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Teachers’ trainers’ intention and motivation to transfer ICT training: The role of ICT individual factors, gender, and ICT self-efficacy

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Abstract

Important variables related to transfer information & communication technologies (ICT) training include the individual’s perceived motivation to learn, motivation to transfer, and intention to transfer the ICT training. Most previous studies investigate the transfer of ICT training and its application in the daily teaching practice by ordinary teachers, usually neglecting the important population of the teachers’ trainers. These teachers’ trainers receive advanced ICT training before start training their colleagues. Therefore, the main purpose of this study is to investigate the teachers’ trainers’ transfer of ICT training analyzing the structural relationships of their afore-mentioned variables with their gender, ICT self-efficacy, and a set of ICT individual factors. The study employed structural equation modeling using data collected from 117 teachers’ trainers in primary and secondary education who participated in a national ICT Transfer Training Programme for teachers’ trainers in Greece. The results reveal strong associations between ICT-related self-efficacy and transfer training measures. Both gender and ICT factors cause significant differences in the levels of their ICT self-efficacy measures. ICT expertise and gender highlight significant relationship paths in the model, while gender seems to play a moderating role as well.

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  1. See http://e-epimorfosi.cti.gr/en

References

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behaviour and Human Decision Processes, 5(2), 179–211.

  • Al-Swidi, A., & Al Yahya, M. (2017). Training transfer intention and training effectiveness: Assessing the gender differences using multi-group structural equation modelling approach. International Journal of Organizational Analysis, 25(5), 839–860

    Article  Google Scholar 

  • Alt, D. (2018). Science teachers’ conceptions of teaching and learning, ICT efficacy, ICT professional development and ICT practices enacted in their classrooms. Teaching and Teacher Education, 73, 141–150.

  • Appova, A., & Arbaugh, F. (2018). Teachers’ motivation to learn: Implications for supporting professional growth. Professional Development in Education, 44(1), 5–21

    Article  Google Scholar 

  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94

    Article  Google Scholar 

  • Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.

    Google Scholar 

  • Bell, B. S., & Ford, J. K. (2007). Reactions to skill assessment: The forgotten factor in explaining motivation to learn. Human Resource Development Quarterly, 18(1), 33–62.

  • Binkhorst, F., Handelzalts, A., Poortman, C. L., & van Joolingen, W. R. (2015). Understanding teacher design teams—a mixed methods approach to developing a descriptive framework. Teaching and Teacher Education, 51, 213–224

    Article  Google Scholar 

  • Blume, B. D., Ford, J. K., Baldwin, T. T., & Huang, J. L. (2010). Transfer of training: A meta-analytic review. Journal of Management, 36, 1065–1105

    Article  Google Scholar 

  • Buhasho, E., Wausi, A., & Njihia, J. (2021). Moderating effect of organizational capability on the relationship between business intelligence capability and performance among public listed firms in Kenya. European Scientific Journal ESJ, 17(1), 335–352. https://doi.org/10.19044/esj.2021.v17n1p335

    Article  Google Scholar 

  • Burić, I., & Kim, L. E. (2020). Teacher self-efficacy, instructional quality, and student motivational beliefs: An analysis using multilevel structural equation modeling. Learning and Instruction, 66, 101302. https://doi.org/10.1016/j.learninstruc.2019.101302.

  • Burke, L. A., & Hutchins, H. M. (2007). Training transfer: An integrative literature review. Human Resource Development Review, 6, 263–296

    Article  Google Scholar 

  • Burnett, M., Stumpf, S., Macbeth, J., Makri, S., Beckwith, L., Kwan, I., Peters, A., & Jernigan, W. (2016). GenderMag: A method for evaluating software’s gender inclusiveness. Interacting with Computers, 28(6), 760–787

    Article  Google Scholar 

  • Carlson, D. S., Bozeman, D. P., Kacmar, M. K., Wright, P. M., & McMahan, G. C. (2000). Training motivation in organizations: An analysis of individual-level antecedents. Journal of Managerial Issues, 12, 271–287

    Google Scholar 

  • Chiaburu, D. S., & Lindsay, D. R. (2008). Can do or will do? The importance of self-efficacy and instrumentality for training transfer. Human Resource Development International, 11(2), 199–206

    Article  Google Scholar 

  • Chin, W. W. (2010). How to write up and report PLS snalyses. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of Partial Least Squares: Concepts Methods and Applications. (pp. 655–690). Springer.

    Chapter  Google Scholar 

  • Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In R. H. Hoyle (Ed.), Statistical strategies for small sample research (pp. 307–341). Thousand Oaks: CA: Sage Publications.

  • Chin, W. W., Marcolin, B. L., & Newsted, P. N. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189–217

    Article  Google Scholar 

  • Chin, W.W., Marcolin, B.L. & Newsted, P.R. (1996). A partial least squares latent variable modeling approach for measuring interaction effects. Results from a Monte Carlo simulation study and voice mail emotion/adoption study. In J.I., DeGross, S., Jarvenpaa, & A., Srinivasan (Eds), Proceedings of the Seventeenth International Conference on Information Systems (pp. 21-41). Association for Information Systems.

  • Cin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern business research methods. (pp. 295–336). Lawrence Erlbaum Associates.

    Google Scholar 

  • Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309–319

    Article  Google Scholar 

  • EC (2019). Online: https://ec.europa.eu/digital-single-market/en/women-ict. Online Accessed 18/2/2019.

  • Facteau, J. D., Dobbins, G. H., Russell, J. E. A., Ladd, R. T., & Kudisch, J. D. (1995). The influence of general perceptions of the training environment on pretraining motivation and perceived transfer of training. Journal of Management, 21, 1–25

    Article  Google Scholar 

  • Farrell, A. M. (2010). Insufficient discriminant validity: A comment on Bove, Pervan, Beatty, and Shiu (2009). Journal of Business Research, 63(3), 324–327. https://doi.org/10.1016/j.jbusres.2009.05.003

    Article  Google Scholar 

  • Fassott, G., Henseler, J., & Coelho, P. (2016). Testing moderating effects in PLS path models with composite variables. Industrial Management & Data Systems, 116(9), 1887–1900

    Article  Google Scholar 

  • Field, A. (2000). 3: Nonparametric tests part 3. Research Methods I: SPSS for Windows, 1–6.

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50

    Article  Google Scholar 

  • Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems. https://doi.org/10.17705/1cais.00407.

  • Gegenfurtner, A., Festner, D., Gallenberger, W., Lehtinen, E., & Gruber, H. (2009). Predicting autonomous and controlled motivation to transfer training. International Journal of Training and Development, 13, 124–138

    Article  Google Scholar 

  • Gibson, S. K. (2004a). Social learning (cognitive) theory and implications for Human Resource Development. Advances in Developing Human Resources, 6, 193–210

    Article  Google Scholar 

  • Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214

    Article  Google Scholar 

  • Grigoreanu, V., Cao, J., Kulesza, T., Bogart, C., Rector, K., Burnett, M., & Wiedenbeck, S. (2008) Can feature design reduce the gender gap in end-user software development environments? In: Proc. Symposium on Visual Languages and Human-Centric Computing (pp. 149–156). IEEE.

  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2006). Multivariant data analysis. Pearson International Edition.

    Google Scholar 

  • Hair, J. F., Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLSSEM). Sage Publications.

    MATH  Google Scholar 

  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139–152

    Article  Google Scholar 

  • Harrison, D. A., McLaughlin, M. E., & Coalter, T. M. (1996). Context, cognition, and common method variance: Psychometric and verbal protocol evidence. Organizational Behavior and Human Decision Processes, 68, 246–261

    Article  Google Scholar 

  • Hasan, B. (2003). The influence of specific computer experiences on computer self-efficacy beliefs. Computers in Human Behavior, 19(4), 443–450

    Article  Google Scholar 

  • Hatlevik, I., & Hatlevik, O. E. (2018). Examining the relationship between teachers’ ict self-efficacy for educational purposes, collegial collaboration, lack of facilitation and the use of ICT in teaching practice. Frontiers in Psychology, 9, 935

    Article  Google Scholar 

  • Henseler, J., Ringle, C.M. & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135.

  • Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20, 195–204

    Article  Google Scholar 

  • Instefjord, E. J., & Munthe, E. (2017). Educating digitally competent teachers: A study of integration of professional digital competence in teacher education. Teaching and Teacher Education, 67, 37–45

    Article  Google Scholar 

  • Judge, T. A., & Bono, J. E. (2001). Relationship of core self-evaluations traits – self-esteem, generalized self-efficacy, locus of control, and emotional stability–with job satisfaction and job performance: A meta-analysis. Journal of Applied Psychology, 86, 80–92.

  • Kassis, W., Graf, U., Keller, R., Ding, K., & Rohlfs, C. (2019). The role of received social support and self-efficacy for the satisfaction of basic psychological needs in teacher education. European Journal of Teacher Education, 42(3), 391–409

    Article  Google Scholar 

  • Kay, R. H. (2006). Evaluating strategies used to incorporate technology into preservice education: A review of the literature. Journal of Research on Technology in Education, 38(4), 383–408

    Article  Google Scholar 

  • Kenny, D. A., & Judd, C. M. (1984). Estimating the nonlinear and interactive effects of latent variables. Psychological Bulletin, 96(1), 201–210

    Article  Google Scholar 

  • Keshavarz, S., & Baharudin, R. (2012). The moderating role of gender on the relationships between perceived paternal parenting style, locus of control and self-efficacy. Procedia - Social and Behavioral Sciences, 32, 63–68

    Article  Google Scholar 

  • Kim, S. W., & Kim, J. H. (2003). An exploratory study for development of learning transfer model in corporate training. Korean Journal of Corporate Education, 5, 83–105.

  • Kline, R. B. (2011). Principles and practice of structural equation modeling. Guilford Press.

    MATH  Google Scholar 

  • Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227–261

    Article  Google Scholar 

  • Kontoghiorghes, C. (2002). Predicting motivation to learn and motivation to transfer learning back to the job in a service organization: A new systemic model for training effectiveness. Performance Improvement Quarterly, 15, 114–129

    Article  Google Scholar 

  • Lauermann, F., & König, J. (2016). Teachers’ professional competence and wellbeing: Understanding the links between general pedagogical knowledge, self-efficacy and burnout. Learning and Instruction, 45, 9–19

    Article  Google Scholar 

  • Lee, C., Lee, H., Lee, J., & Park, J. (2014). A multiple group analysis of the training transfer model: Exploring the differences between high and low performers in a Korean insurance company. The International Journal of Human Resource Management, 25(20), 2837–2857

    Article  Google Scholar 

  • Liebermann, S., & Hoffmann, S. (2008). The impact of practical relevance on training transfer: Evidence from a service quality training program for German bank clerks. International Journal of Training and Development, 12, 74–76.

  • Lipowsky, F. (2010). LernenimBeruf: EmpirischeBefundezurWirksamkeit von Lehrerfortbildung [Workplace learning. Empirical findings regarding the effectiveness of teacher trainings]. In F. H. Müller (Ed.), Lehrerinnen und Lehrer lernen. Konzepte und BefundezurLehrerfortbildung. Waxmann.

  • Ma, F., Bai, Y., Bai, Y. et al. (2018). Factors influencing training transfer in nursing profession: A qualitative study. BMC Medical Education, 18, 44.

  • McMillan, D. J., McConnell, B., & O’Sullivan, H. (2016). Continuing professional development – why bother? Perceptions and motivations of teachers in Ireland. Professional Development in Education, 42(1), 150–167

    Article  Google Scholar 

  • Metaxa-Kakavouli, D., Wang, K., Landay, J.A., & Hancock, J. (2018). Gender-inclusive design: Sense of belonging and bias in web interfaces. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18). Association for Computing Machinery, New York, NY, USA, Paper 614, 1–6.

  • Moreira-Fontán, E., García-Señorán, M., Conde-Rodríguez, A., & González, A. (2019). Teachers’ ICT-related self-efficacy, job resources, and positive emotions: Their structural relations with autonomous motivation and work engagement. Computers & Education, 134, 63–77

    Article  Google Scholar 

  • Morris, D. B., Usher, E. L., & Chen, J. A. (2017). Reconceptualizing the sources of teaching self-efficacy: A critical review of emerging literature. Educational Psychology Review, 29(4), 795–833.

  • Mullins, M. E., Fisher, S. L., Howell, A. W., Schmitt, N., & Kozlowski, S. W. J. (1998). Motivational and contextual influences on training effectiveness: A field study. Training Research Journal, 4, 11–26

    Google Scholar 

  • Nistor, N., Gogus, A., & Lerche, T. (2013). Educational technology acceptance across national and professional cultures: A European study. Education Technology Research Development, 61, 33–749

    Article  Google Scholar 

  • Noe, R. A. (1986). Trainees’ attributes and attitudes: Neglected influences on training effective-ness. Academy of Management Review, 11, 736–749

    Article  Google Scholar 

  • Norris, C., Sullivan, T., Poirot, J., & Soloway, E. (2003). No access, no use, no impact: Snapshot surveys of educational technology in K-12. Journal of Research on Technology in Education, 36(1), 15–27. https://doi.org/10.1080/15391523.2003.10782400.

  • Ong, C., & Lai, J. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behaviour, 22(5), 816–829

    Article  Google Scholar 

  • Peng, D. X., & Lai, F. (2012). Using partial least squares in operations management research: A practical guideline and summary of past research. Journal of Operations Management, 30(6), 467–480

    Article  Google Scholar 

  • Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879–903

    Article  Google Scholar 

  • Pugh, K. J., & Bergin, D. A. (2006). Motivational influences on transfer. Educational Psychologist, 41, 147–160

    Article  Google Scholar 

  • Ringle, C. M., Da Silva, D., & Bido, D. D. S. (2014). Structural equation modeling with the smartpls. RevistaBrasileira de Marketing, 13(2), 56–73

    Google Scholar 

  • Ringle, C.M., Wende, S., & Becker, J-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS. Retrieved from http://www.smartpls.com. Accessed June 2020.

  • Rowold, J. (2007). Individual influences on knowledge acquisition in a call center training context in Germany. International Journal of Training and Development, 11(1), 21–34.

  • Sang, G., Tondeur, J., Chai, C. S., & Dong, Y. (2016). Validation and profile of Chinese pre-service teachers’ technological pedagogical content knowledge scale. Asia-Pacific Journal of Teacher Education, 44(1), 49–65.

  • Scherer, R., & Siddiq, F. (2015). Revisiting teachers’ self-efficacy: A differentiated view on gender differences. Computers & Education, 53, 48–57

    Google Scholar 

  • Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3–4), 591–611.

  • Simosi, M. (2012). The moderating role of self-efficacy in the organizational culture–training transfer relationship. International Journal of Training and Development, 16(2), 92–106

    Article  Google Scholar 

  • Swanson, R. A. (2001). Human resource development and its underlying theory. Human Resource Development International, 4, 299–312

    Article  Google Scholar 

  • Teo, T. (2014). Unpacking teachers’ acceptance of technology: Tests of measurement invariance and latent mean differences. Computers & Education, 75, 127–135

    Article  Google Scholar 

  • Teo, T. S. H., Srivastava, S. C., & Jiang, L. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99–132

    Article  Google Scholar 

  • Terzis, V., Moridis, C. N., Economides, A. A., & Rebolledo-Mendez, G. (2013). Computer based assessment acceptance: A cross-cultural study in Greece and Mexico. Educational Technology & Society, 16(3), 411–424

    Google Scholar 

  • Tondeur, J., Aesaert, K., Prestridge, S., & Consuegra, E. (2018). A multilevel analysis of what matters in the training of pre-service teacher’s ICT competencies. Computers & Education, 122, 32–42

    Article  Google Scholar 

  • Tondeur, J., Valcke, M., & van Braak, J. (2008). A multidimensional approach to determinants of computer use in primary education: Teacher and school characteristics. Journal of Computer Assisted Learning, 24, 494–506

    Article  Google Scholar 

  • Tziner, A., Fisher, M., Senior, T., & Weisberg, J. (2007). Effects of trainee characteristics on training effectiveness. International Journal of Selection and Assessment, 15, 167–174.

  • van Braak, J., Tondeur, J., & Valcke, M. (2004). Explaining different types of computer use among primary school teachers. European Journal of Psychology of Education, 19, 407–422

    Article  Google Scholar 

  • Velada, R., Caetano, A., Michel, J., Lyons, B., & Kavanagh, M. (2007). The effects of training design, individual, and work environment variables on transfer of training. International Journal of Training and Development, 11, 282–294.

  • Wong, E. M. L., & Li, S. C. (2008). Framing ICT implementation in a context of educational change: A multilevel analysis. School effectiveness and school improvement, 19(1), 99–120

    Article  Google Scholar 

  • Yelon, S., Sheppard, L., Sleight, D., & Ford, J. K. (2004). Intention to transfer: How do autonomous professionals become motivated to use new ideas? Performance Improvement Quarterly, 17, 82–103

    Article  Google Scholar 

  • Zhou, Z., Jin, X.-L., & Fang, Y. (2014). Moderating role of gender in the relationships between perceived benefits and satisfaction in social virtual world continuance. Decision Support Systems, 65, 69–79

    Article  Google Scholar 

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Authors and Affiliations

  1. SMILE Lab (Smile.Uom.Gr) &, Department of Economics, University of Macedonia, Egnatia 156, 54636, Thessaloniki, Greece

    Katerina Tzafilkou

  2. Thessaloniki, Greece

    Katerina Tzafilkou

  3. SMILE Lab (Smile.Uom.Gr), University of Macedonia, Thessaloniki, Greece

    Maria A. Perifanou

  4. SMILE Lab (Smile.Uom.Gr), Information Systems IPPS, University of Macedonia, Thessaloniki, Greece

    Anastasios A. Economides

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  1. Katerina Tzafilkou
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  3. Anastasios A. Economides
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Appendix A

Appendix A

Table 12 Questionnaire items used
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Fig. 4
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Plot slop of the moderating effect of gender in the relationship ICT-ML ➔ ICT- IT

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Fig. 5
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Plot slop of the moderating effect of gender in the relationship ICT-MT ➔ ICT- IT

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Fig. 6
figure 6

Plot slop of the moderating effect of gender in the relationship ICT-SET ➔ ICT-IT

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Tzafilkou, K., Perifanou, M.A. & Economides, A.A. Teachers’ trainers’ intention and motivation to transfer ICT training: The role of ICT individual factors, gender, and ICT self-efficacy. Educ Inf Technol 26, 5563–5589 (2021). https://doi.org/10.1007/s10639-021-10541-z

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