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The Changing Landscape of Digital Technologies for Learning
Dagmar Monett1, Claudia Lemke2, Amanda Jefferies3, Gert Faustmann2 and Tom
Brandherm1
1Computer Science, Berlin School of Economics and Law, Germany
2Business Information Systems, Berlin School of Economics and Law, Germany
3School of Physics, Engineering and Computer Science, University of Hertfordshire,
Hatfield, UK
dagmar.monett-diaz@hwr-berlin.de
claudia.lemke@hwr-berlin.de
a.l.jefferies@herts.ac.uk
gert.faustmann@hwr-berlin.de
s_brandherm19@stud.hwr-berlin.de
DOI: 10.34190/EEL.21.067
Abstract: Digital technologies are and will continue to be changing the way we learn and teach today and in the future. This
includes not only offering every learner and teacher equal access to these technologies, but it also involves completely new
forms of content delivery. Additionally, digital skills must be fundamentally strengthened as a basic human skill that is
urgently needed today. It is therefore essential that learners own or have easy access to the necessary digital technologies
to participate fully in the digital education era. How learners concretely use them in diverse and creative ways is of particular
interest not only for educators. In this regard, we sought to study the changing landscape of technology ownership and use
by students for both learning and leisure. To accomplish this, we designed and conducted three surveys. After an analysis of
related work, we present a comparative, quantitative analysis of the survey results from 2013 (N1=275), 2015 (N2=336), and
2020 (N3=481). It investigates the evolution of ownership and use of digital technologies over the years. Then, we explore
the extent to which the use of different digital technologies has changed during this period, and the purposes for which
technologies are now used in enhancing and supporting student learning. We also present a qualitative evaluation of the
learners' responses. The aim is to determine how digital technologies are used and how they may depend on specific learning
contexts. Finally, we give some recommendations and suggestions for further research.
Keywords: digital technologies, technology ownership, technology use, digital learning, learner’s digital behaviour
1. Introduction
In recent years and especially during the COVID-19 pandemic we have seen digital technologies fundamentally
changing the way we learn and teach. Digital technologies have had a significant impact on our attitudes towards
education; are changing learning in schools and universities every day and are requiring all those involved to
rethink the skills that are needed for the future. Extending beyond the need to offer all teachers and learners
equal access to these technologies, it also involves completely new forms of didactics and content delivery. At
the same time, digital skills must be fundamentally strengthened as a basic human skill that is as necessary today
as reading, calculating and writing. It is therefore of particular importance that learners own the necessary digital
technologies to be able to participate in digital education.
In this paper we introduce an empirical and longitudinal study consisting of three surveys conducted in 2013,
2015, and 2020, respectively. We present a comparative, quantitative analysis of the surveys’ results that
investigate the evolution of ownership and use of digital technologies over the years. Additionally, we present a
qualitative evaluation of the learners' responses and give guidance on further attention.
2. Related work
It has become essential that students can access appropriate digital technologies to complete their studies
(Sailer, Schultz-Pernice and Fischer, 2021). That includes devices such as laptops or tablets and to have access
to various applications such as software solutions for writing academic papers, revising digital learning materials,
or collaborating with fellow students. In any case, a 2018 study showed this connection for several American
HEIs (Higher Education Institutions) and across nine countries (Galanek, Gierdowski and Brooks, 2018). That
study also emphasized the increasing importance of smartphones as a learning device for students in the
classroom, but also for self-paced learning. Mobile learning is increasingly becoming the standard for young
learners (Romero-Rodríguez et al., 2020; Viberg, Andersson and Wiklund, 2021). Other studies also show that
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students in Anglophone countries in particular use this sort of device (Kay and Lauricella, 2011; Galanek,
Gierdowski and Brooks, 2018; Dahlstrom, 2012). Other influential works on digital experiences of learners and
educators cover similar countries and situations (Essel et al., 2018; Beetham, Newman and Knight, 2019; Killen
and Langer-Crame, 2020).
The International Association of Universities, IAU, investigated the impact of the current pandemic for higher
education (HE). Their study shows the significance of digital technologies for implementing technology-
enhanced learning concepts (Marinoni, van’t Land and Jensen, 2020, p. 11). In Germany, the association of the
nine leading technical universities, TU9, is calling for comprehensive investment in the necessary digital
infrastructures as the basis for meaningful digital learning and teaching concepts (TU9, 2020). This will also be
critical in a post-pandemic time, i.e. how to implement new learning and teaching concepts students need to
use and which technology they should own for that.
Across most research, there is a consensus that the intensive use of digital technologies has a direct impact on
students' learning behaviour (Jalal and Mahmood, 2018). Some of the reasons deal with the changed behaviour
of the digital-native generation (Palfrey and Gasser, 2010), which increasingly prefers informal, social learning
(Viberg, Andersson and Wiklund, 2021) that becomes feasible through digital technologies. Achieving digital
competence for lifelong learning, where students proactively design, contribute to, and transform theirs and
society’s future, requires both to perceive and evaluate their experiences online; it must acknowledge
technology ownership and use.
The EDUCAUSE 2018 study (Galanek, Gierdowski and Brooks, 2018), for instance, investigates the specific ways
of how students use digital technologies. Interestingly, it became apparent that the lecturer's encouragement
to use digital technologies in the classroom is critical in determining the actual type of use. Nevertheless, other
studies show that the advanced use of applications in the classroom also positively influences students’ learning
(Wankel and Blessinger, 2013). It is also apparent that there is often a prevailing attitude among lecturers that
students do not need to be trained in the use of digital technologies. However, students begin their studies with
a background of experience “based on play, leisure, and entertainment” (Gulatee and Combes, 2018).
3. Methodology
The main goal of our research is to study the development of digital technology ownership and use over the
years at the HWR Berlin, a university of applied sciences in Germany. In this case, we define digital technologies
as the aggregation of diverse hardware equipment like computers and physical network connections, as well as
a variety of software-based applications. To accomplish this, three surveys were designed, conducted, and
analysed, as well as their results compared: S1 in 2013, S2 in 2015, and S3 in 2020. They constitute an empirical,
longitudinal study that focuses on technology ownership by students and its use for learning and leisure.
Some of the central research topics guiding our research are: students' ownership and use of digital technology,
tools that students use/have used for learning, challenges that might depend on the current situation (e.g.
related to the COVID-19 pandemic), as well as implications for the future of online teaching and learning, among
others.
All three surveys were conducted and administered online. Invitations to participate in the surveys were sent to
both graduate and undergraduate students per email. The original source of the questionnaires and their
content are introduced in (Jefferies, Monett and Kornbrot, 2016). The surveys consisted of groups of both closed
and open-ended questions in four main categories: demographics, technology ownership, use of technology,
and general comments. With each survey, new questions were added to account not only for the new
technological advances, but also for the teaching and learning conditions of each surveyed period. Subsequent
surveys built upon the 2013 survey and followed similar, basic research questions, research design, conduction,
and analysis. The time periods that were considered are: (i) September 11th, 2013, to November 27th, 2013, for
S1, (ii) October 28th, 2015, to December 14th, 2015, for S2, and (iii) December 14th, 2020, to January 11th, 2021,
for S3, i.e. all falling in the last study quarter of the year to allow for a better comparison.
4. Results and discussion
Conducting three surveys in similar research settings over seven years has made it possible to gather data for
analysing it. The following sections present and discuss the key relevant findings.
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4.1 Demographics and general data
Table 1 shows general information about the surveys as well as some demographics. The number of students
willing to participate increased from survey to survey, especially the proportion of female students surveyed,
representing 59.9% of the respondents in the last survey. The number of participants in the age group 30+ has
been increasing too, with almost four times the number of students surveyed in that category in 2020 with
respect to 2015. The majority of the students surveyed are first year students, an explanation for that being the
time of the year at which the surveys were administered. Also increasing over the years is the number of
international students and those whose native language is not German.
Table 1: General information about the surveys
S1 (2013)
S2 (2015)
S3 (2020)
No. of responses received
275
336
481
Female, male, other*
53.2%, 46.8%, –
55.4%, 44.6%, –
59.9%, 38.9%, 1.2%
International students
2.4%
9%
9.4%
Native language German
96.3%
87.4%
86.3%
*: In the first two surveys, there were no options for a gender other than female or male.
4.2 Digital technology ownership
The ownership of digital technologies increases for almost all devices (see Figures 1 (a) and (b)). The increase is
remarkable for the case of laptops and notebooks, with almost nine in ten students owning such a device in
2020. A similar trend can be observed for tablets and related devices. Also for smartphones with the market-
dominating mobile operating systems iOS and Android, with half of the surveyed students owning at least one
such a device. However, no increase can be observed for classic stationary devices—like desktop computers. In
general, students now own higher-quality devices, which are faster, more expensive but also demanding high
connectivity.
(a)
(b)
Figure 1: Technology ownership of desktop computer, laptop/netbook, and tablets, as well as smartphone
devices by students
All three studies also asked about the ownership of other devices such as diverse digital camera products, video
players, HD TV Sets or mp3 players. A consistent picture emerges here that illustrates a decline of such devices,
except HD TV Sets. One major reason seems to be found in the technological convergence of devices that has
been going on for years. The emergence of different hardware components with “many functions and support
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many content formats” (Alt, 2021) manifests this trend. A smartphone and a tablet not only combine formerly
stand-alone devices such as cameras or video and audio players, but also provide completely new forms of
applications and use. We also see this trend in modern television sets, which are often offered as smart TVs and
can thus partially replace new, so far desktop-driven device developments. This could explain the increased
ownership of higher-quality TV sets. The most essential insights from the device ownership range by students is
consistent with other studies conducted that clearly show a dominance of mobile and convergent devices for
learning (Gulatee and Combes, 2018; Galanek, Gierdowski and Brooks, 2018; Marinoni, van’t Land and Jensen,
2020). Interestingly, the comparatively higher increase in Apple devices such as iPhones or iPads shows that
students might have a higher willingness to buy higher-priced devices.
Mobile devices in particular promote informal learning (Viberg, Andersson and Wiklund, 2021) that can be
described “by being self-initiated and non-prescribed” (Carraro and Trinder, 2021, p. 41) outside formal face-to-
face or distance learning formats. That might require different course designs and formats, also for motivating
and engaging students to learn in self-paced environments. The mobile devices available for such learning
settings are no longer regulatory, much like network connectivity.
Connectivity to the internet, e.g. via WLAN or Wi-Fi at home (Wi-Fi: 96.7% S2, and 99.4% S3), has already
achieved high penetration since the first study in 2013, which is not surprising. Germany is one of the countries
where social status also determines access to education and therefore to HEIs (Blossfeld, 2019). Furthermore,
such social groups have been among the highest internet users since the early years of the digital age (Destatis,
2021).
4.3 Quantitative analysis of digital technology use
In the first two studies (S1 and S2), we distinguished between the categories ‘for study’ and ‘for leisure’ when
asking about the concrete use of technology. In the most recent study (S3), we no longer make this distinction,
as our digital lives are becoming more and more blurred at the boundaries between private and professional
(Lemke and Brenner, 2015), in a student's case for learning. The data gathered from the three surveys shows a
consistent, high use of applications in the group of office automation over time compared to other application
categories. For instance, in 2020 respondents used much more word processing applications (54,5%),
presentation software (30,4%), and spreadsheet-based software (29,3%), than university library search tools
(11,9%) or collaborative software tools (5%).
That application usage can be analysed together with the variety of digital activities that students perform as
part of their studies. Figure 2 shows a range of those activities that respondents from the first two surveys used
to perform online on a daily basis. For example, a passive usage of technology (understood e.g. as reading wikis
or blogs, downloading videos, etc.) dominated an active one (understood e.g. as contributing to wikis or blogs,
posting videos, etc.) in 2013. Two years later, there are many more students performing such activities online,
in general, and some of these activities start to show either a decline or an increase in their frequency.
In contrast to the steadily increasing end device use, without increasing diversity due to technological
convergence, application use shows a broadly diverse picture and this for each study. In order to take a closer
look at the state of technology use in 2020, we asked in the third survey about the frequency with which online
activities were performed. The results are presented in Figure 3. Important to notice this time is that we also
focused on activities undertaken in preparation for or during study. Furthermore, concrete examples of
applications widely used by young people or with high penetration in their group ages were considered for
evaluation, too (this is why special cases of currently extended social networks like Instagram or TikTok appear
together with categories or more general kinds of activities performed online).
As Figure 3 shows, both asynchronous and synchronous messaging still dominate the activities performed online
in 2020; video-based applications as essential tools for communicating would need to mature further. Even
when all these activities are performed for/when studying, the overall use of many of them drastically increased
from 2015 to 2020. Using social networks like Facebook, LinkedIn, Twitter, and TikTok, is not even popular
for/when studying in 2020 compared to YouTube, Spotify or Instagram, the big winners in this study. Teachers
could take note of this when designing their teaching by being aware of which activities could be expected to
have a higher engagement of students. On the other hand, if creating and posting videos online was a skill that
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should be reinforced during the studies, then teachers should find better ways to engage students in this activity
since only one in ten students includes it in her repertoire of activities performed online.
Figure 2: Activities performed online on a daily basis (i.e. "Several times a day" and/or "Once a day"), surveys
2013 and 2015
Figure 3: Activities performed online in the last 12 months, for/when studying: daily (i.e. "Several times a day"
and/or "Once a day") and less often (i.e. "A few times a week" and/or "Less often"), survey 2020
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Regardless of the classification, there is a continuing trend towards the use of social and mobile applications
that foster interaction and collaboration and increase students’ engagement into the learning process. In
combination with a nearly complete penetration of mobile devices, the lectures and also the HEI are responsible
for redesigning the presentation and delivery of the course materials, thereby exploiting the potential of
informal learning. As other studies show (Gulatee and Combes, 2018; Galenek et al., 2018), it requires explicit
tool training involved in the learning processes of both students and lecturers. The move towards informal
learning is one of the most important shifts using the advantages of mobile and social digital technologies.
The 2020 study took place in the middle of the COVID-19 pandemic and the second lockdown in Germany. Our
university was in its second full online term. This is why it was of special interest to analyse the use of online
video conferencing systems, something that was not considered in the previous surveys. The corresponding
survey question was posed separately and the related activities analysed independently of other online
activities. The data gathered from S3 shows the following: The video conferencing programs that were most
used in the classroom are BigBlueButton (65%) and Zoom (30.8%), followed by MS Teams (19.1%) and Adobe
Connect (16.3%). An explanation for these numbers may strongly depend on the compliance requirements of
our university to use secure tools for teaching and that are integrated into the IT infrastructure of our institution.
Figure 4 depicts different communication and interaction activities typical for online learning and teaching
during 2020, according to students’ responses from the third survey.
Figure 4: Communicating and interacting online in the last 12 months: daily (i.e. "Several times a day" and/or
"Once a day") and less often (i.e. "A few times a week" and/or "Less often"), survey 2020
Students use chat on a daily basis (89.8%), amounting to almost 9 in 10 students making use of this option several
times a day (82.3%) or at least once a day (7.5%). In the figure, without camera (resp. audio) means, for example,
participating in an online lecture but without activating the camera or lacking one (resp. muting the microphone,
or unable or not willing to connect one). It is remarkable that only one in five students share their screen or files
with others, e.g. for co-editing, these being behaviours that denote an active participation in teamwork or
classroom activities. When asked about the reasons why some of those activities were avoided or not
performed, some students answered they had no intention to, did not need them, did not know how to use
them, or the options available were not appropriate for the actual purpose or learning situation.
4.4 Qualitative analysis of digital technology use
The question arises as to how students use digital technologies in such a way that they complement each other
and optimally support their own learning process. For this purpose, open questions were asked in all three
surveys, e.g. about how digital technologies are used or how learning can be improved. As a more advanced
research approach, we started to think about a functional use model based on the ownership of digital
technologies, which we evaluated in first interviews.
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4.4.1 Open questions within the three surveys
The first guiding question asked for how technology components of teaching can still be improved. In all three
questionnaires, it can be seen that the basic infrastructure capacities are demanded first. While in 2013 there
were still components on site (such as power connections), in the year of the pandemic there were more
demands for higher data bandwidth and special technology components (better network capacities were
demanded throughout, but also standards for e.g. microphones for teachers). In 2013, there was a desire for
more use of technology to support teaching. This was the case later anyway due to the pandemic, but could be
further improved by enriching the teaching materials, such as supplementing slides with spoken information or
usage instructions for extensive learning materials.
A second guiding question enquired about the perceived advantages of the technologies used. As expected, new
technologies such as cloud services and the possibility of document annotation (e.g. pdf) were also readily used
in the first two surveys. The diverse sources of information available through the web, as well as the possibility
of structuring and storing these knowledge shares in a simple way, were also seen as an advantage. Later, the
time saved in both searching for information and conducting online courses (by saving on travel to the university,
for example) was also mentioned by some respondents. The keyword ‘efficiency in study life’ is found in some
answers belonging to this category.
When asked why certain digital technologies were not used, the reasons provided fell into two broad areas:
Firstly, respondents were not aware of a particular technology or application due to the lack of a situation in
which such technology is used, e.g. having an online exam. Secondly, it was also due to a lack of experience with
existing applications, which might be a direct consequence of a deliberate restriction or too little experience
with technology in general and thus sometimes an unwillingness to use other alternatives.
In 2020, we also asked what general tips students could give to teachers. A frequent point of criticism was the
commitment and abilities of the lecturers when teaching online. Here, the students found significant differences
between the lecturers. As far as the future of digital teaching is concerned, one can find very contradictory
opinions: while some students see the efficiency already mentioned above in the foreground and enjoy the great
potential of saving time, others complain about difficulties to focus, which in their experience occur much less
with face-to-face teaching. One participant even commented they had already “[t]oo much time on a screen per
day.”
4.4.2 Interviews on functional use
The qualitative use of digital technologies, although determined by the availability and level of awareness of the
technologies, can still vary significantly. An indication of this can be seen in the quantitative observations of
software use in the overwhelming predominance of office automation software (see Section 4.3). Here one can
assume that the depth of application of the systems is not sufficient.
However, information of this kind of interaction with technology is difficult to elicit through direct questions in
surveys. The primary question type in surveys is choice, which must always prescribe a set of answers. High-
quality use of equipment and software systems, however, can take place in many different ways. For this reason,
in an exploratory setting, we set up an initial interview with the goal to get indicators for how the development
of technologies affects the respondents and how the functions offered by the systems are actually used.
Figure 5 summarises the corresponding relationships we see between students and the technologies they may
use, which can be both devices and applications.
Students initially know about or maybe own digital technologies as a pre-requisite for using them for learning.
Furthermore, they may plan to purchase new technologies that they have heard about and that they expect to
add some kind of value to their studies. When using digital technologies, students draw on a range of functions,
which are perhaps only the most common ones in certain learning settings. This difference can lead to using a
technology or a set of digital technologies only very superficially and, thus, not to their full potential.
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Figure 5: Relationship between students and digital technologies
We drafted four questions in line with the Figure 5 relationships to discuss in interviews:
1. From the digital technologies you use or have used for studying, which one has fulfilled your expectations
or disappointed you the most?
2. What digital technologies explicitly for studying are you planning to purchase in the near future?
3. When using a specific technology, were you able to use it extensively according to the range of functions
it provided?
4. Did the use of different digital technologies influence your learning behaviour?
The answers that were provided indicate that technology is often perceived as positive, as it quickly results in
easily manageable use scenarios. As an example, the parallel use of different end devices in online le ctures is
mentioned in order to be able to follow the lecturer or others better. Monitoring one's own progress is also seen
positively. Students do not seem overly concerned to purchase more and higher special technology if their
current technology is sufficient for their study needs. The depth of the use of tools is assessed rather critically.
The students interviewed are aware that there are probably still many functionalities in the systems they have
not yet discovered and are, nevertheless, quite satisfied with the current way of using them.
Further discussion in focus groups is planned and will be reported at a later date.
5. Conclusion
“Before covid it was mostly Moodle and the library search that was really updated by the university
and also used. With the rise of online courses now i (sic) feel that more professors are forced to use
online resources which imo (sic) is a step in the right direction.” — 4th year student (2020)
Our longitudinal study shows very clear trends in favour of online learning supported by devices such as laptops,
tablets and smartphones. There are also evident changes in the ownership and use of digital technologies. In
addition, the use of digital technologies for studying shows an increasing and more intensive use of various social
applications over the years, be it instant messaging, the use of multimedia content platforms or online
processing of documents. At the same time essential digital technologies for learning, such as literature
management systems, are integrated into everyday learning only to a limited extent. Such a limited use of those
technologies, however, may imply only basic knowledge and command of them, this being insufficient in more
complex learning situations.
Other possible use scenarios of digital technologies should be investigated more closely in the future, especially
concerning the learning design and competencies of teachers. Here, a reference to the concrete learning
environment must be established. For teachers and HEIs themselves, this could mean that:
learning opportunities should be more open and include an intensive use of mobile and social apps,
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young people need to be explicitly trained in the use of specific applications for studying, especially for
academic work,
for the post-pandemic period, HEIs must invest in a high-performance and secure infrastructure with a high
bandwidth, and
teachers themselves need to be empowered to integrate digital technologies into their teaching, as role
models to have a positive impact on students' behaviour.
References
Alt, R. (2021). Electronic Markets on the next convergence. Electron Markets, 31, pp. 1–9.
Beetham, H., Newman, T. and Knight, S. (2019). Digital experience insights survey 2018: findings from Australian and New
Zealand university students. Jisc [online]. Available at: http://repository.jisc.ac.uk/7202/1/digital-experience-insights-
survey-anz-2018.pdf (Accessed: 10 October 2020).
Blossfeld, P. N. (2019). Soziale Herkunft und langfristige Veränderungen der Übergänge zwischen akademischen und nicht-
akademischen Karrieren nach dem ersten Bildungsabschluss: Bedeutung für das berufliche Bildungssystem in
Deutschland. Z Erziehungswiss, 22, pp 535–565.
Carraro, K. and Trinder, R. (2021). Technology in formal and informal learning environments: Student perspectives. Global
Journal of Foreign Language Teaching, 11(1), pp. 39–50.
Dahlstrom, E. (2012). ECAR Study of Undergraduate Students and Information Technology, 2012. Louisville: EDUCAUSE
Centre for Applied Research [online]. Available at: https://library.educause.edu/-
/media/files/library/2012/9/ers1208.pdf?la=en&hash=4AB35D01C0B609A289AF775CA54F1465FA67B872 (Accessed:
10 October 2020).
Destatis (2021). Computer- und Internetnutzung im ersten Quartal des jeweiligen Jahres von Personen ab 10 Jahren.
Statistisches Bundesamt [online]. Available at: https://www.destatis.de/DE/Themen/Gesellschaft-
Umwelt/Einkommen-Konsum-Lebensbedingungen/IT-Nutzung/Tabellen/zeitvergleich-computernutzung-
ikt.html%3Bjsessionid=5061AC73E3643A65FD71673ED88CE0CA.live732 (Accessed: 24 May 2021).
Essel, H. B., Nunoo, F. K. N., Tachie-Menson, A. and Amankwa, J. O. (2018). Higher education students’ ownership and
usage of smart phones and tablets: the case of Kwame Nkrumah University of Science and Technology (KNUST).
International Journal of Educational Technology, 5(1), pp. 20–28.
Galanek, J. D., Gierdowski, D. C. and Brooks, D. C. (2018). ECAR Study of Undergraduate Students and Information
Technology, 2018. Research report. Louisville, CO: ECAR.
Gulatee, Y. and Combes, B. (2018). Owning ICT: Student use and ownership of technology. Walailak Journal of Science and
Technology (WJST), 15(1), pp. 81–94.
Jalal, A. and Mahmood, M. (2019). Students’ behavior mining in e-learning environment using cognitive processes with
information technologies. Educ Inf Technol, 24, pp. 2797–2821.
Jefferies, A., Monett, D. and Kornbrot, D. (2016). Digital Learners in Higher Education: Exploring Technology Ownership
Patterns and Learning Engagement. In J. Novotna and A. Jancarik (eds.), Proceedings of the 15th European Conference
on eLearning, ECEL 2016. Reading, UK: ACPI, pp. 315–322.
Kay, R. and Lauricella, S. (2011). Exploring the benefits and challenges of using laptop computers in higher education
classrooms: A formative analysis. Canadian Journal of Learning and Technology/La revue canadienne de
l’apprentissage et de la technologie, 37(1).
Killen, C. and Langer-Crame, M. (2020). Learner digital experience insights survey 2020: UK further education (FE) survey
findings. Jisc [online]. Available at: https://www.jisc.ac.uk/sites/default/files/student-dei-fe-report-2020.pdf
(Accessed: 10 October 2020).
Lemke, C. and Brenner, W. (2015). Einführung in die Wirtschaftsinformatik, Band 1: Verstehen des digitalen Zeitalters.
Berlin ,Heidelberg: Springer.
Marinoni, G., van’t Land, H. and Jensen, T. (2020). The impact of COVID-19 on Higher Education around the world, IAU
Global Survey Report. IAU [online]. Available at: https://www.iau-aiu.net/Covid-19-Higher-Education-challenges-and-
responses (Accessed: 24 May 2021).
Palfrey, J. and Gasser, U. (2010). Born digital: Understanding the first generation of digital natives. New York: Basic Books.
Romero-Rodríguez, J. M., Aznar-Díaz, I., Hinojo-Lucena, F. J. and Gómez-García, G. (2020). Mobile learning in higher
education: Structural equation model for good teaching practices. IEEE Access, 8, pp. 91761–91769.
Sailer, M., Schultz-Pernice, F. and Fischer, F. (2021). Contextual facilitators for learning activities involving technology in
higher education: The C♭-model, Computers in Human Behavior, 121(106794), pp. 2–13.
TU9 (2020). TU9-Positionspapier: Digitalpakt für die Lehre. TU9 [online]. Available at:
https://www.tu9.de/media/download/tu9_pp_digitalpakt_fuer_die_lehre_07-2020_de.pdf (Accessed: 24 May 2021).
Viberg, O., Andersson, A. and Wiklund, M. (2021). Designing for sustainable mobile learning – re-evaluating the concepts
“formal” and “informal.” Interactive Learning Environments, 29(1), pp. 130–141.
Wankel, L. A. and Blessinger, P. (2013). Increasing Student Engagement and Retention using Mobile Applications:
Smartphones, Sykpe and Texting Technologies. Cutting-Edge Technologies in Higher Education. Bingley: Emerald.
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