A Quantitative Survey of Digital Competencies of Music Teachers in the
European Union
O Nuan
1 a
, Esther Vi
nuela Lozano
, Kadri Steinbach
, Yvan Corbat
Themuri Sulamanidze
, Raquel L
and Maria O’Connor
MTU Cork School of Music, Cork, Ireland
Reina Sof
ıa School of Music, Madrid, Spain
University of Tartu, Tartu, Estonia
Grupo DEX, Oviedo, Sapin
Music Pegagody, Digital Skills.
In this paper we offer a quantitative survey of the digital skills of music teachers practising in the European
Union. As part of the Erasmus+ Digital Skills for Music Teachers (DISK) project, one of the work packages
is to see how well they are integrated into the everyday teaching of music teachers of all specialisations, from
junior level to conservatoire. To examine this we conducted an online survey that first quizzed teachers on
their experiences through a combination of quantitative Likert scale ratings and open-ended feedback. We
present the results and initial analysis of 221 teachers’ responses and conclude with a discussion of the next
steps based on this data.
Teachers and educators need a broad toolkit of digital
skills and strategies in the delivery of high quality tu-
ition to their students. In the case of music institutions
and conservatories, the application of digital skills is
particularly challenging due to the specialist, applied
and practical nature of delivery. Instrumental and en-
semble tuition is principally a physical, in-person and
interactive activity that poses major hurdles when at-
tempting to coordinate over video teleconferencing
solutions like Zoom and Microsoft Teams.
These challenges were accelerated and brought to
the fore during the COVID-19 pandemic, which saw
institutions and teachers at all levels forced to adapt
and bring their lessons online within a very short and
intense period of time. Meanwhile, educators across
all disciplines are constantly evolving and adapting
to profound developments and obstacles in areas like
artificial intelligence (AI) and cybersecurity.
The Erasmus+ project Digital Skills for Music
Teachers (DISK) was initiated in 2024 by three con-
servatories from Spain, Ireland and Estonia to study
the role of digital technologies in music education and
prepare frameworks and modules for upskilling its
practitioners. It builds on knowledge gained through
the completion of the previous New Skills for New
Artists (NS4NA) that produced as its primary output
a set of reusable Creative Commons licensed mate-
rials for enhancing the entrepreneurial and technical
skills of recent music graduates (noa, 2022).
The DISK project seeks to extend this work to mu-
sic teachers with the following objectives.
1. To provide a scientific framework for the devel-
opment of various strategies for the digitisation of
music education.
2. To design and test a training curriculum in digital
competencies for music teachers.
3. To generate a toolbox for scaling up the digitisa-
tion of music education at the European level.
The most noticeable differentiator is its evidence-
based approach at the outset. To provide justification
for developing and testing a high quality curriculum
we describe in this paper a large-scale quantitative
survey that examines the extent of digital skills among
221 music teachers.
The European Framework for the Digital Compe-
tence of Educators (DigCompEdu) provides a ”scien-
Nuanáin, C., Lozano, E., Steinbach, K., Corbat, Y., Sulamanidze, T., López, R. and O’Connor, M.
A Quantitative Survey of Digital Competencies of Music Teachers in the European Union.
DOI: 10.5220/0012763700003693
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 16th International Conference on Computer Supported Education (CSEDU 2024) - Volume 1, pages 614-619
ISBN: 978-989-758-697-2; ISSN: 2184-5026
Proceedings Copyright © 2024 by SCITEPRESS Science and Technology Publications, Lda.
tifically sound framework describing what it means
for educators to be digitally competent” (Redecker,
2017). Since then there has been significant re-
search investigating and implementing the framework
within European educational institutions (Buckley
and Pears, 2021; Economou, 2023), including several
surveys that evaluate digital competencies using qual-
itative (Ghomi and Redecker, 2019; Rubio-Gragera
et al., 2023) means. In the context of music educa-
tion there have been several surveys published (Pabst-
Krueger and Ziegenmeyer, ), with many focussing
on the Spanish system (Guill
amez and Ramos,
2021; Garc
ıa et al., 2021; Cuervo et al., 2023)
The paper is structured as follows. Section 2 de-
scribes the methodology from instrument design to.
Section 3 discusses some of the results. Section 4
concludes with some overall remarks and discussion
of the next steps.
2.1 Survey Design and Pilot
The survey design phase commenced with a series of
online brainstorming sessions between the 3 partner
conservatoires in an effort to provoke discussion, so-
licit ideas and generate as many possible questions as
possible. These were all collected loosely in shared
documents that allowed further review and discussion
after formal meetings via comments.
Questions were refined based on relevance or re-
dundancy and transferred to a spreadsheet were or-
ganised thematically into sections that align with the
following areas of study of the project (as well as
an introductory ”general profile” category to aid with
subgrouping and data slicing later):
1. General Profile
2. Basic and transversal digital skills
3. Online safety and addressing ethics within the
new technological environment
4. Pedagogical skills
5. Specific Skills for digital teachers
Question types (e.g. multiple choice versus mul-
tiple answer) and possible options for the questions
were captured. Next the questions were coded into a
Microsoft Forms survey. Using manual and machine-
assisted translation the surveys were localised for
Spanish and Estonian. This pilot survey was then
shared with 5 colleagues from partner institutions but
who were not associated directly with the project for
independent feedback and testing.
2.2 Data Collection
After addressing pilot feedback, the survey was re-
fined and finalised for collection from the sample pop-
ulation. The survey was shared firstly amongst col-
leagues within the three conservatory partner institu-
tions, then widened to other institutions in the net-
works of the partners. In addition we targeted spe-
cific organisations and social media channels related
to music pedagogy, particularly the Association of
European Conservatoires (AEC).
2.3 Data Analysis
Following the closing of the data collection window,
the survey results were downloaded in Excel format
from the Microsoft Forms backend. The data was
ingested into Python using the Pandas data analysis
and manipulation library (pandas development team,
2024; McKinney, 2010). Readable ordinal categories
such as age, years teaching and Likert ratings were
replaced with integers to aid numerical analysis.
Preliminary descriptive statistics were carried out
using pandas and numpy. Inferential statistics were
performed using statsmodel (Seabold and Perktold,
2010). Microsoft Forms helpfully prepares some sim-
ple pie and bar charts, which were supplemented with
more detailed graphs prepared in matplotlib (Hunter,
2007) and seaborn (Waskom, 2021).
3.1 Reliability
The Likert ratings were first examined to ensure suf-
ficient reliability using Cronbach’s alpha measure as
carried out in the work of. We reported a high alpha
coefficient of 0.964177 within a confidence interval
of 0.957 - 0.971 a which can be interpreted to indicate
that the scale we have used has high internal consis-
3.2 Descriptive Statistics
3.2.1 General Confidence Profiles
Figure 1 shows the distribution of responses for the
general questions gauging participants’ confidence in
the high-level category descriptors. While not as pre-
cise, these broad category questions act as a useful
A Quantitative Survey of Digital Competencies of Music Teachers in the European Union
Figure 1: High-level Confidence Categories.
(a) Communication.
(b) Productivity.
Figure 2: Confidence Ratings - Basic Digital Skills.
control and broad indicator for the precise question-
ing that follows in preceding sections.. Most of the
participants indicate that they are broadly confident in
their use of computers, while the most notable lack of
knowledge lies in the area of online safety, copyright
and intellectual property
3.2.2 Basic Digital Skills (Communication and
In the category of basic digital skills we queried the
abilities of music teachers in general digital compe-
tencies not unique to music pedagogy - such as usage
of common communication and productivity tools.
Figure 2 shows the distribution of scores in these two
categories. Encouragingly, our participants scored
consistently high for tools like email, cloud storage
and telecommunication, indicating a baseline literacy
and understanding. Lower scoring categories such as
forum usage, task organisation and interactive apps
indicate that teachers may not be aware or have the
time to discover more bespoke tools.
(a) Safety.
(b) Ethics and Intellectual Property.
Figure 3: Confidence Ratings - Safety, Ethics and Intellec-
tual Property.
3.2.3 Safety, Ethics and Intellectual Property
A constant challenge and concern for music teach-
ers with digital delivery at all levels - but especially
younger children - is the issue of online safety. Figure
3a shows a fairly balanced distribution of scores with
the lowest weighting in the categories of phishing and
online bullying. This reflects the often smaller size
of music teaching schools in many communities who
may not have the resources, budget or knowledge to
develop formal policies and train their staff effectively
in these highly important issues.
Another unique issue in music education deliv-
ery is the issue of copyright and intellectual property.
Music teachers make frequent use of wide-ranging
multimedia resources in addition to sheet music and
recordings. Professional music performers leaving
music institutions also need to understand how mu-
sic royalties and intellectual property is handled in
their regions. Our survey revealed a marked lack of
understanding in the latter. In this section we also
asked about teachers’ knowledge of automatic plagia-
rism detectors, commonplace in other disciplines but
likely less so in music tuition due to the practical na-
ture of delivery. This is reflected in the lower distri-
bution of scores for this quality.
3.2.4 Specific Digital Skills
Our final category queried the usage of specialised
tools for music tuition, divided by software and hard-
ware. The software tools examined the teachers’
CSME 2024 - 5th International Special Session on Computer Supported Music Education
(a) Software.
(b) Hardware.
Figure 4: Specific Digital Skills.
awareness or familiarity with music pedagogy spe-
cific and adjacent software skills such as notation
software, audiovisual editing and theory apps along
with new AI innovations. As expected but still very
skewed, teachers are very unprepared for the impact
of Chat-GPT, but also music specific generative appli-
cations that can compose or co-create music. Many
teachers are also unaware of the benefit of theory and
ear training apps that allow students to interactively
improve such skills in their own time.
3.3 Inferential Statistics
3.3.1 Overall and Individual Confidence
Our first and most intuitive hypothesis is that indi-
viduals who rate themselves confident in the overall
control question should be reflected in the categor-
ical confidence ratings. To test this hypothesis we
computed the Spearman’s rank correlation coefficient
between the overall confidence and each individual
facet. We report moderate correlations (0.4 - 0.7) in
all instances and all coefficients are statistically sig-
nificant with (p <0.05) as indicated in the heatmap in
Figure 5.
3.3.2 Effect of Age
We were interested in studying the effect of age and
on the digital expertise and confidence of music teach-
Figure 5: Overall and Individual Confidences - Correlation
Figure 6: Confidence of Under-45s versus Over-45s.
Table 1: Overall Confidence Correlation Analysis.
General Category Spearman’s rho p-value
-0.217865 0.001115
Overall confidence -0.191543 0.004265
Online safety -0.127213 0.059010
Online teaching
-0.100994 0.134472
Royalties, rights, IP -0.003983 0.953052
ers. A possible hypothesis would suppose that older
teachers who rely on more traditional methods of tu-
ition would be less confident in terms of digital skills.
To investigate this we firstly computed Spear-
man’s rank correlation between the ordered age vari-
able and each of the general confidence categories.
Table 1 shows the top 5 correlation coefficients along
with the significance levels. As we can see there are
A Quantitative Survey of Digital Competencies of Music Teachers in the European Union
Table 2: Specific Confidence Correlation Analysis.
Digital Competency Spearman’s Rho Significance Level
Music streaming (Spotify, SoundCloud, BandCamp, Apple Mu-
-0.324158 0.000001
Theory/Ear training apps and games (e.g. Auralia, Musition,
Practica Musica, Ear Master)
-0.236085 0.000400
e. Tasks organisation (Notion, Trello, Evernote, etc.) -0.234820 0.000431
Digital Publications (Online books and works, eBooks, digital
workbooks, online repositories)
-0.230316 0.000559
d. Time management (Google Calendar, Notion, Coda, etc.), -0.218825 0.001059
a. Cloud-based file sharing (Google Drive, Dropbox, Teams,
-0.218761 0.001063
weak negative correlations but statistically significant
effects of age on the overall digital confidence and on-
line collaboration.
In terms of specific digital skills we drilled down
and performed the same procedure with all the Likert
confidence ratings. Table 2 overleaf shows the sorted
table of the top 5 correlation coefficients and their sig-
nificant levels, indicating a number of statistically sig-
nificant relationships with aspects such as digital pro-
ductivity, music streaming and music theory apps.
Another approach was to compare specific groups
by partitioning the participants into two age groups
above and below age 45. Figure 6 shows the superim-
posed bar plots of the percentage scores. Performing
this sort of division allowed us to compare the cen-
tral tendencies of both groups, using additional statis-
tical tests. Comparing the medians (under-45 = 4.0,
over-45 = 3.0) we performed a Mann-Whitney U test
to establish whether the medians of the two groups
are statistically different. This was confirmed with a
statistic=5854.0 and a significant p-value=0.0121.
In this paper we presented initial findings of a quan-
titative survey of the digital skills of music teachers
practising in the European Union. We introduced the
aims of the survey in the context of the DISK Eras-
mus+ project, which seeks to offer an evidence-based
approach to digital skills enhancement of those teach-
We produced descriptive and inferential analysis
of the results that revealed important aspects and gaps
in the knowledge of the music teachers under scrutiny.
Many of these details were suspected from the outset
i.e. a lack of awareness around next generation tools
such as AI and immersive technologies. Others were
more surprising, such as the lack of uptake in theory
training apps and games and understanding of music
Our next steps are to follow up the quantitative
survey with a qualitative instrument that will give tex-
ture to the numerical data through a series of semi-
structured interviews with selected music teachers.
We are also producing a similar quantitative survey
that gives the perspective of students and their impres-
sions of the extent of digital usage within their class-
rooms. The evidence we are gleaning from these ex-
periments have proved highly informative as we pre-
pare materials for the delivery of training modules in
the next work package, and as we gather more data we
are constantly refining the content to meet the needs
of the music teachers in the EU.
This publication is part of a project that has received
funding from the European Union’s Erasmus+ pro-
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A Quantitative Survey of Digital Competencies of Music Teachers in the European Union