Research Article

A pilot study on individual and contextual factors influencing teachers’ digitalisation process

Stefania Cataudella 1 , Maria Lidia Mascia 2 * , Mirian Agus 1 , Dirk Ifenthaler 3 4 , Łukasz Tomczyk 5 , Maria Pietronilla Penna 1
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1 Department of Pedagogy, Psychology, Philosophy, University of Cagliari, Cagliari, ITALY2 Department of History, Human Sciences and Education, University of Sassari, Sassari, ITALY3 Economic and Business Education, University of Mannheim, Mannheim, GERMANY4 UNESCO Co-Chair on Data Science in Higher Education Learning and Teaching, Curtin University, Perth, AUSTRALIA5 Institute of Education, Jagiellonian University, Kraków, POLAND* Corresponding Author
Contemporary Educational Technology, 16(4), October 2024, ep532, https://doi.org/10.30935/cedtech/15189
Published Online: 23 September 2024, Published: 01 October 2024
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ABSTRACT

The process of school digitalisation has been on the rise in recent years, but the relationship between technology and teachers has had a strong acceleration during the global pandemic due to the coronavirus disease 2019. 198 teachers from primary to high school fill a questionnaire about demographic variables (age, gender, education level, school level in which they teach and years of seniority at work), perceptions of using some digital tools and specific platforms before and during the pandemic (after the first lockdown), self-esteem, self-efficacy, cognitive flexibility, and burnout perceptions. A non-parametric analysis was first conducted with the application of the Wilcoxon test for paired measures. Subsequently, a MANOVA was applied to verify any differences between teachers belonging to different school levels and having different levels of seniority. According to literature we found that self-efficacy, self-esteem, cognitive flexibility, burnout and service seniority are influential factors for teachers’ perceived digitalisation level.
Keywords: school digitalisation, teachers, self-esteem, self-efficacy, cognitive flexibility, burnout, seniority service

CITATION (APA)

Cataudella, S., Mascia, M. L., Agus, M., Ifenthaler, D., Tomczyk, Ł., & Penna, M. P. (2024). A pilot study on individual and contextual factors influencing teachers’ digitalisation process. Contemporary Educational Technology, 16(4), ep532. https://doi.org/10.30935/cedtech/15189

REFERENCES

  1. Adov, L., & Mäeots, M. (2021). What can we learn about science teachers’ technology use during the COVID-19 pandemic? Education Sciences, 11(6), Article 255. https://doi.org/10.3390/educsci11060255
  2. Assunção Flores, M., & Gago, M. (2020). Teacher education in times of COVID-19 pandemic in Portugal: National, institutional and pedagogical responses. Journal of Education for Teaching, 46(4), 507–516. https://doi.org/10.1080/02607476.2020.1799709
  3. Avidov-Ungar, O., & Magen-Nagar, N. (2014). Teachers in a changing world: Attitudes toward organizational change. Journal of Computers in Education, 1(4), 227-249. https://doi.org/10.1007/s40692-014-0014-x
  4. Ay, Y., Karadag, E., & Acat, M. B. (2016). ICT integration of Turkish teachers: An analysis within TPACK-practical model. International Journal of Progressive Education, 12(2), 149–165.
  5. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191
  6. Bandura, A. (1982). The assessment and predictive generality of self-percepts of efficacy. Journal of Behavior Therapy and Experimental Psychiatry, 13(3), 195–199. https://doi.org/10.1016/0005-7916(82)90004-0
  7. Bandura, A. (1998). Personal and collective efficacy in human adaptation and change. Advances in Psychological Science, 1(1), 51–71.
  8. Bao, W. (2020). COVID-19 and online teaching in higher education: A case study of Peking University. Human Behavior and Emerging Technologies, 2(2), 113–115. https://doi.org/10.1002/HBE2.191
  9. Barnes, G. V. (2000). Self-efficacy and teaching effectiveness. Journal of String Research, 1, 627–643. https://doi.org/10.1177/1948499200OS-100103
  10. Bergdahl, N., & Nouri, J. (2021). COVID-19 and crisis-prompted distance education in Sweden. Technology, Knowledge and Learning, 26(3), 443–459. https://doi.org/10.1007/s10758-020-09470-6
  11. Biasi, V., Domenici, G., Patrizi, N., & Capobianco, R. (2014). Teacher self-efficacy scale (Scala sull’auto-efficacia del Docente–SAED): adattamento e validazione in Italia [Adaptation and validation in Italy]. Journal of Educational, Cultural and Psychological Studies, 10, 485–509. https://doi.org/10.7358/ecps-2014-010-bias
  12. Brandenburg, R., McDonough, S., Burke, J., & White, S. (Eds.). (2016). Teacher education: Innovation, intervention and impact. Springer. https://doi.org/10.1007/978-981-10-0785-9
  13. Califf, C. B., & Brooks, S. (2020). An empirical study of techno-stressors, literacy facilitation, burnout, and turnover intention as experienced by K-12 teachers. Computers & Education, 157, Article 103971. https://doi.org/10.1016/j.compedu.2020.103971
  14. Cartwright, K. B. (2008). Cognitive flexibility and reading comprehension: Relevance to the future. In C. C. Block, & S. R. Parris (Eds.), Comprehension instruction: Research-based best practices (2nd ed., pp. 50–64). The Guilford Press.
  15. Cataudella, S., Carta, S. M., Mascia, M. L., Masala, C., Petretto, D. R., Agus, M., & Penna, M. P. (2021a). Teaching in times of the COVID-19 pandemic: A pilot study on teachers’ self-esteem and self-efficacy in an Italian sample. International Journal of Environmental Research and Public Health, 18(15), Article 8211. https://doi.org/10.3390/IJERPH18158211
  16. Cataudella, S., Carta, S. M., Mascia, M. L., Masala, C., Petretto, D. R., & Penna, M. P. (2021b). Psychological aspects of students with learning disabilities in e-environments: A mini review and future research directions, Frontiers in Psychology, 11, Article 611818. https://doi.org/10.3389/fpsyg.2020.611818
  17. Chandio, A. R. (2021). Evaluating ICT utilization in education administration and management during the COVID-19 outbreak in Pakistan: An empirical review. Journal of Research in Instructional, 1(2), 81–94. https://doi.org/10.30862/jri.v1i2.15
  18. Chesnut, S. R., & Burley, H. (2015). Self-efficacy as a predictor of commitment to the teaching profession: A meta-analysis. Educational Research Review, 15, 1–16. https://doi.org/10.1016/j.edurev.2015.02.001
  19. Chigona, A. (2018). Digital fluency: Necessary competence for teaching and learning in connected classrooms. The African Journal of Information Systems, 10(4), Article 7.
  20. Daniel, S. J. (2020). Education and the COVID-19 pandemic. Prospects, 49(1–2), 91–96. https://doi.org/10.1007/s11125-020-09464-3
  21. DeCoito, I., & Richardson, T. (2018). Teachers and technology: Present practice and future directions. Contemporary Issues in Technology and Teacher Education, 18(2), 362–378.
  22. Delcker, J., & Ifenthaler, D. (2021). Teachers’ perspective on school development at German vocational schools during the COVID-19 pandemic. Technology, Pedagogy and Education, 30(1), 125–139. https://doi.org/10.1080/1475939X.2020.1857826
  23. Dennis, J. P., & Vander Wal, J. S. (2010). The cognitive flexibility inventory: Instrument development and estimates of reliability and validity. Cognitive Therapy and Research, 34(3), 241–253. https://doi.org/10.1007/s10608-009-9276-4
  24. Dickson, M., McMinn, M., & Kadbey, H. (2019). Do years of teaching experience make a difference for teachers working in Abu Dhabi government schools? Cypriot Journal of Educational Science, 14(4), 471–481. https://doi.org/10.18844/cjes.v11i4.347
  25. Dietrich, N., Kentheswaran, K., Ahmadi, A., Teychene, J., Bessiere, Y., Alfenore, S., Laborie, S., Bastoul, D., Loubiere, K., Guigui, C., Sperandio, M., Barna, L., Paul, E., Cabassud, C., Line, A., & Hebrard, G. (2020). Attempts, successes, and failures of distance learning in the time of COVID-19. Journal of Chemical Education, 97(9), 2448–2457. https://doi.org/10.1021/acs.jchemed.0c00717
  26. Ertmer, P. A., & Simons, K. D. (2005). Scaffolding teachers’ efforts to implement problem-based learning. International Journal of Learning, 12(4), 319–328. https://doi.org/10.18848/1447-9494/CGP/v12i04/46447
  27. Fiorilli, C., De Stasio, S., Benevene, P., Fioredistella Iezzi, D., Pepe, A., & Albanese, O. (2015). Copenhagen burnout inventory (CBI): A validation study in an Italian teacher group. TPM: Testing, Psychometrics, Methodology in Applied Psychology, 22(4), 537–551. https://doi.org/10.4473/TPM22.4.7
  28. Fransson, G., Holmberg, J., Lindberg, O. J., & Olofsson, A. D. (2019). Digitalise and capitalise? Teachers’ self-understanding in 21st-century teaching contexts. Oxford Review of Education, 45(1), 102–118. https://doi.org/10.1080/03054985.2018.1500357
  29. Geraci, A., Di Domenico, L., Inguglia, C., & D’Amico, A. (2023). Teachers’ emotional intelligence, burnout, work engagement, and self-efficacy during COVID-19 lockdown. Behavioral Sciences, 13(4), Article 296. https://doi.org/10.3390/bs13040296
  30. Giritli Nygren, K., & Olofsson, A. (2020). Managing the COVID-19 pandemic through individual responsibility: The consequences of a world risk society and enhanced ethopolitics. Journal of Risk Research, 23(7–8), 1031–1035. https://doi.org/10.1080/13669877.2020.1756382
  31. Gómez-Domínguez, V., Navarro-Mateu, D., Prado-Gascó, V. J., & Gómez-Domínguez, T. (2022). How much do we care about teacher burnout during the pandemic: A bibliometric review. International Journal of Environmental Research and Public Health, 19(12), Article 7134. https://doi.org/10.3390/ijerph19127134
  32. Graham, L. J., White, S. L. J., Cologon, K., & Pianta, R. C. (2020). Do teachers’ years of experience make a difference in the quality of teaching? Teaching and Teacher Education, 96, 1–10. https://doi.org/10.1016/j.tate.2020.103190
  33. Gudmundsdottir, G. B., & Hatlevik, O. E. (2018). Newly qualified teachers’ professional digital competence: Implications for teacher education. European Journal of Teacher Education, 41(2), 214–231. https://doi.org/10.1080/02619768.2017.1416085
  34. Gunawan, G., Suranti, N. M. Y., & Fathoroni, F. (2020). Variations of models and learning platforms for prospective teachers during the COVID-19 pandemic period. Indonesian Journal of Teacher Education, 1(2), 61–70.
  35. Hampton, D., Culp-Roche, A., Hensley, A., Wilson, J., Otts, J. A., Thaxton-Wiggins, A., Frush, S., & Moser, D. K. (2020). Self-efficacy and satisfaction with teaching in online courses. Nurse Educator, 45(6), 302–306. https://doi.org/10.1097/NNE.0000000000000805
  36. Han, J., Yin, H., Wang, J., & Zhang, J. (2020). Job demands and resources as antecedents of university teachers’ exhaustion, engagement and job satisfaction. Educational Psychology, 40(3), 318–335. https://doi.org/10.1080/01443410.2019.1674249
  37. Hanife, E. A. (2018). The relationship between pre–service teachers’ cognitive flexibility and interpersonal problem solving skills. Eurasian Journal of Educational Research, 18(77), 105–128. https://doi.org/10.14689/ejer.2018.77.6
  38. Harrell, S., & Bynum, Y. (2018). Factors affecting technology integration in the classroom. Alabama Journal of Educational Leadership, 5, 12–18.
  39. Hatlevik, O. E. (2017). Examining the relationship between teachers’ self-efficacy, their digital competence, strategies to evaluate information, and use of ICT at school. Scandinavian Journal of Educational Research, 61(5), 555–567. https://doi.org/10.1080/00313831.2016.1172501
  40. Hechter, R., & Vermette, L. A. (2014). Tech-savvy science education? Understanding teacher pedagogical practices for integrating technology in K-12 classrooms. Journal of Computers in Mathematics and Science Teaching, 33(1), 27–47.
  41. Hsu, C. Y., Tsai, M. J., Chang, Y. H., & Liang, J. C. (2017). Surveying in-service teachers’ beliefs about game-based learning and perceptions of technological pedagogical and content knowledge of games. Journal of Educational Technology & Society, 20(1), 134–143.
  42. Huber, S. G., & Helm, C. (2020). COVID-19 and schooling: Evaluation, assessment and accountability in times of crises—reacting quickly to explore key issues for policy, practice and research with the school barometer. Educational Assessment, Evaluation and Accountability, 32(2), 237–270. https://doi.org/10.1007/s11092-020-09322-y
  43. Johnson, S., Cooper, C., Cartwright, S., Donald, I., Taylor, P., & Millet, C. (2005). The experience of work-related stress across occupations. Journal of Managerial Psychology, 20(2), 178–187. https://doi.org/10.1108/02683940510579803
  44. Karakus, I., & Kiliç, F. (2022). ‘Digital’ overview at the profiles of pre-service teachers: Digital awareness, competence and fluency. Problems of Education in the 21st Century, 80(2), 324–338. https://doi.org/10.33225/pec/22.80.324
  45. Karataşlıoğlu, R. E., & Özkanal, B. (2023). Digital burnout in distance education process: Investigation of secondary school teachers’ opinions. Journal of Advanced Education Studies, 5(2), 319–341. https://doi.org/10.48166/ejaes.1353517
  46. Khan, A., Fleva, E., & Qazi, T. (2015). Role of self-esteem and general self-efficacy in teachers’ efficacy in primary schools. Psychology, 6, 117–125. https://doi.org/10.4236/psych.2015.61010
  47. Kim, J., & Kim, E. (2022). Relationship between self-esteem and technological readiness: Mediation effect of readiness for change and moderated mediation effect of gender in South Korean teachers. International Journal of Environmental Research and Public Health, 19(14), Article 8463. https://doi.org/10.3390/ijerph19148463
  48. Kim, L. E., Oxley, L., & Asbury, K. (2022). “My brain feels like a browser with 100 tabs open”: A longitudinal study of teachers’ mental health and well-being during the COVID-19 pandemic. British Journal of Educational Psychology, 92, 299–318. https://doi.org/10.1111/bjep.12450
  49. Kiok, P. K., Din, W. A., Said, N., & Swanto, S. (2021). The experiences of pre-service teachers teaching practicum during the COVID-19 pandemic: A systematic literature review. International Journal of Education, Psychology and Counseling, 6(43), 280–295. https://doi.org/10.29329/ijpe.2022.431.5
  50. Kristensen, T. S., Borritz, M., Villadsen, E., & Christensen, K. B. (2005). The Copenhagen Burnout Inventory: A new tool for the assessment of burnout. Work & Stress, 19(3), 192–207. https://doi.org/10.1080/02678370500297720
  51. Krumsvik, R. J. (2011). Digital competence in the Norwegian teacher education and schools. Högre Utbildning, 1(1), 39–51. https://doi.org/10.23865/hu.v1.874
  52. Kwon, K., Ottenbreit-Leftwich, A. T., Sari, A., Khlaif, Z., Zhu, M., Nadir, H., & Gok, F. (2019). Teachers’ self-efficacy matters: Exploring the integration of mobile computing device in middle schools. TechTrends, 63, 682–692. https://doi.org/10.1007/s11528-019-00402-5
  53. Landa, N., Zhou, S., & Marongwe, N. (2021). Education in emergencies: Lessons from COVID-19 in South Africa. International Review of Education, 67(1), 167–183. https://doi.org/10.1007/s11159-021-09903-z
  54. Lee, M., & Tsai, C. (2010). Exploring teachers’ perceived self efficacy and technological pedagogical content knowledge with respect to educational use of the world wide web. Instructional Science: An International Journal of the Learning Sciences, 38(1), 1–21. https://doi.org/10.1007/s11251-008-9075-4
  55. Legrottaglie, S., & Ligorio, M. (2014). The use of technology at school: Teachers’ point of view. Italian Journal of Educational Technology, 22(3), 183–190. https://doi.org/10.17471/2499-4324/188
  56. Li, L., Worch, E., Zhou, Y. & Aguiton, R. (2015). How and why digital generation teachers use technology in the classroom: An explanatory sequential mixed methods study. International Journal for the Scholarship of Teaching and Learning, 9(2). https://doi.org/10.20429/ijsotl.2015.090209
  57. Li, M., & Yu, Z. (2022). Teachers’ satisfaction, role, and digital literacy during the COVID-19 pandemic. Sustainability, 14, Article 1121. https://doi.org/10.3390/su14031121
  58. Loague, A., Loague, A., Caldwell, N., & Balam, E. (2018). Professors’ attitudes and perceptions about technology use in the classroom. Alabama Journal of Educational Leadership, 5(1), 1–11.
  59. Lucas, M., Bem-Haja, P., Siddiq, F., Moreira, A., & Redecker, C. (2021). The relation between in-service teachers’ digital competence and personal and contextual factors: What matters most? Computers & Education, 160, Article 104052. https://doi.org/10.1016/j.compedu.2020.104052
  60. MacIntyre, P. D., Gregersen, T., & Mercer, S. (2020). Language teachers’ coping strategies during the COVID-19 conversion to online teaching: Correlations with stress, wellbeing and negative emotions. System, 94, Article 102352. https://doi.org/10.1016/j.system.2020.102352
  61. Maican, C. I., Cazan, A.-M., Lixandroiu, R. C., & Dovleac, L. (2019). A study on academic staff personality and technology acceptance: The case of communication and collaboration applications. Computers & Education, 128, 113–131. https://doi.org/10.1016/j.compedu.2018.09.010
  62. Malandrino, A., & Sager, F. (2021). Can teachers’ discretion enhance the role of professionalism in times of crisis? A comparative policy analysis of distance teaching in Italy and Switzerland during the COVID-19 pandemic. Journal of Comparative Policy Analysis: Research and Practice, 23(1), 74–84. https://doi.org/10.1080/13876988.2020.1844544
  63. Mannila, L., Nordén, L. Å., & Pears, A. (2018). Digital competence, teacher self-efficacy and training needs. In Proceedings of the 2018 ACM Conference on International Computing Education Research (pp. 78–85). https://doi.org/10.1145/3230977.3230993
  64. Mao, J., Ifenthaler, D., Fujimoto, T., Garavaglia, A., & Rossi, P. G. (2019). National policies and educational technology: A synopsis of trends and perspectives from five countries. TechTrends, 63, 284–293. https://doi.org/10.1007/s11528-019-00396-0
  65. Martin, M. M., & Rubin, R. B. (1995). A new measure of cognitive flexibility. Psychological Reports, 76(2), 623–626. https://doi.org/10.2466/pr0.1995.76.2.623
  66. Moorhouse, B. L. (2020). Adaptations to a face-to-face initial teacher education course ‘forced’ online due to the COVID-19 pandemic. Journal of Education for Teaching: International Research and Pedagogy, 46(4), 609–611. https://doi.org/10.1080/02607476.2020.1755205
  67. Muscarà, M., & Messina, R. (2015). Perceived competency, perceived ICT usefulness in classroom and teachers training models. Italian Journal of Educational Research, (13), 181–196.
  68. Nelson, M. J., Voithofer, R., & Cheng, S. L. (2019). Mediating factors that influence the technology integration practices of teacher educators. Computers & Education, 128, 330–344. https://doi.org/10.1016/j.compedu.2018.09.023
  69. Niemi, K. (2021). ‘The best guess for the future? ‘Teachers’ adaptation to open and flexible learning environments in Finland. Education Inquiry, 12(3), 282–300. https://doi.org/10.1080/20004508.2020.1816371
  70. Novković Cvetković, B., Stošić, L., & Belousova, A. (2018). Media and information literacy-the basis for applying digital technologies in teaching from the discourse of educational needs of teachers. Croatian Journal of Education: Hrvatski Časopis za Odgoj i Obrazovanje, 20(4), 1089–1114. https://doi.org/10.15516/cje.v20i4.3001
  71. Olofsson, A. D., Fransson, G., & Lindberg, J. O. (2019). A study of the use of digital technology and its conditions with a view to understanding what ‘adequate digital competence’ may mean in a national policy initiative. Educational Studies, 46(6), 727–743. https://doi.org/10.1080/03055698.2019.1651694
  72. Önen, A. S., & Koçak, C. (2015). The effect of cognitive flexibility on higher school students’ study strategies. Procedia-Social and Behavioral Sciences, 191, 2346–2350. https://doi.org/10.1016/j.sbspro.2015.04.680
  73. Orakcı, Ş. (2021). Exploring the relationships between cognitive flexibility, learner autonomy, and reflective thinking. Thinking Skills and Creativity, 41, Article 100838. https://doi.org/10.1016/j.tsc.2021.100838
  74. Özen, F., & Üçüncü, A. S. (2022). The effect of teachers’ cognitive flexibility on attitudes towards compulsory distance education during the COVID-19 pandemic. International Journal of Psychology and Educational Studies, 9(2), 492–508. https://doi.org/10.52380/ijpes.2022.9.2.752
  75. Özgenel, M., & Mert, P. (2019). The role of teacher performance in school effectiveness. International Journal of Education Technology and Scientific Researches, 4(10), 417–434. https://doi.org/10.35826/ijetsar.42
  76. Öztürk, G., Karamete, A., & Çetin, G. (2020). The relationship between pre-service teachers’ cognitive flexibility levels and techno-pedagogical education competencies. International Journal of Contemporary Educational Research, 7(1), 40–53. https://doi.org/10.33200/ijcer.623668
  77. Panisoara, I. O., Lazar, I., Panisoara, G., Chirca, R., & Ursu, A. S. (2020). Motivation and continuance intention towards online instruction among teachers during the COVID-19 pandemic: The mediating effect of burnout and technostress. International Journal of Environmental Research and Public Health, 17(21), Article 8002. https://doi.org/10.3390/ijerph17218002
  78. Pastore, S., Manuti, A., & Scardigno, A. F. (2019). Formative assessment and teaching practice: The point of view of Italian teachers. European Journal of Teacher Education, 42(3), 359–374. https://doi.org/10.1080/02619768.2019.1604668
  79. Pears, A., Dagiene, V., & Jasute, E. (2017). Baltic and Nordic K-12 teacher perspectives on computational thinking and computing. In V. Dagienė, & A. Hellas (Eds.), Informatics in schools: Focus on learning programming (pp. 141–152). Springer. https://doi.org/10.1007/978-3-319-71483-7_12
  80. Pellerone M. (2021). Self-perceived instructional competence, self-efficacy and burnout during the COVID-19 pandemic: A study of a group of Italian school teachers. European Journal of Investigation in Health, Psychology and Education, 11(2), 496–512. https://doi.org/10.3390/ejihpe11020035
  81. Penna, M. P., & Stara, V. (2010). Opinions on computers, and efficacy of a computer-based learning: A pilot study. Education and Information Technologies, 15(3), 181–204. https://doi.org/10.1007/s10639-009-9104-1
  82. Pianta, R. C., & Hamre, B. K. (2009). Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher, 38(2), 109–119. https://doi.org/10.3102/0013189X09332374
  83. Portoghese, I., Lasio, M., Conti, R., Mascia, M. L., Hitchcott, P., Agus, M., Gemignani, A., & Penna, M. P. (2020). Cognitive Flexibility Inventory: Factor structure, invariance, reliability, convergent, and discriminant validity among Italian university students. PsyCh Journal, 9(6), 934–941. https://doi.org/10.1002/pchj.401
  84. Pressley, T. (2021). Factors contributing to teacher burnout during COVID-19. Educational Researcher, 50(5), 325–327. https://doi.org/10.3102/0013189X211004138
  85. Pressley, T., & Ha, C. (2021). Teaching during a pandemic: United States teachers’ self-efficacy during COVID-19. Teaching and Teacher Education, 106, Article 103465. https://doi.org/10.1016/j.tate.2021.103465
  86. Prezza, M., Trombaccia, F. R., & Armento, L. (1997). La scala dell'autostima di Rosenberg: Traduzione e validazione Italiana [The Rosenberg self-esteem scale: Italian translation and validation]. Giunti Organizzazioni Speciali, 223, 35–44.
  87. Rahman, M. M. (2023). Sample size determination for survey research and non-probability sampling techniques: A review and set of recommendations. Journal of Entrepreneurship, Business and Economics, 11(1), 42–62.
  88. Ranieri, M., Bruni, I., & Orban de Xivry, A.-C. (2017). Teachers’ professional development on digital and media literacy. Findings and recommendations from a European project. Research on Education and Media, 9(2). https://doi.org/10.1515/rem-2017-0009
  89. Rey-Merchán, M. D. C., & López-Arquillos, A. (2021). Management of technostress in teachers as occupational risk in the context of COVID-19. Medical Sciences Forum, 4(1), Article 5. https://doi.org/10.3390/ECERPH-3-08999
  90. Richter, F. R., & Yeung, N. (2012). Memory and cognitive control in task switching. Psychological Science, 23(10), 1256–1263. https://doi.org/10.1177/0956797612444613
  91. Rocha, F. L. R., Jesus, L. C. D., Marziale, M. H. P., Henriques, S. H., Marôco, J., & Campos, J. A. D. B. (2020). Burnout syndrome in university professors and academic staff members: Psychometric properties of the Copenhagen Burnout Inventory–Brazilian version. Psicologia: Reflexão e Crítica, 33. https://doi.org/10.1186/s41155-020-00151-y
  92. Ruggiero, D., & Mong, C. J. (2015). The teacher technology integration experience: Practice and reflection in the classroom. Journal of Information Technology Education: Research, 14, 161–178. https://doi.org/10.28945/2227
  93. Salmieri, L. (2019). The rhetoric of digitalization in Italian educational policies: Situating reception among digitally skilled teachers. Italian Journal of Sociology of Education, 11(1), 162–183. https://doi.org/10.14658/pupj-ijse-2019-1-8
  94. Sánchez-Cruzado, C., Santiago Campión, R., & Sánchez-Compaña, M. T. (2021). Teacher digital literacy: The indisputable challenge after COVID-19. Sustainability, 13, Article 1858. https://doi.org/10.3390/su13041858
  95. Sangeeta, & Tandon, U. (2021). Factors influencing adoption of online teaching by school teachers: A study during COVID-19 pandemic. Journal of Public Affairs, 21, Article e2503. https://doi.org/10.1002/pa.2503
  96. Schaufeli, W. B., Leiter, M. P., & Maslach, C. (2009). Burnout: 35 years of research and practice. Career Development International, 14(3), 204–220. https://doi.org/10.1108/13620430910966406
  97. Scherer, R., Siddiq, F., & Teo, T. (2015). Becoming more specific: Measuring and modeling teachers’ perceived usefulness of ICT in the context of teaching and learning. Computers & Education, 88, 202–214. https://doi.org/10.1016/j.compedu.2015.05.005
  98. Scull, J., Phillips, M., Sharma, U., & Garnier, K. (2020). Innovations in teacher education at the time of COVID-19: An Australian perspective. Journal of Education for Teaching, 46(4), 497–506. https://doi.org/10.1080/02607476.2020.1802701
  99. Şen, N., & Yildiz Durak, H. (2022). Examining the relationships between English teachers’ lifelong learning tendencies with professional competencies and technology integrating self-efficacy. Education and Information Technologies, 27, 5953–5988. https://doi.org/10.1007/s10639-021-10867-8
  100. Shagiakhmetova, M. N., Bystritskaya, E. V., Demir, S., Stepanov, R. A., Grishnova, E. E., & Kryukova, N. I. (2022). Primary teachers difficulties related to compulsory distance education during COVID-19. Contemporary Educational Technology, 14(2), Article ep357. https://doi.org/10.30935/cedtech/11589
  101. Siddiq, F., Scherer, R., & Tondeur, J. (2016). Teachers’ emphasis on developing students’ digital information and communication skills (TEDDICS): A new construct in 21st century education. Computers & Education, 92–93, 1–14. https://doi.org/10.1016/j.compedu.2015.10.006
  102. Skaalvik, E. M., & Skaalvik, S. (2014). Teacher self-efficacy and perceived autonomy: Relations with teacher engagement, job satisfaction, and emotional exhaustion. Psychological Reports, 114(1), 68–77. https://doi.org/10.2466/14.02.PR0.114k14w0
  103. Sokal, L. J., Eblie Trudel, L. G., & Babb, J. C. (2020). Supporting teachers in times of change: The job demands-resources model and teacher burnout during the COVID-19 pandemic. International Journal of Contemporary Education, 3(2), 67–74. https://doi.org/10.11114/ijce.v3i2.4931
  104. Spiro, R. J., Feltovich, P. J., Feltovich, P. L., Jacobson, M. J., & Coulson, R. L. (1991). Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. Educational Technology, 31(5), 24–33.
  105. Stein, K. C., Miness, A., & Kintz, T. (2018). Teachers’ cognitive flexibility on engagement and their ability to engage students: A theoretical and empirical exploration. Teachers College Record, 120(6), 1–38. https://doi.org/10.1177/016146811812000607
  106. Szyszka, M., Tomczyk, Ł., & Kochanowicz, A. M. (2022). Digitalisation of schools from the perspective of teachers’ opinions and experiences: The frequency of ICT use in education, attitudes towards new media, and support from management. Sustainability, 14, Article 8339. https://doi.org/10.3390/su14148339
  107. Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Pearson.
  108. Tomczyk, Ł. (2021). Declared and real level of digital skills of future teaching staff. Education Sciences, 11(10), Article 619. https://doi.org/10.3390/educsci11100619
  109. Tomczyk, Ł., & Walker, C. (2021). The emergency (crisis) e-learning as a challenge for teachers in Poland. Education and Information Technologies, 26(6), 6847–6877. https://doi.org/10.1007/s10639-021-10539-7
  110. Tondeur, J., Pareja Roblin, N., van Braak, J., Voogt, J., & Prestridge, S. (2016a). Preparing beginning teachers for technology integration in education: Ready for take-off? Technology, Pedagogy and Education, 26(2), 157–177. https://doi.org/10.1080/1475939X.2016.1193556
  111. Tondeur, J., Scherer, R., Baran, E., Siddiq, F., Valtonen, T., & Sointu, E. (2019). Teacher educators as gatekeepers: Preparing the next generation of teachers for technology integration in education. British Journal of Educational Technology, 50(3), 1189–1209. https://doi.org/10.1111/bjet.12748
  112. Tondeur, J., Tondeur, J., Forkosh-Baruch, A., Prestridge, S., Albion, P., & Edirisinghe, S. (2016b). Responding to challenges in teacher professional development for ICT integration in education. Journal of Educational Technology & Society, 19(3), 110–120.
  113. Toto, A., Limone, P., Rodrigo San Juan, C., & Caballé, S. (2021). Motivation, stress and impact of online teaching on Italian teachers during COVID-19. Computers, 10, Article 75. https://doi.org/10.3390/COMPUTERS10060075
  114. Tschannen-Moran, M., & Johnson, D. (2011). Exploring literacy teachers’ self-efficacy beliefs: Potential sources at play. Teaching and Teacher Education, 27(4), 751–761. https://doi.org/10.1016/j.tate.2010.12.005
  115. Tschannen-Moran, M., & Woolfolk Hoy, A. (2001). Teacher efficacy: Capturing and elusive construct. Teaching and Teacher Education, 17, 783–805. https://doi.org/10.1016/S0742-051X(01)00036-1
  116. UNESCO. (2021). Education: From COVID-19 school closures to recovery. UNESCO: Building Peace through Education, Science and Culture, Communication and Information. https://www.unesco.org/en/covid-19/education-response
  117. Winter, E., Costello, A., O’Brien, M., & Hickey, G. (2021). Teachers’ use of technology and the impact of COVID-19. Irish Educational Studies, 40(2), 235–246. https://doi.org/10.1080/03323315.2021.1916559
  118. Wotto, M. (2020). The future high education distance learning in Canada, the United States, and France: Insights from before COVID-19 secondary data analysis. Journal of Educational Technology Systems, 49(2), 262–281. https://doi.org/10.1177/0047239520940624
  119. Xu, J. (2022). A person-centered approach to teacher motivation towards information technology: Integrating achievement goals and expectancy-value perspectives. Educational Technology Research and Development, 70, 397–417. https://doi.org/10.1007/s11423-022-10085-0
  120. Zadok-Gurman, T., Jakobovich, R., Dvash, E., Zafrani, K., Rolnik, B., Ganz, A. B., & Lev-Ari, S. (2021). Effect of inquiry-based stress reduction (IBSR) intervention on well-being, resilience and burnout of teachers during the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 18(7), Article 3689. https://doi.org/10.3390/ijerph18073689
  121. Zhang, W., Wang, Y., Yang, L., & Wang, C. (2020). Suspending classes without stopping learning: China’s education emergency management policy in the COVID-19 outbreak. Journal of Risk and Financial Management, 13(3), Article 55. https://doi.org/10.3390/JRFM13030055