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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Rapid digital competence development through emergency remote teaching: a three-wave analysis of teacher training during COVID-19</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Tetiana A. Vakaliuk</string-name>
          <email>tetianavakaliuk@gmail.com</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Oleg M. Spirin</string-name>
          <email>spirin@iitlt.gov.ua</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Oleksii V. Chyzhmotria</string-name>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Olena H. Chyzhmotria</string-name>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Inesa V. Novitska</string-name>
          <email>inesanovicka@gmail.com</email>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Svitlana O. Didkivska</string-name>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Iurii M. Iefremov</string-name>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="editor">
          <string-name>PCWrEooUrckResehdoinpgs ISSNc1e6u1r-3w-0s0.o7r3g</string-name>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Academy of Cognitive and Natural Sciences</institution>
          ,
          <addr-line>54 Universytetskyi Ave., Kryvyi Rih, 50086</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Institute for Digitalisation of Education of the NAES of Ukraine</institution>
          ,
          <addr-line>9 M. Berlynskoho Str., Kyiv, 04060</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Kraków University of Economics</institution>
          ,
          <addr-line>27 Rakowicka Str., Kraków, 31-510</addr-line>
          ,
          <country country="PL">Poland</country>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>Kryvyi Rih State Pedagogical University</institution>
          ,
          <addr-line>54 Universytetskyi Ave., Kryvyi Rih, 50086</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
        <aff id="aff4">
          <label>4</label>
          <institution>Zhytomyr Ivan Franko State University</institution>
          ,
          <addr-line>30 Velyka Berdychivska Str., Zhytomyr, 10002</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
        <aff id="aff5">
          <label>5</label>
          <institution>Zhytomyr Polytechnic State University</institution>
          ,
          <addr-line>103 Chudnivsyka Str., Zhytomyr, 10005</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
      </contrib-group>
      <fpage>68</fpage>
      <lpage>77</lpage>
      <abstract>
        <p>The COVID-19 pandemic necessitated immediate digital transformation in education, revealing critical gaps in teachers' technological competencies. This study examines a rapid-response professional development program implemented across three waves during March-April 2020, engaging 1,500 registered Ukrainian educators. The ifve-day intensive course addressed essential cloud-based teaching competencies through Google Workspace tools. Data analysis reveals a 54.4% completion rate among the 1,029 active participants, with subsequent implementation tracking showing marked improvement in technology adoption. Post-training surveys (n=263) demonstrate a shift from 11.8% independent task management to 82.5% conducting synchronous online classes by 2021. The research identifies critical implementation challenges including technical literacy barriers, collaborative document management dificulties, and participant engagement patterns. Two additional face-to-face cohorts (n=91) provided comparative data on instructional modality efectiveness. Longitudinal assessment indicates sustained behavioral change, with 56.7% of teachers adopting previously unused digital tools. These findings inform emergency professional development design, suggesting optimal participant cohort sizes, prerequisite assessment protocols, and structured deadline management. The study contributes empirical evidence on rapid competency development under crisis conditions, with implications for resilient educational system design.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;emergency remote teaching</kwd>
        <kwd>teacher professional development</kwd>
        <kwd>digital competence</kwd>
        <kwd>cloud-based learning</kwd>
        <kwd>COVID19 education response</kwd>
        <kwd>Google Workspace for Education</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction</title>
      <p>
        The global COVID-19 pandemic created unprecedented disruption in educational systems worldwide,
forcing an immediate transition from traditional classroom instruction to emergency remote teaching
[
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. This sudden shift exposed significant disparities in educators’ digital competencies [
        <xref ref-type="bibr" rid="ref2 ref3 ref4">2, 3, 4</xref>
        ] and
their preparedness to deliver quality instruction through online modalities [
        <xref ref-type="bibr" rid="ref5">5, 6, 7, 8, 9, 10</xref>
        ]. Ukrainian
educational institutions faced particular challenges, as teachers had minimal preparation time to adapt
pedagogical practices developed over decades for face-to-face instruction.
      </p>
      <p>The “Procedure for the professional development of pedagogical and scientific-pedagogical workers”
identifies distance learning as an approved professional development modality, specifically emphasizing
information and communication technology integration and digital competence development as priority
areas [11]. This regulatory framework provided the foundation for rapid deployment of professional
development initiatives during the quarantine period.</p>
      <p>Prior research demonstrates varying levels of digital literacy among educators before the pandemic
[12, 13]. While some institutions had initiated technology integration programs, systematic preparation
for fully online instruction remained limited. The pandemic accelerated a digital transformation that
might otherwise have taken years to implement, compressing adoption timelines from months to days
[14].</p>
      <p>This study examines the design, implementation, and outcomes of an intensive professional
development program delivered to Ukrainian educators during the initial pandemic response period. The
research addresses three primary questions: (1) What instructional design features facilitate rapid
competency development under crisis conditions? (2) How do participant engagement patterns difer
between distance and face-to-face modalities? (3) What sustained behavioral changes result from
emergency professional development interventions?</p>
    </sec>
    <sec id="sec-2">
      <title>2. Theoretical framework</title>
      <p>Digital competence encompasses technical skills, pedagogical knowledge, and adaptive capacity required
for efective technology integration in teaching and learning processes [ 15]. The European Framework
for the Digital Competence of Educators (DigCompEdu) identifies six competence areas: professional
engagement, digital resources, teaching and learning, assessment, empowering learners, and facilitating
learners’ digital competence [16].</p>
      <p>Emergency remote teaching difers fundamentally from planned online learning in design time,
preparation, and support structures [17]. While planned online courses undergo systematic instructional
design processes, emergency remote teaching requires rapid adaptation of existing materials and
methods. This distinction has significant implications for professional development approaches.</p>
      <p>
        Cloud-based platforms provide scalable, accessible infrastructure for educational delivery [18, 19].
Google Workspace for Education emerged as a widely adopted solution during the pandemic, ofering
integrated tools for communication, collaboration, content creation, and classroom management [
        <xref ref-type="bibr" rid="ref6">20</xref>
        ].
Research indicates that successful cloud technology adoption requires both technical proficiency and
pedagogical recontextualization [
        <xref ref-type="bibr" rid="ref7 ref8 ref9">21, 22, 23</xref>
        ].
      </p>
      <p>
        Previous implementations of cloud-based learning environments demonstrate the importance of
scafolded support and gradual complexity increases [
        <xref ref-type="bibr" rid="ref10">15, 24</xref>
        ]. However, pandemic conditions eliminated
opportunities for such gradual adoption, necessitating compressed training timelines and simultaneous
skill development across multiple competency areas.
      </p>
      <p>
        Crisis-driven professional development difers from traditional models in urgency, scope, and
evaluation criteria [
        <xref ref-type="bibr" rid="ref11 ref12">25, 26</xref>
        ]. Efective emergency training programs share several characteristics: focused
objectives, practical application emphasis, peer support mechanisms, and immediate implementation
opportunities [
        <xref ref-type="bibr" rid="ref13 ref14">27, 28</xref>
        ].
      </p>
      <p>
        Adult learning principles suggest that relevance, experience integration, and problem-centered
approaches enhance engagement and retention [
        <xref ref-type="bibr" rid="ref15 ref16">29, 30</xref>
        ]. These principles become particularly salient
when participants face immediate application requirements and high-stakes implementation contexts.
      </p>
    </sec>
    <sec id="sec-3">
      <title>3. Methodology</title>
      <sec id="sec-3-1">
        <title>3.1. Course design and development</title>
        <p>The certificate educational program “Information systems and cloud technologies in the educational
process” was developed within specialty 126 “Information systems and technologies” at Zhytomyr
Polytechnic State University [31]. The course “Cloud technologies in the educational process in
quarantine” adapted existing content for emergency deployment [32].</p>
        <p>Course objectives focused on practical competencies: (1) understanding cloud service models and
architectures; (2) utilizing Google Workspace tools for instruction; (3) creating and managing digital
content; (4) implementing online assessment strategies; (5) establishing virtual classroom environments.</p>
        <p>Content delivery employed an asynchronous model with structured daily modules. Each module
included theoretical materials, video demonstrations, practical exercises, and collaborative activities.
Assessment relied on task completion rather than traditional testing, emphasizing application over
memorization.</p>
      </sec>
      <sec id="sec-3-2">
        <title>3.2. Participant recruitment and demographics</title>
        <p>Three implementation waves occurred: March 30-April 3, 2020 (Wave 1), April 6-10, 2020 (Wave 2), and
April 13-17, 2020 (Wave 3). Registration utilized online forms distributed through educational networks
and oficial channels.</p>
        <p>Participants represented diverse educational sectors: general secondary education (n=499), preschool
education (n=16), higher education (n=70), vocational education (n=82), educational administration
(n=94), and other roles (n=55). Geographic distribution included all Ukrainian regions, with 40 higher
education institutions represented.</p>
      </sec>
      <sec id="sec-3-3">
        <title>3.3. Data collection and analysis</title>
        <p>Multiple data sources informed the analysis:
1. Registration and completion records (n=1,500 registered, n=816 completed).
2. Task submission timestamps and interaction logs.
3. Post-course evaluation surveys.
4. Follow-up surveys with first-year university students ( n=263) regarding their secondary school
experience.
5. Comparative data from face-to-face implementations (n=91).</p>
        <p>Quantitative analysis employed descriptive statistics and completion rate calculations. Qualitative
data from open-ended survey responses underwent thematic analysis to identify implementation
challenges and success factors.</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>4. Results</title>
      <sec id="sec-4-1">
        <title>4.1. Participation and completion patterns</title>
        <p>The 31.4% attrition between registration and active participation resulted primarily from technical
issues: incorrect email addresses (n=113), inability to access platforms, and external time constraints.
Among active participants, the overall completion rate of 79.3% exceeded typical MOOC completion
rates, suggesting high motivation and perceived relevance.</p>
      </sec>
      <sec id="sec-4-2">
        <title>4.2. Implementation challenges</title>
        <p>Analysis identified five primary challenge categories:
1. Technical literacy barriers: Participants struggled with basic digital tasks including screenshot
capture, file uploads, and navigation between platforms. Despite step-by-step instructions,
repeated questions about identical procedures consumed significant instructor time.
2. Collaborative document management: Tasks requiring shared editing generated confusion and
occasional conflicts. Participants inadvertently modified others’ content or deleted existing work,
particularly in group presentation exercises where all participants edited simultaneously.
3. Time management: Asynchronous deadlines created cascading delays when participants failed to
complete prerequisite tasks. Late submissions afected collaborative exercises, reducing learning
opportunities for punctual participants.
4. Instructional clarity: Despite comprehensive written materials, participants frequently requested
clarification on previously explained concepts. This pattern suggests cognitive overload or
insuficient processing time for complex technical information.
5. Attribution understanding: Academic collaboration concepts proved challenging, with participants
interpreting peer editing as criticism rather than constructive engagement.</p>
      </sec>
      <sec id="sec-4-3">
        <title>4.3. Learning outcomes and artifacts</title>
        <p>Participants produced diverse learning artifacts demonstrating concept application:
• Mind maps covered subject-specific topics including mathematics, biology, language learning,
and computer science. Visual quality and structural sophistication varied, but all demonstrated
basic competency with collaborative tools (figure 1).
• Presentations utilized various cloud-based platforms, with content ranging from lesson
introductions to complete instructional modules (figure 2). Technical proficiency improved markedly
between initial and final submissions.
• Website creation exercises yielded functional educational sites, though design sophistication
varied considerably. Most participants achieved basic functionality requirements.</p>
      </sec>
      <sec id="sec-4-4">
        <title>4.4. Comparative analysis: distance versus face-to-face delivery</title>
        <p>Two face-to-face implementations (August 25-28, 2020; September 14-18, 2020) with 91 participants
provided comparative data. Face-to-face participants demonstrated similar challenge patterns: inattention
to instructions, dificulty with screen capture procedures, and collaborative task confusion.</p>
        <p>However, face-to-face delivery enabled immediate clarification and peer support, reducing time to
task completion. Physical presence also increased accountability and reduced attrition rates.</p>
      </sec>
      <sec id="sec-4-5">
        <title>4.5. Long-term impact assessment</title>
        <p>Follow-up surveys with university freshmen (September 2021) assessed sustained changes in secondary
school instruction. Results indicate substantial shifts in instructional delivery methods:
• March-April 2020 (pre-intervention):
• September 2020-May 2021 (post-intervention):
– Independent task completion: 11.8%
– Material distribution via messaging apps: 35.7%
– Synchronous online instruction: 52.5%
– Independent task completion: 3.8%
– Material distribution via messaging apps: 13.7%
– Synchronous online instruction: 82.5%</p>
        <p>The data reveal a 30 percentage point increase in synchronous online instruction, suggesting
successful technology adoption and sustained behavioral change.</p>
      </sec>
    </sec>
    <sec id="sec-5">
      <title>5. Discussion</title>
      <p>The compressed timeline necessitated design decisions prioritizing immediate applicability over
comprehensive coverage. Task-based assessment proved efective for skill demonstration while reducing
evaluation burden. Collaborative exercises, despite implementation challenges, provided authentic
practice opportunities mirroring actual teaching contexts.</p>
      <p>Success factors included clearly defined daily objectives, multimedia instructional materials, and
lfexible support mechanisms. The registration-to-completion pipeline revealed critical failure points
requiring targeted interventions in future implementations.</p>
      <p>High completion rates among active participants suggest strong intrinsic motivation driven by
immediate professional needs. The pandemic context created authentic urgency absent in traditional
professional development programs. Participants recognized direct connections between course content
and daily teaching challenges.</p>
      <p>However, engagement patterns revealed concerning behaviors including insuficient attention to
instructions and repeated requests for previously provided information. These patterns suggest cognitive
overload or inadequate metacognitive strategies for managing complex technical learning.</p>
      <p>The three-wave implementation demonstrated both scalability potential and resource limitations.
Instructor workload increased exponentially with participant numbers, particularly given repetitive
support requests. Future implementations should incorporate automated support systems and peer
mentoring structures.</p>
      <p>Sustained behavioral change evidenced in follow-up data validates the intervention’s efectiveness.
However, long-term support mechanisms remain necessary for continued skill development and
adaptation to evolving technologies.</p>
      <p>Several design principles emerge from this analysis:
1. Modular content architecture – self-contained daily modules accommodate varying participation
patterns and technical dificulties.
2. Progressive complexity – initial tasks should establish baseline competencies before introducing
collaborative elements.
3. Redundant communication channels – multiple information delivery methods account for varying
learning preferences and technical limitations.
4. Embedded assessment – task completion as assessment reduces additional cognitive burden while
providing authentic performance evidence.
5. Community support structures – peer networks sustain motivation and provide distributed
support capacity.</p>
    </sec>
    <sec id="sec-6">
      <title>6. Limitations</title>
      <p>Several limitations constrain generalizability. Self-selection bias afects participant composition, as
motivated educators were more likely to register and complete the course. The Ukrainian educational
context may not reflect conditions in other national systems. Follow-up data collection relied on student
perceptions rather than direct teacher observation.</p>
      <p>Technical infrastructure assumptions may not hold in resource-constrained environments. The study
period coincided with initial pandemic responses when motivation for change peaked. Subsequent
“pandemic fatigue” might yield diferent engagement patterns.</p>
    </sec>
    <sec id="sec-7">
      <title>7. Conclusions</title>
      <p>This study demonstrates the feasibility of rapid digital competency development under crisis conditions.
The intervention successfully prepared 816 educators for emergency remote teaching within a
compressed five-day timeline. Key success factors included relevant content, practical focus, and immediate
application opportunities.</p>
      <p>Critical design considerations for emergency professional development include:
• Realistic scope definition acknowledging time and cognitive constraints.
• Pre-assessment protocols identifying baseline competencies.
• Structured collaboration with clear role definitions.
• Technical support scaling proportional to participant numbers.</p>
      <p>• Post-training support sustaining initial gains.</p>
      <p>The research contributes empirical evidence on emergency professional development efectiveness,
informing future crisis response strategies. As educational systems develop resilience frameworks,
rapid competency development mechanisms become essential infrastructure components.</p>
      <p>Future research should examine optimal cohort sizes, investigate cultural factors afecting technology
adoption, and develop automated support systems reducing instructor burden. Longitudinal studies
tracking skill retention and evolution would inform sustained professional development approaches.</p>
      <p>The COVID-19 pandemic accelerated educational digitalization by several years. While crisis-driven
transformation creates challenges, it also reveals latent capacity for rapid adaptation. This study’s
ifndings suggest that carefully designed interventions can catalyze lasting positive change even under
adverse conditions.</p>
    </sec>
    <sec id="sec-8">
      <title>Acknowledgments</title>
      <p>The authors thank all participating educators for their commitment to professional growth during
challenging circumstances. Special recognition goes to technical support staf who maintained platform
stability throughout the implementation period.</p>
    </sec>
    <sec id="sec-9">
      <title>Declaration on Generative AI</title>
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