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|title=Embracing digital innovation and cloud technologies for transformative learning experiences
|pdfUrl=https://ceur-ws.org/Vol-3679/paper00.pdf
|volume=Vol-3679
|authors=Stamatios Papadakis,Serhiy O. Semerikov,Andrii M. Striuk,Hennadiy M. Kravtsov,Mariya P. Shyshkina,Maiia V. Marienko,Hanna B. Danylchuk
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==Embracing digital innovation and cloud technologies for transformative learning experiences==
https://ceur-ws.org/Vol-3679/paper00.pdf
Embracing digital innovation and cloud technologies for
transformative learning experiences
Stamatios Papadakis1 , Serhiy O. Semerikov2,3,4,5,6 , Andrii M. Striuk5,2,6 ,
Hennadiy M. Kravtsov7 , Mariya P. Shyshkina4 , Maiia V. Marienko4 and Hanna B. Danylchuk8
1
University of Crete, Gallos Campus, Rethymnon, 74100, Greece
2
Kryvyi Rih State Pedagogical University, 54 Universytetskyi Ave., Kryvyi Rih, 50086, Ukraine
3
Zhytomyr Polytechnic State University, 103 Chudnivsyka Str., Zhytomyr, 10005, Ukraine
4
Institute for Digitalisation of Education of the NAES of Ukraine, 9 M. Berlynskoho Str., Kyiv, 04060, Ukraine
5
Kryvyi Rih National University, 11 Vitalii Matusevych Str., Kryvyi Rih, 50027, Ukraine
6
Academy of Cognitive and Natural Sciences, 54 Gagarin Ave., Kryvyi Rih, 50086, Ukraine
7
Kherson State University, 27 Universytetska Str., Kherson, 73003, Ukraine
8
The Bohdan Khmelnytsky National University of Cherkasy, 81 Shevchenko Blvd., Cherkasy, 18031, Ukraine
Abstract
The 11th Workshop on Cloud Technologies in Education (CTE 2023) was held in Kryvyi Rih, Ukraine, on
December 22, 2023. This volume of proceedings comprises 18 peer-reviewed papers that explore the state-of-the-
art advancements and applications of cloud technologies in various educational contexts.
Keywords
cloud computing, education, e-learning, adaptive learning, blended learning, artificial intelligence, virtual labs,
learning platforms, soft skills, asynchronous learning, HyFlex learning
1. Introduction
1.1. CTE 2023 at a glance
Cloud Technologies in Education (CTE) is a peer-reviewed international Computer Science workshop
focusing on research advances and applications of cloud technology in education.
The workshop considers contributions in all aspects of educational technologies and cloud-based
learning tools, platforms, paradigms and models, functioning programmes, or papers relevant to modern
engineering and technological decisions in the IT age.
CTE topics of interest since 2012 [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]:
• Adaptive Cloud Learning Platforms
• Blended Learning
• Blockchain in Education
• Cloud-based AI Education Applications
Figure 1: CTE 2023 logo.
• Cloud-based E-learning Platforms, Tools and Services
• Cloud-based Learning Environments
• Competency-Based Education Platforms
• Digital Transformation of Education
CTE 2023: 11th Workshop on Cloud Technologies in Education, December 22, 2023, Kryvyi Rih, Ukraine
" stpapadakis@gmail.com (S. Papadakis); semerikov@gmail.com (S. O. Semerikov); andrey.n.stryuk@gmail.com
(A. M. Striuk); kgmkherson@gmail.com (H. M. Kravtsov); marimodi@gmail.com (M. P. Shyshkina); popel@iitlt.gov.ua
(M. V. Marienko); abdanilchuk@gmail.com (H. B. Danylchuk)
~ https://ptpe.edc.uoc.gr/en/staff/stamatis-papadakis (S. Papadakis); https://kdpu.edu.ua/semerikov (S. O. Semerikov)
0000-0003-3184-1147 (S. Papadakis); 0000-0003-0789-0272 (S. O. Semerikov); 0000-0001-9240-1976 (A. M. Striuk);
0000-0003-3680-2286 (H. M. Kravtsov); 0000-0001-5569-2700 (M. P. Shyshkina); 0000-0002-8087-962X (M. V. Marienko);
0000-0002-9909-2165 (H. B. Danylchuk)
© 2024 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
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Stamatios Papadakis et al. CEUR Workshop Proceedings 1–21
• Educational Data Mining
• Emotion AI
• Immersive Technology Applications in Education
• Mobile Learning
• Smart Campus Technologies
• Social Analytics in Education
This volume represents the proceedings of the 11th Workshop on Cloud Technologies in Education
(CTE 2023), held in Kryvyi Rih, Ukraine, on December 22, 2023. It comprises 18 contributed papers that
were carefully peer-reviewed and selected from 37 submissions. Two program committee members
reviewed each submission. The accepted papers present a state-of-the-art overview of successful cases
and provide guidelines for future research.
1.2. CTE 2023 committees
Program committee
• Antonio Sarasa-Cabezuelo, Universidad Complutense de Madrid, Spain [12]
• Nadire Cavus, Near East University, North Cyprus [13]
• Irina Alexandra Georgescu, Bucharest University of Economic Studies, Romania [14]
• Sven Hartmann, Clausthal University of Technology, Germany [15]
• Michail Kalogiannakis, University of Thessaly, Greece [16]
• Yuriy Kondratenko, Petro Mohyla Black Sea National University, Ukraine [17]
• Chung-Sheng Li, PwC Lab, United States [18]
• Jinwei Liu, Florida Agricultural and Mechanical University, United States [19]
• Vincenzo Moscato, University of Naples Federico II, Italy [20]
• Thomas Moser, St. Pölten University of Applied Sciences, Austria [21]
• Stamatios Papadakis, University of Crete, Greece [22]
• Daniël Thalmann, École Polytechnique Fédérale de Lausanne, Switzerland [23]
Additional reviewers
• Rui Gong, Mercer University at Macon, United States [24]
• Olha Hniedkova, Kherson State University, Ukraine [25]
• Oksana Klochko, Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University, Ukraine [26]
• Oleksandr Kolgatin, Simon Kuznets Kharkiv National University of Economics, Ukraine [27]
• Vladyslav Kruhlyk, Bogdan Khmelnitsky Melitopol State Pedagogical University, Ukraine [28]
• Yuliya Krylova-Grek, Uppsala Universitet, Sweden [29]
• Vladimir Kukharenko, Kharkiv National Automobile Highway University, Ukraine [30]
• Olena Kuzminska, National University of Life and Environmental Sciences of Ukraine, Ukraine
[31]
• Liliia Luparenko, Institute for Digitalisation of Education of the NAES of Ukraine, Ukraine [32]
• Yuliia Nosenko, Institute for Digitalisation of Education of the NAES of Ukraine, Ukraine [33]
• Vasyl Oleksiuk, Ternopil Volodymyr Hnatiuk National Pedagogical University, Ukraine [34]
• Oksana Ovcharuk, Institute for Digitalisation of Education of the NAES of Ukraine, Ukraine [35]
• Paweł Plaskura, Academy in Piotrków Trybunalski, Poland [36]
• Nataliia Soroko, Institute for Digitalisation of Education of the NAES of Ukraine, Ukraine [37]
• Alisa Sukhikh, Institute for Digitalisation of Education of the NAES of Ukraine, Ukraine [38]
• Ivan Tsidylo, Ternopil Volodymyr Hnatiuk National Pedagogical University, Ukraine [39]
• Alexander Weissblut, Kherson State University, Ukraine [40]
• Longkai Wu, Central China Normal University, China [41]
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Stamatios Papadakis et al. CEUR Workshop Proceedings 1–21
Organizing committee
• Serhiy Semerikov, Kryvyi Rih State Pedagogical University, Ukraine [42]
• Andrii Striuk, Kryvyi Rih National University, Ukraine [43]
• Hennadiy Kravtsov, Kherson State University, Ukraine [44]
• Mariya Shyshkina, Institute for Digitalisation of Education of the NAES of Ukraine, Ukraine [45]
• Maiia Marienko, Institute for Digitalisation of Education of the NAES of Ukraine, Ukraine [46]
• Hanna Danylchuk, The Bohdan Khmelnytsky National University of Cherkasy, Ukraine [47]
2. Workshop overview
2.1. Adaptive Cloud Learning Platforms
The article “Modeling ship cybersecurity using Markov chains: an educational approach” by Kaminska
et al. [48] proposes using Markov chain models to represent and analyse the cybersecurity system on
ships mathematically. The authors emphasise the growing importance of cybersecurity in the maritime
industry, citing guidance from the International Maritime Organization requiring proper consideration
of cyber risks. They argue that while general provisions exist, shipping companies must implement
effective cybersecurity systems.
The core contribution is developing a Markov chain model to characterise the states of a ship’s
cybersecurity system (safe, potential threat, risk of attack, active attack) and the probabilities of
transitioning between states over time. They define the states, lay out the mathematical formulation
using transition matrices, and illustrate with a numerical example.
A strength of the article is that it grounds the modelling approach in the practical cybersecurity
vulnerabilities and attack vectors affecting ships based on established maritime guidelines. Mapping
this context to the model states lends real-world relevance. The Markov chain formulation also seems
reasonable for capturing the memoryless property of cyberattack occurrences.
Figure 2: Presentation of paper [48].
The article “Cloud-oriented systems for open science: supporting virtual research teams through
adaptive content management and collaboration tools” by Shyshkina and Svetsky [49] discusses the
development of cloud-oriented systems for open science to support virtual research teams through
adaptive content management and collaboration tools. It examines the use of such systems in the “V4
Educational Academic Portal for Integrating IT into Education” (EDUPORT) project. The key points are:
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Stamatios Papadakis et al. CEUR Workshop Proceedings 1–21
1. Open science principles promote cooperation, exchange of results, and systemic changes in
scientific research implementation. Cloud-oriented open science systems provide tools to support
virtual teams’ open research activities.
2. The modern trends in forming open science cloud systems in higher education, including cloud
platforms, educational software, and communication services to enable virtual team collaboration,
are analysed.
3. The EDUPORT project created a cloud-oriented IT system to support a virtual research team,
consisting of network infrastructure, educational software WPadV4, and an online communication
system PIKS.
4. WPadV4 is database software that processes and manages educational content in tables, enabling
adaptive content management.
5. Using cloud platforms and various corporate cloud services allows the creation of specialised
environments tailored to research needs, introducing new forms and models of educational and
scientific activities.
6. Broader involvement of cloud tools and services in higher education can positively impact learning
outcomes, scientific research development, organisation level, and efficiency.
Figure 3: Presentation of paper [49].
2.2. Blended Learning
The article “Three-subject didactic model for teaching algorithmisation and programming online” by
Lvov et al. [50] proposes a three-subject didactic model for teaching algorithmisation and programming
online. It describes the pedagogical system and learning process model used for students in the “Software
Engineering” speciality, focusing on courses involving programming mathematical tasks.
The article “Use of information and communication technologies in the organisation of blended learn-
ing of future vocational education professionals” by Kucher et al. [51] is devoted to using information
and communication technologies (ICT) in organising blended learning for students training to become
vocational education professionals.
The article discusses the importance of ICT and modern educational technologies in today’s educa-
tional system. It outlines key competencies that vocational education students should develop, including
using ICT, managing projects, implementing learning strategies, etc.
The results describe various ways ICT can be leveraged throughout the stages of an educational
design project:
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Stamatios Papadakis et al. CEUR Workshop Proceedings 1–21
Figure 4: Presentation of paper [50].
• In the planning/brainstorming stage, online whiteboards and mind-mapping tools can facilitate
collaboration and idea generation.
• For designing clothing patterns, open-source CAD programs like Valentina allow students to
practice computer-aided design skills.
• Online learning platforms like Moodle with multimedia resources provide the basis for blended
learning courses.
• Tools like online boards, video conferencing, and messaging enable communication, feedback,
and group work.
The article argues that integrating these ICT tools into project-based learning helps systematically
develop students’ competencies in computer literacy, design, modelling, evaluation, and self-evaluation
compared to traditional approaches.
Figure 5: Presentation of paper [51].
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2.3. Cloud-based AI Education Applications
The article “Application of neural networks for adaptive and flexible electronic tourist guide” by Moroz
et al. [52] makes a case for the promising applications of large language models and neural networks to
create more intelligent, flexible and adaptive electronic tourist query systems compared to traditional
logic-based approaches.
Figure 6: Presentation of paper [52].
The article “Accelerating software development with AI: exploring the impact of ChatGPT and
GitHub Copilot” by Solohubov et al. [53] investigates the impact of artificial intelligence tools on code
development. The authors analyse two particular AI tools, Copilot and ChatGPT, which can be used to
generate code, correct errors, and answer questions about programming. The study finds that Copilot
can accelerate development by suggesting code completions and helping developers write boilerplate
code. ChatGPT can be used to learn new programming languages and libraries more quickly and
find solutions to specific programming problems. The authors conclude that AI tools are having a
revolutionary impact on software development and enabling programmers to focus on more creative
and strategic tasks.
Figure 7: Presentation of paper [53].
The article “Artificial intelligence literacy in secondary education: methodological approaches and
challenges” by Marienko et al. [54] examines the challenges and prospects of using artificial intelligence
(AI) in secondary education in Ukraine. The authors begin by highlighting the lack of understanding
and use of AI among the general Ukrainian population, as evidenced by a survey conducted by ZN.UA.
They argue that there is a need to develop “AI literacy” as a component of digital competence, including
understanding AI concepts and technologies, awareness of potential ethical issues, and the ability to
effectively and ethically use AI throughout one’s education and beyond.
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Stamatios Papadakis et al. CEUR Workshop Proceedings 1–21
The authors provide an overview of recent research on AI literacy, including its components (under-
standing, using, evaluating/creating with AI, and ethics) and pedagogical approaches such as digital
storytelling. They also discuss the inclusion of AI services in the European Open Science Cloud and
provide a practical example of using the AI-GeoSpecies service for studying plant species in biology
and geography lessons.
The authors report on an intermediate stage of their pedagogical experiment, which involved sur-
veying educators’ attitudes towards and using AI services. The results indicate a positive attitude and
interest in further training on using AI in education despite a lack of established methodologies.
The article draws on relevant literature and provides insights from the authors’ research. It also
highlights the interdisciplinary nature of AI literacy and the potential for AI to enhance inclusive
education. On the other hand, the article could be improved by addressing potential counterarguments or
limitations to the widespread adoption of AI in education and providing more specific recommendations
for curriculum development and teacher training.
Figure 8: Presentation of paper [54].
2.4. Cloud-based E-learning Platforms, Tools and Services
The article “Development and implementation of virtual physics laboratory simulations for enhanced
learning experience in higher education” by Tsvetkova et al. [55] describes the development and
implementation of virtual laboratory simulations for physics courses at Pryazovskyi State Technical
University in Ukraine. The authors make a strong case for the importance of virtual labs in enhancing
student learning, mainly when physical lab access is limited or unsafe.
The introduction provides an overview of the role of physics labs and the need for virtual simulations
to supplement traditional hands-on activities. The authors highlight how the COVID-19 pandemic and
the ongoing war in Ukraine have made virtual labs even more essential.
The theoretical background section reviews prior work on virtual labs at different educational levels.
The authors critique existing school-level virtual labs as being too simplistic “illusions” rather than
accurate simulations. They emphasise that high-quality university-level virtual labs should accurately
model real equipment and experimental processes.
The heart of the paper is the “Experience in developing virtual labs in physics” section, which
describes the various virtual lab simulations created by the authors across topics like thermodynamics,
electromagnetism, and quantum mechanics. Screenshots illustrate how the virtual interfaces mimic
actual lab setups and measurement devices. The authors have put considerable effort into making the
virtual experience as authentic as possible.
One strength is that some of the virtual labs go beyond what is possible with real equipment by
allowing multiple-varied inputs, pausing, zooming in on small scales, and safely simulating hazardous
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conditions. The integrative mass spectrometry and Compton effect virtual labs that combine multiple
physics domains are particularly innovative.
The conclusion persuasively argues that the 27 virtual labs provide comprehensive support for the
university’s physics curriculum. The authors also discuss limitations, like the current unavailability of
real lab video due to the war, and outline plans for continued improvement of the virtual labs.
Figure 9: Presentation of paper [55].
The article “Evaluating the effectiveness of a cloud-based laboratory for teaching Linux operating
systems to Computer Science students” by Oleksiuk et al. [56] investigates using a cloud lab called CL-OS
to teach the Linux operating system to future computer science teachers. The authors developed this
cloud lab by integrating the Cisco Network Academy’s NDG Linux Essentials MOOC course with Apache
Cloudstack and Proxmox VE private cloud platforms. They outlined the cloud lab architecture and
described additional teaching materials like tests, essays, and assignments they created to complement
the MOOC resources.
The authors conducted a pedagogical experiment using the CL-OS cloud lab to evaluate its effective-
ness. Statistical analysis methods like ANOVA for repeated measures and Spearman’s rank correlation
were used to analyse factors influencing student performance in learning Linux, such as prior experience,
gender, and satisfaction with different course components.
The authors conclude that the cloud lab approach, supplemented with short theoretical lectures
and immediate practical tasks, enhances computing resource utilisation and improves students’ time
management skills for successful course completion. Overall, their methodology using cloud labs
positively impacted the study of Linux by future computer science teachers.
The article “Leveraging cloud technologies to create an effective educational environment for devel-
oping soft skills in future primary school teachers” by Vasko et al. [57] examines the potential of cloud
technologies for creating an effective educational environment aimed at developing soft skills in future
primary school teachers. The authors provide a thorough overview of the topic, supported by relevant
literature and their practical experience implementing cloud technologies.
The article begins by emphasising the growing importance of soft skills and the need for higher
education to produce graduates with skills aligned with labour market demands. It defines an effective
educational environment and outlines its key characteristics, such as fostering collaboration, providing
an individualised approach, and utilising modern technologies like cloud tools.
The authors describe cloud technologies’ various possibilities for soft skills development, including
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Stamatios Papadakis et al. CEUR Workshop Proceedings 1–21
Figure 10: Presentation of paper [56].
access to advanced content, enabling collaboration and communication, personalised learning, indepen-
dent skills acquisition, and mobile/flexible learning. They reference the SAMR model for evaluating
technology integration, which guided their practical implementation.
Practical examples of cloud tools like Mentimeter, Padlet, and Jamboard are provided for activities
like determining emotional state, reflection, collaborative projects, and visualising ideas. Screenshots
illustrate the application of these tools, mapped to their level on the SAMR model. The examples
effectively demonstrate how cloud technologies can facilitate specific activities that develop essential
soft skills like communication, teamwork, critical thinking and creativity.
The advantages of cloud technologies, such as accessibility, flexibility, and data storage, are discussed.
Potential challenges like internet dependence, privacy concerns, and costs are also acknowledged. The
authors persuasively argue that cloud technologies have significant potential for creating environments
conducive to soft skills development.
Figure 11: Presentation of paper [57].
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The article “Implementing innovative teaching methods for asynchronous learning using Moodle
LMS” by Morze et al. [58] addresses an important issue in education today – how to effectively imple-
ment innovative teaching methods like project-based learning, formative assessment, and facilitate
communication/collaboration in an asynchronous online learning environment. The context is partic-
ularly relevant given the challenges faced by universities in Ukraine during the ongoing war, where
synchronous online learning is often complex due to air raid alerts, power outages, and students/faculty
being dispersed across different locations and time zones.
The authors make a strong case for leveraging the capabilities of learning management systems (LMS)
like Moodle to overcome these obstacles. They provide an excellent overview of innovative pedagogical
approaches like problem-based learning, gamification, storytelling, etc. and analyse survey results
showing that while many instructors at their university are familiar with these methods, adoption in
online courses still needs to be improved.
A key contribution is a detailed walkthrough of how various activities in Moodle, such as Forums,
Workshops, Wikis, etc., can enable effective asynchronous communication, peer assessment, group
project work, and other student-centred learning experiences. The screenshots and step-by-step
explanations are quite valuable for instructors looking to utilise the full potential of their LMS.
Figure 12: Presentation of paper [58].
2.5. Cloud-based Learning Environments
The article “Evaluating transactional distance and student engagement in HyFlex art therapy education
amidst the war in Ukraine” by Bondar et al. [59] presents an in-depth examination of transactional
distance and student engagement in the context of a HyFlex art therapy course taught at a Ukrainian
university during the ongoing war. The authors provide a comprehensive overview of the challenges
faced by Ukrainian higher education institutions amidst the conflict, including internal displacement,
infrastructure damage, and the need to adapt teaching methods to accommodate students’ diverse
circumstances.
One of the study’s strengths is its multifaceted approach, employing quantitative and qualitative
methods to analyse transactional distance and student experiences. The authors effectively integrate
concepts such as “trickle-down engagement” and the empathetic course design perspective, emphasising
the importance of considering students’ cognitive and emotional perspectives in the learning process.
The article offers valuable insights into the design and implementation of the HyFlex art therapy
course, highlighting innovative strategies such as integrating interactive online art therapy tools, re-
sponsive attendance policies, and student-centred assignments. The authors’ attention to the reframing,
reforming, and reclaiming concepts within art therapy practice is particularly noteworthy, as it aligns
with promoting self-exploration, personal growth, and empowerment among students.
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The study’s findings reveal the prevalence of stress among students, with a substantial proportion
experiencing moderate to high-stress levels. This underscores the need for effective stress management
strategies within the educational context. Additionally, the analysis of transactional distance highlights
positive student satisfaction, valuable learning experiences, and strong engagement with online art
therapy tools.
However, the authors acknowledge limitations, such as potential bias in student self-reports due
to the stress of war, varying attendance conditions, and limited generalizability to other art therapy
programs. Nonetheless, the article contributes valuable insights into the challenges and opportunities
of delivering art therapy education in a HyFlex format during conflict.
Figure 13: Presentation of paper [59].
2.6. Digital Transformation of Education
The article “The role of information technologies in developing innovative bioeconomic ecosystems for
sustainable transformation” by Vostriakova et al. [60] starts by motivating the need for bioeconomic
transformation to address challenges like climate change, resource depletion, and ecosystem loss. It
highlights the potential of the bioeconomy, especially in combining knowledge from different sectors
like agriculture, processing industries, biotechnology, and information technology.
The authors then evaluate innovative activities in Ukraine’s bioeconomic sector. They find that while
the processing industry accounts for the most innovative enterprises, the level of innovation, especially
in low-tech bioeconomy subsectors like food and wood, is very low compared to European standards.
This low innovativeness is attributed to limited investment in R&D and innovation in these sectors.
The core contribution lies in conceptualising “innovative bioeconomic ecosystems” as regional
agglomerations that provide formal and informal support services for bio-innovative entrepreneurship.
The authors argue that such ecosystems, driven by a culture of innovation and involving diverse
stakeholders, can catalyse the bioeconomic transformation by facilitating knowledge transfer, creating
value networks, and attracting investment.
The article assesses the development of Ukraine’s IT sector, highlighting its growth potential de-
spite challenges like Russian aggression. It then provides a systematic overview of how information
technologies can contribute to bio-innovation, including integrating biotechnology with engineering
design cycles, green biotechnology, data analysis, security, skills development, and digitising biological
resources.
A conceptual model is proposed outlining four critical roles for IT in bio-innovative ecosystems:
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(1) digital networks to connect sectors and blockchain, (2) bioresource management and satellite
technologies, (3) new biomaterials databases and decentralised production, and (4) augmented reality
for training and smart manufacturing.
Figure 14: Presentation of paper [60].
The article “Integrating digital competencies of researchers into Ph.D. curricula: a case study on open
science education” by Kuzminska et al. [61] examines the importance of integrating digital competencies
and open science practices into training Ph.D. students and future researchers. The authors argue that
the openness and digitalisation of science are increasingly critical in the modern era, requiring new
approaches to scholarly work and innovation at universities. However, these skills are often overlooked
in traditional Ph.D. curricula.
The authors set out to determine the key digital competencies needed by researchers, evaluate how
well they are integrated into current Ph.D. programs, develop an elective training module on “Open
Science” to build these competencies and assess the module’s effectiveness through an empirical study.
A significant contribution is the detailed mapping and comparison of frameworks for defining digital
competencies, like DigComp and the Jisc Researcher profile. The authors leverage the Jisc profile as the
basis for specifying the target digital competencies for researchers. They then analyse the current Ph.D.
curricula and design a new “Open Science” module aligned with building those competencies.
The module covers open-access publishing, research data management, open-source tools, scholarly
communication networks, research integrity, and interdisciplinary platforms. The authors validate the
module’s importance and relevance through expert evaluation.
The paper’s core is an empirical study assessing the module’s impact on Ph.D. students at a Ukrainian
university. Using surveys and statistical analysis, the authors find that students who took the module
showed significantly higher self-assessed digital competencies compared to a control group across
several key areas, such as digital research skills, productivity, and identity development.
While the module proved effective for building basic digital capabilities, the authors identify gaps
in fully integrating open science practices and digitalisation into the Ph.D. experience. They propose
expanding practical experiences through stronger connections between universities and research
projects.
The article “Formation of digital competence of specialists in socionomic professions as a pedagogical
problem” by Lovianova et al. [62] examines the critical issue of developing digital competence among
professionals working in “socionomic” fields like teaching, law, social work, psychology, etc. The authors
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Figure 15: Presentation of paper [61].
rightly point out that digitalisation rapidly transforms society and the workplace, necessitating new
competencies for successful job performance. This article makes a valuable contribution by synthesising
prior work and convincingly arguing why developing digitally competent socionomic professionals
should be a pedagogical priority. Future research could pilot digitally-infused curriculum models focused
on shared socionomic core competencies to push the thesis further. However, within its scope, the
paper capably frames the issue’s importance for modern professional education.
Figure 16: Presentation of paper [62].
2.7. Educational Data Mining
The article “A content analysis software system for efficient monitoring and detection of hate speech in
online media” by Krylova-Grek and Burov [63] presents an interdisciplinary project that combines a
computer program for quantitative content analysis with a psycholinguistic approach for qualitative
analysis to identify hate speech in online media. The key aims were to develop a content analysis
program to monitor Russian media outlets and apply psycholinguistic methods to detect hidden and
manipulative hate speech.
The quantitative analysis was conducted using a Python program that searched selected websites
using a dictionary of hate keywords, periods, and outlet names. This allowed efficient filtering of many
articles that potentially contained hate speech for further qualitative review.
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The qualitative analysis utilised the authors’ psycholinguistic text analysis method to categorise the
articles into three types: direct hate speech, indirect/hidden hate speech, and manipulative hate speech.
This manual analysis could identify nuances like sarcasm, newly constructed hate words, and implicit
meanings that automated methods would miss.
The combined approach was applied to monitor 11 Russian language online media outlets publishing
on the Ukraine-Russia conflict from December 2020 to May 2021. Out of 1,284 publications analysed,
560 were identified as containing hate speech elements after the qualitative review.
Figure 17: Presentation of paper [63].
2.8. Social Analytics in Education
The article “Assessing the state of research e-infrastructures for open science in Ukrainian higher
education institutions” by Drach et al. [64] provides a thorough analysis of the current state of research
e-infrastructures within the realm of Open Science at Ukrainian higher education institutions (HEIs).
The authors ground their research in the context of the challenges posed by the Russian invasion of
Ukraine in 2022, which has severely impacted HEIs’ operations and research capabilities.
The authors establish a robust theoretical framework by examining existing literature, policies, and
initiatives related to Open Science and research e-infrastructures in Ukraine and Europe. They propose
a model for the ecosystem of research e-infrastructures, encompassing components such as open access
to publications, open research data, citizen science, education and skills development, research integrity,
and performance evaluation.
The study’s empirical component employs a comprehensive survey involving 1,502 participants from
over 110 HEIs across Ukraine. The findings reveal areas for improvement in organisational support,
awareness, and utilisation of research e-infrastructure services. While some HEIs have established
dedicated units or appointed staff for e-infrastructure development, many need more systematic efforts,
leading researchers to rely on publicly available resources.
The authors highlight discrepancies in perceptions and awareness levels among staff categories,
scientific degrees, and research experience. Limited awareness is particularly evident regarding services
for open data management, research integrity, and professional development in Open Science.
The study identifies institutional and national repositories as the primary sources for facilitating
open access to publications, while the adoption of international services remains limited. The authors
also note challenges related to server damage due to military operations and the need for better support
and guidance, especially for young researchers.
The paper’s strengths lie in its comprehensive coverage, empirical data analysis, and practical recom-
mendations. The authors propose establishing a pervasive culture of Open Science at the institutional
level, enhancing normative documents, appointing competent professionals for e-infrastructure man-
agement, fostering communication and awareness, engaging IT and library staff, and prioritising
continuous professional development.
The article “Information-analytical systems for supporting scientific research in Ukraine: development
and applications” by Kamyshyn et al. [65] provides an in-depth analysis of the role of information-
analytical systems (IAS) in supporting scientific research activities, with a focus on Ukraine’s experience
14
Stamatios Papadakis et al. CEUR Workshop Proceedings 1–21
Figure 18: Presentation of paper [64].
and efforts in developing and implementing such systems. The authors effectively establish the sig-
nificance of IAS in the digital era, highlighting their multifaceted benefits, including data collection,
analysis, collaboration, information retrieval, modelling, and decision support.
The article commences with a well-structured literature review, underscoring the growing interest in
leveraging digital technologies to enhance scientific endeavours. The authors then articulate the study’s
aim and objectives, which revolve around exploring how Ukrainian IAS contribute to the digitalisation
of science and the organisational support of research activities.
A noteworthy strength of the article lies in its systematic examination of the concept of “IAS for
supporting scientific activities” and elucidating their pivotal role in research processes. The authors
provide a comprehensive overview of the functions and advantages offered by IAS, substantiating their
arguments with relevant citations from the existing literature.
Furthermore, the article presents a detailed account of Ukraine’s experience in the digital era, show-
casing the various IAS developed by the State Scientific Organization “Ukrainian Institute of Scientific
Technical and Expertise and Information” (UkrISTEI). The authors meticulously describe the features
and capabilities of these systems, such as the National Repository of Academic Texts, the Automated
System for Formation of Interstate Information Resources, and the Electronic Registration System for
Open Scientific Research and Development Works, among others. This section offers valuable insights
into IAS’s practical implementation and real-world applications in supporting scientific research in
Ukraine.
The authors also acknowledge the challenges and limitations associated with implementing IAS,
including regulatory, organisational, and software-related hurdles and the need to enhance digital and
information-analytical competencies among scientific and academic staff.
3. Conclusion and outlook
The 11th Workshop on Cloud Technologies in Education (CTE 2023) has once again demonstrated its
commitment to fostering the growth of emerging researchers and providing a platform for exchanging
innovative ideas and early research findings. The CTE 2023 proceedings offer valuable insights into the
potential of cloud technologies to transform and enhance educational experiences. The papers showcase
a diversity of innovative approaches and applications across various disciplines and educational levels.
They highlight the potential for cloud-based solutions to address challenges faced by educators, such
as limited access to physical resources, the need for flexible learning environments, and the growing
importance of soft skills development.
15
Stamatios Papadakis et al. CEUR Workshop Proceedings 1–21
Figure 19: Presentation of paper [65].
As we conclude this successful edition of the workshop, we extend our gratitude to all the authors,
delegates, program committee members, and peer reviewers who have contributed to its success. Their
invaluable efforts and commitment have ensured the high quality and relevance of the presented work,
further elevating the standards of academic excellence.
We want to acknowledge the developers and professional staff of the Academy of Cognitive and
Natural Sciences (https://acnsci.org) and the Not So Easy Science Education platform (https://notso.
easyscience.education) for providing us with the excellent and comprehensive conference management
system that facilitated the smooth running of the workshop.
Since CTE 2017, our workshop is sponsored by the CEUR Workshop Proceedings (CEUR-WS.org),
the world’s best Diamond Open-Access proceedings publisher for Computer Science workshops. Long
live CEUR-WS.org!
We look forward to the next instalment of CTE, scheduled for December 27, 2024, in Kryvyi Rih,
Ukraine. This future gathering promises to be an even more enriching and thought-provoking experience,
where emerging talents will converge to share their latest discoveries, engage in stimulating discussions,
and forge lasting connections that will shape the future of these dynamic and ever-evolving fields.
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