On the Technology Acceptance Behavior of Romanian Preschool Teachers
Abstract
:1. Introduction
1.1. Literature Review
1.2. Current Research
2. Materials and Methods
2.1. Research Design
2.2. Participants and Procedure
2.3. Measures
2.4. Data Analysis
3. Results
3.1. Correlation Analyses
3.2. The Sequential Mediating Effects Analyses
3.3. RBF Neural Network Modelling of the Variable’s Relationship
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Ifenthaler, D.; Schweinbenz, V. The acceptance of Tablet-PCs in classroom instruction: The teachers’ perspectives. Comput. Hum. Behav. 2013, 29, 525–534. [Google Scholar] [CrossRef]
- Hong, X.; Zhang, M.; Liu, Q. Preschool teachers’ technology acceptance during the COVID-19: An adapted technology acceptance model. Front. Psychol. 2021, 12, 691492. [Google Scholar] [CrossRef]
- Mueller, J.; Wood, E.; Willoughby, T.; Ross, C.; Specht, J. Identifying discriminating variables between teachers who fully integrate computers and teachers with limited integration. Comput. Educ. 2008, 51, 1523–1537. [Google Scholar] [CrossRef]
- Pultoo, A.; Bullee, A.; Meunier, J.N.; Sheoraj, K.; Panchoo, S.; Naseeven, P.; Ujoodha, M.; Roocha, V.; Rajcoomar, H.; Oojorah, A. Classe21. Educators’ Acceptance of Technology-Enhanced Classroom Using the UTAUT Model. J. Educ. Soc. Sci. 2020, 14, 39–48. [Google Scholar]
- Ajzen, I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
- Venkatesh, V.; Morris, M.G.; Davis, G.B.; Davis, F.D. User Acceptance of Information Technology: Toward a Unified View. MIS Q. 2003, 27, 425–478. [Google Scholar] [CrossRef]
- Davis, F.D. Perceived usefulness, perceived ease of use, and user acceptance of Information Technology. MIS Q. 1989, 13, 319–340. [Google Scholar] [CrossRef]
- Taylor, S.; Todd, P.A. Understanding Information Technology Usage: A Test of Competing Models. Inf. Syst. Res. 1995, 6, 144–176. [Google Scholar] [CrossRef]
- Rogers, E.M.; Singhal, A.; Quinlan, M.A. Diffusion of Innovations. In An Integrated Approach to Communication Theory and Research, 2nd ed.; Stacks, D.W., Salwon, M.B., Eds.; Routledge: New York, NY, USA, 2009; pp. 418–434. [Google Scholar]
- Teo, T.; van Schalk, P. Understanding Technology Acceptance in Pre-Service Teachers: A Structural-Equation Modeling Approach. Asia-Pac. Educ. Res. 2009, 18, 47–66. [Google Scholar] [CrossRef]
- Teo, T.; Fan, X.; Du, J. Technology acceptance among pre-service teachers: Does gender matter? Australas. J. Educ. Technol. 2015, 31, 235–251. [Google Scholar] [CrossRef]
- Aypay, A.; Çelik, H.C.; Aypay, A.; Sever, M. Technology Acceptance in Education: A Study of Pre-Service Teachers in Turkey. Turk. Online J. Educ. Technol. 2012, 11, 264–272. [Google Scholar]
- Al-Abdullatif, A.M. Towards Digitalization in Early Childhood Education: Pre-Service Teachers’ Acceptance of Using Digital Storytelling, Comics, and Infographics in Saudi Arabia. Educ. Sci. 2022, 12, 702. [Google Scholar] [CrossRef]
- Fridin, M.; Belokopytev, M. Acceptance of socially assistive humanoid robot by preschool and elementary school teachers. Comput. Hum. Behav. 2014, 33, 23–31. [Google Scholar] [CrossRef]
- Kewalramani, S.; Havu-Nuutinen, S. Preschool Teachers’ Beliefs and Pedagogical Practices in the Integration of Technology: A Case for Engaging Young Children in Scientific Enquiry. EURASIA J. Math. Sci. Technol. Educ. 2019, 15, 1–13. [Google Scholar] [CrossRef]
- Liu, X.; Toki, E.I.; Pange, J. The use of ICT in preschool education in Greece and China: A comparative study. Procedia Soc. Behav. Sci. 2014, 112, 1167–1176. [Google Scholar] [CrossRef]
- Konca, A.S.; Erden, F.T. Digital Technology (DT) Usage of Preschool Teachers in Early Childhood Classrooms. J. Educ. Future 2021, 19, 1–12. [Google Scholar] [CrossRef]
- Schina, D.; Esteve-González, V.; Usart, M. An overview of teacher training programs in educational robotics: Characteristics, best practices and recommendations. Educ. Inf. Technol. 2021, 26, 2831–2852. [Google Scholar] [CrossRef]
- Schina, D.; Valls Bautista, C.; Borrull Riera, A.; Usart, M.; Esteve González, V. An associational study: Preschool teachers’ acceptance and self-efficacy towards Educational Robotics in a pre-service teacher training program. Int. J. Educ. Technol. High. Educ. 2021, 18, 28. [Google Scholar] [CrossRef]
- Hu, P.J.-H.; Clark, T.H.K.; Ma, W.W. Examining technology acceptance by school teachers: A longitudinal study. Inf. Manag. 2003, 41, 227–241. [Google Scholar] [CrossRef]
- Holden, H.; Rada, R. Understanding the Influence of Perceived Usability and Technology Self-Efficacy on Teachers’ Technology Acceptance. J. Res. Technol. Educ. 2011, 43, 343–367. [Google Scholar] [CrossRef]
- Eickelmann, B.; Vennemann, M. Teachers’ attitudes and beliefs regarding ICT in teaching and learning in European countries. Eur. Educ. Res. J. 2017, 16, 733–761. [Google Scholar] [CrossRef]
- Koral Gümüşoğlu, E.; Akay, E. Measuring Technology Acceptance Level of Teachers by Using Unified Theory of Acceptance and Use of Technology. Int. J. Lang. Educ. Teach. 2017, 5, 378–394. [Google Scholar] [CrossRef]
- Abel, V.R.; Tondeur, J.; Sang, G. Teacher Perceptions about ICT Integration into Classroom Instruction. Educ. Sci. 2022, 12, 609. [Google Scholar] [CrossRef]
- Fokides, E.; Kapetangiorgi, D.-M. The Use of Computers by Greek Educators. Did the COVID-19 Pandemic Change Anything? J. Inf. Technol. Educ: Res. 2022, 21, 217–244. [Google Scholar] [CrossRef]
- Jiang, L. Factors influencing EFL teachers’ implementation of SPOC-based blended learning in higher vocational colleges in China: A study based on grounded theory. Interact. Learn. Environ. 2022, 30, 1–20. [Google Scholar] [CrossRef]
- Khong, H.; Celik, I.; Le, T.T.T.; Lai, V.T.T.; Nguyen, A.; Bui, H. Examining teachers’ behavioural intention for online teaching after COVID-19 pandemic: A large-scale survey. Educ. Inf. Technol. 2022, 27, 1–28. [Google Scholar] [CrossRef]
- Deslonde, V.; Becerra, M. The Technology Acceptance Model (TAM) Exploring School Counselors’ Acceptance and Use of Naviance. Prof. Couns. 2018, 8, 369–382. [Google Scholar] [CrossRef]
- Alharbi, S.; Drew, S. Using the Technology Acceptance Model in Understanding Academics’ Behavioural Intention to Use Learning Management Systems. Int. J. Adv. Comput. Sci. Appl. 2014, 5, 143–155. [Google Scholar] [CrossRef]
- Ramirez-Anormaliza, R.; Sabaté, F.; Llinàs-Audet, X. The Acceptance and Use of the E-Learning Systems Among the University Teachers in Ecuador. In Proceedings of the EDULEARN16 Conference, Barcelona, Spain, 4–6 July 2016; pp. 3666–3674. [Google Scholar]
- Olipas, C.N.P.; Gardoce, A.P., Jr. Electronic Learning Modules in Mobile Devices: A Technology Acceptance Model Approach Using PLS-SEM. Int. J. Sci. Res. Multidiscip. Stud. 2022, 8, 37–44. [Google Scholar]
- Salele, N.; Khan, M.S.H. Engineering Trainee-Teachers’ Attitudes Toward Technology Use in Pedagogical Practices: Extending Computer Attitude Scale (CAS). SAGE Open 2022, 12, 21582440221102436. [Google Scholar] [CrossRef]
- Iovu, B.; Runcan, R.; Runcan, P.-L.; Andrioni, F. Association between Facebook Use, Depression and Family Satisfaction: A Cross-Sectional Study of Romanian Youth. Iran. J. Public Health 2020, 49, 2111–2119. [Google Scholar] [CrossRef] [PubMed]
- Sârbu, E.A.; Nadolu, B.; Runcan, R.; Tomiță, M.; Lazăr, F. Social predictors of the transition from anomie to deviance in adolescence. PLoS ONE 2022, 17, e0269236. [Google Scholar] [CrossRef] [PubMed]
- Runcan, P.L. The time factor: Does it influence the parent-child relationship? Procedia—Soc. Behav. Sci. 2012, 33, 11–14. [Google Scholar] [CrossRef] [Green Version]
- Heerink, M.; Kröse, B.; Evers, V.; Wielinga, B. Influence of social presence on acceptance of an assistive social robot and screen agent by elderly users. Adv. Robot. 2009, 23, 1909–1923. [Google Scholar] [CrossRef]
- Hidson, E. Challenges to Pedagogical Content Knowledge in lesson planning during curriculum transition a multiple case study of teachers of ICT and Computing in England. Ph.D. Thesis, Durham University, Durham, UK, 2018; 297p. [Google Scholar]
- Jack, C.; Higgins, S. Embedding educational technologies in early years education. Res. Learn. Technol. 2019, 27, 1–27. [Google Scholar] [CrossRef]
- Burnett, C. Technology and literacy in early childhood educational settings: A review of research. J. Early Child. Lit. 2010, 10, 247–270. [Google Scholar] [CrossRef]
- Yurt, Ö.; Cevher-Kalburan, N. Early childhood teachers’ thoughts and practices about the use of computers in early childhood education. Procedia Comput. Sci. 2011, 3, 1562–1570. [Google Scholar] [CrossRef]
- Hew, K.F.; Brush, T. Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Educ. Technol. Res. Dev. 2007, 55, 223–252. [Google Scholar] [CrossRef]
- Mertala, P. Digital technologies in early childhood education–a frame analysis of preservice teachers’ perceptions. Early Child Dev. Care 2019, 189, 1228–1241. [Google Scholar] [CrossRef]
- Undheim, M. Children and teachers engaging together with digital technology in early childhood education and care institutions: A literature review. Eur. Early Child. Educ. Res. J. 2022, 30, 472–489. [Google Scholar] [CrossRef]
- Zomer, N.R.; Kay, R.H. Technology Use in Early Childhood Education: A Review of Literature. J. Educ. Inform. 2016, 1, 1–25. [Google Scholar] [CrossRef]
- Tsitouridou, M.; Vryzas, K. Early childhood teachers’ attitudes towards computer and information technology: The case of Greece. Inf. Technol. Child. Educ. Annu. 2003, 2003, 187–207. [Google Scholar]
- Romero-Tena, R.; Barragán-Sánchez, R.; Llorente-Cejudo, C.; Palacios-Rodríguez, A. The challenge of initial training for early childhood teachers. A Cross Sect. Study Digit. Competences. Sustain. 2020, 12, 4782. [Google Scholar]
- Masoumi, D. Preschool teachers’ use of ICTs: Towards a typology of practice. Contemp. Issues Early Child. 2015, 16, 5–17. [Google Scholar] [CrossRef]
- Casillas Martín, S.; Cabezas González, M.; García Peñalvo, F.J. Digital competence of early childhood education teachers: Attitude, knowledge and use of ICT. Eur. J. Teach. Educ. 2020, 43, 210–223. [Google Scholar] [CrossRef]
- Alelaimat, A.M.; Ihmeideh, F.M.; Alkhawaldeh, M.F. Preparing preservice teachers for technology and digital media integration: Implications for early childhood teacher education programs. Int. J. Early Child. 2020, 52, 299–317. [Google Scholar] [CrossRef]
- Blackwell, C.K.; Lauricella, A.R.; Wartella, E. Factors influencing digital technology use in early childhood education. Comput. Educ. 2014, 77, 82–90. [Google Scholar] [CrossRef]
- Keengwe, J.; Onchwari, G. Technology and early childhood education: A technology integration professional development model for practicing teachers. Early Child Educ. J. 2009, 37, 209–218. [Google Scholar] [CrossRef]
- Zaranis, N.; Kalogiannakis, M.; Papadakis, S. Using mobile devices for teaching realistic mathematics in kindergarten education. Creat. Educ. 2013, 4, 1–10. [Google Scholar] [CrossRef]
- Ogegbo, A.A.; Aina, A. Early childhood development teachers’ perceptions on the use of technology in teaching young children. S. Afr. J. Child. Educ. 2020, 10, 1–10. [Google Scholar] [CrossRef]
- Nikolopoulou, K.; Gialamas, V. Barriers to the integration of computers in early childhood settings: Teachers’ perceptions. Educ. Inf. Technol. 2015, 20, 285–301. [Google Scholar] [CrossRef]
- Negru-Subtirica, O.; Pop, E.I.; Crocetti, E. Developmental trajectories and reciprocal associations between career adaptability and vocational identity: A three-wave longitudinal study with adolescents. J. Vocat. Behav. 2015, 88, 131–142. [Google Scholar] [CrossRef]
- Haibo, Y.; Xiaoyu, G.; Xiaoming, Z.; Zhijin, H. Career adaptability with or without career identity: How career adaptability leads to organizational success and individual career success? J. Career Assess. 2018, 26, 717–731. [Google Scholar] [CrossRef]
- Islam, A.N. Investigating e-learning system usage outcomes in the university context. Comput. Educ. 2013, 69, 387–399. [Google Scholar] [CrossRef]
- Weibel, D.; Stricker, D.; Wissmath, B. The use of a virtual learning centre in the context of a university lecture: Factors influencing satisfaction and performance. Interact. Learn. Environ. 2012, 20, 77–87. [Google Scholar] [CrossRef]
- Huang, H.M.; Liaw, S.S. Exploring learners’ self-efficacy, autonomy, and motivation toward e-learning. Percept. Mot. Ski. 2007, 105, 581–586. [Google Scholar] [CrossRef]
- Guan, Y.; Yang, W.; Zhou, X.; Tian, Z.; Eves, A. Predicting Chinese human resource managers’ strategic competence: Roles of identity, career variety, organizational support and career adaptability. J. Vocat. Behav. 2016, 92, 116–124. [Google Scholar] [CrossRef]
- Suki, N.M.; Suki, N.M. Exploring the relationship between perceived usefulness, perceived ease of use, perceived enjoyment, attitude and subscribers’ intention towards using 3G mobile services. J. Inf. Technol. Manag. 2011, 22, 1–7. [Google Scholar]
- Rad, D.; Magulod, G.C., Jr.; Balas, E.; Roman, A.; Egerau, A.; Maier, R.; Ignat, S.; Dughi, T.; Balas, V.; Demeter, E.; et al. A Radial Basis Function Neural Network Approach to Predict Preschool Teachers’ Technology Acceptance Behavior. Front. Psychol. 2022, 13, 880753. [Google Scholar] [CrossRef]
- Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach; Guilford Publications: New York, NY, USA, 2017. [Google Scholar]
- Wen, Z.; Ye, B. Mediating effect analysis: Method and model development. Adv. Psychol. Sci. 2014, 22, 731–745. [Google Scholar] [CrossRef]
- Chao, C.M. Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Front. Psychol. 2019, 10, 1652. [Google Scholar] [CrossRef]
- Ahn, M.; Kang, J.; Hustvedt, G. A model of sustainable household technology acceptance. Int. J. Consum. Stud. 2016, 40, 83–91. [Google Scholar] [CrossRef]
- Koenig-Lewis, N.; Marquet, M.; Palmer, A.; Zhao, A.L. Enjoyment and social influence: Predicting mobile payment adoption. Serv. Ind. J. 2015, 35, 537–554. [Google Scholar] [CrossRef]
- Oh, J.; Yoon, S.J. Validation of haptic enabling technology acceptance model (HE-TAM): Integration of IDT and TAM. Telemat. Inform. 2014, 31, 585–596. [Google Scholar] [CrossRef]
- Lai, C.; Wang, Q.; Lei, J. What factors predict undergraduate students’ use of technology for learning? A case from Hong Kong. Comput. Educ. 2012, 59, 569–579. [Google Scholar] [CrossRef]
- Kalogiannakis, M.; Papadakis, S. Evaluating pre-service kindergarten teachers’ intention to adopt and use tablets into teaching practice for natural sciences. Int. J. Mob. Learn. Organ. 2019, 13, 113–127. [Google Scholar] [CrossRef]
- Jeong, H.I.; Kim, Y. The acceptance of computer technology by teachers in early childhood education. Interact. Learn. Environ. 2017, 25, 496–512. [Google Scholar] [CrossRef]
- Joo, Y.J.; Park, S.; Lim, E. Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model. J. Educ. Technol. Soc. 2018, 21, 48–59. [Google Scholar]
- Gialamas, V.; Nikolopoulou, K. In-service and pre-service early childhood teachers’ views and intentions about ICT use in early childhood settings: A comparative study. Comput. Educ. 2010, 55, 333–341. [Google Scholar] [CrossRef]
- Sadaf, A.; Newby, T.J.; Ertmer, P.A. Exploring factors that predict preservice teachers’ intentions to use Web 2.0 technologies using decomposed theory of planned behavior. J. Res. Technol. Educ. 2012, 45, 171–196. [Google Scholar] [CrossRef]
- Holdack, E.; Lurie-Stoyanov, K.; Fromme, H.F. The role of perceived enjoyment and perceived informativeness in assessing the acceptance of AR wearables. J. Retail. Consum. Serv. 2020, 65, 102259. [Google Scholar] [CrossRef]
- Hasan, A.A.T.; Sumon, S.M.; Islam, M.T.; Hossain, M.S. Factors influencing online shopping intentions: The mediating role of perceived enjoyment. Turk. J. Mark. 2021, 6, 239–253. [Google Scholar] [CrossRef]
- Sun, Y.; Bhattacherjee, A.; Ma, Q. Extending technology usage to work settings: The role of perceived work compatibility in ERP implementation. Inf. Manag. 2009, 46, 351–356. [Google Scholar] [CrossRef]
- Kriek, J.; Stols, G. Teachers’ beliefs and their intention to use interactive simulations in their classrooms. S. Afr. J. Educ. 2010, 30. [Google Scholar] [CrossRef]
- Calisir, F.; Gumussoy, C.A.; Bayram, A. Predicting the behavioral intention to use enterprise resource planning systems: An exploratory extension of the technology acceptance model. Manag. Res. News 2009, 32, 597–613. [Google Scholar] [CrossRef]
- Blackwell, C. Teacher practices with mobile technology integrating tablet computers into the early childhood classroom. J. Educ. Res. 2013, 7, 1–25. [Google Scholar]
- Blackwell, C.K.; Lauricella, A.R.; Wartella, E.; Robb, M.; Schomburg, R. Adoption and use of technology in early education: The interplay of extrinsic barriers and teacher attitudes. Comput. Educ. 2013, 69, 310–319. [Google Scholar] [CrossRef]
- Beaudry, A.; Pinsonneault, A. The other side of acceptance: Studying the direct and indirect effects of emotions on information technology use. MIS Q. 2010, 34, 689–710. [Google Scholar] [CrossRef] [Green Version]
- Christou, E.; Kassianidis, P. Consumer’s perceptions and adoption of online buying for travel products. J. Travel Tour. Mark. 2002, 12, 93–107. [Google Scholar] [CrossRef]
- Murcia, K.; Campbell, C.; Aranda, G. Trends in Early Childhood Education Practice and Professional Learning with Digital Technologies. Pedagogika 2018, 68, 249–264. [Google Scholar] [CrossRef]
- Hatzigianni, M.; Kalaitzidis, I. Early childhood educators’ attitudes and beliefs around the use of touchscreen technologies by children under three years of age. Br. J. Educ. Technol. 2018, 49, 883–895. [Google Scholar] [CrossRef]
- Tao, D. Intention to use and actual use of electronic information resources: Further exploring Technology Acceptance Model (TAM). Annu. Symp. Proc. AMIA Symp. 2009, 2009, 629–633. [Google Scholar] [PubMed]
- Alshammari, S.H.; Ali, M.B.; Rosli, M.S. The influences of technical support, self efficacy and instructional design on the usage and acceptance of LMS: A comprehensive review. Turkish Online J. Educ. Technol. 2016, 15, 116–125. [Google Scholar]
- Yang, Y.; and Wang, X. Modeling the intention to use machine translation for student translators: An extension of technology acceptance model. Comput. Educ. 2019, 133, 116–126. [Google Scholar] [CrossRef]
- Marici, M.; Clipa, O.; Runcan, R.; Iosim, I. Perceptions of Parenting during the COVID-19 Quarantine Period, in Suceava, the Epicenter of the COVID-19 Outbreak in Romania. Int. J. Environ. Res. Public Health 2022, 19, 16188. [Google Scholar] [CrossRef]
- Iosim, I.; Runcan, P.; Dan, V.; Nadolu, B.; Runcan, R.; Petrescu, M. The Role of Supervision in Preventing Burnout among Professionals Working with People in Difficulty. Int. J. Environ. Res. Public Health 2021, 19, 160. [Google Scholar] [CrossRef] [PubMed]
- Iosim, I.; Runcan, P.L.; Runcan, R.; Jomiru, C.; Gavrila-Ardelean, M. The Impact of Parental External Labour Migration on the Social Sustainability of the Next Generation in Developing Countries. Sustainability 2022, 14, 4616. [Google Scholar] [CrossRef]
- Costin, A.; Roman, A.F. Discussing with the Parents of High School Students: What do They Know about Drugs? Postmod. Open. 2020, 11, 01–19. [Google Scholar] [CrossRef]
- Maier, R.; Maier, A.; Maier, C. Volunteering and Prosocial Behaviour. BRAIN. Broad Res. Artif. Intell. Neurosci. 2021, 12, 79–88. [Google Scholar] [CrossRef]
- Maier, R. The Participatory Behaviour and the Students’ Adaptability in the Online Environment during the Pandemic. BRAIN. Broad Res. Artif. Intell. Neurosci. 2021, 12, 112–121. [Google Scholar] [CrossRef]
D3 | D4 | D5 | D6 | ||
---|---|---|---|---|---|
D3. Perceived enjoyment | Pearson’s r | — | |||
p-value | — | ||||
D4. Intention to use | Pearson’s r | 0.822 *** | — | ||
p-value | <0.001 | — | |||
D5. Actual use | Pearson’s r | 0.738 *** | 0.795 *** | — | |
p-value | <0.001 | <0.001 | — | ||
D6. Compatibility | Pearson’s r | 0.737 *** | 0.696 *** | 0.671 *** | — |
p-value | <0.001 | <0.001 | <0.001 | — |
Sample | Observed | Predicted | |||||
---|---|---|---|---|---|---|---|
1.00 | 2.00 | 3.00 | 4.00 | 5.00 | Percent Correct | ||
Training | 1.00 | 10 | 4 | 2 | 0 | 0 | 62.5% |
2.00 | 3 | 16 | 12 | 1 | 0 | 50.0% | |
3.00 | 0 | 7 | 19 | 12 | 1 | 48.7% | |
4.00 | 0 | 1 | 3 | 23 | 3 | 76.7% | |
5.00 | 0 | 0 | 0 | 6 | 5 | 45.5% | |
Overall Percent | 10.2% | 21.9% | 28.1% | 32.8% | 7.0% | 57.0% | |
Testing | 1.00 | 3 | 3 | 0 | 0 | 0 | 50.0% |
2.00 | 4 | 5 | 2 | 1 | 0 | 41.7% | |
3.00 | 0 | 0 | 15 | 5 | 0 | 75.0% | |
4.00 | 0 | 0 | 1 | 7 | 1 | 77.8% | |
5.00 | 0 | 0 | 1 | 1 | 5 | 71.4% | |
Overall Percent | 13.0% | 14.8% | 35.2% | 25.9% | 11.1% | 64.8% |
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Rad, D.; Egerău, A.; Roman, A.; Dughi, T.; Kelemen, G.; Balaș, E.; Redeș, A.; Schipor, M.-D.; Clipa, O.; Mâță, L.; et al. On the Technology Acceptance Behavior of Romanian Preschool Teachers. Behav. Sci. 2023, 13, 133. https://doi.org/10.3390/bs13020133
Rad D, Egerău A, Roman A, Dughi T, Kelemen G, Balaș E, Redeș A, Schipor M-D, Clipa O, Mâță L, et al. On the Technology Acceptance Behavior of Romanian Preschool Teachers. Behavioral Sciences. 2023; 13(2):133. https://doi.org/10.3390/bs13020133
Chicago/Turabian StyleRad, Dana, Anca Egerău, Alina Roman, Tiberiu Dughi, Gabriela Kelemen, Evelina Balaș, Adela Redeș, Maria-Doina Schipor, Otilia Clipa, Liliana Mâță, and et al. 2023. "On the Technology Acceptance Behavior of Romanian Preschool Teachers" Behavioral Sciences 13, no. 2: 133. https://doi.org/10.3390/bs13020133
APA StyleRad, D., Egerău, A., Roman, A., Dughi, T., Kelemen, G., Balaș, E., Redeș, A., Schipor, M. -D., Clipa, O., Mâță, L., Maier, R., Rad, G., Runcan, R., & Kiss, C. (2023). On the Technology Acceptance Behavior of Romanian Preschool Teachers. Behavioral Sciences, 13(2), 133. https://doi.org/10.3390/bs13020133