{
  "id": "2018-blayone-surveyingdigitalcompetenciesuniversity-Q62J4DZK",
  "title": "Surveying digital competencies of university students and professors in Ukraine for fully online collaborative learning",
  "authors": [
    "Blayone, Todd J.B.",
    "Mykhailenko, Olena",
    "vanOostveen, Roland",
    "Grebeshkov, Oleksiy",
    "Hrebeshkova, Olena",
    "Vostryakov, Oleksandr"
  ],
  "year": "2018",
  "abstract": "Collaborative-constructivist online learning appears well aligned with Ukraine’s post-revolutionary aspirations for globalised and transformed higher education. This study explores digital competencies of students and professors at Kyiv National Economic University, Ukraine, to probe readiness for fully online collaborative learning. The General Technology Competency and Use profile tool was completed by 244 participants to measure digital experience and confidence across four categories of human–computer activity. To assess readiness, reported levels of competencies were related to the three dimensions of successful collaborative learning described by the Community of Inquiry model. Despite some key differences between students and teachers, general findings include moderate-to-low levels of self-reported technical, social and informational competency, accompanied by consistently low levels of epistemological competency. These findings suggest that neither students nor teachers are adequately prepared for achieving high levels of social, cognitive and teaching presence in a fully online learning environment. It is recommended that digital-competency development become an educational priority.",
  "keywords": [],
  "biblio": {
    "type": "article-journal",
    "container_title": "Technology, Pedagogy and Education",
    "volume": "27",
    "issue": "3",
    "pages": "1-18",
    "doi": "10.1080/1475939X.2017.1391871",
    "url": "",
    "publisher": "",
    "publisher_place": "",
    "issn": "",
    "isbn": ""
  },
  "sections": [
    {
      "label": "abstract",
      "heading": "Abstract",
      "level": 1,
      "text": "Collaborative-constructivist online learning appears well aligned with Ukraine’s post-revolutionary aspirations for globalised and transformed higher education. This study explores digital competencies of students and professors at Kyiv National Economic University, Ukraine, to probe readiness for fully online collaborative learning. The General Technology Competency and Use profile tool was completed by 244 participants to measure digital experience and confidence across four categories of human–computer activity. To assess readiness, reported levels of competencies were related to the three dimensions of successful collaborative learning described by the Community of Inquiry model. Despite some key differences between students and teachers, general findings include moderate-to-low levels of self-reported technical, social and informational competency, accompanied by consistently low levels of epistemological competency. These findings suggest that neither students nor teachers are adequately prepared for achieving high levels of social, cognitive and teaching presence in a fully online learning environment. It is recommended that digital-competency development become an educational priority. \n\n## **ARTICLE HISTORY** \n\nReceived 30 May 2016 accepted 13 May 2017 \n\n## **KEYWORDS** \n\ndigital competence; fully online learning; educational transformation; ukraine; higher education",
      "page_span": {
        "start": 1,
        "end": 1
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Context",
      "level": 1,
      "text": "Ukraine, a country with a declining population of about 44 million people (Worldometers, 2017), is a transitional post-Soviet nation (Roztocki & Weistroffer, 2015). Despite making strides towards democratisation since independence in 1991, full integration with Europe, and Western levels of socio-economic development, have not been realised (Nikolayenko, 2009; Wilson, 2013). Researchers have described Ukrainians as experiencing low self-confidence and pessimism about the future (Nikolayenko, 2009), low levels of trust (Rose-Ackerman, 2001), acute social atomisation (Pjesivac, 2014) and weak civil engagement (Way, 2014). One positive Soviet legacy is mass education: almost 30% of Ukrainians have completed higher education (Wilson, 2013). \n\nIn early 2014, two million Ukrainian protesters, initially led by university students, ousted the Russianbacked president Viktor Yanukovych, after he refused to sign a major economic agreement with the EU (Onuch, 2014). This ‘Euromaidan revolution’ crystallised democratic values – including freedom of expression, self-direction, universalism and openness to change (Sviatnenko & Vinogradov, 2014). In \n\n**CONTACT** Todd J. B. Blayone todd.blayone@collaboritsi.com \n\npost-Maidan Ukraine, educational reform efforts are a high priority (Kovtun & Stick, 2009; Kutsyuruba, 2011; Kutsyuruba & Kovalchuk, 2015). New learning models aligned with democratic transformation and digital innovation are especially coveted (Powell, Kuzmina, Yamchynska, Shestopalyuk, & Kuzmin, 2015; Sharkova, 2014).",
      "page_span": {
        "start": 1,
        "end": 2
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Purpose",
      "level": 1,
      "text": "Although not focused on cross-cultural comparison, this study evolved from transnational conversations between Canadian digital-learning researchers at the Educational Informatics Laboratory (EILAB), University of Ontario Institute of Technology (UOIT), and several Ukrainian professors at the Faculty of Economics, Kyiv National Economic University (KNEU). After a partnership was established (UOIT & KNEU, 2015), a seminal research question was formulated: Might fully online learning, like that practised at UOIT (vanOostveen, 2015; vanOostveen & Desjardins, 2013; vanOostveen, DiGiuseppe, Barber, Blayone, & Childs, 2016), offer Ukrainians an effective model for democratising learning and transforming education ‘from below’? In order to pursue this question, an online pilot course was conceived, and a research team was formed to survey the digital competencies of students and professors at the host Ukrainian institution. This preparatory step was considered vital because: (a) digital competencies, developed through experience and confidence (Akaslan & Law, 2012), represent a key facet of online-learning readiness (Borotis & Poulymenakou, 2004; Machado, 2007; Mosa, Naz’ri bin Mahrin, & Ibrrahim, 2016); (b) digital competency levels have a significant impact on group functioning in online-learning communities (Gunawardena et al., 2001); and (c) profiling digital competencies has proven useful at UOIT to support students and faculty in fully online degree programmes (Barber, DiGiuseppe, vanOostveen, Blayone, & Koroluk, 2016; Desjardins, vanOostveen, Bullock, DiGiuseppe, & Robertson, 2010; DiGiuseppe, Partosoedarso, vanOostveen, & Desjardins, 2013). \n\nThe guiding research questions were formulated as follows: \n\n- (1)  What digital competencies are most relevant to achieving successful participation in a fully online collaborative learning environment? \n\n- (2)  What levels of these digital competencies do Ukrainian students and professors report? \n\n- (3)  Are there significant differences between reported student and professor competencies? \n\n- (4)  Do the competency profiles of Ukrainian students and professors suggest readiness for successful functioning in a fully online collaborative learning environment?",
      "page_span": {
        "start": 2,
        "end": 2
      },
      "confidence": "high"
    },
    {
      "label": "theory",
      "heading": "Theoretical frameworks",
      "level": 1,
      "text": "In order to address these questions, a theoretical apparatus was constructed from the literature. First, the General Technology Competency and Use (GTCU) framework (Desjardins, 2005; Desjardins, Lacasse, & Belair, 2001; Desjardins & Peters, 2007) was selected to conceptualise and measure digital competencies. Second, the Community of Inquiry (CoI) digital-learning model (Garrison, 2011, 2013, 2016) was selected to conceptualise successful social-constructivist learning. Finally, the constituent dimensions of both models were related so that reported digital competencies (measured by the GTCU) could be interpreted by the researchers as indicators of readiness (and non-readiness) for successful, collaborative-constructivist learning (as defined by the CoI).",
      "page_span": {
        "start": 2,
        "end": 2
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "The General Technology Competency and Use framework: a model for conceptualising and measuring digital competencies",
      "level": 2,
      "text": "The GTCU framework was selected owing to several strengths. First, it is an extensively theorised and operationalised, digital-competency framework developed in a university context of fully online education (Desjardins, 2005; Desjardins, Davidson, Blayone, vanOostveen, & Childs, 2015). Second, the \n\nGTCU’s survey instrument has been used successfully over time to probe the digital readiness of both students and teachers (Barber et al., 2016; Desjardins et al., 2010; Desjardins & vanOostveen, 2015; DiGiuseppe et al., 2013; DiGiuseppe, vanOostveen, Childs, Blayone, & Barber, 2017). Finally, by incorporating behavioural and attitudinal indicators, and associating items with specific types of devices, this instrument provides a depth of data beyond other e-learning readiness instruments (Blayone, vanOostveen, Mykhailenko, & Barber, 2017b). \n\nThe GTCU offers a highly reduced model that remains stable over time despite ongoing changes to digital devices, software functionality and human motives for technology use (Desjardins et al., 2015). This is achieved by conceptualising three foundational ‘orders’ (dimensions) of digital competency using the Institute of Electrical and Electronics Engineers’ definition of computer hardware: ‘physical equipment used to _process_ , _store_ , or _transmit_ computer programs or data’ (IEEE, 1990, p. 99, emphasis in original). As shown in Figure 1, Desjardins (2001) called these competency orders _epistemological_ (process), _informational_ (store) and _social_ (transmit). Knowledge and abilities in each of these orders support effective functioning as digital learners and teachers. A secondary _technical_ order was added to acknowledge operational competencies that are prerequisite to successful interaction in the three primary orders. \n\nThe epistemological order of use is theorised as those interactions in which a person assigns cognitive (algorithmic) tasks to a computer using a programming language or the features of a software application (e.g. a spreadsheet or concept-mapping tool). Key competencies relate to effective data analysis, problem solving and hypothesis development (Desjardins, 2005). The informational order relates to interactions between humans and information objects. Key competencies relate to effective searching, evaluation, synthesis and the production of new knowledge (Desjardins, 2005). The social order addresses competencies related to effective digital communication, collaboration and publication (Desjardins, 2005).",
      "page_span": {
        "start": 2,
        "end": 3
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Community of Inquiry: a model for fully online collaborative learning",
      "level": 2,
      "text": "Many online learning models, like massive open online courses (MOOCs), emphasise open access to expert content and individualised learning (Dalsgaard & Paulsen, 2009; De Corte, Engwall, & Teichler, 2016; Paulsen, 2008; Siemens, Gašević, & Dawson, 2015). Others focus on building highly collaborative \n\n**Figure 1.** dimensions of digital competency according to the gTcu framework, authored by François desjardins. \n\nlearning communities. The Community of Inquiry model (Garrison, 2011, 2013) belongs to the latter group, and was selected as a guiding model for the Ukrainian pilot course. Like some other collaborative-constructivist models (Blayone, vanOostveen, Barber, DiGiuseppe, & Childs, 2017; Gunawardena et al., 2004, 2006), the CoI offers a foundation for democratised education at the level of course interactions. It builds on the theories of Dewey (1897), Piaget (1959) and Vygotsky (1978) to envision learners as ‘post-industrial’ inquirers (Swan, 2010). More specifically, the CoI models _ideal_ learning communities (Garrison & Archer, 2000) which: \n\n- integrate individual and social priorities, incorporating the fundamental ideals and values of participatory democracy (Dewey, 1897, 1916; Garrison, 2013); \n\n- promote ‘deep learning’ instead of rote learning, fostering reflective thinking and cognitive agility (Akyol & Garrison, 2011; Garrison, Anderson, & Archer, 2001); \n\n- facilitate active collaboration, freedom of expression, and deliberation vital for effective entrepreneurship, innovation and social development (Garrison, 2016); \n\n- adapt to the cultural values of participants, recognising experience as an essential foundation for new knowledge (Dewey, 1897); \n\n- emphasise learner-driven, problem-based learning and group inquiry (vanOostveen & Desjardins, 2013). \n\nNot only does the CoI appear well aligned with Ukrainian aspirations for educational transformation, it provides detailed, and empirically researched, descriptions of successful functioning in fully online learning communities – organising successful collaborative learning into three ‘presences’, for which instructors and students share responsibility.",
      "page_span": {
        "start": 3,
        "end": 4
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Relating digital competencies and fully online collaborative learning",
      "level": 2,
      "text": "The CoI’s three presences address social, cognitive and teaching transactions _essential_ to optimal community functioning. To conceptualise the prerequisite digital competencies required to achieve high levels of each presence, the researchers conceptually mapped the GTCU’s orders of digital competency to the CoI presences, as shown in Figure 2. \n\nSocial presence encompasses interpersonal, open and cohesive communication, thus facilitating trust and community cohesion, and aligning directly with the GTCU’s social dimension (Garrison, 2011). Cognitive presence includes facets of critical inquiry (e.g. exploration, synthesis and resolution), and \n\n**Figure 2.** digital competencies for successful, collaborative online learning. \n\nrelies heavily on informational and epistemological competencies, supported by social competencies for effective collaboration (Garrison, 2011). Teaching presence (TP), conceptualised as a shared function, refers to curriculum design, activity facilitation and instruction (Garrison, 2011), thus facilitating cognitive outcomes and requiring high levels of competency across all GTCU orders in fully digital learning environments.",
      "page_span": {
        "start": 4,
        "end": 5
      },
      "confidence": "high"
    },
    {
      "label": "methods",
      "heading": "Method",
      "level": 1,
      "text": "In May and June 2015, data were gathered from students and teachers at KNEU in Kyiv, Ukraine, using the GTCU profile tool. Because the GTCU is an extensive instrument, indicators most relevant to successful online learning were selected for analysis based on two data-reduction processes. Scores on these indicators were analysed in SPSS. Significant differences between students and professors were identified using the Mann–Whitney _U_ test for comparing non-parametric means.",
      "page_span": {
        "start": 5,
        "end": 5
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "The GTCU profile tool",
      "level": 2,
      "text": "Based on an earlier instrument (Desjardins et al., 2001), the GTCU profile tool is a custom, online application developed by the EILAB, UOIT, and used at institutions of higher education around the world. Version 1, used in this study, offered survey and profile-visualisation functionality (Figure 3), and a persistent data repository, facilitating cross-contextual and longitudinal analyses. Version 2, renamed the Digital Competency Profiler, offers a substantially redesigned interface, new profile-visualisation algorithms, and profile-comparison functionality at both the group and individual levels (R. vanOostveen, personal communication, 1 September 2017). \n\nThe GTCU profile tool collects three sets of data: (a) socio-demographic; (b) digital device access and general purposes of use (i.e. work, personal, teaching or studying); and (c) frequency and confidence performing digital activities, measured on 5-point Likert scales. Frequency is measured using _never, a few times a year, a few times a month, a few times a week, daily_ . Frequency of use is an important indicator of competency because transferable procedural knowledge is reinforced through repeated use (i.e. practice leads to acquired ability). Confidence is measured using _do not know how to use; not confident, require assistance to use; confident, can solve some problems; fairly confident, can use with no assistance; very confident, can teach others how to use_ . Confidence of use is an important predictor, not necessarily of acquired ability, but rather of an individual’s willingness to explore novel situations and extend abilities already acquired (Bandura, 1993). Both frequency and confidence are measured in relation to specific devices because device size, degree of mobility and target audience all influence use. \n\nIn total, the GTCU gathers 337 points of data. To prepare the GTCU profile tool for application in Kyiv, a Ukrainian localisation file was created by a co-investigator, and validated by two other Ukrainian academics.",
      "page_span": {
        "start": 5,
        "end": 5
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Validation",
      "level": 3,
      "text": "The originating GTCU instrument of 20 activity items in French underwent content validation through the participation of 10 Canadian teachers and parents (Desjardins et al., 2001). Subsequently, six experts joined Desjardins et al. (2001) in a process of construct validation, which included statistical investigation of correlation matrices. All retained items related well to their conceptualised dimension (Desjardins et al., 2001). Cronbach’s alpha was used to confirm the reliability of the scales in a later study involving 225 Canadian teacher-participants (Desjardins, 2005). The current, updated GTCU profile application of 26 activity items (available in several languages) is based directly on this validated instrument. Furthermore, a recent study compared the reported GTCU competencies of individuals with digitally recorded performances of authentic online-learning scenarios. This study found generally high positive correlations between reported competency levels and performance quality, suggesting the instrument’s predictive value as an online-learning readiness tool (Blayone, vanOostveen, Mykhailenko, & Barber, 2017a).",
      "page_span": {
        "start": 5,
        "end": 7
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Participants and setting",
      "level": 3,
      "text": "Students and professors were recruited from the Department of Enterprise Strategy at the Faculty of Economics and Management, Kyiv National Economic University (KNEU), Ukraine – the sponsoring department of the planned digital-learning pilot course. Twenty professors (two-thirds of departmental teachers) and 224 students (almost one-third of those registered in the faculty) volunteered to complete the GTCU online survey. Student participants were primarily undergraduate students in their twenties. Two-thirds were female, which represents a demographic trend in non-technical fields (O. Mykhailenko, personal communication, 3 April 2016). Full participant characteristics ( _N_ = 244) are provided in Table 1. The logic of collecting data from both students and professors flowed from a collaborative-constructivist ideal whereby, despite role and identity distinctions, students and teachers share responsibility for developing successful, fully online learning communities. \n\n**Table 1.** Socio-demographic characteristics of participants. \n\n|Variables|Values|_N_|%|\n|---|---|---|---|\n|gender|Male|81|33|\n||Female|163|67|\n|age group|19–25|205|84|\n||26–35|23|9|\n||36–49|12|5|\n||50+|4|2|\n|Role|Student|224|92|\n||Professor|20|8|\n|Specialty|economics|122|50|\n||other|12|5|\n||not reported|110|45|\n|highest degree held|diploma|80|33|\n||Bachelor|131|54|\n||Masters|16|6|\n||doctoral|17|7|",
      "page_span": {
        "start": 7,
        "end": 7
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Consent and collection period",
      "level": 3,
      "text": "Having obtained approval from UOIT’s Research Ethics Board and KNEU’s Academic Council, this project proceeded under an international partnership (UOIT & KNEU, 2015). In May 2015, a co-investigator presented the project to colleagues at KNEU, and several professors opted both to participate and share the opportunity with students. Data were collected online from mid May until mid June 2015.",
      "page_span": {
        "start": 7,
        "end": 7
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "GTCU data-reduction strategy",
      "level": 2,
      "text": "In order to identify those GTCU items most pertinent to the research questions, the data were reduced to a manageable and highly relevant subset prior to completing a full, statistical analysis. This was achieved through two data-reduction procedures. \n\nThe first procedure reduced the number of items by reviewing reported device usage, and selecting the device items most relevant to the educational research context. Almost all participants (97%) owned a computer with about half (52%) reporting ‘learning’ as the primary context of use. The same amount (97%) also owned a cell phone or smartphone, but 82% used them primarily for personal purposes. Similarly, very few participants (18%) used a tablet for learning. Therefore, those activity items related to desktop/laptop computers were selected as key indicators. By treating the mobile-device data as supplementary, the primary data set was reduced to 52 items, measuring frequency and confidence for 26 activities. \n\nThe second procedure required two of the authors with online facilitation experience to review all 26 activity items independently, and list those most relevant to fully online collaborative learning, \n\n**Table 2.** Technical activities: frequency and confidence results. \n\n|Activity item|Segment|_N_|_M_(Frequency)|_SD_|(Confdence)|_SD_|\n|---|---|---|---|---|---|---|\n|**T1. Create/edit documents**|all|244|3.4|1.0|3.9|1.0|\n||Students|224|3.4*|1.0|3.9|1.0|\n||Professors|20|4.0*|.0|4.0|1.0|\n|T2. create/edit audio|all|244|1.4|1.3|2.7|1.4|\n||Students|224|1.5|1.3|2.8|1.4|\n||Professors|20|1.0|1.1|2.3|1.4|\n|**_T3. Create/edit multimedia_**|all|244|2.2|1.2|3.5|1.2|\n||Students|224|2.1|1.2|3.5|1.2|\n||Professors|20|2.3|1.0|3.3|1.2|\n|**T4. Manage online accounts**|all|244|3.1|1.3|3.9|1.3|\n||Students|224|3.0|1.3|3.9|1.3|\n||Professors|20|3.6|.8|3.0|1.0|\n|T5. operate other devices|all|244|.4|1.0|1.5|1.2|\n||Students|224|.5|1.0|1.6|1.2|\n||Professors|20|.4|.9|1.3|.8|\n\nnote: Values are presented for all reported gTcu activities performed with a computer/laptop. **Bold** activity items are those judged directly relevant to collaborative online learning. _**Bold and italicized**_ activity items are directly relevant, but present values falling at or below the recommended (3.0) frequency-of-use threshold. asterisked values represent statistically significant differences between students and professors \n\n**Table 3.** Social activities: frequency and confidence results. \n\n|Activity item|Segment|_N_|_M_(Frequency)|_SD_|(Confdence)|_SD_|\n|---|---|---|---|---|---|---|\n|**S1. Send/receive text messages**|all|244|3.1|1.4|4.0|1.4|\n||Students|224|3.1|1.4|4.0*|1.4|\n||Professors|20|3.0|1.1|3.5*|1.1|\n|**_S2. Audio chat or conference_**|all|244|2.3|1.4|3.6|1.4|\n||Students|224|2.3|1.4|3.6|1.4|\n||Professors|20|2.4|.9|3.4|1.1|\n|**_S3. Video chat or Web conference_**|all|244|2.0|1.3|3.5|1.4|\n||Students|224|2.0|1.3|3.5|1.4|\n||Professors|20|2.3|1.0|3.3|1.0|\n|**S4. Communicate with email**|all|244|3.0|1.3|4.0|1.2|\n||Students|224|3.0*|1.3|4.0|1.2|\n||Professors|20|3.7*|1.0|4.1|1.0|\n|**S5. Participate in social networks**|all|244|3.3|1.3|4.1|1.3|\n||Students|224|3.3|1.3|4.1*|1.3|\n||Professors|20|3.7|.6|3.9*|.9|\n|**_S6. Share fles and collaborate_**|all|244|2.2|1.3|3.2|1.3|\n||Students|224|2.1|1.3|3.3|1.4|\n||Professors|20|2.5|1.3|3.0|1.1|\n|**_S7. Publish media and ideas online_**|all|244|.9|1.2|2.1|1.4|\n||Students|224|.9|1.2|2.1|1.5|\n||Professors|20|.9|1.1|2.0|1.1|\n\nnote: Values are presented for all reported gTcu activities performed with a computer/laptop. **Bold** activity items are those judged directly relevant to collaborative online learning. _**Bold and italicised**_ activity items are directly relevant, but present values falling at or below the recommended (3.0) frequency-of-use threshold. asterisked values represent statistically significant differences between students and professors. \n\nas modelled by the CoI. These reviewers then met to discuss differences between the two lists, and negotiate a consensus. Within the technical dimension, both reviewers dropped two items (T2 and T5, as shown in Table 2). They agreed that T2 was a specialised proxy for technical competence, and T5 was related to a digital lifestyle foreign to the research context. Items T1, T3 and T4 were retained (bolded in Table 2). Within the social dimension, all items were retained (Table 3). Within the informational dimension, I1, I4 and I5 were dropped by both reviewers. After lengthy discussion, I7 was dropped because it related to algorithmic information aggregation (Bucher, 2012; Mager, 2014), rather than learner selection of information based on critical analysis of context and purpose. This left three items (bolded in Table 4). Within the epistemological dimension, E1, E2 and E3 were independently included \n\n**Table 4.** informational activities: frequency and confidence results. \n\n|Activity item|Segment|_N_|_M_(Frequency)|_SD_|(Confdence)|_SD_|\n|---|---|---|---|---|---|---|\n|i1. use maps or gPS|all|244|1.6|1.3|3.0|1.6|\n||Students|224|1.6|1.3|3.1|1.6|\n||Professors|20|1.5|1.2|2.7|1.5|\n|**I2. Find and use articles or news**|all|244|2.7|1.3|3.8|1.3|\n||Students|224|2.6*|1.3|3.8|1.3|\n||Professors|20|3.4*|.6|4.1|1.0|\n|**_I3. Find and view short videos_**|all|244|2.7|1.3|3.8|1.3|\n||Students|224|2.7|1.4|3.8|1.4|\n||Professors|20|3.0|.7|4.0|.9|\n|i4. Watch or download movies|all|244|2.4|1.2|3.9|1.3|\n||Students|224|2.4|1.2|3.9|1.3|\n||Professors|20|2.1|.9|3.7|1.1|\n|i5. listen or download music|all|244|2.2|1.4|3.6|1.5|\n||Students|224|2.3*|1.4|3.7*|1.5|\n||Professors|20|1.4*|1.2|2.9*|1.5|\n|**_I6. Read or download digital books_**|all|244|1.8|1.3|3.3|1.5|\n||Students|224|1.8|1.3|3.3|1.5|\n||Professors|20|1.9|1.0|3.4|1.3|\n|i7. automate information sources|all|244|.7|1.2|1.8|1.3|\n||Students|224|.8|1.2|1.8|1.3|\n||Professors|20|.5|.9|1.6|1.1|\n\nnote: Values are presented for all reported gTcu activities performed with a computer/laptop. **Bold** activity items are those judged directly relevant to collaborative online learning. _**Bold and italicised**_ activity items are directly relevant, but present values falling at or below the recommended (3.0) frequency-of-use threshold. asterisked values represent statistically significant differences between students and professors. \n\n**Table 5.** epistemological activities: frequency and confidence results. \n\n|Activity item|Segment|_N_|(Frequency)|_SD_|(Confdence)|_SD_|\n|---|---|---|---|---|---|---|\n|**_E1. Use calendar or organiser_**|all|244|.8|1.3|1.9|1.4|\n||Students|224|.8|1.3|2.0|1.4|\n||Professors|20|1.0|1.3|1.8|1.0|\n|**_E2. Use concept map or fow chart_**|all|244|.9|1.2|2.1|1.3|\n||Students|224|.9|1.2|2.1|1.3|\n||Professors|20|1.0|1.2|2.0|1.1|\n|**_E3. Create fgures and diagrams_**|all|244|1.7|1.2|3.0|1.3|\n||Students|224|1.7*|1.2|3.0|1.3|\n||Professors|20|2.3*|.7|3.5|1.0|\n|e4. Sort large amounts of data|all|244|1.7|1.3|3.0|1.4|\n||Students|224|1.7|1.3|3.0|1.4|\n||Professors|20|1.6|1.4|2.7|1.3|\n|**_E5. Generate graphs from numbers_**|all|244|1.7|1.2|3.1|1.3|\n||Students|224|1.7|1.2|3.0|1.3|\n||Professors|20|2.0|.9|3.2|1.1|\n|**_E6. Automate complex calculations_**|all|244|1.7|1.4|2.8|1.4|\n||Students|224|1.7|1.4|2.8|1.4|\n||Professors|20|1.5|1.1|2.6|1.4|\n|e7. Program or automate procedures|all|244|.6|1.1|1.6|1.1|\n||Students|224|.6|1.1|1.7*|1.1|\n||Professors|20|.3|1.0|1.1*|.2|\n\nnote: Values are presented for all reported gTcu activities performed with a computer/laptop. **Bold** activity items are those judged directly relevant to collaborative online learning. _**Bold and italicised**_ activity items are directly relevant, but present values falling at or below the recommended (3.0) frequency-of-use threshold. asterisked values represent statistically significant differences between students and professors. \n\nby both reviewers, and E4 dropped. Both reviewers marked items E5 and E6 for discussion. These items were included by reflecting on a recent online group activity incorporating analyses of _World Values Survey_ data (http://www.worldvaluessurvey.org/). This resulted in five items being retained, displayed in bold type in Table 5. \n\nIn the end, 36 items, measuring frequency and confidence for 18 activities using a laptop/desktop computer, were considered most relevant to fully online collaborative learning in this context, and most capable of functioning as general readiness indicators.",
      "page_span": {
        "start": 7,
        "end": 10
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Interpreting activity frequency and confidence of use values",
      "level": 2,
      "text": "Students and teachers were analysed as separate groups in order to explore significant differences. A group Mean value of three or above (indicating a frequency of activity from ‘a few times month’ to ‘daily’) was defined as a good level of experience. Supported by adequate levels of confidence, defined as a Mean value of three or above (indicating ‘some confidence’ to ‘high level of confidence’), participants were considered likely to possess the necessary motivational resources to apply their skills to new situations and increase abilities through active participation. \n\nValues are presented in Tables 2–5. Bolded and italicised items indicate that all frequency-of-use values for a relevant activity fall at or below the competency threshold defined above. Asterisked items represent significant differences as reported in the text. The findings of the mediating technical order are reported first, followed by those of the higher-level orders.",
      "page_span": {
        "start": 10,
        "end": 10
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Technical competencies",
      "level": 3,
      "text": "Activity items in the technical dimension address an individual’s operational abilities with the rationale that frequently performing simple, file creation and management tasks implies the acquisition of underlying skills. Of the three indicators selected as most relevant in contexts of online learning (bold items in Table 2), participants create documents (T1) and manage online accounts (T4) at least a few times a month. However, they create multimedia (T3) less frequently, perhaps suggesting less familiarity with more complex software interfaces and diverse file types (e.g. graphic formats and video codecs). Professors create documents significantly more frequently than students (MeanRank: Profs = 164, Students = 118.8; Sig. = .001), suggesting a slightly greater level of operational experience.",
      "page_span": {
        "start": 10,
        "end": 10
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Social competencies",
      "level": 3,
      "text": "All participants communicate using text messaging (S1) and email (S2). They also use social networks (S5) at least a few times per month. The secondary data set (not shown in tables provided) indicates cell phones and smartphones are used about the same amount for text messaging (Mean frequency = 3.5; _SD_ = 1.2) and social networks (Mean frequency = 3.2; _SD_ = 1.5), and somewhat less for email (Mean frequency = 2.5; _SD_ = 1.6). As a cross-cultural point of reference, Canadian students have reported texting almost daily (Mean frequency = 4.76), but the frequency of email (Mean frequency = 3.92) and social media (Mean frequency = 3.8) uses was only marginally higher than that of Ukrainian students (DiGiuseppe et al., 2013). Ukrainian professors use email significantly more than Ukrainian students (MeanRank: Profs = 168.1, Students = 118.4; Sig. = .001), but students possess more confidence than professors for sending and receiving text messages (MeanRank: Profs = 76.6, Students = 126.6; Sig. = .001), and participating in social networks (MeanRank: Profs = 95.1, Students = 124.9; Sig. = .049). These differences mirror broader usage trends (Pew Research Center, 2016). \n\nAs shown in Table 3, all participants use computers to communicate via audio (Mean frequency = 2.3) and video (Mean frequency = 2.0) only a few times per year. The secondary, smartphone data show somewhat lower activity levels for video (Mean frequency = 1.5; _SD_ = 1.5), but usage jumps to a few times per month for audio communication (Mean frequency = 3.0; _SD_ = 1.5). Therefore, the phone remains the preferred device for voice communication. As a cross-cultural point of comparison, the usage of Canadian students for voice communication with smartphones was higher – closer to a few times per week (Mean frequency = 3.7). Frequency of video communication with smartphones among Canadians was similar to that reported by Ukrainian students (Mean frequency = 2.2) (DiGiuseppe et al., 2013). This may be related to bandwidth costs, and the fact that it is easier to communicate with audio alone while mobile. \n\nTwo items in the social dimension highly relevant to online learning involve sharing files, and collaborating and publishing ideas/content online. The Ukrainian participants collaborate on files only a few times per year (Mean frequency = 2.2), with no significant difference in frequency between students and professors. However, they report being confident in this area. They almost never publish content and ideas online (Mean frequency = .9), with the same results for both students and professors. Moreover, both groups report low levels of confidence in this area of activity.",
      "page_span": {
        "start": 10,
        "end": 11
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Informational competencies",
      "level": 3,
      "text": "The informational indicators most relevant to collaborative-constructivist fully online learning relate to searching, finding, evaluating, selecting and appropriating content in a variety of formats (Table 4). Finding and using online news/journal articles (I2) and digital books (I3) are foundational research skills. As a group, participants access articles less than a few times a month (Mean frequency = 2.7). However, professors report significantly more activity in this area than students (MeanRank: Profs = 157.5, Students = 119.4; Sig. = .02), suggesting that the research practices of Ukrainian university teachers have shifted to the digital space. Confidence for this activity is high for all participants. Both students and professors access digital books only a few times per year (Mean frequency = 1.8), which suggests that digital books are seldom used for academic purposes. This may relate to the scant financial resources available in Ukraine for digitising scholarly books. Finally, participants view online videos (like those on YouTube) a few times a month (Mean frequency = 2.7). For all of these activities confidence is high, suggesting a willingness to develop requisite skills as opportunities arise.",
      "page_span": {
        "start": 11,
        "end": 11
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Epistemological competencies",
      "level": 3,
      "text": "Using the information-processing power of computers to solve problems, map concepts, mine data, perform statistical analyses or engage in collaborative decision making, dramatically increases the functioning of most researchers. Five of the seven GTCU indicators in this dimension were considered relevant to effective fully online learning. These indicators relate to managing one’s schedule (E1), organising and presenting complex information (E2 and E3), and producing knowledge from numerical data (E5 and E6), as shown in Table 5. \n\nParticipants reported never using a calendar or organiser (Mean frequency = .8), and possessing low confidence related to this activity. Concept mapping is often vital for effective knowledge construction, academic writing and problem solving. Yet, this activity was performed seldom (Mean frequency = .9), and participants reported low confidence. Professors reported creating figures and diagrams a few times a year (Mean frequency = 2.3), which is significantly more often than students (MeanRank: Profs = 159.9, Students = 119.2; Sig. = .01). Both groups, however, reported good levels of confidence. Although neither professors nor students generate graphs from numbers or automate complex calculations more than a few times per year (Mean frequency = 1.7), both groups report a good level of confidence. \n\nAs a footnote in this dimension, although neither programing nor scripting was considered highly relevant to successful, collaborative online learning, and therefore excluded as a key activity, students showed significantly more confidence in this area than professors (MeanRank: Profs = 91.5, Students = 125.3; Sig. = .011).",
      "page_span": {
        "start": 11,
        "end": 11
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Assessing readiness for fully online collaborative learning",
      "level": 1,
      "text": "Having reviewed the reported competencies of Ukrainian students and professors in each GTCU dimension, we turn to interpreting the findings in relation to readiness. As noted, the CoI identifies three major dimensions of successful functioning in fully online learning communities – social presence, cognitive presence and teaching presence. This readiness assessment is organised accordingly.",
      "page_span": {
        "start": 11,
        "end": 12
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Readiness for social presence",
      "level": 2,
      "text": "Social presence relates to interpersonal, open and cohesive communication, aimed at building trusting relationships and a cohesive learning community (Garrison, 2011). \n\nImportantly, deep and meaningful learning outcomes in a community of inquiry are facilitated through purposeful and authentic social interaction, leading to mutual respect, trust and a sense of safety (Armellini & De Stefani, 2015). The prerequisite competencies supporting the development and maintenance of social presence relate primarily to the effective use of digital communication affordances. \n\nEncouragingly, good levels of activity and confidence were reported for text-based communication via messaging and email, and social-network participation. The latter is becoming increasingly significant as publicly accessible affordances, such as Facebook groups, emerge as potential learning spaces (Dickie & Meier, 2015; Ellefsen, 2015). However, the low levels of activity reported for communication via audio and video may pose some challenges because these competencies support successful participation in web-conferencing environments, which offer rich forms of interaction and were selected for use in the pilot course.",
      "page_span": {
        "start": 12,
        "end": 12
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Readiness for cognitive presence",
      "level": 2,
      "text": "Cognitive presence addresses processes of critical inquiry (Garrison, 2011). Readiness for building cognitive presence implies rich capabilities to engage effectively in processes of digitally mediated collaboration, information selection and data analysis.",
      "page_span": {
        "start": 12,
        "end": 12
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Readiness for collaboration",
      "level": 3,
      "text": "In fully online learning environments, successful collaboration requires competencies related to file sharing, collaborative editing and self-expression. Unfortunately, both teachers and students report low levels of competency using major collaboration tools such as Dropbox, Google Drive and Google Docs. Additionally, they report little experience and confidence for publishing content and expressing ideas online. Reflecting on the Ukrainian context, low self-expression may be related to a collectivist orientation in which maintaining face within a group tends to be a significant concern (Hofstede, 2001). \n\nIn order to nurture these competencies, one opportunity is to build upon participants’ social-media experience. Although Facebook is still less popular in Ukraine than the Russian VKontakte (‘Facebook’, 2016), it is used by a sizable number of Ukrainians. A Facebook group, for example, can be closed to a particular community, and leveraged as a tool for sharing experience, exchanging ideas and promoting group interaction (Dickie & Meier, 2015; Ellefsen, 2015; Wang, Woo, Quek, Yang, & Liu, 2012).",
      "page_span": {
        "start": 12,
        "end": 12
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Readiness for interacting with digital information",
      "level": 3,
      "text": "A strong capacity to interact with information, including educational videos, peer-reviewed articles and other digital publications, is a core requirement of social-constructivist online learning. Ideally, all members of an online-learning community would have rich capacities for accessing, evaluating and appropriating diverse source materials. Activity levels for the three selected indicators in the informational dimension, however, appear low. Only professors achieved a moderate score in relation to accessing online articles, reporting significantly more experience than students. With high confidence levels also reported, responsibility may fall on facilitators to encourage effective processes of online research and information access.",
      "page_span": {
        "start": 12,
        "end": 12
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Readiness for analysing, mapping and processing data",
      "level": 3,
      "text": "Previous results from GTCU surveys in Canada suggested participants might report less activity and confidence in the epistemological dimension (Desjardins et al., 2010). In other parts of the world, significant gaps have also been found between computational skills and other digital abilities of students (Jun, Han, Kim, & Lee, 2014). Of the five activities judged relevant for online learning, the Ukrainian \n\nprofessors reported modest familiarity with creating diagrams and generating graphs, suggesting some base of experience from which to build. \n\nA major challenge is that the development and application of epistemological competencies have relatively high cognitive demands. Effective use of concept maps, flow charts, visualisation tools, spreadsheets and data-analysis applications requires thoughtfulness, focus and a systematic application of logical procedures – in addition to the requisite operational skills. The payoff for diligence in this area is increased access to a computer’s most powerful capability – to function as a cognitive partner for tackling complex problems (Desjardins, 2005). This function has become increasingly relevant as complex data sets are made available online (e.g. _The World Values Survey_ at http://www.worldvaluessurvey. org/), and ‘big data’ are generated through endless online interactions.",
      "page_span": {
        "start": 12,
        "end": 13
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Readiness for teaching presence",
      "level": 2,
      "text": "Teaching presence refers to curriculum design, activity facilitation and direct instruction (Garrison, 2011). Although conceptualised as a shared function, the professional facilitator typically bears responsibility for TP in new, fully online learning communities. The digital competencies required for success are spread across the GTCU spectrum of social, informational, epistemological and technical. \n\nReported digital competencies of the professors indicate readiness is generally low. However, two findings show promise. Professors reported a higher level of competencies than students on items related to (a) finding academic information online, and (b) completing technical procedures.",
      "page_span": {
        "start": 13,
        "end": 13
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Overall general readiness",
      "level": 2,
      "text": "In the end, overall general readiness for successful functioning in a fully online collaborative learning community appears somewhat low for Ukrainian students and teachers. Consequently, it is recommended that digital-competency development become an educational priority prior to launching the pilot course.",
      "page_span": {
        "start": 13,
        "end": 13
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Contributions and limitations",
      "level": 1,
      "text": "We believe that this conceptual and empirical analysis contributes to research in three ways. First, by extending the GTCU aggregate data set internationally, it creates new opportunities for cross-cultural comparisons, enabling deeper analyses of relationships between digital practices and socio-cultural contexts. \n\nSecond, this study bridges a gap between the domains of digital-competency and digital-learning research, and thus, opens the door for additional synergistic studies. Indeed, the Fully Online Learning Community model (vanOostveen et al., 2016) is a recently published model that bridges these domains, diverging from the CoI by treating digital competencies as endogenous variables in relation to fully online learning (Blayone, vanOostveen, Barber, et al., 2017). \n\nFinally, this study offers an effective methodology for assessing digital-learning readiness in a post-Soviet nation, using an established online application. This may inspire other researchers to leverage the GTCU profile tool, or other existing Western research assets, to support educational transformation in contexts of transition. \n\nWith respect to limitations, first, self-reported digital abilities are sometimes difficult to interpret in relation to performance. The literature reports some misalignments between perceived abilities and observed performance using some other survey instruments (Bradlow, Hoch, & Hutchinson, 2002; Hargittai & Shafer, 2006; Litt, 2013). For example, Hargittai and Schaffer (2006) found misalignments along gender lines. Although both men and women varied in their performance-based abilities, women consistently perceived their abilities to be lower than men. Other challenges with self-report instruments relate to conceptual ambiguity, incompleteness and over-simplification (van Deursen, Helsper, \n\n& Eynon, 2015). Additionally, one would reasonably expect cultural patterns of self-perception, levels of confidence and reporting patterns to differ across national contexts (Hofstede, 2001; Minkov, 2012). \n\nSecond, the GTCU profile tool is a multi-dimensional instrument for collecting a large set of technology-use data. Its use was defended on three grounds above. However, to use it effectively as a readiness tool, data-reduction procedures were required. Future research might develop a short version of the instrument aimed at the specific context of use to increase data-collection efficiency and obviate the need for data reduction. \n\nFinally, the GTCU profile tool was developed within a Canadian, socio-economic and technological context, and thus, makes references to 4G, TLE, wearable computers and digital appliances. A Ukrainian economics professor at KNEU rightly inquired if Canadian researchers were aware how typical incomes in Ukraine relate to prices of devices; ‘they ask how often we use’ (N. Yevdokymova, personal communication, 15 June 2015). In response, the researchers seek to balance sensitivity to specific contexts with the ability to compare data from multiple contexts. Such comparative data are vital for describing and addressing differences and disparities, across national, regional and organisational contexts of application.",
      "page_span": {
        "start": 13,
        "end": 14
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "A postscript",
      "level": 1,
      "text": "In early 2016, the researchers conducted the planned, fully online collaborative pilot course over 10 weeks. Data captured from this course have been discussed at a Canadian academic conference (Mykhailenko, Blayone, & VanOostveen, 2016), and reported in the Ukrainian media (Mykhailenko & Blayone, 2016; Mykhailenko, Hrebeshkova, & Blayone, 2016). Further analysis of learning interactions in relation to cultural dimensions and transformative outcomes is underway. As predicted by this study, using a web-conferencing environment and collaborative tools effectively, particularly in small groups, presented significant challenges for most students and participating professors over the duration of the course. Moreover, role perceptions, occasional student resistance to highly participatory activities, and institutional resistance to online learning also emerged as important facets of successful functioning. Nevertheless, tremendously positive feedback from students regarding the digital tools, collaborative activities, and support for open discussion and self-expression, was an encouraging outcome.",
      "page_span": {
        "start": 14,
        "end": 14
      },
      "confidence": "high"
    },
    {
      "label": "acknowledgements",
      "heading": "Acknowledgements",
      "level": 1,
      "text": "The researchers thank students and professors at the Department of Enterprise Strategy, Kyiv National Economic University for their enthusiastic support for this project. We also thank researchers around the world who provided feedback on the instrument.",
      "page_span": {
        "start": 14,
        "end": 14
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Disclosure statement",
      "level": 1,
      "text": "No potential conflict of interest was reported by the authors.",
      "page_span": {
        "start": 14,
        "end": 14
      },
      "confidence": "high"
    },
    {
      "label": "other",
      "heading": "Notes on contributors",
      "level": 1,
      "text": "_**Todd Blayone**_ is a professional researcher, educator and technologist, exploring digital readiness and post-industrial learning across cultures for individual development and social progress. Living in Kyiv, Ukraine and Toronto, Canada, he is co-founder of Collaboritsi.com, a collaborative-learning and digital-readiness consultancy, and an associate researcher at the Educational Informatics Laboratory (EILAB), University of Ontario Institute of Technology, Canada. \n\n_**Olena Mykhailenko**_ is a trilingual educator, economist, former government advisor and consultant living in Kyiv, Ukraine and Toronto, Canada. As co-founder of Collaboritsi.com and an associate researcher at the Educational Informatics Laboratory (EILAB), University of Ontario Institute of Technology, Canada, she gives workshops for educators and business professionals on collaborative learning and culture. Her diverse publications span development economics, cross-cultural analysis and post-industrial, educational transformation. \n\n_**Roland vanOostveen**_ holds a PhD in Curriculum, Teaching and Learning from the Ontario Institute for Studies in Education at the University of Toronto. He is director of the Educational Informatics Laboratory (EILAB) and the Educational Studies and Digital Technology programmes at the Faculty of Education, University of Ontario Institute of Technology. His research explores digital competency and technology use in learning, and the development of fully online learning environments. \n\n_**Oleksiy Grebeshkov**_ is Associate Professor at the Faculty of Economics and Management, and Head of Innovation at the Educational Technologies Laboratory (IETLab) at Kyiv National Economic University, named after Vadim Hetman. A cloud solutions architect, he is an online-course author with over 4000 students from around the world. He is a co-organiser of scientific conferences on digital educational innovation. \n\n_**Olena Hrebeshkova**_ is an associate professor at the Faculty of Economics and Management, at Kyiv National Economic University, named after Vadim Hetman. She is the author of more than 100 scientific and educational works, coordinator of the project for the implementation of Microsoft Office 365 at the Faculty of Economics and Management, and a Udemy Premium Instructor. She is founder and co-organiser of international scientific conferences on digital educational innovation. \n\n_**Oleksandr Vostryakov**_ is Dean of the Economics and Management Department, at Kyiv National Economic University, named after Vadim Hetman. He is a member of the Scientific and Methodological Council of the Ministry of Education and Science of Ukraine. \n\n## **ORCID** \n\n_Todd J. B. Blayone_ http://orcid.org/0000-0001-6965-7033",
      "page_span": {
        "start": 14,
        "end": 15
      },
      "confidence": "high"
    },
    {
      "label": "references",
      "heading": "References",
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Information and communication technology in education: A competency profile of francophone secondary school teachers in Ontario. _Canadian Journal of Learning and Technology/La revue canadienne de l’apprentissage et de la technologie, 31_ , 1–14. doi:10.21432/T2PG69. Desjardins, F. J., Davidson, A. L., Blayone, T., vanOostveen, R., & Childs, E. (Producer). (2015). _General Technology Competency and Use: Foundations_ . [Information Poster]. Retrieved from http://eilab.ca/wp-content/uploads/2016/01/GTCU-PosterV2-2000px.jpg Desjardins, F. J., Lacasse, R., & Belair, L. M. (2001). Toward a definition of four orders of competency for the use of information and communication technology (ICT) in education. In _Proceedings of the IASTED International Conference. Computers and Advanced Technology in Education_ (pp. 213–217). Banff: ACTA Press. Desjardins, F. J., & Peters, M. (2007). Single-course approach versus a program approach to develop technological competencies in pre-service language teaching. In M.-A. Kassen, L. Lavine, K. Murphy-Judy, & M. Peters (Eds.), _Preparing and developing technology proficient L2 teachers_ (pp. 3–21). San Marcos, TX: Texas State University. Desjardins, F. J., & vanOostveen, R. (2015). Faculty and student use of digital technology in a ‘laptop’ university. In S. Carliner, C. Fulford, & N. Ostashewski (Eds.), _EdMedia: World Conference on Educational Media and Technology 2015_ (pp. 990–996). Montreal: Association for the Advancement of Computing in Education. Desjardins, F. J., vanOostveen, R., Bullock, S., DiGiuseppe, M., & Robertson, L. (2010). Exploring graduate students’ use of computer-based technologies for online learning. In J. Herrington & C. Montgomerie (Eds.), _EdMedia: World Conference on Educational Media and Technology 2010_ (pp. 440–444). Waynesville, NC: Association for the Advancement of Computing in Education. Dewey, J. (1897). My pedagogical creed. _School Journal, 54_ (3), 77–80. Dewey, J. (1916). _Democracy and education_ . New York, NY: The Macmillan Company. Dickie, V. A., & Meier, H. (2015). The Facebook tutor: Networking education. _Ubiquitous Learning: An International Journal, 8_ (2), 15–20. DiGiuseppe, M., Partosoedarso, E., vanOostveen, R., & Desjardins, F. J. (2013). Exploring competency development with mobile devices. In M. B. Nunes & M. McPherson (Eds.), _International Association for Development of the Information Society (IADIS) international conference on e-learning_ (pp. 384–388). Prague: International Association for Development of the Information Society. DiGiuseppe, M., vanOostveen, R., Childs, E., Blayone, T., & Barber, W. (2017, June). _Are you ready? Assessing digital competencies for online learning via the General Technology Competency and Use (GTCU) instrument_ . 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R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. _American Journal of Distance Education, 15_ , 7–23. doi:10.1080/08923640109527071. Garrison, D. R., & Archer, W. (2000). _A transactional perspective on teaching and learning: A framework for adult and higher education_ . New York, NY: Pergamon. Gunawardena, C. N., Jennings, B., Ortegano-Layne, L. C., Frechette, C., Carabajal, K., Lindemann, K., et al. (2004). Building an online wisdom community: A transformational design model. _Journal of Computing in Higher Education, 15_ (2), 40–62. doi:10.1007/bf02940929. Gunawardena, C. N., Nolla, A. C., Wilson, P. L., Lopez-Islas, J. R., Ramirez-Angel, N., & Megchun-Alpizar, R. M. (2001). A cross-cultural study of group process and development in online conferences. _Distance Education, 22_ , 85–121. doi:10.1080/0158791010220106. Gunawardena, C. 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V., & Kuzmin, Y. (2015). Educational technologies for maturing democratic approaches to educational practices in Ukraine. _Procedia – Social and Behavioral Sciences, 176_ , 378–385. doi:10.1016/j.sbspro.2015.01.485 \n\nRose-Ackerman, S. (2001). Trust and honesty in post-socialist societies. _Kyklos, 54_ , 415–443. doi:10.1111/j.00235962.2001.00161.x. \n\nRoztocki, N., & Weistroffer, H. R. (2015). Information and communication technology in transition economies: An assessment of research trends. _Information Technology for Development, 21_ , 330–364. doi:10.1080/02681102.2014.891498. \n\nSharkova, N. (2014). Learning supported by technology in higher education: From experience to practice. _Education Inquiry, 5_ , 429–444. doi:10.3402/edui.v5.24610. \n\nSiemens, G., Gašević, D., & Dawson, S. (2015). _Preparing for the digital university: A review of the history and current state of distance, blended, and online learning_ . 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Oshawa, Canada. \n\nvanOostveen, R., & Desjardins, F. J. (2013). Developing and implementing a new online bachelor program: Formal adoption of videoconferencing and social networking as a step towards m-Learning. In M. B. Nunes & M. McPherson (Eds.), _Proceedings of the IADIS International Conference on e-Learning_ (pp. 223–230). Prague: International Association for Development of the Information Society. \n\nvanOostveen, R., DiGiuseppe, M., Barber, W., Blayone, T., & Childs, E. (2016). New conceptions for digital technology sandboxes: Developing a Fully Online Learning Communities (FOLC) model. In G. Veletsianos (Ed.), _EdMedia 2016: World Conference on Educational Media and Technology_ (pp. 665–673). Vancouver: Association for the Advancement of Computing in Education. \n\nVygotsky, L. S. (1978). _Mind in society: Development of higher psychological processes_ . Cambridge, MA: Harvard University Press. \n\nWang, Q., Woo, H. L., Quek, C. L., Yang, Y., & Liu, M. (2012). Using the Facebook group as a learning management system: An exploratory study. _British Journal of Educational Technology, 43_ , 428–438. doi:10.1111/j.1467-8535.2011.01195.x. Way, L. (2014). Civil society and democratization. _Journal of Democracy, 25_ (3), 35–43. doi:10.1353/jod.2014.0042. Wilson, A. (2013). Ukraine. In I. Coleman & T. Lawson-Remer (Eds.), _Pathways to freedom: Political and economic lessons from democratic transitions_ . New York, NY: Council on Foreign Relations Press. \n\nWorldometers. (2017). _Ukraine population 2017_ . Retrieved from http://www.worldometers.info/world-population/ukrainepopulation/ \n\n## **Technology, Pedagogy and Education** \n\n**ISSN: 1475-939X (Print) 1747-5139 (Online) Journal homepage: http://www.tandfonline.com/loi/rtpe20** \n\n## **Surveying digital competencies of university students and professors in Ukraine for fully online collaborative learning** \n\n## **Todd J. B. Blayone, Olena Mykhailenko, Roland vanOostveen, Oleksiy Grebeshkov, Olena Hrebeshkova & Oleksandr Vostryakov** \n\n**To cite this article:** Todd J. B. Blayone, Olena Mykhailenko, Roland vanOostveen, Oleksiy Grebeshkov, Olena Hrebeshkova & Oleksandr Vostryakov (2018) Surveying digital competencies of university students and professors in Ukraine for fully online collaborative learning, Technology, Pedagogy and Education, 27:3, 279-296, DOI: 10.1080/1475939X.2017.1391871 \n\n**To link to this article:** https://doi.org/10.1080/1475939X.2017.1391871 \n\nPublished online: 31 Oct 2017. \n\nSubmit your article to this journal \n\nArticle views: 179 \n\nView Crossmark data \n\nCiting articles: 2 View citing articles \n\nFull Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=rtpe20",
      "page_span": {
        "start": 15,
        "end": 19
      },
      "confidence": "high"
    }
  ],
  "tables": [
    {
      "headers": [
        "Variables",
        "Values",
        "_N_",
        "%"
      ],
      "rows": [
        [
          "gender",
          "Male",
          "81",
          "33"
        ],
        [
          "",
          "Female",
          "163",
          "67"
        ],
        [
          "age group",
          "19–25",
          "205",
          "84"
        ],
        [
          "",
          "26–35",
          "23",
          "9"
        ],
        [
          "",
          "36–49",
          "12",
          "5"
        ],
        [
          "",
          "50+",
          "4",
          "2"
        ],
        [
          "Role",
          "Student",
          "224",
          "92"
        ],
        [
          "",
          "Professor",
          "20",
          "8"
        ],
        [
          "Specialty",
          "economics",
          "122",
          "50"
        ],
        [
          "",
          "other",
          "12",
          "5"
        ],
        [
          "",
          "not reported",
          "110",
          "45"
        ],
        [
          "highest degree held",
          "diploma",
          "80",
          "33"
        ],
        [
          "",
          "Bachelor",
          "131",
          "54"
        ],
        [
          "",
          "Masters",
          "16",
          "6"
        ],
        [
          "",
          "doctoral",
          "17",
          "7"
        ]
      ],
      "raw": "|Variables|Values|_N_|%|\n|---|---|---|---|\n|gender|Male|81|33|\n||Female|163|67|\n|age group|19–25|205|84|\n||26–35|23|9|\n||36–49|12|5|\n||50+|4|2|\n|Role|Student|224|92|\n||Professor|20|8|\n|Specialty|economics|122|50|\n||other|12|5|\n||not reported|110|45|\n|highest degree held|diploma|80|33|\n||Bachelor|131|54|\n||Masters|16|6|\n||doctoral|17|7|"
    },
    {
      "headers": [
        "Activity item",
        "Segment",
        "_N_",
        "_M_(Frequency)",
        "_SD_",
        "(Confdence)",
        "_SD_"
      ],
      "rows": [
        [
          "**T1. Create/edit documents**",
          "all",
          "244",
          "3.4",
          "1.0",
          "3.9",
          "1.0"
        ],
        [
          "",
          "Students",
          "224",
          "3.4*",
          "1.0",
          "3.9",
          "1.0"
        ],
        [
          "",
          "Professors",
          "20",
          "4.0*",
          ".0",
          "4.0",
          "1.0"
        ],
        [
          "T2. create/edit audio",
          "all",
          "244",
          "1.4",
          "1.3",
          "2.7",
          "1.4"
        ],
        [
          "",
          "Students",
          "224",
          "1.5",
          "1.3",
          "2.8",
          "1.4"
        ],
        [
          "",
          "Professors",
          "20",
          "1.0",
          "1.1",
          "2.3",
          "1.4"
        ],
        [
          "**_T3. Create/edit multimedia_**",
          "all",
          "244",
          "2.2",
          "1.2",
          "3.5",
          "1.2"
        ],
        [
          "",
          "Students",
          "224",
          "2.1",
          "1.2",
          "3.5",
          "1.2"
        ],
        [
          "",
          "Professors",
          "20",
          "2.3",
          "1.0",
          "3.3",
          "1.2"
        ],
        [
          "**T4. Manage online accounts**",
          "all",
          "244",
          "3.1",
          "1.3",
          "3.9",
          "1.3"
        ],
        [
          "",
          "Students",
          "224",
          "3.0",
          "1.3",
          "3.9",
          "1.3"
        ],
        [
          "",
          "Professors",
          "20",
          "3.6",
          ".8",
          "3.0",
          "1.0"
        ],
        [
          "T5. operate other devices",
          "all",
          "244",
          ".4",
          "1.0",
          "1.5",
          "1.2"
        ],
        [
          "",
          "Students",
          "224",
          ".5",
          "1.0",
          "1.6",
          "1.2"
        ],
        [
          "",
          "Professors",
          "20",
          ".4",
          ".9",
          "1.3",
          ".8"
        ]
      ],
      "raw": "|Activity item|Segment|_N_|_M_(Frequency)|_SD_|(Confdence)|_SD_|\n|---|---|---|---|---|---|---|\n|**T1. Create/edit documents**|all|244|3.4|1.0|3.9|1.0|\n||Students|224|3.4*|1.0|3.9|1.0|\n||Professors|20|4.0*|.0|4.0|1.0|\n|T2. create/edit audio|all|244|1.4|1.3|2.7|1.4|\n||Students|224|1.5|1.3|2.8|1.4|\n||Professors|20|1.0|1.1|2.3|1.4|\n|**_T3. Create/edit multimedia_**|all|244|2.2|1.2|3.5|1.2|\n||Students|224|2.1|1.2|3.5|1.2|\n||Professors|20|2.3|1.0|3.3|1.2|\n|**T4. Manage online accounts**|all|244|3.1|1.3|3.9|1.3|\n||Students|224|3.0|1.3|3.9|1.3|\n||Professors|20|3.6|.8|3.0|1.0|\n|T5. operate other devices|all|244|.4|1.0|1.5|1.2|\n||Students|224|.5|1.0|1.6|1.2|\n||Professors|20|.4|.9|1.3|.8|"
    },
    {
      "headers": [
        "Activity item",
        "Segment",
        "_N_",
        "_M_(Frequency)",
        "_SD_",
        "(Confdence)",
        "_SD_"
      ],
      "rows": [
        [
          "**S1. Send/receive text messages**",
          "all",
          "244",
          "3.1",
          "1.4",
          "4.0",
          "1.4"
        ],
        [
          "",
          "Students",
          "224",
          "3.1",
          "1.4",
          "4.0*",
          "1.4"
        ],
        [
          "",
          "Professors",
          "20",
          "3.0",
          "1.1",
          "3.5*",
          "1.1"
        ],
        [
          "**_S2. Audio chat or conference_**",
          "all",
          "244",
          "2.3",
          "1.4",
          "3.6",
          "1.4"
        ],
        [
          "",
          "Students",
          "224",
          "2.3",
          "1.4",
          "3.6",
          "1.4"
        ],
        [
          "",
          "Professors",
          "20",
          "2.4",
          ".9",
          "3.4",
          "1.1"
        ],
        [
          "**_S3. Video chat or Web conference_**",
          "all",
          "244",
          "2.0",
          "1.3",
          "3.5",
          "1.4"
        ],
        [
          "",
          "Students",
          "224",
          "2.0",
          "1.3",
          "3.5",
          "1.4"
        ],
        [
          "",
          "Professors",
          "20",
          "2.3",
          "1.0",
          "3.3",
          "1.0"
        ],
        [
          "**S4. Communicate with email**",
          "all",
          "244",
          "3.0",
          "1.3",
          "4.0",
          "1.2"
        ],
        [
          "",
          "Students",
          "224",
          "3.0*",
          "1.3",
          "4.0",
          "1.2"
        ],
        [
          "",
          "Professors",
          "20",
          "3.7*",
          "1.0",
          "4.1",
          "1.0"
        ],
        [
          "**S5. Participate in social networks**",
          "all",
          "244",
          "3.3",
          "1.3",
          "4.1",
          "1.3"
        ],
        [
          "",
          "Students",
          "224",
          "3.3",
          "1.3",
          "4.1*",
          "1.3"
        ],
        [
          "",
          "Professors",
          "20",
          "3.7",
          ".6",
          "3.9*",
          ".9"
        ],
        [
          "**_S6. Share fles and collaborate_**",
          "all",
          "244",
          "2.2",
          "1.3",
          "3.2",
          "1.3"
        ],
        [
          "",
          "Students",
          "224",
          "2.1",
          "1.3",
          "3.3",
          "1.4"
        ],
        [
          "",
          "Professors",
          "20",
          "2.5",
          "1.3",
          "3.0",
          "1.1"
        ],
        [
          "**_S7. Publish media and ideas online_**",
          "all",
          "244",
          ".9",
          "1.2",
          "2.1",
          "1.4"
        ],
        [
          "",
          "Students",
          "224",
          ".9",
          "1.2",
          "2.1",
          "1.5"
        ],
        [
          "",
          "Professors",
          "20",
          ".9",
          "1.1",
          "2.0",
          "1.1"
        ]
      ],
      "raw": "|Activity item|Segment|_N_|_M_(Frequency)|_SD_|(Confdence)|_SD_|\n|---|---|---|---|---|---|---|\n|**S1. Send/receive text messages**|all|244|3.1|1.4|4.0|1.4|\n||Students|224|3.1|1.4|4.0*|1.4|\n||Professors|20|3.0|1.1|3.5*|1.1|\n|**_S2. Audio chat or conference_**|all|244|2.3|1.4|3.6|1.4|\n||Students|224|2.3|1.4|3.6|1.4|\n||Professors|20|2.4|.9|3.4|1.1|\n|**_S3. Video chat or Web conference_**|all|244|2.0|1.3|3.5|1.4|\n||Students|224|2.0|1.3|3.5|1.4|\n||Professors|20|2.3|1.0|3.3|1.0|\n|**S4. Communicate with email**|all|244|3.0|1.3|4.0|1.2|\n||Students|224|3.0*|1.3|4.0|1.2|\n||Professors|20|3.7*|1.0|4.1|1.0|\n|**S5. Participate in social networks**|all|244|3.3|1.3|4.1|1.3|\n||Students|224|3.3|1.3|4.1*|1.3|\n||Professors|20|3.7|.6|3.9*|.9|\n|**_S6. Share fles and collaborate_**|all|244|2.2|1.3|3.2|1.3|\n||Students|224|2.1|1.3|3.3|1.4|\n||Professors|20|2.5|1.3|3.0|1.1|\n|**_S7. Publish media and ideas online_**|all|244|.9|1.2|2.1|1.4|\n||Students|224|.9|1.2|2.1|1.5|\n||Professors|20|.9|1.1|2.0|1.1|"
    },
    {
      "headers": [
        "Activity item",
        "Segment",
        "_N_",
        "_M_(Frequency)",
        "_SD_",
        "(Confdence)",
        "_SD_"
      ],
      "rows": [
        [
          "i1. use maps or gPS",
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          "244",
          "1.6",
          "1.3",
          "3.0",
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        ],
        [
          "",
          "Students",
          "224",
          "1.6",
          "1.3",
          "3.1",
          "1.6"
        ],
        [
          "",
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          "1.5",
          "1.2",
          "2.7",
          "1.5"
        ],
        [
          "**I2. Find and use articles or news**",
          "all",
          "244",
          "2.7",
          "1.3",
          "3.8",
          "1.3"
        ],
        [
          "",
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          "224",
          "2.6*",
          "1.3",
          "3.8",
          "1.3"
        ],
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          "",
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          "20",
          "3.4*",
          ".6",
          "4.1",
          "1.0"
        ],
        [
          "**_I3. Find and view short videos_**",
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          "2.7",
          "1.3",
          "3.8",
          "1.3"
        ],
        [
          "",
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          "224",
          "2.7",
          "1.4",
          "3.8",
          "1.4"
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        [
          "",
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          "3.0",
          ".7",
          "4.0",
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        [
          "i4. Watch or download movies",
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          "2.4",
          "1.2",
          "3.9",
          "1.3"
        ],
        [
          "",
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          "2.4",
          "1.2",
          "3.9",
          "1.3"
        ],
        [
          "",
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          "20",
          "2.1",
          ".9",
          "3.7",
          "1.1"
        ],
        [
          "i5. listen or download music",
          "all",
          "244",
          "2.2",
          "1.4",
          "3.6",
          "1.5"
        ],
        [
          "",
          "Students",
          "224",
          "2.3*",
          "1.4",
          "3.7*",
          "1.5"
        ],
        [
          "",
          "Professors",
          "20",
          "1.4*",
          "1.2",
          "2.9*",
          "1.5"
        ],
        [
          "**_I6. Read or download digital books_**",
          "all",
          "244",
          "1.8",
          "1.3",
          "3.3",
          "1.5"
        ],
        [
          "",
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          "224",
          "1.8",
          "1.3",
          "3.3",
          "1.5"
        ],
        [
          "",
          "Professors",
          "20",
          "1.9",
          "1.0",
          "3.4",
          "1.3"
        ],
        [
          "i7. automate information sources",
          "all",
          "244",
          ".7",
          "1.2",
          "1.8",
          "1.3"
        ],
        [
          "",
          "Students",
          "224",
          ".8",
          "1.2",
          "1.8",
          "1.3"
        ],
        [
          "",
          "Professors",
          "20",
          ".5",
          ".9",
          "1.6",
          "1.1"
        ]
      ],
      "raw": "|Activity item|Segment|_N_|_M_(Frequency)|_SD_|(Confdence)|_SD_|\n|---|---|---|---|---|---|---|\n|i1. use maps or gPS|all|244|1.6|1.3|3.0|1.6|\n||Students|224|1.6|1.3|3.1|1.6|\n||Professors|20|1.5|1.2|2.7|1.5|\n|**I2. Find and use articles or news**|all|244|2.7|1.3|3.8|1.3|\n||Students|224|2.6*|1.3|3.8|1.3|\n||Professors|20|3.4*|.6|4.1|1.0|\n|**_I3. Find and view short videos_**|all|244|2.7|1.3|3.8|1.3|\n||Students|224|2.7|1.4|3.8|1.4|\n||Professors|20|3.0|.7|4.0|.9|\n|i4. Watch or download movies|all|244|2.4|1.2|3.9|1.3|\n||Students|224|2.4|1.2|3.9|1.3|\n||Professors|20|2.1|.9|3.7|1.1|\n|i5. listen or download music|all|244|2.2|1.4|3.6|1.5|\n||Students|224|2.3*|1.4|3.7*|1.5|\n||Professors|20|1.4*|1.2|2.9*|1.5|\n|**_I6. Read or download digital books_**|all|244|1.8|1.3|3.3|1.5|\n||Students|224|1.8|1.3|3.3|1.5|\n||Professors|20|1.9|1.0|3.4|1.3|\n|i7. automate information sources|all|244|.7|1.2|1.8|1.3|\n||Students|224|.8|1.2|1.8|1.3|\n||Professors|20|.5|.9|1.6|1.1|"
    },
    {
      "headers": [
        "Activity item",
        "Segment",
        "_N_",
        "(Frequency)",
        "_SD_",
        "(Confdence)",
        "_SD_"
      ],
      "rows": [
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          "**_E1. Use calendar or organiser_**",
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          ".8",
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        ],
        [
          "",
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        [
          "**_E2. Use concept map or fow chart_**",
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          "244",
          ".9",
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        [
          "",
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        [
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          "1.0",
          "1.2",
          "2.0",
          "1.1"
        ],
        [
          "**_E3. Create fgures and diagrams_**",
          "all",
          "244",
          "1.7",
          "1.2",
          "3.0",
          "1.3"
        ],
        [
          "",
          "Students",
          "224",
          "1.7*",
          "1.2",
          "3.0",
          "1.3"
        ],
        [
          "",
          "Professors",
          "20",
          "2.3*",
          ".7",
          "3.5",
          "1.0"
        ],
        [
          "e4. Sort large amounts of data",
          "all",
          "244",
          "1.7",
          "1.3",
          "3.0",
          "1.4"
        ],
        [
          "",
          "Students",
          "224",
          "1.7",
          "1.3",
          "3.0",
          "1.4"
        ],
        [
          "",
          "Professors",
          "20",
          "1.6",
          "1.4",
          "2.7",
          "1.3"
        ],
        [
          "**_E5. Generate graphs from numbers_**",
          "all",
          "244",
          "1.7",
          "1.2",
          "3.1",
          "1.3"
        ],
        [
          "",
          "Students",
          "224",
          "1.7",
          "1.2",
          "3.0",
          "1.3"
        ],
        [
          "",
          "Professors",
          "20",
          "2.0",
          ".9",
          "3.2",
          "1.1"
        ],
        [
          "**_E6. Automate complex calculations_**",
          "all",
          "244",
          "1.7",
          "1.4",
          "2.8",
          "1.4"
        ],
        [
          "",
          "Students",
          "224",
          "1.7",
          "1.4",
          "2.8",
          "1.4"
        ],
        [
          "",
          "Professors",
          "20",
          "1.5",
          "1.1",
          "2.6",
          "1.4"
        ],
        [
          "e7. Program or automate procedures",
          "all",
          "244",
          ".6",
          "1.1",
          "1.6",
          "1.1"
        ],
        [
          "",
          "Students",
          "224",
          ".6",
          "1.1",
          "1.7*",
          "1.1"
        ],
        [
          "",
          "Professors",
          "20",
          ".3",
          "1.0",
          "1.1*",
          ".2"
        ]
      ],
      "raw": "|Activity item|Segment|_N_|(Frequency)|_SD_|(Confdence)|_SD_|\n|---|---|---|---|---|---|---|\n|**_E1. Use calendar or organiser_**|all|244|.8|1.3|1.9|1.4|\n||Students|224|.8|1.3|2.0|1.4|\n||Professors|20|1.0|1.3|1.8|1.0|\n|**_E2. Use concept map or fow chart_**|all|244|.9|1.2|2.1|1.3|\n||Students|224|.9|1.2|2.1|1.3|\n||Professors|20|1.0|1.2|2.0|1.1|\n|**_E3. Create fgures and diagrams_**|all|244|1.7|1.2|3.0|1.3|\n||Students|224|1.7*|1.2|3.0|1.3|\n||Professors|20|2.3*|.7|3.5|1.0|\n|e4. Sort large amounts of data|all|244|1.7|1.3|3.0|1.4|\n||Students|224|1.7|1.3|3.0|1.4|\n||Professors|20|1.6|1.4|2.7|1.3|\n|**_E5. Generate graphs from numbers_**|all|244|1.7|1.2|3.1|1.3|\n||Students|224|1.7|1.2|3.0|1.3|\n||Professors|20|2.0|.9|3.2|1.1|\n|**_E6. Automate complex calculations_**|all|244|1.7|1.4|2.8|1.4|\n||Students|224|1.7|1.4|2.8|1.4|\n||Professors|20|1.5|1.1|2.6|1.4|\n|e7. Program or automate procedures|all|244|.6|1.1|1.6|1.1|\n||Students|224|.6|1.1|1.7*|1.1|\n||Professors|20|.3|1.0|1.1*|.2|"
    }
  ],
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    {
      "raw": "## **Technology, Pedagogy and Education**"
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    {
      "raw": "**ISSN: 1475-939X (Print) 1747-5139 (Online) Journal homepage: http://www.tandfonline.com/loi/rtpe20**"
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      "raw": "## **Surveying digital competencies of university students and professors in Ukraine for fully online collaborative learning**"
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    {
      "raw": "## **Todd J. B. Blayone, Olena Mykhailenko, Roland vanOostveen, Oleksiy Grebeshkov, Olena Hrebeshkova & Oleksandr Vostryakov**"
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      "raw": "**To cite this article:** Todd J. B. Blayone, Olena Mykhailenko, Roland vanOostveen, Oleksiy Grebeshkov, Olena Hrebeshkova & Oleksandr Vostryakov (2018) Surveying digital competencies of university students and professors in Ukraine for fully online collaborative learning, Technology, Pedagogy and Education, 27:3, 279-296, DOI: 10.1080/1475939X.2017.1391871",
      "year": "2018"
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      "doi": "10.1080/1475939X.2017.1391871"
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    {
      "raw": "Published online: 31 Oct 2017."
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      "raw": "Citing articles: 2 View citing articles"
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    {
      "raw": "Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=rtpe20"
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