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Teacher Intention to Transfer ICT Training When Integrating Digital Technologies in Education: The Teacher Transfer of ICT Training Model (TeTra-ICT)

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Title: Teacher Intention to Transfer ICT Training When Integrating Digital Technologies in Education: The Teacher Transfer of ICT Training Model (TeTra-ICT)
Language: English
Authors: Perifanou, Maria A. (ORCID 0000-0002-9874-8417), Tzafilkou, Katerina (ORCID 0000-0003-4092-6492), Economides, Anastasios A. (ORCID 0000-0001-8056-1024)
Source: European Journal of Education. Mar 2023 58(1):111-129.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 19
Publication Date: 2023
Document Type: Journal Articles
Reports - Research
Education Level: Elementary Education
Secondary Education
Descriptors: Elementary School Teachers, Secondary School Teachers, Intention, Technology Integration, Information Technology, Educational Technology, Educational Practices, Training, Program Design, Program Evaluation, Teacher Education, Self Efficacy, Usability, Transfer of Training, Motivation, Foreign Countries
Geographic Terms: Greece
DOI: 10.1111/ejed.12534
ISSN: 0141-8211
1465-3435
Abstract: The aim of this study is to propose a new structural model for how teachers transfer their ICT training (TeTra-ICT), shedding light on the factors that tend to affect their intention to integrate digital technologies in educational practices as well as train their colleagues. The proposed model exploits training programme design characteristics and ICT-related individual factors. A total of 117 new ICT instructors for primary and secondary education teachers in Greece were evaluated. The instructors participated in a national Teacher Training Programme on applying ICT in education. Results indicate significant effects of individual (ICT-related self-efficacy in teaching) and programme design characteristics (platform's ease of use, support, content, and resources) on the teachers' final motivation and intention to transfer their ICT knowledge and skills. The model also reveals significant correlations between individual and training characteristics, the teachers' post-training self-efficacy for transferring skills and their perception of the usefulness of the training programme. The examined constructs explain 86% of the variance in teacher intentions to transfer their ICT knowledge and skills, and 72% of their perception of the usefulness of the training programme. Interestingly, while there were no gender differences in individual ICT-related characteristics, women expressed significantly higher values than men in their perception of the usefulness of training, self-efficacy, motivation, and intention to transfer.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1368279
Database: ERIC
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  Value: <anid>AN0162103987;eje01mar.23;2023Mar01.02:37;v2.2.500</anid> <title id="AN0162103987-1">Teacher intention to transfer ICT training when integrating digital technologies in education: The teacher transfer of ICT training model (TeTra‐ICT) </title> <sbt id="AN0162103987-2">INTRODUCTION</sbt> <p>The aim of this study is to propose a new structural model for how teachers transfer their ICT training (TeTra‐ICT), shedding light on the factors that tend to affect their intention to integrate digital technologies in educational practices as well as train their colleagues. The proposed model exploits training programme design characteristics and ICT‐related individual factors. A total of 117 new ICT instructors for primary and secondary education teachers in Greece were evaluated. The instructors participated in a national Teacher Training Programme on applying ICT in education. Results indicate significant effects of individual (ICT‐related self‐efficacy in teaching) and programme design characteristics (platform's ease of use, support, content, and resources) on the teachers' final motivation and intention to transfer their ICT knowledge and skills. The model also reveals significant correlations between individual and training characteristics, the teachers' post‐training self‐efficacy for transferring skills and their perception of the usefulness of the training programme. The examined constructs explain 86% of the variance in teacher intentions to transfer their ICT knowledge and skills, and 72% of their perception of the usefulness of the training programme. Interestingly, while there were no gender differences in individual ICT‐related characteristics, women expressed significantly higher values than men in their perception of the usefulness of training, self‐efficacy, motivation, and intention to transfer.</p> <p>The transfer of Information and Communication Technology (ICT) skills is expected to support educational reforms and provide more opportunities for students and teachers to integrate ICT in classroom instruction for improving teaching practices (Elstad, [<reflink idref="bib16" id="ref1">16</reflink>]; Lawrence & Tar, [<reflink idref="bib34" id="ref2">34</reflink>]; Yurtseven et al., [<reflink idref="bib71" id="ref3">71</reflink>]). Policy makers and educators around the world put significant efforts towards the design and management of numerous programmes in training teachers to use technology. The main purpose of these programmes is to encourage teachers to apply ICT in education and improve their teaching strategies (Sadaf et al., [<reflink idref="bib51" id="ref4">51</reflink>]). Unfortunately, despite these efforts, many teachers report low satisfaction for training to use technology effectively in their teaching practices (European Commission, [<reflink idref="bib18" id="ref5">18</reflink>]; OECD, [<reflink idref="bib44" id="ref6">44</reflink>], [<reflink idref="bib45" id="ref7">45</reflink>]). To this end, the role of teacher educators is crucial for the effectiveness of the transfer training process since they are in part responsible for efficient training outcomes and the preparation of future teachers (Scherer et al., [<reflink idref="bib53" id="ref8">53</reflink>]). In particular, the main role of teacher educators is to efficiently prepare future teachers to transfer necessary skills and knowledge to their students (Binkley et al., [<reflink idref="bib12" id="ref9">12</reflink>]; OECD, [<reflink idref="bib46" id="ref10">46</reflink>]).</p> <p>Throughout the years, several studies have attempted to analyse key factors affecting teachers' ICT integration into classroom instruction, aiming to assist teacher educators and ICT skills transfer training institutions to design their ICT knowledge and skills transfer training strategies and pedagogical practices. For instance, Ertmer and Ottenbreit‐Leftwich ([<reflink idref="bib17" id="ref11">17</reflink>]) investigated the way that contextual, affective, and cognitive factors may act as enablers or barriers for the actual transfer of teachers' ICT knowledge and skills. They propose that ICT integration should provide technology‐enabled engaging learning activities. This aligns with Trucano's ([<reflink idref="bib62" id="ref12">62</reflink>]) suggestion that enabling conditions are needed for ICT to support teachers to transform their teacher practices. Trucano also argues that teachers' reasoning and pedagogical practices can influence their ICT use, and this can impact student performance. Some researchers agree that the successfulness of ICT integration depends on the teachers' ability to effectively integrate ICT into classroom instruction (Comi et al., [<reflink idref="bib15" id="ref13">15</reflink>]) while others (e.g., Joo et al., [<reflink idref="bib31" id="ref14">31</reflink>]; Petko et al., [<reflink idref="bib48" id="ref15">48</reflink>]; Taimalu & Luik, [<reflink idref="bib57" id="ref16">57</reflink>]) argue that the teachers' ICT integration in the classroom depends on several factors related to individual teacher characteristics and the education system. Similarly, some researchers (e.g., Bower, [<reflink idref="bib13" id="ref17">13</reflink>]) note that integrating ICT in teaching practice can be affected by multiple factors including not only the teachers' skills and attitudes but also their environment, resource capacity, and infrastructure sustainability. In the same context, Albion et al. ([<reflink idref="bib2" id="ref18">2</reflink>]) conclude that there is a need for a better understanding of the teacher educator role to improve their impact on teachers' ICT integration practices.</p> <p>Recently, Ifinedo et al. ([<reflink idref="bib30" id="ref19">30</reflink>]) have argued that to achieve effective transfer of ICT knowledge and skills, one should consider learning context and teacher pedagogical practices. In their attempt to analyse both individual and organisational factors, Tondeur et al. ([<reflink idref="bib60" id="ref20">60</reflink>]) investigated the effects of the teachers' individual (e.g., age and gender) and ICT‐related characteristics along with the support they receive from teacher educators for their ICT skills and competencies. Their findings reveal significant influence on teachers' ICT attitudes and perceptions that ICT is easy to use. Tzafilkou et al. ([<reflink idref="bib63" id="ref21">63</reflink>]) recently highlighted the significant role of gender and previous ICT experience and expertise levels on teacher‐trainer intentions and motivation to transfer their acquired knowledge. Other recent works (e.g., Nelson & Hawk, [<reflink idref="bib42" id="ref22">42</reflink>]) highlight the importance of teachers' beliefs and attitudes to technology for the application of constructive learning approaches and ICT in their classrooms. As the authors suggest, beliefs about the utility of technologies should be included in models for predicting teacher intention to use technology in teaching practices.</p> <hd id="AN0162103987-3">Research gap and study contribution</hd> <p>Although several studies have examined key factors affecting teacher effectiveness in integrating ICT, and beliefs and intentions to use technology in general (e.g., Yurtseven et al., [<reflink idref="bib71" id="ref23">71</reflink>]), research related to the transfer of ICT training is limited. Training transfer models are designed and examined, to better understand the conditions for enhancing teachers' use of new ICT knowledge and to measure the effectiveness of training. However, most of the suggested training transfer models consider general study fields, and not specific domains like teachers' ICT integration in education, and they are mainly oriented towards examining teacher motivation as the most important determinant for the transfer of training (e.g., Binkhorst et al., [<reflink idref="bib11" id="ref24">11</reflink>]; Helmke, [<reflink idref="bib25" id="ref25">25</reflink>]).</p> <p>Several training transfer models are based on the model suggested by Baldwin and Ford ([<reflink idref="bib7" id="ref26">7</reflink>]) which is composed of three structural levels: training inputs, training outputs and transfer conditions. An integrative training transfer model is proposed by Lee et al. ([<reflink idref="bib35" id="ref27">35</reflink>]) examining the mediator effects of motivation to learn and motivation to transfer. However, their research is not related to the educational context of teacher training. In addition, Tonhäuser and Büker ([<reflink idref="bib61" id="ref28">61</reflink>]) reviewed several studies on transfer training models within the context of general education studies or industry training but not ICT‐related transfer training in education. Although Tzafilkou et al. ([<reflink idref="bib63" id="ref29">63</reflink>]) have recently examined some structural relationships in a transfer training model for teacher trainers, they did not examine the training programme characteristics (like content and resources, support, etc.) that tend to play an influential role for the main transfer training variables. To contribute to the field of teacher ICT training, a deeper analysis of individual characteristics, like ICT expertise and gender is considered.</p> <p>Drawing on the literature review and recent technological trends in education, we identify a research gap in designing transfer training models for ICT integration in education. Furthermore, only a few models include the factor of intention to transfer knowledge (e.g., Tzafilkou et al., [<reflink idref="bib63" id="ref30">63</reflink>]), while most are oriented towards examining motivation to transfer or actual transfer of training. According to Ajzen's ([<reflink idref="bib1" id="ref31">1</reflink>]) Theory of Planned Behaviour, the intention to transfer knowledge is a crucial factor to achieve effective transfer of training since it plays the role of a direct antecedent for actual behaviour. Therefore, it should not be neglected from the list of (ICT) training transfer dependent variables.</p> <p>Motivated by the above, this study examined the training programme of 300 new ICT teacher instructors in primary and secondary education in Greece, with the aim to propose a simple training transfer model for integrating digital technologies in education. The novelty of the suggested model is the examination of the factors that tend to affect the teachers' intention to transfer the gained ICT knowledge and skills, contrary to previous ICT‐related studies that attempted to analyse either solely the teachers' motivation or their actual post‐training behaviours.</p> <p>In the following, we describe the main research gaps that this study attempts to fill:</p> <p></p> <ulist> <item> Although there are several structural models for explaining the transfer of training (e.g., Binkhorst et al., [<reflink idref="bib11" id="ref32">11</reflink>] ; Helmke, [<reflink idref="bib25" id="ref33">25</reflink>] ; Lee et al., [<reflink idref="bib35" id="ref34">35</reflink>]), there is a significant lack in the context of ICT training transfer models since most studies are focused on exploring teachers' attitudes towards ICT integration in educational practice (e.g., Ertmer & Ottenbreit‐Leftwich, [<reflink idref="bib17" id="ref35">17</reflink>] ; Tondeur et al., [<reflink idref="bib60" id="ref36">60</reflink>]). The present study proposes an ICT oriented transfer training model, named TeTra‐ICT, and examines the relationships among the basic transfer training constructs.</item> <p></p> <item> Most previous studies on ICT transfer training examined teacher motivation to transfer new knowledge (e.g., Moreira‐Fontán et al., [<reflink idref="bib41" id="ref37">41</reflink>]), or they examined their actual transfer of training (e.g., Ifinedo et al., [<reflink idref="bib30" id="ref38">30</reflink>]), not considering intention to transfer in their proposed transfer training models. The present study explicitly examines the factors that tend to affect teacher intention to transfer new knowledge.</item> <p></p> <item> There are only a few previous studies that structurally analyse teacher ICT‐related individual characteristics and/or the training programme design characteristics in the context of ICT integration in education (e.g., Tondeur et al., [<reflink idref="bib60" id="ref39">60</reflink>]). The present study examines the above factors in combination, to predict the teachers' intention to transfer ICT skills and integrate technology‐enabled learning methodologies.</item> <p></p> <item> Previous studies mainly examined the influence of training programme design features and support on motivation to transfer or actual transfer of training (e.g., Lee et al., [<reflink idref="bib35" id="ref40">35</reflink>] ; Mansour et al., [<reflink idref="bib40" id="ref41">40</reflink>] ; Tonhäuser & Büker, [<reflink idref="bib61" id="ref42">61</reflink>]). The proposed model (TeTra‐ICT) integrates teacher perceptions of the usefulness of training as a mediator variable between programme design characteristics and examined transfer related variables.</item> </ulist> <p>Our aim with the study was to contribute to the design of educational practices for teacher training, by acknowledging factors that tend to affect teachers' intention to transfer new knowledge. Moreover, the findings can serve as a steppingstone for designing new ICT‐related training transfer model architectures and measurement models.</p> <hd id="AN0162103987-4">METHODS</hd> <p></p> <hd id="AN0162103987-5">Research model and hypotheses</hd> <p> <emph>Intention to Transfer</emph> is based on Ajzen' ([<reflink idref="bib1" id="ref43">1</reflink>]) Theory of Planned Behaviour that interprets intention as a direct antecedent for behaviour. The term 'intention' is generally perceived as the trainee's desire, sense of responsibility and self‐prediction. <emph>Motivation to Learn</emph> reflects "<emph>a specific desire of the trainee to learn the content of the training programme</emph>" (Noe, [<reflink idref="bib43" id="ref44">43</reflink>], p. 743). In contrast, <emph>Motivation to Transfer</emph> generally reflects the learner's efforts to practically apply the skills and knowledge acquired from a training programme. Motivation to transfer has been mainly studied as an outcome behaviour triggered by motivation to learn and self‐efficacy (Kontoghiorghes, [<reflink idref="bib33" id="ref45">33</reflink>]) or as an input factor positively affecting training transfer (e.g., Lee et al., [<reflink idref="bib35" id="ref46">35</reflink>]). Studies overall conclude that motivation to learn tend to predict motivation to transfer (Bell & Ford, [<reflink idref="bib10" id="ref47">10</reflink>]; Rowold, [<reflink idref="bib50" id="ref48">50</reflink>]). And that pre‐training self‐efficacy is positively correlated with motivation to learn (Lee et al., [<reflink idref="bib35" id="ref49">35</reflink>]). Accordingly, the first two hypotheses are formulated as below:</p> <hd id="AN0162103987-6">1 Hypothesis</hd> <p>Teacher trainer motivation to transfer positively affects their intention to transfer.</p> <hd id="AN0162103987-7">2 Hypothesis</hd> <p>Teacher trainer motivation to learn positively affects their (a) motivation to transfer, and (b) self‐efficacy to transfer.</p> <hd id="AN0162103987-8">Self‐efficacy to transfer</hd> <p>Self‐efficacy to transfer can be interpreted as the perceived ability of trainees to efficiently transfer the gained knowledge and skills. Bandura claimed that high levels of self‐efficacy can convince trainees that they can efficiently perform the tasks following their training (Bandura, [<reflink idref="bib8" id="ref50">8</reflink>], [<reflink idref="bib9" id="ref51">9</reflink>]). Several researchers have examined the relationship between post‐training self‐efficacy motivation to transfer and intention to transfer, confirming that self‐efficacy brings positive effects on motivation and intention to transfer (Al‐Swidi & Al Yahya, [<reflink idref="bib3" id="ref52">3</reflink>]; Simosi, [<reflink idref="bib54" id="ref53">54</reflink>]; Tziner et al., [<reflink idref="bib66" id="ref54">66</reflink>]). Accordingly, we consider the following hypothesis:</p> <hd id="AN0162103987-9">3 Hypothesis</hd> <p>Teacher trainers' self‐efficacy to transfer positively affects their (a) motivation, and (b) intention to transfer.</p> <hd id="AN0162103987-10">Training usefulness</hd> <p>The usefulness of training is an important utilitarian aspect of how teachers perceive ICT training. Intention to transfer can be influenced by perceived usefulness associated with training or importance of learning (e.g., Lim & Morris, [<reflink idref="bib38" id="ref55">38</reflink>]). In terms of technology adoption Huang ([<reflink idref="bib28" id="ref56">28</reflink>]) has recently argued that the more useful the trainees perceive technology, the higher their satisfaction; and this might sustain intentions to use technology. In this study we also examined the potential correlation between training usefulness and self‐efficacy to transfer. Therefore, we hypothesised:</p> <hd id="AN0162103987-11">4 Hypothesis</hd> <p>The usefulness of training positively affects (a) teacher trainers' intentions and (b) self‐efficacy to transfer.</p> <hd id="AN0162103987-12">Support, content relevance and educational resources</hd> <p>Training programme characteristics have shown significant influence on training transfer. <emph>Support</emph> refers here to supportive behaviours of supervisors and colleagues; this has been shown to positively affect the transfer of learning (Festner, [<reflink idref="bib19" id="ref57">19</reflink>]; Hinrichs, [<reflink idref="bib26" id="ref58">26</reflink>]). Similarly, <emph>Content relevance and educational resources</emph> have been shown to positively affect the intention to transfer or to continue the trained activity (Mansour et al., [<reflink idref="bib40" id="ref59">40</reflink>]). Finally, since technology acceptance, ease of use and usefulness are strongly correlated in several research works (e.g., Terzis & Economides, [<reflink idref="bib59" id="ref60">59</reflink>]; Tzafilkou & Protogeros, [<reflink idref="bib64" id="ref61">64</reflink>]), we assumed that acceptance related characteristics, like the learning platform's <emph>ease of use</emph>, can have a positive effect on the usefulness of training (including technical and non‐technical characteristics).</p> <hd id="AN0162103987-13">5 Hypothesis</hd> <p>Support positively affects the usefulness of training.</p> <hd id="AN0162103987-14">6 Hypothesis</hd> <p>Content and resources positively affect the usefulness of training.</p> <hd id="AN0162103987-15">7 Hypothesis</hd> <p>Platform's ease of use positively affects the usefulness of training.</p> <hd id="AN0162103987-16">Experience and gender</hd> <p>Teachers' computer experience is shown to positively relate with ICT integration in teaching (van Braak et al., [<reflink idref="bib67" id="ref62">67</reflink>]). Also, teachers who perceive positively their ICT skills tend to organise more frequent ICT‐based activities in the classroom (Wastiau et al., [<reflink idref="bib69" id="ref63">69</reflink>]). Similarly, teaching experience has been shown to affect the efficiency of ICT integration (Wong & Li, [<reflink idref="bib70" id="ref64">70</reflink>]). ICT‐related self‐efficacy has been shown to positively affect the main technology acceptance constructs like perceived usefulness (e.g., Terzis & Economides, [<reflink idref="bib59" id="ref65">59</reflink>]; Tzafilkou et al., [<reflink idref="bib65" id="ref66">65</reflink>]). Researchers have also shown the relation between trainees' self‐efficacy and their motivation to learn (e.g., Lee et al., [<reflink idref="bib35" id="ref67">35</reflink>]). Accordingly, we hypothesised the following:</p> <hd id="AN0162103987-17">8 Hypothesis</hd> <p>ICT‐related teaching experience positively affects teacher trainers' (a) motivation to learn and (b) their perception of the usefulness of training.</p> <hd id="AN0162103987-18">9 Hypothesis</hd> <p>ICT‐related teaching self‐efficacy positively affects teacher trainers' (a) motivation to learn and (b) their perception of the usefulness of training.</p> <p>Finally, research has revealed several significant <emph>gender‐based differences</emph> in user attitudes and technology acceptance (e.g., Burnett et al., [<reflink idref="bib14" id="ref68">14</reflink>]; Terzis & Economides, [<reflink idref="bib59" id="ref69">59</reflink>], Tzafilkou & Protogeros, 2018; Tzafilkou et al., [<reflink idref="bib65" id="ref70">65</reflink>]). Additionally, teachers' attitudes towards technology can affect their perceptions of the usefulness of technology and, its application in teaching practice (Huang & Liaw, [<reflink idref="bib27" id="ref71">27</reflink>]). Regarding the post‐training ICT integration, Kay ([<reflink idref="bib32" id="ref72">32</reflink>]) found that while teachers who were men had higher levels of computer ability before ICT implementation, there were no gender differences after the implementation of the technology. Since a <emph>gender‐gap</emph> seems to affect only pre‐training characteristics and not training transfer variables we articulated the following hypothesis:</p> <hd id="AN0162103987-19">10 Hypothesis</hd> <p>Gender affects teacher trainers' (a) motivation to learn and (b) the usefulness of training.</p> <p>Figure 1 depicts the Transfer of ICT Training conceptual model, based on the reviewed literature and the inclusion of ICT‐oriented characteristics. The model examines the structural relations among individual characteristics, training programme characteristics and the main outcome transfer training variables (motivation and intention to transfer). The model also proposes the integration of a set of mediator variables, including motivation to learn, training usefulness and self‐efficacy to transfer the gained ICT knowledge and skills.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/EJE/01mar23/ejed12534-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ejed12534-fig-0001.jpg" title="1 Conceptual model for teacher transfer of ICT training (TeTra‐ICT). Source: Authors" /> </p> <p></p> <hd id="AN0162103987-21">Structure and validity of the measurement model</hd> <p>In this study we used a questionnaire survey to measure ICT training transfer variables. The questionnaire was composed of 27 items, using a 5‐point Likert scale for responses ranging from <emph>strongly disagree</emph> to <emph>strongly agree</emph>. The structure of the measurement model was based on previous questionnaires (Lee et al., [<reflink idref="bib35" id="ref73">35</reflink>]; Liebermann & Hoffmann, [<reflink idref="bib37" id="ref74">37</reflink>]; Ma et al., [<reflink idref="bib39" id="ref75">39</reflink>]; Tzafilkou et al., [<reflink idref="bib63" id="ref76">63</reflink>]) and was further adjusted to the current research context. The structure of the measurement model and item wordings are given in Table 1.</p> <p>1 TABLE Measurement model</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Construct</th><th align="left">Item</th><th align="left" /></tr></thead><tbody valign="top"><tr><td>Motivation to learn</td><td /><td>I have participated in this teacher training programme on using and applying ICT in education because</td></tr><tr><td /><td>ML1</td><td>I am interested in learning new knowledge and ICT skills for using ICT in education</td></tr><tr><td /><td>ML2</td><td>I want to improve my teaching using ICT</td></tr><tr><td /><td>ML3</td><td>My colleagues have attended a similar training and believe it is worthwhile</td></tr><tr><td /><td>ML4</td><td>I feel responsible to help my colleagues and students in using ICT in education</td></tr><tr><td>Support</td><td /><td>After participating in this Teachers' Training Program, I believe that</td></tr><tr><td /><td>SP1</td><td>The Administration was helpful</td></tr><tr><td /><td>SP2</td><td>The Instructors' guidance was efficient</td></tr><tr><td>Content and resources</td><td /><td>After participating in this teacher training programme, I believe that</td></tr><tr><td /><td>CR1</td><td>The content and educational resources were credible</td></tr><tr><td /><td>CR2</td><td>The content and educational resources were practical and applicable to my classroom reality</td></tr><tr><td>Platform's ease of use</td><td /><td>After participating in this teacher training programme, I believe that</td></tr><tr><td /><td>PEOU1</td><td>The training platform (Moodle) was easy to use</td></tr><tr><td /><td>PEOU2</td><td>I did not need to try too hard to use the training platform (Moodle) effectively</td></tr><tr><td>ICT‐related teaching self‐efficacy</td><td /><td>Before attending this teacher training programme on using and applying ICT in education, I was feeling</td></tr><tr><td /><td>TSE1</td><td>Confident to teach my students using ICT</td></tr><tr><td /><td>TSE2</td><td>Confident to train my colleagues on how to use ICT in education</td></tr><tr><td>Self‐efficacy to transfer</td><td /><td>After participating in this teacher training programme, I feel</td></tr><tr><td /><td>SET1</td><td>Capable of training my colleagues what I have learned in this training</td></tr><tr><td /><td>SET2</td><td>Capable of teaching my students what I have learned in this training</td></tr><tr><td /><td>SET3</td><td>Confident that I will successfully transfer to my students what I have learned in this training</td></tr><tr><td>Training usefulness</td><td /><td>After participating in this teacher training programme, I believe that</td></tr><tr><td /><td>TU1</td><td>The training was useful</td></tr><tr><td /><td>TU2</td><td>This training will help me to improve my teaching using ICT</td></tr><tr><td /><td>TU3</td><td>The training improved my knowledge and ICT skills in training other teachers to use ICT in teaching practices</td></tr><tr><td /><td>TU4</td><td>The training improved my knowledge and ICT skills for using ICT in teaching</td></tr><tr><td>Motivation to transfer</td><td /><td>After participating in this teacher training programme</td></tr><tr><td /><td>MT1</td><td>I want to transfer my new knowledge and ICT skills to train my colleagues to use ICT in teaching</td></tr><tr><td /><td>MT2</td><td>I feel responsible to share with my colleagues what I have learned in this training</td></tr><tr><td /><td>MT3</td><td>I feel responsible to teach my students what I have learned in this training</td></tr><tr><td>Intention to transfer</td><td /><td>After participating in this teacher training programme</td></tr><tr><td /><td>IT1</td><td>I will apply what I have learned in this training to train my colleagues</td></tr><tr><td /><td>IT2</td><td>I will apply what I have learned in this training to teach my students</td></tr><tr><td /><td>IT3</td><td>I prefer not to use the educational resources of this training to train my colleagues</td></tr><tr><td /><td>IT4</td><td>I will use the educational resources of this training to teach my students</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Source</emph>: Authors.</p> <p>The reliability of measures was assessed by composite reliability (minimum value of 0.70 according to Gefen et al., [<reflink idref="bib21" id="ref77">21</reflink>]) and Cronbach alpha (minimum value of 0.60 according to Hair et al., [<reflink idref="bib23" id="ref78">23</reflink>]). The convergent validity was assessed via the average variance extracted (AVE) (minimum value of 0.50 according to Bagozzi & Yi, [<reflink idref="bib6" id="ref79">6</reflink>]). The discriminant validity was assessed by the square root of AVE and latent variable correlations (Fornell & Larcker, [<reflink idref="bib20" id="ref80">20</reflink>]). The factor loadings were assessed based on their reliability score (greater than 0,50 according to Hulland, [<reflink idref="bib29" id="ref81">29</reflink>], p. 198).</p> <p>Figure 2 depicts the values of items' loadings and the constructs' Cronbach alpha. Table 2 presents the composite reliability and convergent validity of the measurement model, while Table 3 depicts the discriminant validity.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/EJE/01mar23/ejed12534-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="ejed12534-fig-0002.jpg" title="2 Item factor loadings and internal consistency (Cronbach alpha values) of the measurement model. Source: Authors. Values of Cronbach alpha are depicted inside the circle variables; values of factor loadings are depicted inside the path arrows towards the observed items" /> </p> <p></p> <p>2 TABLE Composite reliability and convergent validity results for the measurement model</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Items</th><th align="left">CR</th><th align="left">AVE</th></tr></thead><tbody valign="top"><tr><td>Motivation to learn</td><td>0.90</td><td>0.70</td></tr><tr><td>ML1</td><td /><td /></tr><tr><td>ML2</td><td /><td /></tr><tr><td>ML3</td><td /><td /></tr><tr><td>ML4</td><td /><td /></tr><tr><td>ICT‐related teaching self‐efficacy</td><td>0.85</td><td>0.74</td></tr><tr><td>TSE1</td><td /><td /></tr><tr><td>TSE2</td><td /><td /></tr><tr><td>Platform's ease of use</td><td>0.89</td><td>0.80</td></tr><tr><td>PEOU1</td><td /><td /></tr><tr><td>PEOU2</td><td /><td /></tr><tr><td>Training usefulness</td><td>0.96</td><td>0.85</td></tr><tr><td>TU1</td><td /><td /></tr><tr><td>TU2</td><td /><td /></tr><tr><td>TU3</td><td /><td /></tr><tr><td>TU4</td><td /><td /></tr><tr><td>Content and resources</td><td>0.93</td><td>0.87</td></tr><tr><td>CR1</td><td /><td /></tr><tr><td>CR2</td><td /><td /></tr><tr><td>Support</td><td>0.90</td><td>0.83</td></tr><tr><td>SP1</td><td /><td /></tr><tr><td>SP2</td><td /><td /></tr><tr><td>SP3</td><td /><td /></tr><tr><td>Self‐efficacy to transfer</td><td>0.94</td><td>0.83</td></tr><tr><td>SET1</td><td /><td /></tr><tr><td>SET2</td><td /><td /></tr><tr><td>SET3</td><td /><td /></tr><tr><td>Motivation to transfer</td><td>0.95</td><td>0.86</td></tr><tr><td>MT1</td><td /><td /></tr><tr><td>MT2</td><td /><td /></tr><tr><td>MT3</td><td /><td /></tr><tr><td>Intention to transfer</td><td>0.93</td><td>0.77</td></tr><tr><td>IT1</td><td /><td /></tr><tr><td>IT2</td><td /><td /></tr><tr><td>IT3</td><td /><td /></tr><tr><td>IT4</td><td /><td /></tr></tbody></table> </ephtml> </p> <ulist> <item>2 <emph>Source</emph>: Authors.</item> <item>3 TABLE The discriminant validity of the measurement model</item> </ulist> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th>CR</th><th align="left">TSE</th><th align="left">IT</th><th align="left">ML</th><th align="left">MT</th><th align="left">PEOU</th><th align="left">SET</th><th align="left">SP</th><th align="left">TU</th></tr></thead><tbody valign="top"><tr><td>Construct</td><td align="char" char=".">Latent variables correlations</td></tr><tr><td>CR</td><td align="char" char=".">0.932</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>TSE</td><td align="char" char=".">−0.145</td><td>0.861</td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>IT</td><td align="char" char=".">0.709</td><td>−0.158</td><td>0.877</td><td /><td /><td /><td /><td /><td /></tr><tr><td>ML</td><td align="char" char=".">0.579</td><td>−0.185</td><td>0.627</td><td>0.834</td><td /><td /><td /><td /><td /></tr><tr><td>MT</td><td align="char" char=".">0.681</td><td>−0.144</td><td>0.909</td><td>0.577</td><td>0.930</td><td /><td /><td /><td /></tr><tr><td>PEOU</td><td align="char" char=".">0.431</td><td>−0.040</td><td>0.401</td><td>0.483</td><td>0.417</td><td>0.897</td><td /><td /><td /></tr><tr><td>SET</td><td align="char" char=".">0.682</td><td>−0.217</td><td>0.756</td><td>0.568</td><td>0.746</td><td>0.421</td><td>0.911</td><td /><td /></tr><tr><td>SP</td><td align="char" char=".">0.707</td><td>−0.076</td><td>0.623</td><td>0.577</td><td>0.600</td><td>0.588</td><td>0.634</td><td>0.911</td><td /></tr><tr><td>TU</td><td align="char" char=".">0.787</td><td>0.033</td><td>0.707</td><td>0.552</td><td>0.624</td><td>0.488</td><td>0.674</td><td>0.749</td><td>0.923</td></tr></tbody></table> </ephtml> </p> <p>3 <emph>Source</emph>: Authors.</p> <hd id="AN0162103987-23">Training programme, participants, and procedure</hd> <p>The structured questionnaire was sent as an online form to 300 new ICT instructors of primary and secondary education teachers; specifically, instructors who participated in a national teacher training programme for developing skills to use and apply ICT in teaching practices in Greece. Each one of these 300 teacher trainers attended a training programme of 380 h from January to June 2019. These 300 teachers were clustered in groups of ten teachers by subject matter specialisation.</p> <p>The supporting infrastructure included the Learning Management System (LMS based on Moodle), the synchronous distance education platform (based on Blackboard Collaborate, BBC), the Management Information System (MIS), the Portal and the <emph>Ifigeneia</emph> repository of open educational resources.</p> <p>The training programme consisted of 380 h based on a mixed training model, and included:</p> <p></p> <ulist> <item> 72 h of face‐to‐face teaching sessions, at the facilities of nine University Teacher Training Centres spread all over the country. These sessions were held on six weekends, with six hours of training on Saturday and six hours on Sunday.</item> <p></p> <item> 138 h of synchronous distance sessions. These sessions were held twice a week, each lasting three hours.</item> <p></p> <item> 138 h learning workload that was assigned to teachers via asynchronous sessions. The teachers were assigned activities and tasks to be done during the intervals between the synchronous training sessions.</item> <p></p> <item> 32 h of practical training at schools and teacher training centres.</item> </ulist> <p>The survey instructions and the questionnaire items were provided in English language. Since the survey involved human subjects, all ethical requirements were fulfilled, and participants were informed about the procedure and asked to consent before their anonymous participation. Finally, 117 participants (50 men and 67 women) successfully completed the survey (participation was voluntary). Several participants (22.2%) were teachers in economics, management and the social sciences; foreign language teachers (16.2%) and primary education teachers were also represented (17.1%); 12.8% of the participants were physical education and health teachers; 11.1% teach informatics; while the rest teach courses in the natural sciences (6%), literature (5.1%), special needs education (4.3%), educational engineering (3.4%), mathematics, landscaping and architecture (1.8%). It should be mentioned that some participants chose two or more categories to identify courses they taught, since they are involved in several disciplines. Most of the participants (46.2%) were 41 to 51 years, 39.3% were in the age group of 51–60, while 14.4 were between 31 and 40 years old. Most of them (71%) hold a postgraduate degree, while 23% hold a doctorate degree and 6% only a bachelor's degree. For self‐reported ICT‐teaching experience, most of them (32.5%) have experience within a range from five to ten years, 29% have eleven to fifteen years of experience, 20.5% have fifteen to twenty years of experience, while 11% have more than twenty years of experience.</p> <hd id="AN0162103987-24">Data analysis</hd> <p>The partial least squares structural equation modelling approach (PLS‐SEM) was applied to analyse the collected data. PLS‐SEM multivariate analysis does not require normally distributed data (Hair et al., [<reflink idref="bib24" id="ref82">24</reflink>]) contrary to covariance‐based structural equation modelling (CB‐SEM) which requires the presumption of normal distribution of data. Researchers also support that PLS‐SEM is more appropriate in the social sciences (Astrachan et al., [<reflink idref="bib5" id="ref83">5</reflink>]).</p> <p>To examine potential gender differences in the examined variables, the non‐parametric method of Mann Whitney (Wilcoxon test for independent samples) was implemented.</p> <p>The PLS‐SEM analysis was conducted through SmartPLS 3 (Ringle et al., [<reflink idref="bib49" id="ref84">49</reflink>]) software which was used to assess the measures' reliability and validity and explore the relationships among the formulated hypotheses. SPSS version 21.0 for Windows (SPSS, [<reflink idref="bib56" id="ref85">56</reflink>]) was used to run the two‐sample Mann–Whitney tests.</p> <hd id="AN0162103987-25">RESULTS AND DISCUSSION</hd> <p></p> <hd id="AN0162103987-26">Descriptive statistics</hd> <p>Table 4 provides the descriptive statistics for the measured items which are included in the research model.</p> <p>4 TABLE Descriptive statistics</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Construct</th><th align="left">Mean</th><th align="left">Standard deviation</th></tr></thead><tbody valign="top"><tr><td>Motivation to learn (ML)</td><td>4.239</td><td>0.702</td></tr><tr><td>ICT‐related teaching self‐efficacy (TSE)</td><td>2.623</td><td>1.127</td></tr><tr><td>Platform's perceived ease of use (PEOU)</td><td>4.111</td><td>0.848</td></tr><tr><td>Content resources (CR)</td><td>3.859</td><td>0.853</td></tr><tr><td>Support (SP)</td><td>4.162</td><td>0.762</td></tr><tr><td>Training usefulness (TU)</td><td>3.735</td><td>0.922</td></tr><tr><td>Self‐efficacy to transfer (SET)</td><td>4.213</td><td>0.763</td></tr><tr><td>Motivation to transfer (MT)</td><td>4.162</td><td>0.819</td></tr><tr><td>Intention to transfer (IT)</td><td>4.205</td><td>0.771</td></tr></tbody></table> </ephtml> </p> <ulist> <item>4 <emph>Source</emph>: Authors.</item> <item>5 <emph>Note</emph>: <emph>N</emph> = 117.</item> </ulist> <p>However, as depicted in the high values of the standard deviations, some constructs revealed polarities among teacher perceptions. For this reason, further research is suggested to explore the factors that caused these differences.</p> <p>It is important to notice the difference between ICT‐related Teaching Self‐Efficacy (TSE) and post‐training self‐efficacy to transfer (SET), implying that the teachers' perceived self‐efficacy to transfer was considerably higher than their overall perceived ICT‐related teaching self‐efficacy.</p> <p>The results from the Mann–Whitney test show significant gender differences (<emph>p</emph> < .05) in the construct of SET, revealing the interesting point that women expressed significantly higher levels of SET. No gender differences (<emph>p</emph> > .05) were detected in ICT‐related Teaching Self‐Efficacy for the current sample. Similarly, as depicted in Table 5, the gender‐grouped Mann–Whitney test revealed significant differences (<emph>p</emph> < .05) in the constructs of Content and Resources, Support, Training Usefulness, and Intention to Transfer, where women expressed significantly higher values than men. It is worth to mention that no gender differences were detected in participant experience in ICT teaching, hence we can conclude that there are no gender differences in the ICT‐related individual characteristics of teaching experience and self‐efficacy.</p> <p>5 TABLE Gender‐grouped differences</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">ML</th><th align="left">TSE</th><th align="left">PEOU</th><th align="left">CR</th><th align="left">SP</th><th align="left">TU</th><th align="left">SET</th><th align="left">MT</th><th align="left">IT</th></tr></thead><tbody valign="top"><tr><td>Mann–Whitney U</td><td>1316.500</td><td>1649.000</td><td>1363.500</td><td>1210.000</td><td>1262.500</td><td>1171.500</td><td>1120.500</td><td>1486.500</td><td>1343.000</td></tr><tr><td>Wilcoxon W</td><td>2591.500</td><td>2924.000</td><td>2638.500</td><td>2485.000</td><td>2537.500</td><td>2446.500</td><td>2395.500</td><td>2761.500</td><td>2618.000</td></tr><tr><td>Z</td><td>−2.031</td><td>−.148</td><td>−1.887</td><td>−2.629</td><td>−2.533</td><td>−2.992</td><td>−3.307</td><td>−1.140</td><td>−2.026</td></tr><tr><td>Asymp.Sig. (2‐tailed)</td><td>.061</td><td>.882</td><td>.059</td><td>.009<xref ref-type="fn" rid="tfn7" /></td><td>.011</td><td>.003<xref ref-type="fn" rid="tfn7" /></td><td>.001<xref ref-type="fn" rid="tfn7" /></td><td>.254</td><td>.043<xref ref-type="fn" rid="tfn7" /></td></tr></tbody></table> </ephtml> </p> <ulist> <item>6 <emph>Source</emph>: Authors.</item> <item>7 * Significance at level <emph>p</emph> = .05, <emph>N</emph> = 117.</item> </ulist> <p>The above finding is in accordance with previous research in Human‐Computer Interaction (HCI) and gender, indicating that men and women end‐users tend to express different perceptions, behaviour, and attitudes on computer use (Burnett et al., [<reflink idref="bib14" id="ref86">14</reflink>]; Grigoreanu et al., [<reflink idref="bib22" id="ref87">22</reflink>]; Terzis & Economides, [<reflink idref="bib59" id="ref88">59</reflink>]; Tzafilkou et al., [<reflink idref="bib65" id="ref89">65</reflink>]). However, studies on the transfer of teacher training demonstrate differences only in the pre‐training computer skills and access (Tondeur et al., [<reflink idref="bib60" id="ref90">60</reflink>]).</p> <hd id="AN0162103987-27">Structural model</hd> <p>The TeTra‐ICT structural model was evaluated based on the path coefficients and the <emph>R</emph><sups>2</sups> value, where path coefficients were greater than 0.1 with <emph>t</emph>‐values greater than 1.96 at a significance level of.05. Table 6 presents the <emph>t</emph>‐values and <emph>p</emph>‐values that were extracted through the bootstrapping procedure as well as the descendent constructs' <emph>R</emph><sups>2</sups> values.</p> <p>6 TABLE PLS results in variance and relationships</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left" /><th align="left">Mean</th><th align="left">St. dev</th><th align="left"><italic>R</italic><sup>2</sup></th><th align="left"><italic>t</italic>‐Value</th><th align="left"><italic>p</italic>‐Value</th><th align="left" /></tr></thead><tbody valign="top"><tr><td /><td>ML</td><td /><td /><td>0.06</td><td /><td /><td /></tr><tr><td /><td>TU</td><td /><td /><td>0.72</td><td /><td /><td /></tr><tr><td /><td>SET</td><td /><td /><td>0.45</td><td /><td /><td /></tr><tr><td /><td>MT</td><td /><td /><td>0.60</td><td /><td /><td /></tr><tr><td /><td>IT</td><td /><td /><td>0.86</td><td /><td /><td /></tr><tr><td>H1</td><td>MT➔IT</td><td>0.716</td><td>0.051</td><td /><td>14.090</td><td>0.000</td><td>Support</td></tr><tr><td>H2a</td><td>ML➔MT</td><td>0.224</td><td>0.085</td><td /><td>2.502</td><td>0.013</td><td>Support</td></tr><tr><td>H2b</td><td>ML➔SET</td><td>0.295</td><td>0.117</td><td /><td>2.485</td><td>0.013</td><td>Support</td></tr><tr><td>H3a</td><td>SET➔MT</td><td>0.615</td><td>0.087</td><td /><td>7.177</td><td>0.000</td><td>Support</td></tr><tr><td>H3b</td><td>SET➔IT</td><td>0.085</td><td>0.059</td><td /><td>1.353</td><td>0.177</td><td>Not support</td></tr><tr><td>H4a</td><td>TU➔SET</td><td>0.500</td><td>0.098</td><td /><td>5.242</td><td>0.000</td><td>Support</td></tr><tr><td>H4b</td><td>TU➔IT</td><td>0.208</td><td>0.055</td><td /><td>3.701</td><td>0.000</td><td>Support</td></tr><tr><td>H5</td><td>SP➔TU</td><td>0.360</td><td>0.074</td><td /><td>4.910</td><td>0.000</td><td>Support</td></tr><tr><td>H6</td><td>CR➔TU</td><td>0.517</td><td>0.079</td><td /><td>6.610</td><td>0.000</td><td>Support</td></tr><tr><td>H7</td><td>PEOU➔TU</td><td>0.060</td><td>0.064</td><td /><td>0.872</td><td>0.384</td><td>Not support</td></tr><tr><td>H8a</td><td>ICT Teach. Experience➔ML</td><td>−0.171</td><td>0.105</td><td /><td>1.744</td><td>0.082</td><td>Not support</td></tr><tr><td>H8b</td><td>ICT Teach. Experience➔TU</td><td>−0.058</td><td>0.049</td><td /><td>1.193</td><td>0.233</td><td>Not support</td></tr><tr><td>H9a</td><td>TSE➔ML</td><td>−0.183</td><td>0.091</td><td /><td>2.061</td><td>0.040</td><td>Support</td></tr><tr><td>H9b</td><td>TSE➔TU</td><td>0.129</td><td>0.063</td><td /><td>2.138</td><td>0.033</td><td>Support</td></tr><tr><td>H10a</td><td>Gender➔ML</td><td>0.062</td><td>0.105</td><td /><td>0.404</td><td>0.687</td><td>Not support</td></tr><tr><td>H10b</td><td>Gender ➔TU</td><td>−0.006</td><td>0.051</td><td /><td>0.141</td><td>0.888</td><td>Not support</td></tr></tbody></table> </ephtml> </p> <p>8 <emph>Source</emph>: Authors.</p> <p>As presented in Table 5, the results of the structural model highlighted the confirmation of ten hypotheses and the rejection of six hypotheses. As depicted, the examined constructs explain 86% of the variance of the teachers' intention to transfer their ICT knowledge and skills, 72% of their perception of the usefulness of the training programme, 60% of motivation to learn, 45% of self‐efficacy to transfer and 6% of motivation to learn.</p> <p>Table 6 reveals that the intention to transfer was significantly affected by the motivation to transfer and the mediator variable of how useful the training was perceived to be. Moreover, although self‐efficacy to transfer was affected by both the motivation to learn and training usefulness directly, it affected solely motivation to transfer (not intention). According to the results, the TeTra‐ICT model highlights that self‐efficacy to transfer is indirectly affected by both individual and training design characteristics, and it has indirect, yet significant effects on intention to transfer ICT knowledge. There are significant indirect effects also between intention and motivation to transfer, content, support and perceived usefulness.</p> <hd id="AN0162103987-28">Training programme characteristics</hd> <p>A second research finding is that programme design characteristics, including support, content, and resources, exerted significant effect on training usefulness, as assumed. Interestingly, the TeTra‐ICT model explains 72% of the teachers' perceived training usefulness, revealing the significant effects of individual and programme related ICT characteristics. The training programme was efficiently designed in terms of material and infrastructure, as shown by positive programme outcomes. This finding is important since it integrates training usefulness as a mediator variable between programme design characteristics and transfer related variables, contrary to previous studies that tend to examine the direct effects of training design features and support on motivation to transfer or actual transfer of training (e.g., Lee et al., [<reflink idref="bib35" id="ref91">35</reflink>]; Mansour et al., [<reflink idref="bib40" id="ref92">40</reflink>]; Tonhäuser & Büker, [<reflink idref="bib61" id="ref93">61</reflink>]). This result overall reveals the crucial role of the programme design characteristics on the successfulness of the programme and the efficient transfer of training.</p> <p>Interestingly, the platform's ease of use did not reveal any significant effect on teacher perceptions of the usefulness of training. A plausible explanation is that perceived usefulness of training concerns the usefulness of training in general, and is not limited to technical characteristics; whereas the perceptions of ease of use and usefulness are mainly linked together in research addressing the acceptance of technology (Lee, [<reflink idref="bib36" id="ref94">36</reflink>]; Ong & Lai, [<reflink idref="bib47" id="ref95">47</reflink>]; Terzis & Economides, [<reflink idref="bib59" id="ref96">59</reflink>]; Tzafilkou et al., [<reflink idref="bib65" id="ref97">65</reflink>]). Therefore, this study reveals that the perceived ease of use of the learning platform did not bring any significant effect on the perceived usefulness of the training programme, and hence it did not affect any transfer related variables like motivation or intention to transfer ICT knowledge.</p> <hd id="AN0162103987-29">Individual characteristics</hd> <p>A third important finding concerns the relationship between individual characteristics and the mediator variables of motivation to learn and training usefulness. Particularly, ICT‐related teaching self‐efficacy positively affected both the motivation to learn and the perceived usefulness of training. This finding confirms several previous findings correlating ICT domain‐ self‐efficacy with teacher and student perceptions and motivations (e.g., Moreira‐Fontán et al., [<reflink idref="bib41" id="ref98">41</reflink>]; Scherer & Siddiq, [<reflink idref="bib52" id="ref99">52</reflink>]). This result proved that ICT teaching self‐efficacy prior to training is a vital factor for subjects' intention and motivation to transfer ICT knowledge, since it directly affects the mediator determinant of motivation to learn.</p> <p>Contrary to previous research results showing that teaching experience can significantly affect transfer of training (e.g., Wong & Li, [<reflink idref="bib70" id="ref100">70</reflink>]), this research demonstrates that ICT‐related teaching experience does not play an important role for the teachers' post‐training motivation or intention to transfer ICT knowledge. In the proposed model, ICT‐related teaching experience did not exert any significant effect on the mediator variables of training usefulness and motivation to learn. One possible reason for this may be that all trainees had an extensive ICT‐related teaching experience. Another possible reason is the duration of the programme (380 h) and the group‐based teaching methodology (the teachers were trained in groups of ten) which possibly supported effective training for most of the participants and their perception of ICT‐self‐efficacy by the end of the programme. Similarly, gender did not have a significant effect on the mediator variables of motivation to learn, and perceived usefulness, as expected.</p> <hd id="AN0162103987-30">Practical implications</hd> <p>Teacher educators and ICT skills transfer training institutions may consider the findings of this study in their ICT knowledge transfer training programme design strategies. As this research showed, features of the training programme and teacher trainees' individual characteristics should be taken into serious consideration in the design of knowledge transfer training programmes. Teacher educators may perform continuous research during all the stages of the ICT transfer training programme process to identify programme participants' ICT experience, perceptions of their ICT‐related teaching self‐efficacy, the efficiency of programme resources, the support they receive from teacher educators and colleagues, on how easy the learning platform is to use, and how useful the training programme is. More specifically, there are practical implications for the following three areas:</p> <p></p> <ulist> <item> <emph>The design of ICT knowledge transfer training programme pedagogical approaches</emph> : ICT knowledge transfer training instructors (teacher educators), transfer training programme managers and institutions should consider the factors of the proposed model for the adaptation of appropriate pedagogical approaches. Such approaches can be found in other studies (e.g., Angeli & Valanides, [<reflink idref="bib4" id="ref101">4</reflink>]) which determine how to effectively embed ICT training principles throughout a teacher education programme.</item> <p></p> <item> <emph>The design of ICT expertise and self‐efficacy improvement strategies</emph> : By showing the important role of individual teacher characteristics such as ICT‐related teaching self‐efficacy and ICT experience, this model confirms the necessity for institutions and transfer training programme managers to build on teachers' ICT experience levels and perceived self‐efficacy to positively affect their motivation and intention to transfer ICT training. To support this, pre‐training workshops could be organised to reinforce the ICT knowledge and skills of less experienced teachers on ICT concepts and practices.</item> <p></p> <item> <emph>For research on teacher perceptions of the usefulness of the training programme</emph> : Since perceived usefulness of the training programme seems to be an important mediator construct between individual programme design characteristics and teachers' intention to transfer ICT knowledge and skills, achieving high levels of perceived usefulness is important for the efficiency of the transfer training programme. To this end, teacher educators, education institutions, and transfer training institutions should continue with research on participant perceptions of the usefulness of training, and design flexible methodologies for programme adaptation. Moreover, it is important that teacher educators provide efficient content resources, user friendly learning system interfaces, and continuous support to ensure high levels of perceived usefulness of the training programme and the successful integration of ICT in teaching practices (Teo et al., [<reflink idref="bib58" id="ref102">58</reflink>] ; Tondeur et al., [<reflink idref="bib60" id="ref103">60</reflink>] ; Vongkulluksn et al., [<reflink idref="bib68" id="ref104">68</reflink>]).</item> </ulist> <p>Finally, apart from the relationships of the proposed TeTra‐ICT model, this research also introduces an ICT‐centred training transfer questionnaire that meets all the main requirements suggested in the relevant literature on validity and reliability. The measurement model can also be used for supporting similar research efforts on ICT training transfer.</p> <hd id="AN0162103987-31">Possible issues and limitations</hd> <p>Since this research is the first to design a domain specific (ICT‐related) transfer training model, there are some limitations. A possible limitation is the low response rate, only 117 out of the 300 trainees took part in the survey. Another concern is the generalisability issue. The current field test was conducted on a teacher trainer population with similar ICT background levels and teaching experiences; this limits the extent to which the findings can be generalised. Also, the fact that many of the participants (e.g., 22% out of 117 participants) taught the same subject may have skewed the results. Furthermore, as explained in Siwatu ([<reflink idref="bib55" id="ref105">55</reflink>]), self‐efficacy in teaching may be affected by cultural factors. Also, this study did not incorporate ICT profile in the examined ICT‐related individual variables since there were no significant differences, most of the trainees reported average or above average ICT expertise level. Moreover, since there are no gender differences in the ICT‐related individual characteristics of teaching experience and self‐efficacy, our results may not be generalisable to different populations of teachers with various ICT backgrounds or gender‐based differences in their individual characteristics.</p> <hd id="AN0162103987-32">CONCLUSIONS</hd> <p>As ICT integration in education remarkably increases teacher effectiveness and student engagement in the classroom, teaching and transferring ICT skills represent a global trend in the field of teacher training. However, measuring teacher effectiveness and teacher intention to transfer new ICT knowledge and skills is limited mainly because of a lack of scholarship on ICT‐training transfer models.</p> <p>To remedy this deficiency, we propose an ICT‐training transfer model for integrating digital technologies in classroom instruction. The proposed model examines the effects of individual and programme design characteristics on teacher motivation and intention to transfer ICT knowledge and skills. The model integrates a set of mediator variables including motivation to learn, perceived usefulness of training and self‐efficacy to transfer. The research was conducted with the participation of 117 teacher trainers who participated in a national teacher training programme for supporting the use and application of ICT in education in Greece.</p> <p>The findings reveal the usefulness of the suggested model and confirm several hypothesised relationships among the examined variables. To conclude, this study provides evidence regarding the effect of ICT‐related individual factors and training programme characteristics on teacher training transfer variables, focusing on their final impact on the teachers' intention to transfer ICT knowledge and skills.</p> <p>Despite the contributions of this study, the exploratory character of the survey features limitations mainly concerning the enclosed variables and the sample characteristics. Future research is encouraged to examine the role of more variables integrated in the model, as well as to compare the suggested model findings across different populations.</p> <p>To conclude, four key points made in this article are:</p> <p></p> <ulist> <item> The introduction of a new model for teacher transfer of ICT training (TeTra‐ICT).</item> <p></p> <item> The combined use of individual and training programme ICT‐related characteristics in the model.</item> <p></p> <item> We demonstrate the effects of the integrated characteristics on teacher motivation and intention to integrate ICT knowledge and skills in teaching‐learning practices.</item> <p></p> <item> We show that TeTra‐ICT explains 86% of the variance in <emph>teacher intention to transfer new ICT knowledge and skills</emph> , and 72% of the variance in the perception of the usefulness of training.</item> </ulist> <hd id="AN0162103987-33">ACKNOWLEDGEMENTS</hd> <p>We thank the reviewers for their valuable comments.</p> <hd id="AN0162103987-34">DATA AVAILABILITY STATEMENT</hd> <p>The data that support the findings of this study are available from the corresponding author upon reasonable request.</p> <ref id="AN0162103987-35"> <title> REFERENCES </title> <blist> <bibl id="bib1" idref="ref31" type="bt">1</bibl> <bibtext> Ajzen, I. 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Header DbId: eric
DbLabel: ERIC
An: EJ1368279
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Teacher Intention to Transfer ICT Training When Integrating Digital Technologies in Education: The Teacher Transfer of ICT Training Model (TeTra-ICT)
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Perifanou%2C+Maria+A%2E%22">Perifanou, Maria A.</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9874-8417">0000-0002-9874-8417</externalLink>)<br /><searchLink fieldCode="AR" term="%22Tzafilkou%2C+Katerina%22">Tzafilkou, Katerina</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4092-6492">0000-0003-4092-6492</externalLink>)<br /><searchLink fieldCode="AR" term="%22Economides%2C+Anastasios+A%2E%22">Economides, Anastasios A.</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8056-1024">0000-0001-8056-1024</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22European+Journal+of+Education%22"><i>European Journal of Education</i></searchLink>. Mar 2023 58(1):111-129.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 19
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2023
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Elementary+Education%22">Elementary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Secondary+Education%22">Secondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Elementary+School+Teachers%22">Elementary School Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Secondary+School+Teachers%22">Secondary School Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Intention%22">Intention</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Integration%22">Technology Integration</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Technology%22">Information Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Practices%22">Educational Practices</searchLink><br /><searchLink fieldCode="DE" term="%22Training%22">Training</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Design%22">Program Design</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Evaluation%22">Program Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Education%22">Teacher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Efficacy%22">Self Efficacy</searchLink><br /><searchLink fieldCode="DE" term="%22Usability%22">Usability</searchLink><br /><searchLink fieldCode="DE" term="%22Transfer+of+Training%22">Transfer of Training</searchLink><br /><searchLink fieldCode="DE" term="%22Motivation%22">Motivation</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Greece%22">Greece</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/ejed.12534
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0141-8211<br />1465-3435
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The aim of this study is to propose a new structural model for how teachers transfer their ICT training (TeTra-ICT), shedding light on the factors that tend to affect their intention to integrate digital technologies in educational practices as well as train their colleagues. The proposed model exploits training programme design characteristics and ICT-related individual factors. A total of 117 new ICT instructors for primary and secondary education teachers in Greece were evaluated. The instructors participated in a national Teacher Training Programme on applying ICT in education. Results indicate significant effects of individual (ICT-related self-efficacy in teaching) and programme design characteristics (platform's ease of use, support, content, and resources) on the teachers' final motivation and intention to transfer their ICT knowledge and skills. The model also reveals significant correlations between individual and training characteristics, the teachers' post-training self-efficacy for transferring skills and their perception of the usefulness of the training programme. The examined constructs explain 86% of the variance in teacher intentions to transfer their ICT knowledge and skills, and 72% of their perception of the usefulness of the training programme. Interestingly, while there were no gender differences in individual ICT-related characteristics, women expressed significantly higher values than men in their perception of the usefulness of training, self-efficacy, motivation, and intention to transfer.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2023
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1368279
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1368279
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/ejed.12534
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 111
    Subjects:
      – SubjectFull: Elementary School Teachers
        Type: general
      – SubjectFull: Secondary School Teachers
        Type: general
      – SubjectFull: Intention
        Type: general
      – SubjectFull: Technology Integration
        Type: general
      – SubjectFull: Information Technology
        Type: general
      – SubjectFull: Educational Technology
        Type: general
      – SubjectFull: Educational Practices
        Type: general
      – SubjectFull: Training
        Type: general
      – SubjectFull: Program Design
        Type: general
      – SubjectFull: Program Evaluation
        Type: general
      – SubjectFull: Teacher Education
        Type: general
      – SubjectFull: Self Efficacy
        Type: general
      – SubjectFull: Usability
        Type: general
      – SubjectFull: Transfer of Training
        Type: general
      – SubjectFull: Motivation
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Greece
        Type: general
    Titles:
      – TitleFull: Teacher Intention to Transfer ICT Training When Integrating Digital Technologies in Education: The Teacher Transfer of ICT Training Model (TeTra-ICT)
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Perifanou, Maria A.
      – PersonEntity:
          Name:
            NameFull: Tzafilkou, Katerina
      – PersonEntity:
          Name:
            NameFull: Economides, Anastasios A.
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          Dates:
            – D: 01
              M: 03
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 0141-8211
            – Type: issn-electronic
              Value: 1465-3435
          Numbering:
            – Type: volume
              Value: 58
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: European Journal of Education
              Type: main
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