for the

administration to collect data about the environment.

The collection of data about the environment,

where the citizens live is exactly what the prototypes

presented later in this study were designed for. In ad-

dition, targeting a broad audience alongside the envi-

ronmentalists, who are highly active in preservation

anyway, is possible with a mobile application. Hav-

ing data reported by local citizens as stakeholders can

lead to enhanced quality in environmental decisions

(Reed, 2008). This data is easy to collect and as a

review of ten years of community-based monitoring

found, one of the most efﬁcient methods of monitor-

ing (Conrad and Hilchey, 2011). Preece (2016) ref-

erences multiple technologies and concepts used for

citizen science, like passive and active data collec-

tion, mobile apps, web portals, webcams, drones, and

gamiﬁcation. All of these can be useful approaches to

collect data, which fulﬁll some given requirements.

In addition, these concepts can be combined - like

an active data collection platform available both as

an app and web portal. She also mentions some re-

porting systems like Floracaching, iSpotNature.org,

and iNaturalist.org. The study in this work uses ac-

tive data collection via mobile apps. The domains

of the reports are comparable to the one in iSpotNa-

ture.org, which provides a wide range of species to

report. In contrast, other reporting services like Flo-

racaching focus on one domain only, i.e. plants.

Factors of Mobile UX. An early listing of impor-

tant dimensions affecting mobile UX, in general, was

provided in (Arhippainen and T

ahti, 2003). These di-

mensions were: the user, the social factors, the cul-

tural factors, the context of use, and the given prod-

uct. Along similar lines, Subramanya and Yi (2007)

divided factors contributing to a good user experi-

ence into three categories: device-related (i.e. hard-

ware), communication-related (i.e. provide a feeling

of face-to-face communication as much as possible),

and application-related (i.e. UI related); Wigelius

and V

a (2009) identiﬁed ﬁve dimensions affect-

ing mobile UX: the social context, the spatial context,

the temporal context, the infrastructural as well as the

task contexts; and Ickin et al. (2012) identiﬁed seven

HUCAPP 2021 - 5th International Conference on Human Computer Interaction Theory and Applications

246

factors that inﬂuence mobile UX in their study: appli-

cation interface design, application performance, bat-

tery efﬁciency, phone features, application and con-

nectivity cost, user routines, and user lifestyle. Con-

cerning investigating UX, Korhonen et al. (2010) pro-

posed that mobile UX can be traced back to two fea-

tures of the user’s context: the triggering context (i.e.

single contextual factor that changes the user’s expe-

rience stream in a positive or negative direction), and

the core experience (i.e. experience that was most

memorable to the user during the interaction). The

lessons learned about UI factors in this work intend

to extend this body of knowledge with insight from

UI element design and placement.

Form Design on Mobile Devices. Harms et al.

(2015) investigated the use of long forms on smart-

phones. They tested four different designs and found

scrolling to perform the worst of all possible methods,

while the other three designs (tabs, menus, and col-

lapsible ﬁeldsets) worked equally well. This ﬁnding

matches the framework of Zhang and Adipat (2005),

who stated that the cognitive load needed from the

user should be minimized by avoiding long lists. One

way to avoid scrolling in long forms is to structure the

content in categories, each ﬁtting the screen size. Be-

sides, the framework from (Zhang and Adipat, 2005)

proposes to use as little interaction as possible (which

changes in categories would imply). Hence, the struc-

turing of content on mobile phones should be de-

signed thoughtfully. While Couper et al. (2011) inves-

tigated the placement of buttons in long forms (and

not their structuring), their statement that the design

of forms can affect the user behavior speaks in fa-

vor of further investigating form design in general.

These studies all examined the design of, and interac-

tion with long forms. The question remains whether

the ﬁndings are also applicable to short forms, and if

scrolling in forms should be avoided in general.

Interactive Maps. Degbelo et al. (2019) compared

the merits of form-based and map-based interaction

for geodata creation tasks. They reported that the

sweet spot of interactive maps (on desktop devices)

seems not so much their impact on productivity, but

rather their positive inﬂuence on the overall UX.

Users reported that maps are more stimulating and at-

tractive than forms for information creation tasks. Re-

garding the mobile context of interactive maps, Buri-

gat and Chittaro (2011) investigated mobile maps and

the use of three different approaches to visualizing the

references to off-screen content of maps. In another

study, Burigat et al. (2008) found zoomable maps

with an overview window (overview+detail approach)

to be useful for map interaction. A third study by

Burigat and Chittaro (2013) showed increased perfor-

mance in task completion time with overview+detail

layouts, which users could manipulate. The focus was

on interfaces, which allow map manipulation through

interactions with the overview and highlighting of ob-

jects. Finally, Horbi

nski et al. (2020) provided evi-

dence that positioning of UI elements on mobile maps

matters. Users indeed expressed different preferences

for the positioning of buttons for features such as ge-

olocation, search, or routing. Though these studies

provide valuable insights into the use of interactive

maps on mobile devices, they do not cover an under-

standing of factors affecting mobile map user experi-

ence, which is the topic of this article.

3 USER STUDY

The goal was to investigate differences in users’ per-

ception of the navigation modalities and sequences

of the interactions. The interfaces were designed to

investigate the inﬂuence of map positioning as well

as different form designs on a smartphone. This

study can be viewed, following Schmidt (2009), as

a ‘follow-up study with a replication condition’ to

Harms et al. (2015)’s work. The focus was on two

questions. RQ1: what is the inﬂuence of different

form designs on user experience and usability? The

focus here was on short forms (i.e. up to 10 ﬁelds).

RQ2: what is the inﬂuence of UI component se-

quences on user experience and usability?

Variables. Independent variables: The sequence of

the UI components, and the design of the form UI

were variables controlled by the different prototypes;

dependent variables: usability, user experience, and

task performance. Usability and user experience were

measured using the System Usability Scale (SUS,

Brooke (1995)) and the User Experience Question-

naire (UEQ-S, Schrepp et al. (2017)) respectively.

Since it was not possible to integrate interaction logs

into “Meine Umwelt”, the time to complete the tasks

was measured using screen recordings of the smart-

phone used during the experiment for all prototypes.

Study Design. Besides the application “Meine

Umwelt”, two prototypes were developed for the ex-

periment (Figure 1). The prototypes were designed

to separate the sequences of the UI elements, and

the form designs. Therefore, three applications were

used: Map + Selection + Form (scroll) [hereafter, Pro-

totype 1]; Map + Selection + Form (tab) [hereafter,

User Interface Factors of Mobile UX: A Study with an Incident Reporting Application

247

Prototype 2]; Selection + Form (scroll) + map [here-

after, Base condition] (“Meine Umwelt”). A within-

subject design was used in the experiment. Each par-

ticipant completed three ecological reporting tasks,

with different levels of difﬁculty. The order of the

tasks was counterbalanced using a Latin Square ap-

proach (see supplementary material).

Tasks. Each prototype was tested with three differ-

ent tasks of equivalent properties and difﬁculty. Prop-

erties were the complexity of the task, the complexity

of the place, and the point of time. The complexity

of the task refers to different forms provided in the

tasks. The tested condition of the “Base condition”

provides six categories to report. These were all used

in the tasks, while some of these had to be used multi-

ple times to reach the number of nine tasks. The plant

category “Ambrosia” was used in all task groups, be-

cause the complexity of this task was higher than for

all other conditions. The form to report Ambrosia had

three input ﬁelds more than the remaining categories,

resulting in a more demanding task (as more informa-

tion has to be remembered and ﬁlled in by the user).

Each task group had one task with a point of time re-

quiring the user to go back in the calendar for sev-

eral months, as opposed to the other dates used (e.g.

“right now”, “yesterday”). Lastly, the complexity of

the place was higher for one task per group. This was

used to make users interact with the map more than

just searching for street names. The tasks were in Ger-

man and are available in the supplementary material

The study was approved by the local ethics board and

pilot tested with two participants. A result of the pilot

study was a slight adjustment of the tasks, to improve

their understandability. Also, a search bar was imple-

mented for the prototypes to enable place searches on

the map. The results from the two participants are not

included in the analysis.

Participants. 18 participants (10 females and 8

males) were recruited by e-mail and word of mouth.

Participants all spoke German because the study and

app “Meine Umwelt” were in German. The partic-

ipants included four landscape ecologists and biolo-

gists, who are involved in landscape and environmen-

tal preservation, along with other users, who might

use the app more casually. This mix ensures a repre-

sentative group to the user group of “Meine Umwelt”.

The average age of the participants was 22.7 (SD:

2.7).

See https://doi.org/10.6084/m9.ﬁgshare.13174550.

4 RESULTS

Table 1 presents the results of the study. In line

with recommendations from previous work Dragice-

vic (2016), the whole analysis was done using interval

estimates. Conﬁdence intervals provide much richer

information than p-values alone. A conﬁdence in-

terval that does not include zero indicates statistical

signiﬁcance; the tighter the interval, and the farther

from zero, the stronger the evidence. The analysis

was done using the BootES package (Kirby and Ger-

lanc, 2013) in R. The number of bootstrap resamples

was N = 2000. Task performance (i.e. TimeOnTask)

was similar across all three prototypes.

Regarding usability, the Base condition “Meine

Umwelt” had an average value of 59.7. The differ-

ence between the Base condition and Prototype 1 was

signiﬁcant (9.4, 95%CI [1.5, 18.1]), and so was the

difference between the Base condition and Prototype

2 (7.9, 95%CI [0.7, 15.9]). In contrast, the difference

between Prototype 1 and Prototype 2 was not signiﬁ-

cant with respect to usability ratings.

As regards user experience, the Base condition

(hereafter MU) was rated with a pragmatic quality

of 1.01 by the participants. The hedonic quality was

lower at 0.38 and the overall rating was 0.70. Overall,

users rated the user experience of the Prototype 1 (P1)

signiﬁcantly higher than the user experience of the

Base condition (+0.57, 95%CI [0.25, 0.97]). Proto-

type 2 (P2) collected also signiﬁcantly higher ratings

than the Base condition (+0.54, 95%CI [0.14, 0.96])

for the overall user experience. The difference be-

tween MU and P1 was signiﬁcant for the pragmatic

quality (0.85, 95%CI [0.2, 1.6]), and so was the dif-

ference between the MU and P2 for the pragmatic as-

pects (0.85, 95%CI [0.01, 1.7]). The difference be-

tween P1 and P2 was not signiﬁcant for the pragmatic

quality. The differences between all prototypes were

not signiﬁcant for the hedonic quality.

Regarding the size of the effects, Hedges’ g was

computed for all signiﬁcant differences. This is in

line with recommendations from previous work (e.g.

Sauro, 2014; Lakens, 2013) for studies with less than

20 participants. The values obtained were 0.52 (MU

vs P1, usability); 0.46 (MU vs P2, usability); 0.71

(MU vs P1, user experience total); 0.56 (MU vs P2,

user experience total); 0.50 (MU vs P1, user experi-

ence pragmatic); and 0.44 (MU vs P2, user experience

pragmatic). These suggest a medium effect

Corresponding Cohen’s d values were 0.54 (MU vs P1,

usability); 0.48 (MU vs P2, usability); 0.74 (MU vs P1, user

experience total); 0.59 (MU vs P2, user experience total);

0.53 (MU vs P1, user experience pragmatic); and 0.46 (MU

vs P2, user experience pragmatic).

HUCAPP 2021 - 5th International Conference on Human Computer Interaction Theory and Applications

248

Figure 1: Top: P1 & P2 (map as landing screen) vs MU (map integrated into a form); Middle: P1 with scrollable form vs P2

with tabs to structure the form vs MU (Baseline); Bottom: Example species type in P1 & P2 vs example species type in MU.

User Interface Factors of Mobile UX: A Study with an Incident Reporting Application

249

Gender effects (male vs female) and background

domain effects (landscape ecologist/biologist vs oth-

ers) were tested. These were all non-signiﬁcant on

all dimensions (TimeOnTask, usability, and user ex-

perience). A learning effect was apparent in the data

for task completion time. For 16 of 18 participants,

the ﬁrst app interaction took the most amount of time.

Nevertheless, the effects were apparent for all appli-

cations, because of the Latin square design of the ex-

periment and the resulting order of apps for each par-

ticipant. Therefore, the learning effect did not inﬂu-

ence the results of a single app. The main difference

between the tested applications was the positioning of

the map and the form designs. Both prototypes scored

higher values for both usability and user experience.

These prototypes were using the map as a landing

screen for the application. The inﬂuence of form de-

sign was not apparent, as both prototypes scored sim-

ilar values and performed with similar times. These

results are now discussed in detail.

5 DISCUSSION

This section touches upon ﬁve topics: interpretation

of the task performance results, the effect of form de-

sign on UX (RQ1), the effect of the sequence of UI

elements on UX (RQ2), implications of the results for

theory and design, and the limitations of the study.

Functional Similarity of the Apps. The results of

the user study have shown similar results for the task

performance of the tested applications. All three of

them need approximately the same time to complete

all tasks (Table 1). This indicates that the applica-

tions are all equally suited for the task at hand, namely

the reporting of ecological data. There were no clear

indications for an app hindering users in effectively

performing the provided tasks. A goal of designing

the two additional prototypes was to provide a simi-

lar design, to be able to compare outcomes. With all

applications performing on a similar level regarding

the time required to solve the tasks, this goal seems to

have been achieved.

Effect of Form Design. Considering the ﬁrst re-

search question, the results have shown no signif-

icant difference between scrollable forms and tab-

structured forms. Put differently, the sequences “Map

+ Selection + Form (scroll)” [P1] and “Map + Selec-

tion + Form (tab)” [P2] can be considered equivalent

with regard to task completion, usability and UX. The

main implication is that the ﬁndings of Harms et al.

(2015), who found scrolling to be worse (as to usabil-

ity) for the navigation in long forms, cannot be gen-

eralized to all sizes of forms. The usability of forms

of a size up to 10 input ﬁelds is not signiﬁcantly im-

proved by a tab-based design. Thus, form designs do

not noticeably inﬂuence usability and user experience

in all cases.

Effect of Sequence of UI Elements. Signiﬁcant

differences between the Base condition (MU) and

Prototype 1 were found for the user experience rat-

ings. The differing variable between the two applica-

tions was the positioning of the map. Looking closely

at the dimensions of user experience, hedonic UX was

not signiﬁcantly impacted, while pragmatic UX was

rated differently by the participants. Likewise, usabil-

ity ratings were much higher for Prototype 1. This

answers the second research question: positioning the

interactive map before the form in the sequence of in-

teractions results in better user experience and usabil-

ity. Given that perceived usability is strongly associ-

ated with pragmatic user experience (see e.g. Diefen-

bach et al. (2014); Pettersson et al. (2018)), the con-

vergence of usability and UEQ ratings during the ex-

periment increases our conﬁdence that pragmatic user

experience has been positively affected by the change

in the positioning of the map component. In addition,

given that the sequences “Map + Selection + Form

(scroll)” [P1] and “Map + Selection + Form (tab)”

[P2] can be considered equivalent (see above), the

fact that similar observations are made for Prototype

2 also provide conﬁrmatory evidence for the result.

There may be several reasons for this, and these are

now discussed using two theories: ‘cognitive ﬁt the-

ory’ (Vessey, 1991) and ‘memory-based theory of se-

quence effects’ (Cockburn et al., 2017).

One reason could be that the sequence ‘location

reporting => species type selection => specie report-

ing’ (sequence 1) provides a better cognitive ﬁt than

the sequence ‘species type selection => specie report-

ing => location reporting’ (sequence 2). Cognitive

ﬁt theory Vessey (1991) posits that problem-solving

efﬁciency and effectiveness increases when problem-

solving aids (in this context UI elements) support

strategies required to perform a task. In the case of

sequence 2, the map popping up to enter the location

interrupts the interaction of ﬁlling a form (see Fig-

ure 1, left). In contrast, sequence 1 provides a full-

screen map interface to enter the location and addi-

tionally encapsulates the location input. Hence, users

are done with entering location data, when they start

to provide additional data (e.g. species type, date,

height/number of plants, see Figure 1, middle) using

forms. Thus, sequence 1 offers a ‘cleaner’ task sepa-

HUCAPP 2021 - 5th International Conference on Human Computer Interaction Theory and Applications

250

Table 1: Results. Average values per prototype are reported ﬁrst, followed by the average of the differences between the

prototypes. Cells highlighted in blue indicate signiﬁcant values (i.e. conﬁdence intervals that do not include zero).

MU 95% CI P1 95% CI P2 95% CI

Time (seconds) 318 [298, 339] 306 [279, 335] 323 [287, 379]

Time (Diff, MU) -13 [-42, 23] 4 [-38, 56]

Time (Diff, P2) -17 [-84, 31]

SUS Score 59.7 [52.1, 66.0] 69.2 [65.3, 72.4] 67.6 [63.2, 70.8]

SUS (Diff, MU) 9.4 [1.5, 18.1] 7.9 [0.69, 15.83]

SUS (Diff, P2) 1.53 [-3.3, 5.0]

UEQ (prag.) 1.01 [0.32, 1.65] 1.86 [1.57, 2.10] 1.86 [1.38, 2.18]

UEQ p. (Diff, MU) 0.85 [0.22, 1.63] 0.85 [0.01, 1.69]

UEQ p. (Diff, P2) 0 [-0.38, 0.44]

UEQ (hed.) 0.38 [-0.03, 0.82] 0.64 [0.13, 1.14] 0.61 [0.17, 1.03]

UEQ h. (Diff, MU) 0.26 [-0.05, 0.52] 0.24 [-0.01, 0.44]

UEQ h. (Diff, P2) 0.23 [-0.22, 0.25]

UEQ (total) 0.70 [0.23, 1.17] 1.27 [0.98, 1.51] 1.24 [0.97, 1.60]

UEQ t. (Diff, MU) 0.57 [0.25, 0.97] 0.54 [0.14, 0.96]

UEQ t. (Diff, P2) 0.03 [-0.19, 0.30]

ration and hence a better cognitive ﬁt. It is worth men-

tioning that cognitive ﬁt in the strictest sense only pre-

dicts improved efﬁciency and effectiveness for some

conditions. These were not observed (see Table 1).

Yet, if the scope of cognitive ﬁt theory is broadened to

non-instrumental aspects of interaction, the explana-

tion above is plausible. A single experiment may not

justify broadening the scope of the theory, but based

on the results, the following provisional postulate can

be formulated: user experience and/or performance

increase when problem-solving aids support strate-

gies required to perform a task.

Another reason for differences in the scores might

be that both SUS and UEQ measure the perceived us-

ability and UX respectively. Therefore, the ﬁrst im-

pression of the map as the landing screen for an ap-

plication might simply be perceived more positively.

This explanation would concur with Lindgaard et al.

(2006), who found that users form their judgment

about the visual appeal of web pages during the ﬁrst

50 milliseconds of their interaction. That ﬁnding was

conﬁrmed in (Tractinsky et al., 2006), who also pro-

vided evidence that ﬁrst impressions about the attrac-

tiveness of web pages are not only formed quickly,

but lasting. Since users ﬁnd maps to be more stimu-

lating and attractive than forms for information pro-

vision (see Degbelo et al. (2019)), it is plausible that

their ﬁrst impression seeing the map ﬁrst was much

more positive, and lasted till the end of the interac-

tion. Besides, given that UX was measured after the

experiment, a memory-based view of UX could be

valuable at this point. According to memory-based

theories of UX (Cockburn et al., 2017), three factors

inﬂuence people’s memory of experiences: primacy

(i.e. over-weighted inﬂuence of the initial moments of

an experience), recency (i.e. over-weighted inﬂuence

of the terminating moments of the experience), and

peak-end (i.e. over-weighted inﬂuence of the most in-

tense moments of the experience). Since the map was

present at the beginning in sequence 1 and at the end

in sequence 2, producing in one case a positive pri-

macy effect, and in the other a positive recency effect,

the results suggest that there may be cases where pri-

macy effects with a UI element weight stronger than

recency effects with that element. The explanations

provided in this and the previous paragraph are ar-

guably tentative, but are also useful hypotheses to cor-

roborate in follow-up experiments.

Implications for Theory and Design. “Meine

Umwelt” is an incident reporting app, and as such,

the lessons learned apply to incident reporting apps

more broadly. As to theory, Winckler et al. (2013)

provided a comprehensive model for tasks related to

incident reporting. In their model, they suggested

that sequence does not matter for the sub-tasks: ‘de-

scribe the incident’, ‘locate the incident’, and ‘inform

time for the incident’. The results above suggest that

make the scope of their theoretical model more pre-

cise. Sequence does not matter from the time comple-

tion point of view but does matter from the pragmatic

UX point of view. As to design, Norman (2009) call-

ing designers to design for memorable experiences,

formulated these rules of thumb: “What is the most

important part of an experience? Psychologists em-

phasize what they call the primacy and recency ef-

fects, with recency being the most important. In other

words, what is most important? The ending. What is

most important after that? The start. So make sure the

beginning and the end are wonderful”. The end may

not always be more important than the start according

to the results above.

User Interface Factors of Mobile UX: A Study with an Incident Reporting Application

251

Limitations. Though the prototypes were designed

as closely as possible to the baseline application

“Meine Umwelt”, some minor differences can still

be detected when comparing the applications side by

side (e.g. captions in the pictures, or the choice of

the map tile provider, see Figure 1, left). These dif-

ferences could not be removed, and stem from the

different technologies used for the app development.

“Meine Umwelt” uses an API key for Google Maps

(and thus Google Maps as a base map) while the

prototypes implemented used Open Street Map as a

base map. Besides, while “Meine Umwelt” used the

Cordova framework, React Native was used to de-

velop the prototypes. The native components pro-

vided by React Native have some slightly different

properties than those of Cordova (e.g. the placehold-

ers for <input> tags displayed in a slightly different

way, see Figure 1, middle). These differences (i.e.

map[googlemaps] vs map [openstreetmap] or form

[cordova] vs form [reactnative]) are minor nonethe-

less and are mentioned here for the sake of complete-

ness only

6 CONCLUSION

This article has investigated the effect of sequence of

UI elements and type of forms within a mobile appli-

cation for reporting ecological data. A user study has

shown signiﬁcant preferences for the map as a start-

ing element, instead of the map as an ending element.

Besides, a tab-based, structured design was tested

against a scrollable view. Results have shown no

signiﬁcant difference between these designs in short

forms. With respect to earlier research (Harms et al.,

There is no recent study known to the authors reporting

on a comparison between the user experience - on mobile

devices - of Google Maps vs. OpenStreetMaps, and the

user experience of Cordova Apps vs. React Native apps.

Nonetheless, a study by Schnur et al. (2018) reported that

the perceived user complexity of Google Maps was consis-

tently lower than that of OpenStreetMaps for several levels

of details. Tuch et al. (2009), in the context of websites,

reported an inverse-linear relationship between visual com-

plexity and pleasure. That is, start pages with low visual

complexity were rated by users as more pleasurable. A

replication of several studies (Miniukovich and Marchese,

2020) conﬁrmed that inverse-linear relationships for web-

sites. Miniukovich and De Angeli (2014) also observed

a negative correlation between visual complexity and aes-

thetics for mobile apps. Putting these ﬁndings together sug-

gests - if the difference map [googlemaps] vs. map [open-

streetmap] was important - that P1 & P2 (OpenStreetMaps,

Figure 1, top left) would have obtained lower user experi-

ence ratings than MU (Google Maps, Figure 1, top right).

The opposite was observed during the study.

2015), it can be concluded, that scrolling does not per-

form worse for all sizes of form length. In short, the

sequence of user interface elements on mobile devices

matters, and the type of form design matters, depend-

ing on the length of the forms. Designers should keep

in mind both (besides button placement identiﬁed in

previous work Horbi

nski et al. (2020)) while build-

ing their next incident reporting app. Future work

can replicate this study, for instance, factoring in data

about the complexity of the base maps, and collect-

ing qualitative data about what users dis/liked. Ad-

ditionally, future studies can further investigate why

perceived user experience and usability are better for

some sequences than for others, based on a revised

version of the cognitive ﬁt theory, and memory-based

theories of UX.

ACKNOWLEDGMENTS

We thank xdot GmbH for their support and for sharing

the code of “Meine Umwelt”.

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