=Paper=
{{Paper
|id=Vol-2358/paper-05
|storemode=property
|title=Future Skills: How to Strengthen Computational Thinking in all Software Project Roles
|pdfUrl=https://ceur-ws.org/Vol-2358/paper-05.pdf
|volume=Vol-2358
|authors=Gudrun Socher,Sarah Ottinger,Veronika Thurner,Ralph Berchtenbreiter
|dblpUrl=https://dblp.org/rec/conf/seuh/SocherOTB19
}}
==Future Skills: How to Strengthen Computational Thinking in all Software Project Roles
==
https://ceur-ws.org/Vol-2358/paper-05.pdf
Future Skills: How to strengthen
computational thinking in all
software project roles
Gudrun Socher*, Sarah Ottinger*, Veronika Thurner*, Ralph Berchtenbreitero
*Department of Computer Science and Mathematics | o Department of Tourism
Munich University of Applied Sciences, .@hm.edu
Abstract like product owners, or user experience designers (see
The digital transformation leads to software systems Figure 1), as well as for even more general roles such
pervading almost all spheres of private and profes- as product management or project management.
sional life. To ensure that these software systems are
designed and successfully implemented as needed, in-
tensive collaboration is essential in the key roles in
software projects, in particular for the roles of product
owner, user experience designer, as well as software
engineer. The collaboration of people with usually dif-
ferent levels of IT-savviness requires the appropriate
skills of those involved, which are also called Future
Skills. Computational thinking is an important skill
for everyone involved in software projects, no matter
which role they are in.
We describe an interdisciplinary tool-based
teaching-and-learning program where we build
virtual voice-based assistants (voice apps for Amazon
Alexa) in interdisciplinary student teams to train
computational thinking and collaboration skills. A
first competency test validates the effectiveness of our
approach. Figure 1: Key roles in software projects.
Motivation: Future Skills1 Software products can only be successful if the key
In current digitalization initiatives, there is a lot of roles work hand in hand in software projects: prod-
discussion on how to increase graduation numbers uct owners with their knowledge of the application
in software engineering related study programs in or- domain and product vision, user experience designers
der to have more skilled people driving the ongoing who guide human-computer interaction, and software
digital transformation. In this discussion, however, engineers being responsible for software implemen-
we often forget that digitalization is always related tation. The skills and competencies related to these
to an application domain. The digital transformation roles are essential in successful projects. They are
benefits strongly if software-related skills are strength- required to successfully meet the challenges of digital
ened not only for the core software engineering roles, transformation.
but also for less-technical roles in software projects How do we best train the talents for the ongoing
digital transformation, and what exactly do future em-
1 With ’Future Skills’ we refer to ’competencies’ required by uni-
ployees need to learn? Stifterverband, a joint initiative
versity graduates across all majors in the coming years. These
of German organizations, has published a discussion
competencies are necessary to meet digital requirements as they
are currently expected in business and society (cf. (Kirchherr et al., paper in September 2018 together with McKinsey &
2018)). Company where they address three core competency
V. Thurner, O. Radfelder, K. Vosseberg (Hrsg.): SEUH 2019 56
Future Skills: How to strengthen computational thinking in all software project roles
Gudrun Socher, Sarah Ottinger, Veronika Thurner und Ralph Berchtenbreiter, HS München
Figure 2: Future Skills: Digitalization and new job profiles lead to two challenges for companies. (1) Jobs shift
towards IT related profiles. (2) Work processes and work requirements change for the majority of employees.
Many employees thus need a modified set of digital and non-digital key competencies (cf. (Kirchherr et al.,
2018)).
categories driving the digitalization (Kirchherr et al., clude - among others - data literacy, collaborative skills
2018). Figure 2 illustrates competencies related to and digital learning skills. Based on Wing (2006),
the digital transformation as well as to new forms of computational thinking can be considered as a pre-
work. requisite for digital learning. By now, the relevance
With changes in the job portfolios and new forms of all these skills for virtually any member of our
of work, there has been an expected shortage of quali- professional work force is undisputed and widely rec-
fied people for some time now. In particular, the job ognized.
market will be increasingly dominated by job profiles
that are heavily related to software engineering. Ac- How can we integrate the development of these
cordingly, a lot of effort is spent on increasing the competencies into study programs? Curricula are of-
number of graduates of software engineering related ten overfull and the amount of available (and often
degree programs, in order to increase the number of essential) knowledge is increasing in almost every
software engineers in the market and thus to meet the application domain. Solutions have to be found to
growing demand for qualified specialists. systematically integrate key competencies required
At the same time, it is essential to strengthen ev- for the digital transformation into the teaching-and-
erybody’s digital and non-digital key competencies. learning processes without weakening the core foun-
Digitalization is not just an IT issue. Digitalization dation in the respective application domains.
is inherently linked to the digital transformation and
thus the creation of digital automation or digital assis- Project-based learning is a successful instructional
tance systems in an application domain. Therefore, it learning format that has been proven to systematically
is just as important for employees and students of all strengthen some of the required future skills (Bell,
application domains to acquire software engineering 2010). Interdisciplinary project-based learning is even
competencies. more effective, as team diversity is an additional suc-
Stifterverband (Kirchherr et al., 2018) stresses that cess factor for creative, goal-oriented collaboration in
both digital and non-digital key competencies are a addition to the future skills mentioned above (Digital-
must-have for all current students. Key digital skills in- isierung, 2016; Meier et al., 2007).
V. Thurner, O. Radfelder, K. Vosseberg (Hrsg.): SEUH 2019 57
Future Skills: How to strengthen computational thinking in all software project roles
Gudrun Socher, Sarah Ottinger, Veronika Thurner und Ralph Berchtenbreiter, HS München
Related work ciplinary student teams. To achieve this, we use a
Wing (2006) introduced the importance of compu- tool-chain for creating voice-based virtual assistants
tational thinking for computer science-related tasks (such as Amazon Alexa), as well as by using Github.
12 years ago. She defines computational thinking as Over the last years, the usability of many tools for
the interplay of decomposition and abstraction and creating software systems has evolved and improved
recommends strengthening computational thinking in significantly. Digital tools in the context of software
all study programs. engineering are nowadays no longer editors that are
The ability of abstract thinking, in turn, has long specifically tailored to computer nerds. Rather, nowa-
been recognized as a key competency of many techni- days they often are web-based interactive tools that
cal disciplines, especially for computer science (Bucci are fun to use and that guarantee good results even
et al., 2001; Kramer, 2007) and software engineer- for people without IT- and software engineering skills.
ing (Ghezzi et al., 2002). A distinction is made be- Our student teams include tourism majors and com-
tween static and dynamic abstraction, i.e. the abstrac- puter science students. Github is used as a source code
tion of structural entities (static) and of processes or repository by computer science students, as well as a
behavior (dynamic) (Davis et al., 2014). ticketing and project communication tool for all stu-
The central element of computational thinking is a dents. We furthermore use the Github project board
problem-oriented (as opposed to a solution-oriented) as a virtual agile board. In this way, we enable all
approach (Lorenz and Wurzer, 2014). It is essential to students to make an active, creative contribution in
get to the root of a problem or task, to abstract it and a digital software project even without programming
to understand contexts and regularities. The goal is to knowledge.
reduce the complexity of the task (keyword: decom- The non-IT students (i.e. students of an application
position (Wing, 2006)) and to systematically limit the domain) are either in the role of product owner or
choice of possible solutions. Only then are potential user experience designer. The role of product owner in-
solution components identified and abstracted into cludes gathering and aggregating the users’ needs and
an overall behavior. Computational thinking requires desires which requires static abstraction capabilities.
not only the ability to decompose, but also the ability The user experience designer role focuses on reflecting
to abstract behavior (Wing, 2006), thus requiring a what users expect. This definitely requires consid-
very high degree of dynamic abstraction in particular. eration of dynamic processes. In parallel, computer
Since algorithms always work on data entities, a cor- science students deepen their experience in the role
responding degree of static abstraction is necessary. of software engineer by using new technologies for the
In teaching-and-learning practice, it can be ob- implementation of voice-based assistants.
served that not all students have a sufficient level We use pseudonymized pre- and post-tests to ana-
of abstraction and computational thinking to be able lyze to what extent our interdisciplinary tool-based
to cope with the study program requirements. This is teaching-and-learning program actually fosters the ad-
especially true for students of subjects related to com- dressed competencies of static and dynamic abstrac-
puter science. Accordingly, various approaches have tion in the students.
been developed to systematically strengthen these
abilities (Hazzan and Kramer, 2007; Böttcher et al., Computational thinking and
2016). These approaches mainly focus on promot- voice-based assistants
ing computational thinking in students of computer Voice-based virtual assistants (voice apps) are cur-
science related majors, but do not provide teaching- rently being massively pushed by major software com-
and-learning concepts for strengthening these skills in panies. Examples are Amazon Alexa, Google Assistant,
students of non-technical subjects, where little to no Cortana, and many more. In particular, Amazon and
IT-affinity can be expected. Google provide well-designed, web-based tools that
developers can use to create new voice apps with their
Goals cloud offerings. These tools and cloud offerings are
In this work, we develop and apply a teaching-and- available free of charge for educational use. In ad-
learning program for promoting computational think- dition, the tools are so sophisticated that it’s fun to
ing in students – and, as an essential basis for this, play with them. In just a few minutes, cool voice-user-
for fostering students’ static and dynamic abstraction interfaces can be created without previous knowledge,
competency. To this end, we develop a teaching-and- so first success can be achieved quickly. Figure 3 shows
learning program for interdisciplinary, project-based the Alexa Developer Console, a tool for creating voice
learning that addresses computer science students as apps for Amazon Alexa.
well as non-IT students. Our concept takes into ac- To develop an application for voice-based assistants,
count our students’ prior knowledge as well as their the development team must design the Voice User
individual learning requirements. Interface (Voice UI) and implement the business logic.
In our teaching-and-learning program, we create A voice UI must be structured in such a way that
an easy introduction to digital projects for interdis- the dialogue appears natural to the users. At the
V. Thurner, O. Radfelder, K. Vosseberg (Hrsg.): SEUH 2019 58
Future Skills: How to strengthen computational thinking in all software project roles
Gudrun Socher, Sarah Ottinger, Veronika Thurner und Ralph Berchtenbreiter, HS München
Figure 3: Alexa Developer Console: Web-based tool to create voice apps for Amazon Alexa.
same time, the dialogue must be designed so that the behavior). This process is rather simple for the joke-
goals expressed by the users or the intentions behind of-the-day application (see Figure 5).
them can be clearly identified and assigned to the
The design of a dialog for a voice-based virtual
implemented business logic. In the jargon of voice UIs,
assistant is thus well suited to train both static and
these intentions are called intents. Each intent must
dynamic abstraction skills, and to guide students to-
clearly invoke a feature of the implemented business
wards computational thinking. Therefore, we use
logic.
dialog design and implementation for a voice-based
Figure 4 shows an example dialog with Alexa for assistant as a task for an interdisciplinary tool-based
an application called the "joke-of-the-day". A person teaching-and-learning program to strengthen compu-
starts the voice app and gets told one joke. More jokes tational thinking.
can be requested. If no more joke is desired, the voice
app closes.
Structuring a dialogue into intents strengthens both Interdisciplinary project to
static and dynamic abstraction abilities. strengthen computational thinking
The identification of the individual intents in a dia-
logue requires a static abstraction. For example, the Our didactic concept for the promotion of computa-
joke-of-the-day application is structured into the fol- tional thinking and communicative future skills struc-
lowing intents and the resulting dialog steps: tures the learning process into several phases (see
Table 1). Initially, the students are taught core con-
• welcome cepts in non-interdisciplinary groups.
More precisely, the computer science students first
• joke
learn the technical basics of voice-based assistants,
• closing and are introduced to tools for designing and imple-
menting them. Furthermore, computer science stu-
The individual dialog steps or intents must then dents learn requirements engineering. Having that
be arranged in a meaningful sequence (the dynamic down their belts, these students are well equipped to
V. Thurner, O. Radfelder, K. Vosseberg (Hrsg.): SEUH 2019 59
Future Skills: How to strengthen computational thinking in all software project roles
Gudrun Socher, Sarah Ottinger, Veronika Thurner und Ralph Berchtenbreiter, HS München
Task Computer Science Students Students of Application Domain
Introduction to voice- Examples and tutorial for creating a Examples and simulation of dia-
based assistants first voice app logues between two partners
Idea for voice app and
Invocation, intents, slots Generating ideas and defining MVP
its structure
Concept for Voice App Requirements engineering Specification of a first dialogue
Invocable, Alexa Developer Console,
Using tools Alexa Developer Console, Github
Github
1st Pitch: Students of application domain pitch their ideas to find computer science students for their
developer team.
1st Sprint 1st Release Refining the dialogues
2nd Sprint 2nd Release Test 1st Release → Change Requests
2nd Pitch: Voice app demos by computer science students.
Test 2nd Release → Final changes and
3rd Sprint 3rd Release
improvements
3rd Pitch: Final presentation with guests.
Table 1: Structure of the teaching-and-learning process throughout the semester for our interdisciplinary
tool-based teaching-and-learning program for developing Alexa voice apps.
take on the role of software engineer in the interdisci- development team. Following these pitches, mixed
plinary teams that are formed later on. teams are formed each consisting of computer science
The task of the application domain students is to students and students of the application domain.
develop an idea for a voice-based assistant (in this
Within the interdisciplinary teams, the computer
case an Alexa voice app). For this idea, they then
science students give feedback to the students of the
define the dialogue between the user and the voice-
application domain on the design of the dialog that
based assistant required for a Minimum Viable Product
underlies the respective prototype. Based on this, the
(MVP). This dialog thus contains at least those steps
voice user interface is subsequently refined together.
and procedures that are necessary for the minimal
The computer science students take their "natural role"
functional implementation of the idea. It is important
as software engineer in the interdisciplinary project.
to break down the dialogue into short, simple steps
The application domain students, on the other hand,
and to structure it. The complexity of creating the
are both product owner and user experience designer.
voice app is significantly greater than the example
So they design the interaction between the user and
of the "joke-of-the-day" shown in Figure 4. Suitable
the voice-based assistant in such a way that this in-
ideas for voice apps are (quiz) games, guides, or useful
teraction is technically meaningful and needs-based
assistants.
from their own perspective. So far in our didactic con-
The dialogue is tested and tuned by the students
cept, user experience design is not explicitly taught
of the application domain. Then, using Invocable2 ,
due to lack of time. However, it would be desirable to
the students of the application domain create a first
improve this in the future.
interactive but hard-coded prototype of the voice app.
The interdisciplinary collaboration in the teams be- Computer science students implement the back-end,
gins when the students of the application domain while students of the application domain are respon-
present their ideas to the computer science students. sible for the front-end in the implementation phase
The students of the application domain pitch the pro- of the voice-based assistant. A simple form of Scrum
totypes of their voice-based assistants to computer is useful for organizing the development process into
science students and try to motivate them to join their sprints, thus structuring the semester process. Github
repositories, including the integrated project boards
2 Invocable: https://www.invocable.com and the integrated ticketing system (Github issues),
V. Thurner, O. Radfelder, K. Vosseberg (Hrsg.): SEUH 2019 60
Future Skills: How to strengthen computational thinking in all software project roles
Gudrun Socher, Sarah Ottinger, Veronika Thurner und Ralph Berchtenbreiter, HS München
Figure 5: Dynamic structure of the example applica-
tion joke-of-the-day.
Assessing computational thinking
skills
As we were interested in investigating the develop-
Figure 4: An example dialogue with a voice-based ment of our students’ computational thinking skills
virtual assistant telling jokes. during the interdisciplinary tool-based teaching- and
learning program, students were requested to work
on a competency test at the beginning (week 2) and at
the end of the semester (week 11). The test covered
support team collaboration through an appropriate two facets of computational thinking, namely static
tooling infrastructure. and dynamic abstract thinking processes.
This teaching-and-learning program was used for The test was taken by two groups of students, all of
the first time in the winter semester 2018/19 at Mu- which were working on voice-based virtual assistants
nich University of Applied Sciences. Four computer in a project based way. The first group are computer
science students (3rd semester) and two to three stu- science students and students of the application do-
dents of tourism management (6th semester) form a main who worked together in interdisciplinary teams.
mixed team for the pilot run of our program. The other group, our control group, consisted purely
of computer science students.
Even if static and dynamic abstraction are not ex- All these students were asked to solve two tasks
plicitly addressed, all students in this one-semester that both form our competency test and that require
interdisciplinary tool-based program train their static static and dynamic abstract thinking processes, re-
and dynamic abstraction abilities by structuring and spectively. Using pseudonyms allowed us to match the
specifying the dialogue between a person and the students’ pre- and post-tests and thus, to analyze their
voice-based assistant in such a way that a correspond- individual learning outcomes. (Regarding the tourism-
ing Alexa voice app can be built. All students (in- management students’ test performances, we will dis-
cluding application domain students) work with the cuss the results in the next section “Coding scheme
Alexa Developer Console and Invocable tools. The use of the abstract thinking test & first results”. The test
of tools enables all students to work with a working performances of the computer science students have
interactive voice app. The working prototype provides also been analyzed, but will not be presented in this
rapid feedback so that in particular the students of paper.)
the application domain can immediately check their
Our hypothesis is that the computational thinking
dialogue structuring.
skills of students that actively participated in our inter-
From our perspective, this interdisciplinary tool- disciplinary tool-based program increased significantly.
based teaching-and-learning setting is well suited to More specifically, we assume that all students benefit
foster our students’ abstraction skill and more effective from developing and implementing their innovative
in this area than regular class exercises. Furthermore, ideas on Alexa voice apps, as both the design and
standardized processes, such as completing Github the creation of voice-user-interfaces require static and
Issues in team communication, help to structure col- dynamic abstract thinking processes. Note that even
laboration. though we expect that students working in interdisci-
V. Thurner, O. Radfelder, K. Vosseberg (Hrsg.): SEUH 2019 61
Future Skills: How to strengthen computational thinking in all software project roles
Gudrun Socher, Sarah Ottinger, Veronika Thurner und Ralph Berchtenbreiter, HS München
plinary teams strongly train their collaboration skills • Criterion S3: presenting categories in a
during the course, we have not explicitly assessed structurally-sound way, e. g. as UML-diagrams.
theses skills in a test.
The first task of our competency test includes a • Criterion S4: using formal notations in a logically
menu of 22 different coffee specialties and requests consistent way.
the students to teach a new barista about the coffee • Criterion S5: recognizing familiar structures and
recipes. The menu contains pictures and ingredient realizing that the structures are coherent in a
lists for each coffee specialty. The challenge is to given situation.
structure the various coffees and their ingredients in
such a way that a new barista can quickly grasp and Dynamic abstract thinking processes are opera-
learn them. In the second task, students are asked to tionalized by defining these three criteria:
generalize the abstraction process they applied when • Criterion D1: identifying a coherent chain of pro-
solving the first task. cesses.
To successfully accomplish the second task, the par-
ticipants first have to become aware of their own • Criterion D2: presenting a coherent chain of pro-
actions, identify and structure those processes, and cesses in a structurally sound way.
derive a procedure that would be transferable to simi-
• Criterion D3: relating the identified chain of pro-
lar tasks. Therefore, they have to dynamically abstract
cesses to one’s own solution, e. g. using one’s own
from their own approaches and accurately document
approach as a basis for generalizing and inferring
their solutions. From our perspective, task 1 mainly
appropriate processes.
deals with static abstract thinking processes, whereas
task 2 covers dynamic abstract thinking processes. We considered two additional criteria, character-
Students are allowed 20 minutes for working on the izing one’s ability for self-reflection as well as meta-
first task and 15 minutes for completing the second cognitive thinking skills:
task. Once the students begin working on task two,
they are not allowed to use the documents they have • Criterion R1: identifying errors and reflecting
generated in task one. In winter semester 2018/2019, one’s own approach.
18 tourism students and 54 computer science students • Criterion R2: taking the users’ preferences into
participated in the computational thinking compe- account, as well as the requirements.
tency test.
First results indicate that the computer science
Coding scheme of the computational students demonstrate a significantly higher initial
level of static abstract thinking skills (mean-value
thinking competency test & first M=2.04; standard-derivation SD=0.49), in compar-
results ison to the tourism majors (M=1.77; SD=0.46)
To analyze the competency test of computational (t=2.119; df=70; p=0.030).
thinking skills, a comprehensive coding scheme was Regarding the students’ initial dynamic abstract
developed incorporating five criteria to evaluate static thinking skills, we found no statistically significant
abstract thinking processes (S1-S5) and three crite- differences between the performances of computer
ria to measure dynamic abstract thinking processes science students (M=2.12; SD=0.51) and tourism
(D1-D3). We defined two additional criteria opera- students (M=2.28; SD=0.43; whereby U=384.00;
tionalizing one’s ability for self-reflection (R1) and for p=0.210). It seems that tourism students have
identifying the requirements needed (R2). All crite- reached a slightly higher level of dynamic abstract
ria differentiate between four levels of competency thinking skills than computer science students.
(outstanding, good, satisfactory, not yet satisfactory). Furthermore, the results indicate that computer sci-
Score 1 characterizes the lowest level of competency, ence students (M = 2.07, SD = 0.78) and tourism
score 4 the highest one. students (M = 1.81, SD = 0.73) do not differ signifi-
We attempted to capture static abstract thinking cantly in their self-reflection skills (U = 384.00, p =
processes by evaluating students’ performances along 0.210). We observe only a slight tendency in favor of
these four criteria: the computer science students.
Overall, the competency test gives some insight that
• Criterion S1: developing categories that ideally
most of the students – computer science students (3rd
simplify the given representations (of coffee spe-
semester) as well as tourism students (6th semester) –
cialties) and structuring ingredients;
struggle with demonstrating their static and dynamic
Levels of competency may be described as ’un-
abstract thinking skills. According to Wing (2006)
refined’, ’put together’, ’structured’ and ’orga-
and based on our results, we strongly recommend the
nized’ (Hershkowitz et al., 2001).
integration of interdisciplinary teaching- and learning-
• Criterion S2: identifying and parameterizing at- programs in students’ curricula to foster students’ com-
tributes. putational thinking skills.
V. Thurner, O. Radfelder, K. Vosseberg (Hrsg.): SEUH 2019 62
Future Skills: How to strengthen computational thinking in all software project roles
Gudrun Socher, Sarah Ottinger, Veronika Thurner und Ralph Berchtenbreiter, HS München
Regarding students’ reflection skills, it seems to between the students in a purely virtual way, using
be important to encourage students to reflect their the cloud-based Alexa Developer Console as well as
own approaches and to think about the requirements Github and Github issues. The classroom events where
needed. both computer science students and students of the
The results of the pre- and post-tests provide empir- application domain are together are the three pitches
ical evidence that the tourism students’ static abstract which are highlighted in gray in Table 1, i.e. the
thinking skills development can be characterized by pitch of the prototypes by the students of the appli-
a significant increase (t = -3.986, p = 0.001) sup- cation domain, the pitch of the voice app demos by
porting our hypothesis. After actively participating in the computer science students, and finally the joint
the interdisciplinary tool-based teaching-and-learning pitch during the final presentation. A mix of virtual
program (M = 2.21, SD = 0.48) the tourism students and physical collaboration creates enough space for
score significantly better in terms of their static ab- both teaching and learning sessions to accommodate
stract thinking skills than before their participation in the specific contents of the respective modules and
this program (M = 1.77, SD = 0.46). The effect size the corresponding competencies according to the defi-
by Cohen (1992) is around r = 0.695, thus indicating nition of learning goals.
a strong effect. Regarding the tourism students’ dy- The interdisciplinary project was a lot of fun for
namic abstract thinking skills, no significant effect can everyone involved. For that reason alone, it is highly
be reported (t = -1,475, p = 0.159). However, there recommended to repeat the project. The use of new
is also a tendency towards an increase of dynamic web-based development tools was well received by
abstract thinking skills (M = 2.24, SD = 0.44). Our all participating students independent of their field of
hypothesis that tourism students improve their com- study.
putational thinking skills during the interdisciplinary The computer science students were motivated pri-
tool-based program can be confirmed. marily by the fact that new voice technologies were
used in the context of this project. In turn, tourism
Challenges and experiences students have grown into the role of product owner
Project-based teaching presents many challenges to during the project. Furthermore, by using the de-
teachers (Barron et al., 1998), among others: velopment tools, they were in able to increase their
competency in using web-based tools. They also liked
• Formulate clear definitions of learning goals and to creatively integrate sound effects into the Alexa
competencies students should acquire. voice apps.
• Make sure that the project tasks cover the planned
learning content to the desired extent and ade- Summary and outlook
quately demand and strengthen the competencies It is important for all students to develop and to
to be acquired. strengthen their ability of computational thinking in
order to meet the requirements of the digital transfor-
• Build social interaction structures within the mation. As a basis, it is helpful that the students first
project teams that allow a balanced distribution develop the skills for static and dynamic abstraction
of roles and tasks. as these are a basic building block of the ability of
computational thinking. Computational thinking is
• Create a good (i.e. applicable) schedule.
one of the Future Skills (Kirchherr et al., 2018), which
128 students in computer science and tourism man- are important core competencies for the future work-
agement were in the pilot group in the winter semester ing life as well as for the participation in business and
2018/19. We combined a software engineering mod- society in the era of the digital transformation and the
ule and a module for digital marketing and manage- new forms of work linked to it.
ment. Both modules have their own learning objec- We strengthen computational thinking through in-
tives and content. In addition to the learning objec- terdisciplinary, tool- and project-based learning. As a
tives of these respective modules, additional learning project topic and work context, we select the design
objectives of the interdisciplinary tool-based teaching- and implementation of voice-based digital assistants
and-learning program include the increase in static (so-called voice apps). The students are encouraged to
and dynamic abstraction abilities mentioned in this use static and dynamic abstraction for the specification
paper as well as the improvement of collaboration and of the dialogue between a human and a voice-based
communication skills in digital projects. Therefore, in- assistant.
structors need to encourage students in their learning A competency test was developed in order to mea-
process. At the same time, instructors have to take sure the effectiveness of our approach. The test was
care to not overburden their students. run at the beginning and at the end of the semester.
We solve the challenges of the different learning (The evaluation of the post-test is not yet completed.)
objectives and content of the initial modules by run- The pseudonymized test results are used to determine
ning some part of the interdisciplinary collaboration the extent to which the students were able to improve
V. Thurner, O. Radfelder, K. Vosseberg (Hrsg.): SEUH 2019 63
Future Skills: How to strengthen computational thinking in all software project roles
Gudrun Socher, Sarah Ottinger, Veronika Thurner und Ralph Berchtenbreiter, HS München
their abilities of static and dynamic abstraction during Hershkowitz, R., B. B. Schwarz, and T. Dreyfus
the program. 2001. Abstraction in context: Epistemic actions.
More tests are required for a more detailed analy- Journal for Research in Mathematics Education,
sis of future skills through interdisciplinary tool- and Pp. 195–222.
project-based learning in digital projects. Accordingly,
we plan to improve and further expand our approach Kirchherr, J., J. Klier, C. Lehmann-Brauns, and
so that additional competencies are targeted and the M. Winde
effects are captured by additional measuring instru- 2018. Future Skills: Welche Kompetenzen in
ments. Deutschland fehlen.
Kramer, J.
2007. Is abstraction the key to computing. Commu-
nications of the ACM, 50.
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