International Association of Educators   |  ISSN: 2834-7919   |  e-ISSN: 1554-5210

Original article | International Journal of Progressive Education 2020, Vol. 16(2) 175-194

Associations Between Emotional States, Self-Efficacy For and Attitude Towards Using Educational Technology

Oğuzhan Atabek

pp. 175 - 194   |  DOI: https://doi.org/10.29329/ijpe.2020.241.12   |  Manu. Number: MANU-1910-14-0002

Published online: April 02, 2020  |   Number of Views: 477  |  Number of Download: 986


Abstract

The purpose of this study was to investigate the associations between alternative certification preservice teachers’ levels of depression, stress, educational technology anxiety, self-efficacy for educational technology, and attitude towards using technology in education to provide insight into the interplay between intrinsic factors affecting technology integration. Participants were 451 preservice teachers enrolled in the alternative certification program at a public university in the southwestern part of Turkey (N=451). Data were collected using the Educational Technology Standards Self-Efficacy Scale, Attitude towards Using Technology in Education Scale, Educational Technology Anxiety Scale, Perceived Stress Scale, and Beck’s Depression Inventory. In addition to descriptive techniques, Pearson’s product-moment correlation coefficient and multiple linear regression were used for data analysis. Findings revealed that preservice teachers suffer from stress, depression, and anxiety, even more so than other undergraduate students. Age did not correlate with any of the parameters. Stress and depression did not differ according to gender; however, females were more anxious about using educational technology. Additionally, findings indicated bidirectional and cyclical relationships between emotional states, self-efficacy, and attitude. Finally, using educational technology for instructional purposes and for secondary purposes such as classroom management were associated with different sets of self-efficacy beliefs, and attitudes. Findings of the research were discussed and suggestions were made.

Keywords: Alternative Certification; Pedagogical Formation; Teacher Training; Technology Acceptance; Technology Integration


How to Cite this Article?

APA 6th edition
Atabek, O. (2020). Associations Between Emotional States, Self-Efficacy For and Attitude Towards Using Educational Technology . International Journal of Progressive Education, 16(2), 175-194. doi: 10.29329/ijpe.2020.241.12

Harvard
Atabek, O. (2020). Associations Between Emotional States, Self-Efficacy For and Attitude Towards Using Educational Technology . International Journal of Progressive Education, 16(2), pp. 175-194.

Chicago 16th edition
Atabek, Oguzhan (2020). "Associations Between Emotional States, Self-Efficacy For and Attitude Towards Using Educational Technology ". International Journal of Progressive Education 16 (2):175-194. doi:10.29329/ijpe.2020.241.12.

References
  1. Abbitt, J. T. (2011). An investigation of the relationship between self-efficacy beliefs about technology integration and technological pedagogical content knowledge (TPACK) among preservice teachers. Journal of Digital Learning in Teacher Education, 27(4), 134-143. https://doi.org/10.1080/21532974.2011.10784670 [Google Scholar] [Crossref] 
  2. Adkins, S. S. (2018). The 2017 global learning technology investment patterns. Metaari. Retrieved from http://www.metaari.com/whitepapers.html [Google Scholar]
  3. Al-Awidi, H. M., & Alghazo, I. M. (2012). The effect of student teaching experience on preservice elementary teachers’ self-efficacy beliefs for technology integration in the UAE. Educational Technology Research and Development, 60(5), 923-941. https://doi.org/10.1007/s11423-012-9239-4 [Google Scholar] [Crossref] 
  4. Al-Senaidi, S., Lin, L., & Poirot, J. (2009). Barriers to adopting technology for teaching and learning in Oman. Computers & Education, 53(3), 575-590. https://doi.org/10.1016/j.compedu.2009.03.015 [Google Scholar] [Crossref] 
  5. Albion, P. R., & Ertmer, P. A. (2002). Beyond the foundations: The role of vision and belief in teachers’ preparation for integration of technology. TechTrends, 46(5), 34-38. https://doi.org/10.1007/BF02818306 [Google Scholar] [Crossref] 
  6. American Psychological Association. (2002). Ethical principles of psychologists and code of conduct. American Psychologist, 57(12), 1060-1073. https://doi.org/10.1037/0003-066X.57.12.1060 [Google Scholar] [Crossref] 
  7. Arslan, A. (2008). The correlation between attitude and self-efficacy with regard to computer assisted education. Electronic Journal of Social Sciences, 7(24), 101-109. Retrieved from https://dergipark.org.tr/esosder/issue/6138/82343 [Google Scholar]
  8. Bandura, A. (1977). Social learning theory. New York: General Learning Press [Google Scholar]
  9. Bandura, A. (1995). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs: Prentice Hall. [Google Scholar]
  10. Beaudry, A., & Pinsonneault, A. (2010). The other side of acceptance: studying the direct and indirect effects of emotions on information technology use. MIS Quarterly, 34(4), 689-710. https://doi.org/10.2307/25750701 [Google Scholar] [Crossref] 
  11. Beck, A. T., Ward, C. H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4(6), 561-571. https://doi.org/10.1001/archpsyc.1961.01710120031004 [Google Scholar] [Crossref] 
  12. Beri, N., & Sharma, L. (2019). Teachers’ attitude towards integrating ICT in teacher education. International Journal of Innovative Technology and Exploring Engineering, 8(8), 285-295. Retrieved from https://www.ijitee.org/download/volume-8-issue-8/ [Google Scholar]
  13. Berry, B. (2001). No shortcuts to preparing good teachers. Educational Leadership, 58(8), 32-36. Retrieved from http://www.ascd.org/publications/educational-leadership/may01/vol58/num08/toc.aspx [Google Scholar]
  14. Berry, B., Montgomery, D., & Snyder, J. (2008). Urban teacher residency models and institutes of higher education: Implications for teacher preparation. Washington: NCATE. [Google Scholar]
  15. Bouffard-Bouchard, T. (1990). Influence of self-efficacy on performance in a cognitive task. The Journal of Social Psychology, 130(3), 353-363. https://doi.org/10.1080/00224545.1990.9924591 [Google Scholar] [Crossref] 
  16. Brindley, R., & Parker, A. (2010). Transitioning to the classroom: Reflections of second-career teachers during the induction year. Teachers and Teaching: Theory and Practice, 16(5), 577-594. https://doi.org/10.1080/13540602.2010.507967 [Google Scholar] [Crossref] 
  17. Brown, S. A., Fuller, R. M., & Vician, C. (2004). Who's afraid of the virtual world? Anxiety and computer-mediated communication. Journal of the Association for Information Systems, 5(2), 79-108. Retrieved from https://aisel.aisnet.org/jais/vol5/iss2/2 [Google Scholar]
  18. Chatzoglou, P. D., Sarigiannidis, L., Vraimaki, E., & Diamantidis, A. (2009). Investigating Greek employees’ intention to use web-based training. Computers & Education, 53(3), 877-889. https://doi.org/10.1016/j.compedu.2009.05.007 [Google Scholar] [Crossref] 
  19. Chau, P. Y. & Hu, P. J. H. (2002). Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories. Information & Management, 39(4), 297-311. https://doi.org/10.1016/S0378-7206(01)00098-2 [Google Scholar] [Crossref] 
  20. Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Computers & Education, 63, 160-175. https://doi.org/10.1016/j.compedu.2012.12.003 [Google Scholar] [Crossref] 
  21. Cobb, R., Jr. (2003). The relationship between self-regulated learning behaviors and academic performance in web-based courses (Unpublished doctoral dissertation). Virginia Polytechnic Institute and State University, Blacksburg, USA. [Google Scholar]
  22. Cohen, S. (1994). Perceived stress scale. Palo-Alto: Mind Garden. Retrieved from http://www.mindgarden.com/documents/PerceivedStressScale.pdf [Google Scholar]
  23. Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 385-396. https://doi.org/10.2307/2136404 [Google Scholar] [Crossref] 
  24. Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158. https://doi.org/10.2307/249749 [Google Scholar] [Crossref] 
  25. Damasio, A. R. (2000). A second chance for emotion. In R. D. Lane & L. Nadel (Eds.), Cognitive neuroscience of emotion (pp.12-23). Oxford: Oxford University Press. [Google Scholar]
  26. Darling-Hammond, L., Chung, R., & Frelow, F. (2002). Variation in teacher preparation: How well do different pathways prepare teachers to teach? Journal of Teacher Education, 53(4), 286-302. https://doi.org/10.1177/0022487102053004002 [Google Scholar] [Crossref] 
  27. Darling-Hammond, L., Holtzman, D. J., Gatlin, S. J., & Heilig, J. V. (2005). Does teacher preparation matter? Evidence about teacher certification, Teach for America, and teacher effectiveness. Education Policy Analysis Archives, 13(42), 1-48. Retrieved from http://epaa.asu.edu/epaa/v13n42/ [Google Scholar]
  28. Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Unpublished doctoral dissertation). Massachusetts Institute of Technology, Cambridge, USA. [Google Scholar]
  29. Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-machine Studies, 38(3), 475-487. https://doi.org/10.1006/imms.1993.1022 [Google Scholar] [Crossref] 
  30. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982 [Google Scholar] [Crossref] 
  31. Dishaw, M., Strong, D. M., & Bandy, D. B. (2002). Extending the task-technology fit model with self-efficacy constructs. AMCIS 2002 Proceedings. Paper 143. Retrieved from https://aisel.aisnet.org/amcis2002/143/ [Google Scholar]
  32. Erol, Y. C., Özdemir, T. Y., Turhan, M., Özan, M. B., & Polat, H. (2017). Metaphoric perceptions of teacher candidates in pedagogic formation about the program itself. Cumhuriyet International Journal of Education, 6(3), 348-364. https://doi.org/10.30703/cije.332081 [Google Scholar] [Crossref] 
  33. Ertmer, P. A. (1999). Addressing first-and second-order barriers to change: Strategies for technology integration. Educational Technology Research & Development, 47(4), 47-61. https://doi.org/10.1007/BF02299597 [Google Scholar] [Crossref] 
  34. Ertmer, P., Conklin, D., Lewandowski, J., Osika, E., Selo, M., & Wignall, E. (2003). Increasing preservice teachers’ capacity for technology integration through the use of electronic models. Teacher Education Quarterly, 30(1), 95-112. Retrieved from http://www.jstor.org/stable/23478427 [Google Scholar]
  35. Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers & Education, 59(2), 423-435. https://doi.org/10.1016/j.compedu.2012.02.001 [Google Scholar] [Crossref] 
  36. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading: Addison-Wesley. [Google Scholar]
  37. Fox, C. (2018). The misuse of technology in the modern classroom and a guide for solutions (Unpublished master’s thesis). California State University San Marcos, USA. [Google Scholar]
  38. Fraillon, J., Ainley, J., Schulz, W., Friedman, T., & Gebhardt, E. (2014). Preparing for life in a digital age: The IEA International Computer and Information Literacy Study international report. London: Springer. https://doi.org/10.1007/978-3-319-14222-7 [Google Scholar] [Crossref] 
  39. Glendinning, S. (2018). A new rootedness? Education in the technological age. Studies in Philosophy and Education, 37(1), 81-96. https://doi.org/10.1007/s11217-016-9562-z [Google Scholar] [Crossref] 
  40. Grossman, P., & Loeb, S. (2010). Learning from multiple routes. Educational Leadership, 67(8), 22-27. Retrieved from http://www.ascd.org/publications/educational-leadership/may10/vol67/num08/toc.aspx [Google Scholar]
  41. Guzey, S. S., & Roehrig, G. H. (2012). Integrating educational technology into the secondary science teaching. Contemporary Issues in Technology and Teacher Education, 12(2), 162-183. Retrieved from https://www.learntechlib.org/primary/p/39130/ [Google Scholar]
  42. Gülbağcı Dede, H., & Akkoç, H. (2016). A comparison of professional identity of pre-service mathematics teachers in pedagogical formation program and undergraduate teacher education program. Turkish Journal of Computer and Mathematics Education, 7(1), 188-206. https://doi.org/10.16949/turcomat.69917 [Google Scholar] [Crossref] 
  43. Gürer, M., Tekinarslan, E., & Gönültaş, S. (2019). Development and validation of an attitude assessment scale for the use of 3D printing in education. International Journal of Education and Development using ICT, 15(1), 190-203. Retrieved from https://www.learntechlib.org/p/209744/ [Google Scholar]
  44. Haddad, W. D., & Draxler, A. (2002). The dynamics of technologies for education. In W. D. Haddad & A. Draxler (Eds.), Technologies for education: Potential, parameters, and prospects (pp. 2-17). Washington, DC: AED. [Google Scholar]
  45. Hew, K. F., & Brush, T. (2007). Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Educational Technology Research and Development, 55(3), 223-252. https://doi.org/10.1007/s11423-006-9022-5 [Google Scholar] [Crossref] 
  46. Holden, H., & Rada, R. (2011). Understanding the influence of perceived usability and technology self-efficacy on teachers’ technology acceptance. Journal of Research on Technology in Education, 43(4), 343-367. https://doi.org/10.1080/15391523.2011.10782576 [Google Scholar] [Crossref] 
  47. Hoy, A. W., & Spero, R. B. (2005). Changes in teacher efficacy during the early years of teaching: A comparison of four measures. Teaching and Teacher Education, 21(4), 343-356. https://doi.org/10.1016/j.tate.2005.01.007 [Google Scholar] [Crossref] 
  48. Hussein, Z. (2015). Explicating students’ behaviours of e-learning: A viewpoint of the extended technology acceptance. International Journal of Management and Applied Science, 1(10), 68-73. Retrieved from http://ijmas.iraj.in/volume.php?volume_id=202 [Google Scholar]
  49. Hyndman, B. (2018, August 13). Ten reasons teachers can struggle to use technology in the classroom. The Conversation. Retrieved from http://theconversation.com/ten-reasons-teachers-canstruggle-to-use-technology-in-the-classroom-101114 [Google Scholar]
  50. International Society for Technology in Education. (2014). ISTE Standards Teachers. Retrieved from http://www.iste.org/docs/pdfs/20-14_ISTE_Standards-T_PDF.pdf [Google Scholar]
  51. İnceoğlu, M. (2010). Tutum algı iletişim (5th ed.). İstanbul: Beykent. [Google Scholar]
  52. Jerusalem, M., & Mittag, W. (1995). Self-efficacy in stressful life transitions. In A. Bandura (Ed.), Self-Efficacy in Changing societies (pp. 177-201). Cambridge: Cambridge University Press. doi:10.1017/CBO9780511527692.008 [Google Scholar] [Crossref] 
  53. Johnson, A. M., Jacovina, M. E., Russell, D. E., & Soto, C. M. (2016). Challenges and solutions when using technologies in the classroom. In S. A. Crossley & D. S. McNamara (Eds.), Adaptive educational technologies for literacy instruction (pp. 13-29). New York: Taylor & Francis. [Google Scholar]
  54. Joo, Y. J., Lim, K. Y., & Kim, N. H. (2016). The effects of secondary teachers’ technostress on the intention to use technology in South Korea. Computers & Education, 95, 114-122.  https://doi.org/10.1016/j.compedu.2015.12.004 [Google Scholar] [Crossref] 
  55. Juutinen, S., & Saariluoma, P. (2010). Emotional obstacles for e-learning: A user psychological analysis. European journal of Open, Distance and E-learning, 1, 1-7. [Google Scholar]
  56. Kağıtçıbaşı, Ç. (2006). Yeni insan ve insanlar (10th ed.). İstanbul: Evrim. [Google Scholar]
  57. Kanadlı, S. (2017). Prospective teachers' professional self-efficacy beliefs in terms of their perceived autonomy support and attitudes towards the teaching profession: A mixed methods study. Educational Sciences: Theory & Practice, 17(5), 1847-1871. https://doi.org/10.12738/estp.2017.5.0597 [Google Scholar] [Crossref] 
  58. Kauppinen, M., Kiili, C., & Coiro, J. (2018). Experiences in digital video composition as sources of self-efficacy toward technology use. International Journal of Smart Education and Urban Society, 9(1), 1-12. https://doi.org/10.4018/IJSEUS.2018010101 [Google Scholar] [Crossref] 
  59. Kee, A. (2012). Feelings of preparedness among alternatively certified teachers: What is the role of program features? Journal of Teacher Education, 63(1), 23-38. https://doi.org/10.1177/0022487111421933 [Google Scholar] [Crossref] 
  60. Kurt, G., & Atay, D. (2009). Prospective teachers’ self-efficacy for technology integration: effects of an experiential method. Proceedings from EDULEARN09: 1st International Conference on Education and New Learning Technologies (pp. 3117-3122). Barcelona, Spain. [Google Scholar]
  61. Kutluca, T., & Ekici, G. (2010). Examining teacher candidates’ attitudes and self-effıcacy perceptions towards the computer assisted education. Hacettepe University Journal of Education, 38, 177-188. Retrieved from http://www.efdergi.hacettepe.edu.tr/shw_artcl-426.html [Google Scholar]
  62. Laczko-Kerr, I., & Berliner, C. (2003). In harm’s way: How uncertified teachers hurt their students. Educational Leadership, 60(8), 34-39. Retrieved from http://www.ascd.org/publications/educational-leadership/may03/vol60/num08/toc.aspx [Google Scholar]
  63. Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191–204. https://doi.org/10.1016/S0378-7206(01)00143-4 [Google Scholar] [Crossref] 
  64. Lewis, M., & Saarni, C. (1985). Culture and emotions. In M. Lewis & C. Saarni (Eds.), The Socialization of Emotions (pp. 1-17). Boston: Springer. https://doi.org/10.1007/978-1-4613-2421-8_1 [Google Scholar] [Crossref] 
  65. Liu, S. H., Liao, H. L., & Pratt, J. A. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52(3), 599-607. https://doi.org/10.1016/j.compedu.2008.11.002 [Google Scholar] [Crossref] 
  66. Louho, R., Kallioja, M. & Oittinen, P., (2006). Factors affecting the use of Hybrid media applications. Graphic Arts in Finland, 35(3), 11-21. Retrieved from https://research.aalto.fi/en/journals/graphic-arts-in-finland(41793b7a-c231-4929-9618-a5d7f727184e)/publications.html [Google Scholar]
  67. Momani, A. M., & Jamous, M. (2017). The evolution of technology acceptance theories. International Journal of Contemporary Computer Research, 1(1), 51–58. Retrieved from https://ssrn.com/abstract=2971454 [Google Scholar]
  68. Nagy, C., & Wang, N. (2007). The alternate route teachers transition to the classroom: Preparation, support, and retention. National Association of Secondary School Principals Bulletin, 9(1), 98-113. https://doi.org/10.1177/0192636506299153 [Google Scholar] [Crossref] 
  69. Neto, A. F. B., & da Silva, F. S. C. (2012). A computer architecture for intelligent agents with personality and emotions. In M. Zacarias & J. V. de Oliveira (Eds.), Human-Computer Interaction: The Agency Perspective (pp. 263-285). Berlin: Springer. https://doi.org/10.1007/978-3-642-25691-2_11 [Google Scholar] [Crossref] 
  70. Otieno, O. C., Liyala, S., Odongo, B. C., & Abeka, S. O. (2016). Theory of reasoned action as an underpinning to technological innovation adoption studies. World Journal of Computer Application and Technology, 4(1), 1-7. https://doi.org/10.13189/wjcat.2016.040101 [Google Scholar] [Crossref] 
  71. Oye, N. D., Lahad, N. A., & Rahim, N. Z. A. (2012). Computer self-efficacy, anxiety and attitudes towards use of technology among university academicians: A case study of university of Port Harcourt-Nigeria. International Journal of Computer Science and Technology, 3(1), 213-9. Retrieved from http://www.ijcst.com/archives/pass1/vol-3-issue-1-2/ [Google Scholar]
  72. Öztürk, T. (2006). Evaluation of social studies teacher nominees’ competency regarding their use of technology in education (Balikesir sample) (Unpublished master’s thesis). Gazi University, Ankara, Turkey. [Google Scholar]
  73. Pajares, F., & Schunk, D. (2002). Development of academic self-efficacy. In A. Wigfield & J. Eccles (Eds.), Development of achievement motivation (pp.16-31). San Diego: Academic Press. [Google Scholar]
  74. Pengnate, S. (2013). Essays on the influence of website emotional design features on users' emotional and behavioral responses (Unpublished doctoral dissertation). Oklahoma State University, Stillwater, USA. [Google Scholar]
  75. Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31(6), 459-470. https://doi.org/10.1016/S0883-0355(99)00015-4 [Google Scholar] [Crossref] 
  76. Polat, S. (2014). The reasons for the pedagogical formation training certificate program students’-who have jobs- tending to choose the teaching profession. Journal of Human Sciences, 11(1), 128-144. Retrieved from https://www.j-humansciences.com/ojs/index.php/IJHS/article/view/2740 [Google Scholar]
  77. Rebora, A. (2016). Teachers still struggling to use technology to transform instruction, survey says. Education Week. Retrieved from https://www.edweek.org/ew/articles/2016/06/09/teachers-still-struggling-to-use-tech-to.html [Google Scholar]
  78. Redmann, D., & Kotrlik, J. (2009). Family and consumer sciences teachers’ adoption of technology for use in secondary classrooms. Journal of Family and Consumer Sciences, 27(1), 29-45. [Google Scholar]
  79. Rivers, S. E., & Brackett, M. A. (2010). Achieving standards in the English language arts (and more) using The RULER Approach to social and emotional learning. Reading & Writing Quarterly, 27(1-2), 75-100. https://doi.org/10.1080/10573569.2011.532715 [Google Scholar] [Crossref] 
  80. Roberts, T. G., & Dyer, J. E. (2004). Inservice needs of traditionally and alternatively certified agriculture teachers. Journal of Agricultural Education, 45(4), 57-70. https://doi.org/10.5032/jae.2004.04057 [Google Scholar] [Crossref] 
  81. Sánchez-Mena, A., Martí-Parreño, J., & Aldás-Manzano, J. (2019). Teachers’ intention to use educational video games: The moderating role of gender and age. Innovations in Education and Teaching International, 56(3), 318-329. https://doi.org/10.1080/14703297.2018.1433547 [Google Scholar] [Crossref] 
  82. Saravanan, T., & Nagadeepa, N. (2017). Impact of information communication and technology integration on stress & cognitive load. International Journal of Pure and Applied Mathematics, 116(10), 349-359. Retrieved from https://acadpubl.eu/jsi/2017-116-8/issue10.html [Google Scholar]
  83. Sarver, V. T. (1983). Ajzen and Fishbein’s “theory of reasoned action”: A critical assessment. Journal for the Theory of Social Behaviour, 13(2), 155-163. http://dx.doi.org/10.1111/j.1468-5914.1983.tb00469.x [Google Scholar]
  84. Schaper, L. K. & Pervan, G. P. (2007). ICT and OTs: A model of information and communication technology acceptance and utilisation by occupational therapists. International Journal of Medical Informatics, 76(1), 212-221. https://doi.org/10.1016/j.ijmedinf.2006.05.028 [Google Scholar] [Crossref] 
  85. Schonfeld, I. S., & Feinman, S. J. (2012). Difficulties of alternatively certified teachers. Education and Urban Society, 44(3), 215-246. https://doi.org/10.1177/0013124510392570 [Google Scholar] [Crossref] 
  86. Schunk, D. H. (1981). Modeling and attributional effects on children's achievement: A self-efficacy analysis. Journal of Educational Psychology, 73(1), 93. http://dx.doi.org/10.1037/0022-0663.73.1.93 [Google Scholar]
  87. Schunk, D. H. (1985). Self‐efficacy and classroom learning. Psychology in the Schools, 22(2), 208-223. https://doi.org/10.1002/1520-6807(198504)22:2<208::AID-PITS2310220215>3.0.CO;2-7 [Google Scholar] [Crossref] 
  88. Schwarzer, R., & Fuchs, R. (1995). Changing risk behaviors and adopting health behaviors: The role of self-efficacy beliefs. In A. Bandura (Ed.), Self-Efficacy in changing societies (pp. 259-288). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511527692.011 [Google Scholar] [Crossref] 
  89. Sezgin Nartgün, Ş., & Gökçer, İ. (2014). Metaphorical perceptions of pedagogical formation students on their occupatıon, future, employment and education policies. E-International Journal of Educational Research, 5(4), 57-69. https://doi.org/10.19160/e-ijer.56142 [Google Scholar] [Crossref] 
  90. Shank, D. (2014). Technology and emotions. In J. Stets & J. Turner (Eds.), Handbook of the Sociology of Emotions Volume II (pp. 511-528). Dordrecht: Springer. https://doi.org/10.1007/978-94-017-9130-4_24 [Google Scholar] [Crossref] 
  91. Shulman, R. D. (2018). EdTech investments rise to a historical $9.5 billion: What your startup needs to know. Forbes. Retrieved from https://www.forbes.com/sites/robynshulman/2018/01/26/edtech-investments-rise-to-a-historical-9-5-billion-what-your-startup-needs-to-know/ [Google Scholar]
  92. Somekh, B. (2008). Factors affecting teachers’ pedagogical adoption of ICT. In Joke Voogt & Gerald Knezek (Eds.), International handbook of information technology in primary and secondary education (pp. 449-460). Boston: Springer. https://doi.org/10.1007/978-0-387-73315-9_27 [Google Scholar] [Crossref] 
  93. Şimşek, O., & Yazar, T. (2016). Education technology standards self-efficacy (ETSSE) scale: A validity and reliability study. Eurasian Journal of Educational Research, 16(63), 311-334. https://doi.org/10.14689/ejer.2016.63.18 [Google Scholar] [Crossref] 
  94. Terzis, V., Moridis, C. N., & Economides, A. A. (2012). The effect of emotional feedback on behavioral intention to use computer based assessment. Computers & Education, 59(2), 710-721. https://doi.org/10.1016/j.compedu.2012.03.003 [Google Scholar] [Crossref] 
  95. Thatcher, J. B., & Perrewe, P. L. (2002). An empirical examination of individual traits as antecedents to computer anxiety and computer self-efficacy. MIS Quarterly, 26(4), 381-396. https://doi.org/10.2307/4132314 [Google Scholar] [Crossref] 
  96. Tosuntaş, Ş. B., Karadağ, E., & Orhan, S. (2015). The factors affecting acceptance and use of interactive whiteboard within the scope of FATIH project: A structural equation model based on the Unified Theory of acceptance and use of technology. Computers & Education, 81, 169-178. https://doi.org/10.1016/j.compedu.2014.10.009 [Google Scholar] [Crossref] 
  97. Tweed, S. R. (2013). Technology implementation: Teacher age, experience, self-efficacy, and professional development as related to classroom technology integration (Unpublished doctoral dissertation). East Tennessee State University, Johnson City, USA. [Google Scholar]
  98. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365. https://doi.org/10.1287/isre.11.4.342.11872 [Google Scholar] [Crossref] 
  99. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540 [Google Scholar] [Crossref] 
  100. Usher, E. L., & Pajares, F. (2008). Sources of self-efficacy in school: Critical review of the literature and future directions. Review of Educational Research, 78(4), 751–796. https://doi.org/10.3102/0034654308321456 [Google Scholar] [Crossref] 
  101. Uzman, E., & Telef, B. B. (2015). Öğretmen adaylarının ruh sağlığı ve yardım arama davranışları. Düşünen Adam: Psikiyatri ve Nörolojik Bilimler Dergisi, 28, 242-254. https://doi.org/10.5350/DAJPN2015280307 [Google Scholar] [Crossref] 
  102. Ünal, E., Yamaç, A., & Uzun, A. M. (2017). The effect of the teaching practice course on pre-service elementary teachers’ technology integration self-efficacy. Malaysian Online Journal of Educational Technology, 5(3), 39-53. Retrieved from https://www.mojet.net/volume/volume-5-issue-3 [Google Scholar]
  103. Wang, Y., & Guan, L. (2008). Recognizing human emotional state from audiovisual signals. IEEE Transactions on Multimedia, 10(5), 936-946. https://doi.org/10.1109/TMM.2008.927665 [Google Scholar] [Crossref] 
  104. Washington, M. L. (2016). Supporting the professional needs of alternatively certified secondary education teachers (Unpublished doctoral dissertation). Walden University, Minneapolis, USA. [Google Scholar]
  105. Whisman, M. A., & Richardson, E. D. (2015). Normative data on the Beck Depression Inventory–second edition (BDI‐II) in college students. Journal of Clinical Psychology, 71(9), 898–907. https://doi.org/10.1002/jclp.22188 [Google Scholar] [Crossref] 
  106. Wong, G. K. W. (2015). Understanding technology acceptance in pre-service teachers of primary mathematics in Hong Kong. Australasian Journal of Educational Technology, 31(6), 713-735. Retrieved from https://www.learntechlib.org/p/171328/ [Google Scholar]
  107. Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221-232. https://doi.org/10.1016/j.chb.2016.10.028 [Google Scholar] [Crossref] 
  108. Yalçınalp, S., & Cabı, E. (2015). A scale development study: Educational technologies anxiety scale (ETAS). Elementary Education Online, 14(3), 1005-1016. http://dx.doi.org/10.17051/io.2015.50515 [Google Scholar]