=Paper=
{{Paper
|id=Vol-1918/reiter
|storemode=property
|title=Teaching Computational Aspects in the Digital Humanities Program at University of Stuttgart – Intentions and Experiences
|pdfUrl=https://ceur-ws.org/Vol-1918/reiter.pdf
|volume=Vol-1918
|authors=Nils Reiter,Sarah Schulz,Gerhard Kremer,Roman Klinger,Gabriel Viehhauser,Jonas Kuhn
|dblpUrl=https://dblp.org/rec/conf/gldv/ReiterSKKVK17
}}
==Teaching Computational Aspects in the Digital Humanities Program at University of Stuttgart – Intentions and Experiences==
https://ceur-ws.org/Vol-1918/reiter.pdf
Teaching Computational Aspects in the Digital Humanities Program at
University of Stuttgart – Intentions and Experiences
Nils Reiter1 , Sarah Schulz1 , Gerhard Kremer1 ,
Roman Klinger1 , Gabriel Viehhauser2 and Jonas Kuhn1
1 Institut für Maschinelle Sprachverarbeitung
2 Institut für Literaturwissenschaft
Universität Stuttgart
viehhauser@ilw.uni-stuttgart.de
firstname.lastname@ims.uni-stuttgart.de
Abstract each student deepens their knowledge in the field
they studied in a previous undergraduate program,
The structure of the Digital Humanities
(2) Digital Humanities, and (3) Computer Sci-
master’s program at University of Stuttgart
ences (CS). While different computer science in-
is characterized by a big proportion of
stitutes are offering courses in this program, a ma-
classes related to natural language process-
jority of the courses are offered by the Institut für
ing. In this paper, we discuss the moti-
Maschinelle Sprachverarbeitung (Institute for Nat-
vation for this design and associated chal-
ural Language Processing), both electable and com-
lenges students and teachers are faced with.
pulsory courses.
To provide background information, we
In this paper, we present the intentions behind
also sum up our underlying perspective
the study program and report on results of a survey
on Digital Humanities. Our discussion is
conducted among the first two cohorts of students.
driven by a qualitative analysis of a survey
handed to the students of the program. 2 Digital Humanities and Computational
Linguistics
1 Introduction
Digital Humanities is a new and diverse field, and
The importance of computer-assisted methods is pinpointing and defining its actual novelty has been
increasing in various research fields, for instance in a hot topic in the past years (Presner and Johan-
Biology (Bioinformatics and Computational Biol- son, 2009; Berry, 2011; Gibbs, 2011; Svensson,
ogy), Media Sciences (Mediainformatics), or Geog- 2012; Kuhn and Reiter, 2015; Dunst, 2017; Thaller,
raphy (Geoinformatics). More recently, the broad 2017). While differing views are plausible and
fields of Humanities and Social Sciences adopted valid, we believe that formalization is one key as-
the use of computational methods, which are of- pect of the field’s novelty, applied to both the re-
ten referred to as Digital Humanities (Jannidis et search questions and to the analysis objects. The
al., 2017). However, in contrast to preceding re- formal definition of – in principle – quantifiable
search domains and sciences, the use of quantitative properties is a fundamental step when switching
and statistical methods in this area is less popular, the focus from particular, incomparable pieces of
which poses additional challenges to the introduc- art to comparing, counting and categorizing ob-
tion of formal methods to the field. jects. Only properly formalized concepts can be
The University of Stuttgart introduced a mas- reliably applied on different objects of interest, and
ter’s program for Digital Humanities (DH) in 2015. only then can these objects be compared or viewed
While other universities have been offering DH pro- quantitatively in the first place (for instance, the
grams in various forms, one key characteristics of comparison of syntactic profiles for different au-
the DH program in Stuttgart is the strong influence thors relies on the proper formalization of syntax).
of Computational Linguistics (CL) on the program, Formalization, in this view, does not necessarily
both on the design and planning of the program imply the implementation of such approaches in
and on the actual courses. a computer. There are formalized approaches to
The program consists of three main areas: (1) Humanities research questions or objects that are
A specific discipline in Humanities, in which non- or pre-digital, e. g., John Snow’s map of a
Master’s program Digital Humanities , University of Stuttgart
1st semester 2nd semester 3rd semester 4th semester
Electives Humanities – In-Depth Humanities * 12-18
In-Depth
Humanities DH in the DH in the
Humanities I 6 Humanities II 6
Subject (lecture series) (lecture series) ***
Master
Theoretical and Methods of Methods of thesis 30
Specialization informatics basics DH 6 DH 6
for the DH 9 (seminar) (seminar)
Digital (lecture + practice) ----------------------------- -----------------------------
Project work 9 Research Coll. 6
Humanities
Computational
Specialization Linguistics Methods
for the DH 9 Electives Computer Science ** 12-18
Computer ----------------------------
Programming 3
Science
Semester 1 30 CP Semester 2 30 CP Semester 3 30 CP Semester 4 30 CP
Figure 1: Structure of the master’s program Digital Humanities at University of Stuttgart
* import module from the Humanities
** import module from Computer Science
*** DH course in the Humanities – offered by a Humanities subject
London cholera outbreak in 1854 (which enabled most prominent example is the annotation work-
a visual detection of the outbreak center), or the flow, including measuring inter-annotator agree-
configuration analysis of 19th century traveling ment as a metric for annotation guideline quality
theaters (which enabled a quick overview of the (Hovy and Lavid, 2010) or the use of shared tasks
required number of actors to perform a play). As to foster tool or corpus creation (Reiter et al., 2017).
the examples show, formalized approaches do not
imply ‘big data’ or large-scale analyses. 3 Structure of the DH Master’s Program
Applications that have been popular in the Digi- at University of Stuttgart
tal Humanities (e. g., network analysis or stylome- Given the above, the DH master’s program in
try) are all built on this formalization: Independent Stuttgart aims at both teaching conceptual un-
of the visualization, a network is a formal model, in derstanding and practical experience, while at
which data properties are represented by nodes and the same time deepening students’ Humanities
edges between them. Stylometric analysis, e. g., backgrounds and interdisciplinary skills. This is
implies a formalized notion of what tokens are, and achieved through a combination of theoretical lec-
how they are counted and compared. tures and practical exercises, programming courses,
Given the fact that text is a frequently used and group projects.
medium in many Humanities disciplines (on the ob- The program is open for undergraduate students
ject and/or meta-level), Computational Linguistics of a Humanities discipline that is also taught in
plays a crucial role in two – complementary – ways: Stuttgart (e. g., Literary Studies, History, Philos-
(i) On the operationalization level, formalizations ophy, or Art History). Interested undergraduates
of, for instance, literary concepts can be built upon may apply once a year and start each year in Oc-
linguistic structures (for which operationalizations tober. The program is designed to be completed
do exist). In many cases, this requires tested and within four semesters. Courses are split into three
proven annotation guidelines as well as implemen- categories, although not all classes can be clearly
tations of tools for the automatic discovery of such assigned: Humanities, Digital Humanities, and
structures – (computational) linguistic structures Computer Sciences. The structure of the program
can therefore form the basis of more complex and is illustrated in Figure 1.
abstract formalizations (e. g., narrative categories In the set of Humanities courses, students take
defined on the phrase-level). (ii) On the method- classes in the discipline of their undergraduate pro-
ological level, CL has established a number of best gram, where they are joined by their non-DH fellow
practices for creating such formalizations, which students (e. g., master students of German studies).
can be put to use on non-linguistic phenomena. The In contrast, Digital Humanities classes are spe-
cific to the DH students, only. After a compulsory puter Science bachelor’s and master’s programs, in
introductory lecture (6 hours/week, lecture and ex- which they share courses with the students from
ercises), students take part in a group project in the the respective programs (e. g., data visualization).
second semester, where ‘real-world’ research tasks It is a deliberate choice that DH students take
of delimited scope are tackled. Emphasis is put courses that are also offered in the CS and CL
on teamwork and on the independent development programs. This way, students are exposed to dif-
of research strategies, two competences we regard ferent disciplinary styles and cultures, reflecting
as crucial and also characteristic for research in the ‘in between worlds’-nature of DH in general.
the DH. Thus, students learn to split up a research In addition, many of the courses that feature exer-
problem in smaller parts and establish data models cises foster group exercises in order to strengthen
that serve as the base for the application of formal- team-skills (which are crucial when working across
ized computational methods. Those who choose a disciplines).
CL-oriented project are advised by teachers from Strong interdisciplinary ties are also present
Computational Linguistics. Other courses in the among the teachers involved in the program, who
DH area are seminars to familiarize students with all are experienced in working in mixed teams with
the most recent research in preparation of their members from different disciplines.
master’s theses.
4 Evaluation of DH Students’ Appraisal
The third area covers Computer Sciences and
includes the Computational Linguistics courses. In 4.1 Methodology
total, these courses cover roughly one third of the To get an impression of how the conceptional
credit points each student has to achieve (excluding course design decisions are reflected and perceived
the master’s thesis). Two courses from this area are by the students, we created an online questionnaire
compulsory, both in the first semester: Computa- and distributed this survey among both cohorts cur-
tional Linguistics Methods for Digital Humanities rently enrolled, first and second year students, by
(6 hours/week; lecture and exercises) and Program- the end of the teaching term. Since there were
ming (2 hours/week; lecture and exercises). These slight adjustments to the courses after the first year
compulsory courses are designed for and offered such as an emphasis on independent learning and
specifically to the DH students and are only taken changes to the programming course which was ad-
by DH students. Content-wise, Computational Lin- justed to the needs of Digital Humanities students,
guistics Methods for Digital Humanities resembles we analyze their feedback separately.
introductory courses for students in the computa- The questionnaire covers topics with respect to
tional linguistics programs. In addition, the use of the students’ overall satisfaction with their choice
Natural Language Processing (NLP) tools and/or of study, the differences they perceive between
workflows for addressing non-linguistic research their humanities discipline and the Digital Humani-
questions is covered. In Programming, no fore- ties context, but especially the integration of NLP
knowledge at all is assumed, treating every student courses in their curriculum. We inquired their per-
as a first-time programmer. Some emphasis is on sonal attitude towards the practical courses, their
the fact that many programming concepts exist in assessment of the difficulty of the offered courses,
many programming languages, although we use and their opinion about the necessity of the acquisi-
Python (version 3) throughout as our programming tion of NLP-related knowledge and skills for their
language in teaching. The main reason for this is understanding of Digital Humanities. Appendix A
that Python is widely used in the DH community. contains the complete questionnaire content.
Many exercises in the programming course cover We distributed 34 questionnaires out of which 15
algorithms and ideas that have been discussed in the were returned completely filled out. Since the en-
NLP-methods course (e. g., to implement functions tire study program has a small number of students
that measure precision and recall). In general, we and a return of 15 does not allow for a reliable
aim at performing exercises that students perceive statistical analysis, we rather catch the mood of
as being related to (Digital) Humanities. Apart approval of the program’s structure rather than a
from these two compulsory courses, students are full-fledged evaluation.
free to choose from a selection of courses that are The questionnaire comprised a few free-text an-
offered in the Computational Linguistics and Com- swers, but mostly, participants were asked to mark
their personal view of adequateness for given state- more persons who are not very confident in their
ments on a 6-point Likert scale. ability of familiarizing themselves with a new topic
on their own. At the same time, divergent opin-
4.2 Results ions also exist with respect to the question whether
they attach importance to a deeper understanding
Firstly, students stated to enjoy their DH studies
of NLP tools. Even though students seem to agree
and both cohorts presume that their future career
that an understanding contributes to their abilities
will profit from their education in Digital Human-
in DH, the second cohort in particular tends to find
ities, whereas the second year cohort commits
it more essential. The same trend can be observed
stronger to both statements.
in their appraisal of the necessity to possess pro-
Since all of the students hold a bachelor’s de-
gramming skills. The second cohort clearly agrees
gree in a humanities discipline, they emphasize the
that programming should be part of their skill set
shift to a more practical, computational training
as Digital Humanists, whereas the first cohort has
as a clear difference from what they were used to.
more divided views.
However, in the first cohort most students stress the
Thus, it seems that a higher confidence in CL-
addition of CS as a difference, whereas in the sec-
skills also fosters the acceptance of these methods.
ond cohort the focus on practical courses/sessions
But, admittedly, it might alternatively just show the
accompanying a theoretical course is mainly men-
inherent difference between the two cohorts.
tioned as a difference to earlier studies. A few
Being asked about suggestions for improvements
students point out that sometimes basic knowledge
for the program, the students wish for even more
is taken for granted, which leads to excessive de-
practical exercises, concrete preparation for their
mands. These experiences highlight the difficult
professional life and more diversity with respect to
balance of overload and underload resulting from a
application examples.
very heterogeneous group of students.
In summary, we attribute the differences between
This major shift from ‘theory’ (or more abstract
both cohorts to the changes we made after the feed-
humanist approaches) towards ‘practice’ is also
back at the end of the program’s first year. As an
reflected in the students’ expectations of how CL-
overall reflection of the affinity towards program-
methods should be taught: Both cohorts agree that
ming, independent learning, and a preference for
practical exercises are a very important aspect (for
practical courses, the second cohort has a higher
the second cohort it has highest importance for
self-perception of skills and also feels more con-
everyone answering the questionnaire) and some
fident to autonomously carry out a project with a
of the students even wish to have more practical
topic in Digital Humanities. We interpret this as
training.
a sign that our program structure with a focus on
However, it seems that the practical exercises
practical sessions prospers.
should be based on a solid theoretical ground: Stu-
dents in both cohorts tend to prefer a teaching ap- 5 Conclusion and Discussion
proach in which theoretical knowledge serves as
the basis to these practical sessions rather than an An often discussed problem of interdisciplinary col-
approach in which one is introduced to a topic in laborations between humanists and computer sci-
a practical manner and later on provided with the entists are communication difficulties that can lead
theoretical background. to all kinds of misunderstandings, loss of valuable
Regarding self-perception and acceptance of CL- time and frustration on both sides. These issues
skills, our results seem to indicate a characteris- root in the differences of research traditions and
tic difference between the two cohorts: In both the often opposed way of tackling research objec-
groups, students feel capable of coping with the tives. By familiarizing students with both fields and
DH courses in general. But, regarding CL courses, making them aware of these differences, we aim at
most students in the first cohort feel overwhelmed, opening doors to even more fruitful collaborations
whereas the majority of the second cohort does not. in the future.
Instead, in general they feel equally well as in the In this study, we recognize a general difficulty
DH courses. Students who feel overwhelmed often in estimating specific needs and issues of Digital
emphasize the newness of the methods as a reason. Humanities students. The survey that was designed
Among the students in the first cohort there are also to develop an understanding of particularities of
this group revealed that, partially, its characteris- Systematic annotation of literary texts. In Digital
tics are not different from what one might expect Humanities 2017: Conference Abstracts, Montreal,
Canada.
from other discipline switches – we presume that
a student changing from a Humanities program to Patrik Svensson. 2012. Envisioning the Digital Hu-
an engineering field would feel similar aspects to manities. Digital Humanities Quarterly, 6(1).
be eye-catching (for instance, the combination of
Manfred Thaller. 2017. Digital Humanities als Wis-
lectures and exercises). This might indicate that
senschaft. In Jannidis et al. (Jannidis et al., 2017).
the difficulties lie not necessarily in the program
itself, but in the special combination of Humanities Appendix A Questionnaire
with a formal and more technical research area.
In comparing our teaching experiences in Com- Below we provide the English translation of the
puter Science/Computational Linguistics and Dig- student survey questionnaire. Horizontal rules
ital Humanities, another aspect surfaces: CS/CL designate the space for free-text answers. In
students are typically confronted with problems most cases, students were asked to mark the
new to them (and the accompanying solutions), appropriateness of every statement as shown here:
which is a straightforward way in teaching (from I disagree I agree
the teacher’s perspective). In contrast, students 2 2 2 2 2 2
of DH have a background in a Humanities disci-
pline and thus already have been confronted with a 1. I like studying Digital Humanities.
number of research questions and possible solution
methods. Naturally, they are expecting relatively 2. My Humanities area:
concrete new solution methods to these diverse,
pre-existing questions. This makes DH a more 3. The Digital Humanities study program will be
application-oriented subject than many CS disci- helpful for my deliberate professional future
plines. (if assessable).
4. This DH study program differs from my bach-
References elor’s study program.
If you (rather) agree, please explain how it
David Berry. 2011. The computational turn: Thinking
about the Digital Humanities. Culture Machine. differs:
Alexander Dunst. 2017. Digital American stud- 5. I feel overwhelmed in DH courses.
ies: An introduction and rationale. Amerikastudien, If you (rather) agree, please explain why:
61(3):381 – 395.
Fred Gibbs. 2011. Critical discourse in Digital Human- 2 I’m lacking basic knowledge.
ities. Journal of Digital Humanities, 1(1). 2 Pace of the course is too fast.
Eduard Hovy and Julia Lavid. 2010. Towards a ‘sci- 2 The structure of the course is not intuitive
ence’ of corpus annotation: A new methodologi- for me.
cal challenge for Corpus Linguistics. International 2 Other reasons:
Journal of Translation Studies, 22(1), January.
Fotis Jannidis, Hubertus Kohle, and Malte Rehbein, ed- 6. I feel overwhelmed in CL courses.
itors. 2017. Digital Humanities – Eine Einführung. If you (rather) agree, please explain why:
J.B. Metzler.
2 I’m lacking basic knowledge.
Jonas Kuhn and Nils Reiter. 2015. A plea for a method-
driven agenda in the Digital Humanities. In Proceed- 2 Pace of the course is too fast.
ings of Digital Humanities 2015, Sydney, Australia, 2 The structure of the course is not intuitive
June. for me.
Todd Presner and Chris Johanson. 2009. The promise 2 Other reasons:
of Digital Humanities. Available as white paper on-
line from http://humanitiesblast.com/ 7. I can contribute with my skills during CL
Promise of Digital Humanities.pdf.
courses.
Nils Reiter, Evelyn Gius, Jannik Strötgen, and Marcus
Willand. 2017. A shared task for a shared goal – 8. Programming skills are important to me.
9. It is important to me to understand the internal
functional principle of computational linguis-
tics tools.
10. Practical modules (like exercises offered addi-
tionally to lectures) are important to me.
11. I am confident successfully conducting a
hands-on DH project with my skills.
12. I prefer learning the theoretical background
before applying it.
13. I prefer learning about hands-on applications
before addressing the theoretical background.
14. I can perfectly familiarize myself with a topic
on my own.
15. My suggestions to improve the DH study pro-
gram: