“Is Computer Science the Right Study Program for Me?”: Concept

Development of a Mobile Self-Reﬂection App for Prospective University

Students

Sarah Aragon-Hahner

, Sophia Sakel

and Sven Strickroth

LMU Munich, Munich, Germany

{ﬁrstname.lastname}@iﬁ.lmu.de

Keywords:

Online Self-Assessment, Self-Reﬂection, Self-Reﬂection Support System, Decision Support System, Mobile

Application, Career Decision-Making, Study Program Choice.

Abstract:

Online self-assessments (OSAs) are common tools for university orientation. Usually, OSAs are multiple-

choice tests giving prospective students a recommendation on their suitability for the selected study program.

However, they lack true “self-assessment”, which is essential for informed decision-making. To better under-

stand users’ requirements of OSAs, we interviewed two experts, evaluated our university’s current computer

science OSA (N = 228), and conducted a survey with ﬁrst-semester students (N = 51). The results highlight

the importance of self-reﬂection and social exchange in study choices. Moreover, users expressed a wish for

ﬂexible and personalized content. On this basis, we conceptualized a mobile OSA app including the features

that were rated most positively in the pre-studies. The app allows for ﬂexible use by providing micro-content

in a clip format. In a ﬁrst proof-of-concept study (N = 11) the app was perceived as helpful and easy to use.

Moreover, users highlighted the concept’s potential to stimulate self-reﬂection.

1 INTRODUCTION

Career choice is one of the most important and life-

changing decisions for young adults. Many graduates

who want to study at a university have trouble de-

ciding on a major given the wide range of options.

The website Studyportals

lists more than 100,000

Bachelor degree programs all around the world. Even

after identifying a rough direction, prospective stu-

dents face problems in valuing the different options

and are uncertain about the outcomes of their deci-

sion (Germeijs and De Boeck, 2003). Yet, taking

the time to make an informed decision about a future

study program is important to complete it success-

fully. A discrepancy between expectations and the ac-

tual characteristics of a degree program is one of the

main reasons for high dropout rates (Ruthven-Murray,

2022). To prevent this and regulate access to limited

study places, more and more universities are introduc-

ing so-called “online self-assessments” (OSAs) for

prospective students (Hasenberg and Schmidt-Atzert,

https://orcid.org/0000-0001-7587-080X

https://orcid.org/0000-0002-6326-8018

https://orcid.org/0000-0002-9647-300X

https://studyportals.com, last accessed 2023-02-13

2014). Despite their well-established name, OSAs

often lack real self -assessment since they mostly

use multiple-choice questions to determine the user’s

ﬁt to the study program based on predeﬁned rules.

The ﬁnal result is a concrete recommendation as to

whether users should enroll rather than encouraging

them to reﬂect on their interests and expectations to

make an informed decision themselves. However,

internal factors, e. g., “the individual’s present self-

concept” (Harren, 1979, p. 122), play an important

role for potentially life-changing decisions such as ca-

reer choice.

To better understand the current problems and

requirements of OSAs, we conducted expert inter-

views (N = 2), analyzed the evaluation questionnaire

of the Ludwig Maximilian University of Munich’s

(LMU)

current OSA of the Bachelor’s degree pro-

gram in computer science (CS) (N = 228), and con-

ducted a survey with ﬁrst-semester CS students (N =

51). Based on the results of these studies and litera-

ture research, we developed a mobile self-assessment

app concept. The app includes the topics that were

rated most positively in the pre-studies, e. g., per-

sonal skills, expectations, or insights into occupa-

https://www.lmu.de, last accessed 2023-02-13

Aragon-Hahner, S., Sakel, S. and Strickroth, S.

"Is Computer Science the Right Study Program for Me?": Concept Development of a Mobile Self-Reﬂection App for Prospective University Students.

DOI: 10.5220/0011641400003470

In Proceedings of the 15th International Conference on Computer Supported Education (CSEDU 2023) - Volume 2, pages 163-171

ISBN: 978-989-758-641-5; ISSN: 2184-5026

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

163

Figure 1: Screenshots of the online self-assessment app that is conceptualized in this work: (a) home screen with image

carousel of different content modules, (b) overview page of the module “expectations of the course of study”, (c) to (e) three

subsequent clips of the category “required characteristics”.

tions. Each topic is separated into various units –

so-called clips. The clips can contain text, images,

video sequences or interactive elements such as check

boxes or sliders (see Figure 1). In contrast to the rigid

structure of current OSAs, the modular design allows

users to decide for themselves what content they want

to engage with and when. This enables ﬂexible use

over an extended period of time, leaving space for

self-reﬂection and decision-making. In a ﬁrst quali-

tative evaluation of our concept with eleven users, the

app was perceived as helpful and easy to use. Partic-

ipants clearly liked the clip format, and the majority

claimed they would use such an app if it existed.

2 RELATED WORK

2.1 Online Self-Assessments

Hasenberg et al. summarize relevant characteristics of

OSAs (Hasenberg and Schmidt-Atzert, 2014): their

target group are prospective students, they are eas-

ily accessible via the Internet, and they include ex-

ercises, e. g., on prior knowledge, or questions on in-

dividual interests and motivation. After completion,

users get direct feedback by comparing their answers

with the requirements for the course of study. OSAs

are characterized by the participants’ own responsi-

bility: As the name “self-assessment” suggests, the

result is not taken into account in the application pro-

cess and serves solely as a decision-making aid.

Based on extensive research of OSAs currently

offered by German universities (as of spring 2021)

The website https://www.osa-portal.de (last accessed

2023-02-13) offers an overview of German OSAs.

and related literature (Stoll, 2019; R

oder, 2017),

we identiﬁed the following common topics: general

suitability for studies, subject-speciﬁc exercises, per-

sonal characteristics, insights into studies, matching

of expectations, subject guidance, further informa-

tion, e. g., on professional ﬁelds. The content is usu-

ally presented with text, images and videos. Interac-

tive features are limited to multiple-choice questions.

Most OSAs provide a rigid structure and need to be

completed in one piece or in very large chunks. There

are also recent innovative approaches: Schulz et al.

present a virtual reality OSA for engineering stud-

ies (Schulz, 2020).

OSAs hold the potential to be a resource-saving

addition to the study counseling service, a consider-

ation of additional factors of study aptitude, a stimu-

lation of self-reﬂection, and an option for controlling

the access to study programs (Stoll, 2019; Heukamp

et al., 2009). However, based on the literature and our

research on currently available OSAs, we identiﬁed

the following drawbacks of state of the art systems:

(1) OSAs usually give recommendations based on

ﬁxed criteria which are often just subjective require-

ments compiled by professors and university staff.

To allow for actual self-assessment, graduates should

rather be empowered to independently evaluate their

suitability for their desired course of study. Sec-

tion 2.2 outlines the potential of technology as a tool

for self-reﬂection. (2) Most OSAs are content-heavy

and therefore optimized for desktop use. In con-

trast, young people primarily use their smartphones

to access the Internet (Howarth, 2022). Desktop-

optimized OSAs waste the opportunity to integrate

study orientation into the everyday life of prospec-

tive students. Section 2.3 shows the advantages and

limitations of mobile applications for career choice.

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164

2.2 Technology for Stimulating

Self-Reﬂection

Designing for self-reﬂection is an emerging

topic in Human-Computer Interaction (HCI) re-

search (Baumer et al., 2014; Bentvelzen et al.,

2022). A recent literature review of reﬂection

support systems shows an “increasing trend in HCI

studies that report on artefacts designed to enhance

reﬂection” (Bentvelzen et al., 2022, p. 2:9). Typical

application areas are learning, e. g., self-regulated

learning (Carter Jr et al., 2020; Maharsi, 2018; Loksa

et al., 2020) or reﬂective learning (Rivera-Pelayo

et al., 2012) and health, e. g., self-tracking on food

intake (Sun et al., 2020), sleep (Choe et al., 2015),

or general physical activity (Gorm and Shklovski,

2017). Only few recent publications discuss self-

reﬂection support tools for career choice: In their

work with underrepresented job-seekers, Dillahunt et

al. evaluate tools that incorporate positive feedback

and self-reﬂection (Dillahunt and Hsiao, 2020).

Aragon Bartsch et al. aim to stimulate self-reﬂection

by providing realistic job insights (Aragon Bartsch

et al., 2021).

Bentvelzen et al. identiﬁed four key aspects that

describe how support for reﬂection is implemented

in state of the art systems (Bentvelzen et al., 2022):

(1) Offer users a new point of view through a temporal

perspective, e. g., by reﬂecting on the future, (2) in-

clude conversations to add a social dimension, (3) let

users compare their current status to an ideal (abso-

lute reference) or to others (social reference). (4) Help

users discover something new. We are the ﬁrst to in-

corporate all of these four resources in the design of

an online self-assessment application.

2.3 Designing Mobile Interactions

through Micro-Tasking

Chunking, or breaking content into smaller micro-

tasks, is a promising approach in mobile interac-

tion (Cheng et al., 2015). This method addresses the

problems of limited screen size (Ahmad et al., 2018)

and the usually short duration of smartphone inter-

action, which is prone to interruptions (Leiva et al.,

2012; Nagata, 2003). When applied in the learn-

ing domain, this approach is called “micro-learning”

or “learning bits”. Major et al. deﬁne small learn-

ing units presenting information to the learner in

an appropriate size so that it can easily be pro-

cessed (Major and Calandrino, 2018). Another popu-

lar domain using this approach is micro-productivity:

Micro-productivity apps are designed to help users

work on the go and use their time productively by

breaking down complex tasks, such as editing doc-

uments (Iqbal et al., 2018) or programming (Williams

et al., 2019). Chunking is also applied in per-

sonal informatics by dividing large data sets to re-

ﬂect more frequently on small portions of informa-

tion. Jimenez Garcia et al. describe this approach as

“active mini-cycles of self-reﬂection”, which can lead

to a deeper understanding of complicated issues, and

ultimately more informed decisions (Jimenez Garcia

et al., 2014). Aragon Bartsch et al. use the concept of

micro-tasking in the career choice domain to provide

students with realistic insights into the working life

of professionals (Aragon Bartsch et al., 2021). In this

work, we use the concept of micro-tasking to provide

users with a large amount of information on the CS

study program. By dividing the content into smaller

units, users can process the information in their own

pace, leaving room for self-reﬂection. This concept

allows ﬂexible use at home or on the go, according to

individual preferences.

3 REQUIREMENT ANALYSIS

To inform the design of our prototype, we interviewed

two vocational advisors. Moreover, we analyzed the

evaluation questionnaire of the LMU’s current CS

OSA (N = 228) and conducted a survey with ﬁrst-

semester students who had participated in the OSA

before their enrollment (N = 51).

3.1 Expert Interviews

We conducted semi-structured interviews with two

experienced vocational student advisors: a high-

school teacher (E1) and the head of our univer-

sity’s student advisory ofﬁce (E2). The two most

relevant insights we gained are the importance of

self-reﬂection and social exchange. According to

the experts, self-reﬂection is essential for study pro-

gram choice. To support the study orientation phase,

prospective students need to reﬂect on their own

skills, values, and expectations, which can be sup-

ported by providing information and helping them ask

themselves relevant questions. According to E1, ev-

ery consultation should support the students in a way

that allows them to make the ﬁnal decision on their

own. This is also conﬁrmed by E2, highlighting that

many personal factors contribute to this potentially

life-changing decision. E2 also stated that peer ex-

change is beneﬁcial for study orientation. In particu-

lar, contact with students or professors of the respec-

tive discipline can give a ﬁrst impression of the pro-

gram, answer questions and provide personal experi-

"Is Computer Science the Right Study Program for Me?": Concept Development of a Mobile Self-Reﬂection App for Prospective University

Students

165

ence reports. These are valuable insights to clarify

possible questions, achieve realistic expectations of

the study program, and consider one’s own ﬁt.

3.2 Evaluation of our University’s

Current OSA

The LMU’s current CS OSA is a typical multiple-

choice online test. It includes subject-speciﬁc ques-

tions on problem-solving behavior, technical exper-

tise, and logical thinking. Due to its text-heavy con-

tent, it is not optimized for mobile use. Participa-

tion is mandatory to enroll in the Bachelor’s degree

program, but the result is not considered for admis-

sion. In addition to the aptitude test, the OSA contains

pre and post-questionnaires for evaluation purposes.

To gain insights into the assets and drawbacks of the

OSA, two researchers conducted a Thematic Analy-

sis (Braun and Clarke, 2006; Nowell et al., 2017) of

the (optional) open question “Do you have any further

comments on the online self-assessment?”.

242 of 2539 participants gave an answer to this

question between June 11th, 2019, and November

24th, 2020. After data cleansing, we separated the an-

swers of 228 participants into 253 single statements

and grouped them among the four derived themes

“general”, “efﬁcacy”, “content”, and “implementa-

tion”. The overall sentiment of the answers was pos-

itive: 24 participants claimed to have liked the on-

line self-assessment and 19 expressed their gratitude

for the test. Participants commented positively on the

OSA’s efﬁcacy: they found it fun (10), helpful (6), in-

formative (4), and inspiring (4). Moreover, 13 users

stated to have found the test helpful to assess their ﬁt

to the degree program, whereas only 3 claimed the

opposite. The main critique was on the content level:

People criticized the lack of solutions for the tasks

(42). Moreover, some participants did not understand

(28) or like the questions (15). On the positive side,

a number of people found the content interesting (10)

and liked the questions (4), but some also wished for

a different type of content (9), e. g., questions that are

better suited for dyslexics. Users had few but mostly

negative comments on the structure, e. g. they wished

for more tasks (7) and did not like the distribution of

points (6).

From the evaluation, we conclude that the gen-

eral idea of an online self-assessment is well received

and can be a fun and helpful method of assessing the

user’s ﬁt to the prospective study program. However,

the preferred length and content of the test underlie

individual preferences. Therefore, ﬂexible content ac-

cording to the user’s needs is a major goal of our con-

cept development.

3.3 Survey with First-Year Students

To complement the ﬁndings of the OSA evaluation,

we conducted an online survey with ﬁrst-year CS stu-

dents at the LMU. The survey included open-ended

questions about what students wish they had known in

retrospect before they began their studies, what they

(dis)liked about the current OSA, and what content

they missed. We also included Likert ratings on the

perception of the current OSA and the test’s capabil-

ity to stimulate self-reﬂection. In addition, students

had to rate possible features of a mobile OSA app

with German school grades from 1 (very good) to 6

(very bad) and could propose additional features. The

questionnaire concluded with a 5-point Likert rating

of whether they would have used a mobile OSA app

if it existed and whether they would have preferred a

mobile version over the current desktop-based OSA.

Two researchers again performed a Thematic Anal-

ysis of the open-ended questions and discussed any

discrepancies. For reasons of length, we only report

the results relevant to the design of the prototype.

We recruited participants via the mailing list of a

compulsory ﬁrst-semester lecture. 51 people with an

average age of 22.5 years (min = 18, max = 46) com-

pleted the questionnaire (27 male, 22 female, two di-

verse). All of them participated in the current OSA as

part of their university application process.

When asked what they would have liked to know

in advance about their study program, 30 participants

reported speciﬁc information gaps. They would have

wished for “more information” (4) as well as more de-

tails on course preparation (6), requirements for stu-

dents (5), prior math knowledge (4), and the univer-

sity (4). Less frequently mentioned aspects were the

unexpected theory-heavy nature of the program (2),

a wish for information on minor subjects (2) and ca-

reer opportunities (1), and individual problems with

the study start (2). The rating of the item “The test

made me think about my suitability for the computer

science study program.” received mixed results (Me-

dian ˜x = 3, 5-point Likert scale from 1=“fully dis-

agree” to 5=“fully agree”). We observed a similar re-

sult for the statement “Participating in the OSA gave

me a more accurate idea of the computer science pro-

gram at the LMU.” (Median ˜x = 3). In response to the

open-ended question “In what way did the test make

you reﬂect?” 17 participants stated that did not at all

reﬂect through the OSA. Four participants were made

unsure by the test whether the program was feasible

for them. Three people stated that the test revealed a

lack of prior knowledge. In contrast, eleven partici-

pants could positively conﬁrm their choice. Another

seven students stated that the test was fun and moti-

CSEDU 2023 - 15th International Conference on Computer Supported Education

166

vating. Five participants found that the OSA could

provide insights into the study program and four were

encouraged to engage further with the OSA’s content.

When asked “What content and topics did you miss

in the OSA?” participants responded that they would

like to see more math questions (8) and more pro-

gramming and computer science tasks (7).

To identify relevant content modules, we extracted

the items that were most frequently rated as very good

(1) or good (2). The resulting features are: sample

assignments (88 %), insights into future career op-

tions (86 %), contact to enrolled students and mentor-

ing (78 %), videos of example lectures (75 %), contact

to student advisors (75 %), further links and informa-

tion material (73 %), and information about student

life in the city (67 %). For the open-ended questions

on participants’ own ideas, we grouped the answers

of all 51 participants into the themes “exchange and

contact” (28) “information on professors” (4), “video

recordings from lectures” (11), “experience reports”

(7), “career options” (6), “information about study

program content” (7), “information about personal

study management” (3), and “presentation of minor

subjects” (2).

The majority of participants indicated that they

would have liked to use an app for study orientation

(Median ˜x = 4). Opinions varied on whether stu-

dents would have preferred a mobile version over the

current desktop-based system (Median ˜x = 3). This

might be due to the text-heavy nature of the current

OSA, which is not suitable for mobile use.

From the survey, we conclude that OSAs are gen-

erally perceived as helpful. There is an interest in a

mobile version, but the current content is not easily

transferable. Participants’ responses also suggest that

self-reﬂection can only be partially supported through

the current version of the OSA. The features proposed

by the students are diverse, so it might be difﬁcult to

implement a one-size-ﬁts-all solution. Therefore, the

mobile app should be designed in a way that the con-

tent can be adapted to personal preferences.

4 CONCEPT

Based on the results presented in the previous sec-

tion, we derived a mobile OSA app concept and cre-

ated an online click-dummy with the Figma prototyp-

ing software

(see Figure 1). The app is structured

in ﬁve different modules, including the most popu-

lar topics from the survey with ﬁrst-year students: (1)

“expectations of the course of study”, an assessment

https://www.ﬁgma.com, last accessed 2023-02-13

of personal characteristics and abilities followed by

a comparison with necessary qualities as a CS stu-

dent, (2) “sample assignments” representing impor-

tant study content and allowing users test their per-

sonal abilities, (3) “everyday university life” to give

an overview of typical student life, (4) “career oppor-

tunities” to show future possibilities, and (5) a “com-

puter science quiz” about domain facts. The different

categories are displayed as an image carousel on the

start feed of the prototype (see Figure 1a). As shown

in Figure 1a-b, clicking on a category (e. g., expecta-

tions of the course of study) shows the overview of

clip sequences available for this topic (e. g., required

characteristics). Users can see their progress through

the border around the modules and add them to their

personal collection by clicking the star icon in the up-

per right corner. Each clip sequence covers one spe-

ciﬁc aspect of the selected category and is separated

into multiple clips, which represent the micro-content

units (see Figure 1c-e). Clips usually contain pictures

or short videos, short texts, e. g., questions or explana-

tions, and optional interactive elements such as sliders

or buttons for user input. We are adopting a success-

ful social media feature, the so-called “story” func-

tion

that is well-suited for mobile use. The individ-

ual clips (see Figure 1c-e) are only seconds to a few

minutes long and together they form a thematic block.

Users again have the option of selecting and book-

marking clips they want to save and can thus compile

the desired content themselves. Moreover, we include

two social components as recommended by E2 and

the literature (Bentvelzen et al., 2022). First, the app

offers live Q&A sessions with enrolled students and

university staff (see Figure 1a). App users can hand

in questions before each live session or ask them di-

rectly in the chat. Second, we include a “question of

the week” feature, in which multiple CS students an-

swer the same question, for example: “What skills do

you think are required to study computer science?”.

A new question is added to the collection every week.

The OSA app aims to support self-reﬂection

by applying the design resources identiﬁed by

Bentvelzen et al. (Bentvelzen et al., 2022): The tem-

poral perspective is incorporated through tasks on

prior knowledge (past) and information on career op-

portunities (future). The live Q&A sessions provide

conversations between the students and establish con-

tact with university members. Exercises on prior

knowledge and the “question of the week” feature

allow for comparison with a “typical” computer sci-

ence student. Finally, the clip-format facilitates a self-

directed discovery of information.

see, e. g., https://about.instagram.com/features/stories,

last accessed 2023-02-13

"Is Computer Science the Right Study Program for Me?": Concept Development of a Mobile Self-Reﬂection App for Prospective University

Students

167

5 USER STUDY

To perform a ﬁrst proof of concept, we evaluated the

prototype in a qualitative user study. We recruited

high school students with the prerequisite of being

interested in the CS study program (N = 11). The

goal of the study was gathering feedback on the clip

format and evaluating the app’s potential to support

self-reﬂection on study choice.

Nine students and two recent graduates (ﬁve fe-

male, six male) took part in the study. The partici-

pants had to complete a short online questionnaire on

demographics and their current status of study orien-

tation. We then performed online “think aloud” in-

terviews (Charters, 2003) via the video conferencing

software Zoom

. The sessions were recorded for tran-

scription purposes and took 45 to 60 minutes per user.

Participants were compensated with 10 euro vouch-

ers for an online store. After short introduction, we

guided the participants through various usage scenar-

ios to explore the prototype: First, participants should

familiarize with the welcome track and home screen.

Before exploring the category “everyday university

life”, we asked people what content they expected in

this module. After browsing the category, we asked

users how they liked the content presentation through

clips. We repeated the process for the “career op-

portunities” module and asked follow-up questions

if necessary. We ﬁnally directed users towards the

modules “sample assignments” and “CS quiz” and let

them freely explore the content. We asked questions

about the style and difﬁculty of the provided tasks as

well as the level of interactivity. In a second scenario,

we asked participants to further explore the interac-

tion with the clip format in the “expectations of the

course of study” category. The ﬁnal scenario treated

the live Q&A sessions as well as the “question of

the week” and users’ attitudes towards these features.

Participants ﬁnally had the opportunity to state any

further remarks on the app’s content and implementa-

tion. We concluded the study with another short on-

line questionnaire including eight Likert items on the

overall impression and usability of the app as well as

the question of whether participants would use such

an app if it existed. The examiner took notes during

the interviews and a second researcher reviewed the

resulting data table to verify the results.

6 RESULTS

Most participants stated that they had not yet in-

formed themselves in detail about studying CS (Me-

https://zoom.us, last accessed 2023-02-13

dian ˜x = 3, 5-point Likert scale from 1=“fully dis-

agree” to 5=“fully agree”) and also did not yet have

a precise idea about the course of studies (Median

˜x = 3).

Observations showed a generally positive user ex-

perience with the prototype. This is also reﬂected in

the Likert ratings: In the post-study questionnaire,

all eleven participants rated the app as helpful, easy

to use, and clearly structured (Median ˜x = 5 for all

statements). They perceived the app’s content as well-

integrated (Median ˜x = 5). Moreover, all users men-

tioned during the “think aloud” interviews that the

app holds the potential to stimulate self-reﬂection on

study choice. Especially the sample assignments (4)

and the expectations of the course of study (3) were

rated as helpful for promoting self-reﬂection. The live

Q&A sessions and the “question of the week” mod-

ule were also clearly liked by users. According to the

participants, these features facilitate connecting with

enrolled students (4) and hold the potential to give re-

alistic insights (3). One participant also noted that

new content on a regular basis increases engagement

with the app. All participants claimed that they could

imagine participating in the live sessions.

The clips were perceived as a suitable way of con-

tent presentation by all users. This is reﬂected in the

verbal feedback as well as the Likert item “The clip

format is a good way of displaying the app’s con-

tent.” (Median ˜x = 5). In particular, ﬁve users pos-

itively highlighted the choice of short video elements

to convey real insights. Seven participants stated that

the functionality of the clip mode was known to them

through other apps, while four needed a short intro-

duction: We explained the touch gestures to skip or

pause the clips and how to return to the overview

page. Afterwards, all users felt conﬁdent navigating

the app.

In the post-study questionnaire, the majority of

users responded positively to the question of whether

they would use such an app if it existed (Median ˜x = 5,

min = 3).

7 DISCUSSION AND OUTLOOK

A limitation of our work is that the app’s design was

informed by the feedback of ﬁrst-year students, i. e.,

people who already decided for studying CS. Unfor-

tunately, we were not able to contact students who

made a decision against studying CS at our university

or had dropped out during their course of studies. We

did not involve high school students in the require-

ment analysis since they are often overwhelmed by

the career choice process (The Behavioural Insights

CSEDU 2023 - 15th International Conference on Computer Supported Education

168

Team, 2016; Kulcs

ar et al., 2020) and might ﬁnd it

hard to imagine what would help them on an abstract

level (Myers, 1994). A second limitation is that our

concept is based on the CS OSA of the LMU. There-

fore, not all results might be transferable to other

ﬁelds of study and universities. Moreover, the eval-

uation of our concept was performed in a controlled

setting with a click-dummy prototype. However, we

think that our study presents a viable proof of concept

yielding interesting impulses for future research.

Our mobile app is designed to replace traditional

desktop-based OSAs. It is tailored to the smartphone

usage behavior of young adults (Howarth, 2022)

and offers the possibility for regular use in small

chunks (Cheng et al., 2015). Our pre-studies have

shown that the content preferences of users differ in

the amount and difﬁculty of tasks. To allow for ﬂexi-

ble use, the content should be selected with great care.

Tasks should be presented as a broad range of op-

tions rather than mandatory skills to avoid discourag-

ing qualiﬁed participants with less prior knowledge.

In our ﬁnal user study, participants highlighted the

potential of self-reﬂection support through a compar-

ison of expectations with the actual properties of the

study program and through social features. This is

in line with the ﬁndings of Bentvelzen et al., who

identiﬁed conversation and comparison as two key as-

pects of self-reﬂection support systems (Bentvelzen

et al., 2022). Current OSAs often neglect these social

aspects despite their importance for career decision-

making (Harren, 1979). We implement social features

through live sessions and the “question of the week”.

Our concept therefore relies on the active participa-

tion of university staff and students. The app’s con-

tent needs to be maintained and live sessions require

a moderator willing to offer them regularly. In return,

the concept scales well to inform a large number of

users. Up-to-date content potentially leads to a better

image of the university and more informed prospec-

tive students (Stoll, 2019). To reduce the effort of

live sessions, we also see potential in (asynchronous)

online forums or other question-and-answer formats,

e. g., FAQ. In contrast to conventional OSAs, we re-

frain from making a speciﬁc recommendation. This

might be unfamiliar to users who are used to tests

with a ﬁnal result. Future work needs to investigate

whether this could have a negative impact on user sat-

isfaction.

As a next step, we plan to implement a working

prototype for ﬁeld testing. We would like to investi-

gate whether the app is used in several short sessions

as intended. In addition, we would like to see if users

work through the entire app or choose their preferred

content based on their interests. It would also be in-

teresting to study the level of engagement in the live

sessions and whether this feature facilitates social in-

teraction. A long-term goal could be to explore per-

sonalization and adaptive features, such as gradually

unlocking new content modules, e. g., more difﬁcult

sample assignments.

8 CONCLUSION

In this work, we presented the concept development

of a mobile OSA app for CS studies. We ﬁrst per-

formed a requirement analysis by interviewing two

experts, evaluating the LMU’s current OSA (N =

228), and conducting an online survey with ﬁrst-

semester students (N = 51). In contrast to traditional

OSAs, the goal of our concept is to stimulate self-

reﬂection in order to assist users in making an in-

formed study decision. We apply the micro-tasking

method to optimize the OSA for mobile devices and

allow for repeated use in multiple sessions. The app

consists of different content modules composed of

short clips that can be viewed by users in their de-

sired order. A ﬁrst proof-of-concept study (N = 11)

showed that the app was well-received by users. They

liked the clip format as a means of content presen-

tation and conﬁrmed a possible stimulation of self-

reﬂection through the app’s features. We hope that our

concept inspires future research in the area of mobile

decision support systems, especially for life-changing

decisions that require careful consideration and a high

level of self-awareness.

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