Attitudes towards Digital Educational Technologies among University Students of Different Fields of Study: Role of Academic Motivation and Personality Traits

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Abstract

Numerous research in recent years has focused on the pros and cons of using digital technologies in education. It has been established that difficulties associated with the digital transformation of education are determined not only by objective reasons, but also by the psychological characteristics of participants in the educational process and their attitudes towards digital educational technologies (DETs). The purpose of present study is to identify differences both in the attitudes towards DETs, and in the correlation of these attitudes’ indicators with personality traits and academic motivation between university students of different fields of study. The study involved 362 students (90.05% females), including 199 Psychology and 163 Philology students of RUDN University. Students’ attitudes towards DET were measured with The Attitudes towards DETs Scale for University Students based on the Tripartite Model of Attitudes. The educational motivation of students was measured with The Academic Motivation Scales based on Deci and Ryan’s Self-Determination Theory. The personality traits were measured with the short version of the NEO Five-Factor Inventory. The research findings show that the differences between Psychology and Philology students appear not so much in their attitudes towards DETs, but in the correlations and regression models of the studied variables. The most significant predictors of the attitudes towards DETs are Agreeableness, Conscientiousness and Motivation for personal growth in psychologists, and Openness, Extraversion and Intrinsic cognition motivation in philologists.

About the authors

Irina A. Novikova

RUDN University

Author for correspondence.
Email: novikova_ia@pfur.ru
ORCID iD: 0000-0001-5831-1547
SPIN-code: 7717-2834
Scopus Author ID: 35766733000
ResearcherId: Q-5276-2016

Ph.D. in Psychology, Associate Professor, is Associate Professor at the Psychology and Pedagogics Department

6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation

Polina A. Bychkova

RUDN University

Email: bychkova_pa@pfur.ru
ORCID iD: 0000-0002-6526-7262
SPIN-code: 1819-7877
Scopus Author ID: 57222720667
ResearcherId: ACD-4333-2022

Ph.D. in Psychology, is Assistant at the Psychology and Pedagogics Department

6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation

Dmitriy A. Shlyakhta

RUDN University

Email: shlyakhta_da@pfur.ru
SPIN-code: 6172-5460
Scopus Author ID: 57191998066

Ph.D. in Psychology, Associate Professor, is Associate Professor at the Psychology and Pedagogics Department

6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation

Alexey L. Novikov

RUDN University

Email: novikov_al@pfur.ru
ORCID iD: 0000-0003-3482-5070
SPIN-code: 3416-1350
Scopus Author ID: 56005222400
ResearcherId: Q-5419-2016

Ph.D. in Philology, Associate Professor, is Associate Professor at the General and Russian Linguistics Department

6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation

References

  1. Abdullah, Z.D., Ziden, A.B.A., Aman, R.B.C., & Mustafa, K.I. (2015). Students’ attitudes towards information technology and the relationship with their academic achievement. Contemporary Educational Technology, 6(4), 338-354. https://doi.org/10.30935/cedtech/6158
  2. Aleshkovski, I.A., Gasparishvili, A.T., Krukhmaleva, O.V., Narbut, N.P., & Savina, N.E. (2021). Russian students about learning under the COVID-19 pandemic: Resources, opportunities and assessment of the distance learning. RUDN Journal of Sociology, 21(2), 211–224. (In Russ.) https://doi.org/10.22363/2313-2272-2021-21-2-211-224
  3. Al-Said, K. (2023). Influence of teacher on student motivation: Opportunities to increase motivational factors during mobile learning. Education and Information Technologies, 28(10), 13439–13457. https://doi.org/10.1007/s10639-023-11720-w
  4. Araneo, P. (2024). Exploring education for sustainable development (ESD) course content in higher education; a multiple case study including what students say they like. Environmental Education Research, 30(4), 631–660. https://doi.org/10.1080/13504622.2023.2280438
  5. Audet, É.C., Levine, S.L., Metin, E., Koestner, S., & Barcan, S. (2021). Zooming their way through university: Which Big 5 traits facilitated students’ adjustment to online courses during the COVID-19 pandemic. Personality and Individual Differences, 180, 110969. https://doi.org/10.1016/j.paid.2021.110969
  6. Baruth, O., & Cohen, A. (2022). Personality and satisfaction with online courses: The relation between the Big Five personality traits and satisfaction with online learning activities. Education and Information Technologies, 28(1), 879–904. https://doi.org/10.1007/s10639-022-11199-x
  7. Belinskaya, E.P., & Fedorova, N.V. (2020). Personal factors of evaluating the efficiency of distance education. Obrazovanie Lichnosti, (1-2), 44–53. (In Russ.)
  8. Bhagat, K.K., Wu, L.Y., & Chang, C.-Y. (2019). The impact of personality on students’ perceptions towards online learning. Australasian Journal of Educational Technology, 35(4), 98-108. https://doi.org/10.14742/ajet.4162
  9. Biryukov, S.D., & Vasilev, O.P. (1997). Psychogenetic study of the temperament properties and personality characteristics: Analysis of the structure of the studied variables. Works of the RAS Institute of Psychology, 2, 23–51. Moscow: Institute of Psychology RAS. (In Russ.)
  10. Bodunov, M.V., & Biryukov, S.D. (1989). Big 5: Five-Factor Inventory. Adapted and reproduced by special permission of the Publisher, Psychological Assessment Resources from the NEO Five Factor Inventory by P. Costa, R. McCrae. Moscow: Institute of Psycho­logy RAS.
  11. Bovermann, K., Weidlich, J., & Bastiaens, T. (2018). Online learning readiness and attitudes towards gaming in gamified online learning – a mixed methods case study. International Journal of Educational Technology in Higher Education, 15(1), 27. https://doi.org/ 10.1186/s41239-018-0107-0
  12. Brika, S.K.M., Chergui, K., Algamdi, A., Musa, A. A., & Zouaghi, R. (2022). E-learning research trends in higher education in light of COVID-19: A bibliometric analysis. Frontiers in Psychology, 12, 762819. https://doi.org/10.3389/fpsyg.2021.762819
  13. Chou, T.-C. R. (2014). A scale of university students’ attitudes toward e-learning on the Moodle system. International Journal of Online Pedagogy and Course Design, 4(3), 49–65. https://doi.org/10.4018/ijopcd.2014070104
  14. Cohen, A., & Baruth, O. (2017). Personality, learning, and satisfaction in fully online academic courses. Computers in Human Behavior, 72, 1–12. https://doi.org/10.1016/j.chb. 2017.02.030
  15. Costa, P.T., & McCrae, R.R. (1992). Revised NEO Five Factor Inventory (NEO-PI-R) and the NEO Five-Factor Inventory (NEO-FFI). Professional Manual. Odessa, Fl: Psychological Assessment Resources.
  16. Cretu, D.M., & Ho, Y.-S. (2023). The impact of COVID-19 on educational research: A bibliometric analysis. Sustainability, 15(6), 5219. https://doi.org/10.3390/su15065219
  17. Edmunds, R., Thorpe, M., & Conole, G. (2010). Student attitudes towards and use of ICT in course study, work and social activity: A technology acceptance model approach. British Journal of Educational Technology, 43(1), 71–84. https://doi.org/10.1111/j.1467- 8535.2010.01142.x
  18. Fabrigar, L.R., MacDonald, T.K., & Wegener, D.T. (2005). The structure of attitudes. In Albarracín, D., Johnson, B.T., & Zanna, M.P. (Eds.). The Handbook of Attitudes (pp. 79–125). Mahwah, NJ: Lawrence Erlbaum Associates Publishers.
  19. Fırat, M. (2022). Exploring the relationship between personality traits and e-learning autonomy of distance education students. Open Praxis, 14(4), 280–290. https://doi.org/10.55982/openpraxis.14.4.155
  20. Gordeeva, T.O., Sychev, O.A., & Osin, E.N. (2014). “Academic motivation scales” questionnaire. Psikhologicheskii Zhurnal, 35(4), 96–107. (In Russ.)
  21. Guillén-Gámez, F.D., & Mayorga-Fernández, M.J. (2020). Identification of variables that predict teachers’ attitudes toward ICT in higher education for teaching and research: A study with regression. Sustainability, 12(4), 1312. https://doi.org/10.3390/su12041312
  22. Guillén-Gámez, F.D., Romero Martínez, S.J., & Ordóñez Camacho, X.G. (2020). Diagnosis of the attitudes towards ICT of education students according to gender and educational modality. Apertura, 12(1). https://doi.org/10.32870/ap.v12n1.1786
  23. Gustiani, S. (2020). Students’ motivation in online learning during COVID-19 pandemic era: A case study. Holistics Journal, 12(2), 23-40.
  24. He, L., Feng, L., & Ding, J. (2024). The relationship between perceived teacher emotional support, online academic burnout, academic self-efficacy, and online English academic engagement of Chinese EFL learners. Sustainability, 16(13), 5542. https://doi.org/ 10.3390/su16135542
  25. Hung, M.-L., Chou, C., Chen, C.-H., & Own, Z.-Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090. https://doi.org/10.1016/j.compedu.2010.05.004
  26. Ismatullina, V.I., & Zakharov, I.M. (2021). Digital literacy of schoolchildren and their attitudes to STEM, depending on digitization of the school environment. Theoretical and Experimental Psychology, 14(3), 29-35. (In Russ.) https://doi.org/10.24412/2073-0861-2021-3-29-35
  27. Kar, D., Saha, B., & Chandra Mondal, B. (2014). Attitude of university students towards E-learning in West Bengal. American Journal of Educational Research, 2(8), 669–673. https://doi.org/10.12691/education-2-8-16
  28. Keller, H., & Karau, S.J. (2013). The importance of personality in students’ perceptions of the online learning experience. Computers in Human Behavior, 29(6), 2494–2500. https://doi.org/10.1016/j.chb.2013.06.007
  29. Mustafa, S., Qiao, Y., Yan, X., Anwar, A., Hao, T., & Rana, S. (2022). Digital students’ satisfaction with and intention to use online teaching modes, role of big five personality traits. Frontiers in Psychology, 13, 956281. https://doi.org/10.3389/fpsyg.2022.956281
  30. Myasishchev, V.N. (1995). Psychology of relations: Selected psychological works. Moscow: MODEK Publ. (In Russ.)
  31. Narbut, N.P., Aleshkovski, I.A., Gasparishvili, A.T., & Krukhmaleva, O.V. (2020). Forced shift to distance learning as an impetus to technological changes in the Russian higher education. RUDN Journal of Sociology, 20(3), 611–621. (In Russ.) https://doi.org/ 10.22363/2313-2272-2020-20-3-611-621
  32. Nevryuev, A.N., Sychev, O.A., & Sarieva, I.R. (2022). The relationship between the students’ attitude toward distance learning, alienation from studying and emotional burnout. Psychological Science and Education, 27(1), 136–146. (In Russ.) https://doi.org/ 10.17759/pse.2022270111
  33. Novikova, I., & Bychkova, P. (2022). Attitudes towards digital educational technologies, academic motivation and academic achievements among Russian university students. In Alexandrov, D.A., Boukhanovsky, A.V., Chugunov, A.V., Kabanov, Y., Koltsova, O., Musabirov, I., & Pashakhin, S. (Eds.). Digital Transformation and Global Society. DTGS 2021. Communications in Computer and Information Science (vol. 1503, pp. 280–293). Cham: Springer. https://doi.org/10.1007/978-3-030-93715-7_20
  34. Novikova, I.A., & Bychkova, P.A. (2020). Attitude towards digital educational technologies among students of different field of study. Personality in the Modern World: Education, Development, Self-Realization. Proceedings of the International Scientific and Practical Conference (pp. 469–476). Moscow: RUDN University. (In Russ.)
  35. Novikova, I.A., & Bychkova, P.A. (2024). Attitudes towards digital educational technologies among university students: concept, measurement, and gender differences. Theore­tical and Experimental Psychology, 17(1), 70–84. (In Russ.) https://doi.org/10.11621/ TEP-24-04
  36. Novikova, I.A., Bychkova, P.A., & Novikov, A.L. (2021). University students’ attitudes towards digital educational technologies before and after outbreak of COVID-19 pandemic. Tsennosti i Smysly, (2), 23–44. (In Russ.) https://doi.org/10.24412/2071-6427-2021- 2-23-44
  37. Novikova, I.A., Bychkova, P.A., & Novikov, A.L. (2022a). Attitudes towards digital educational technologies among Russian university students before and during the COVID-19 pandemic. Sustainability, 14(10), 6203. https://doi.org/10.3390/su14106203
  38. Novikova, I.A., Bychkova, P.A., Novikov, A.L., & Shlyakhta, D.A. (2022b). Personality traits and academic motivation as predictors of attitudes towards digital educational technologies among Russian university students. RUDN Journal of Psychology and Pedagogics, 19(4), 689–716. https://doi.org/10.22363/2313-1683-2022-19-4-689-716
  39. Novikova, I.A., Bychkova, P.A., Shlyakhta, D.A., & Novikov, A.L. (2023). Attitudes towards digital educational technologies scale for university students: Development and validation. Computers, 12(9), 176. https://doi.org/10.3390/computers12090176
  40. Ordóñez, X.G., & Romero, S.J. (2016). Scale of attitudes towards ICT (SATICT): factor structure and factorial invariance in distance university students. Proceedings of the 1st International Conference on Advanced Research Methods and Analytics (pp. 159–166). València: Editorial Universitat Politècnica de València. https://doi.org/10.4995/carma2016.2016.3114
  41. Peng, M.-H., & Dutta, B. (2023). The mediating effects of innovativeness and system usability on students’ personality differences: Recommendations for E-learning platforms in the post-pandemic era. Sustainability, 15(7), 5867. https://doi.org/10.3390/su15075867
  42. Popova, O.I. (2019). Digitalization of education and university brand: Students’ attitude to processes. Management Issues, (3), 245–250. (In Russ.) https://doi.org/10.22394/2304-3369-2019-3-245-250
  43. Prokop, P., & Fančovičová, J. (2008). Students’ attitudes toward computer use in Slovakia. EURASIA Journal of Mathematics, Science and Technology Education, 4(3), 255–262. https://doi.org/10.12973/ejmste/75347
  44. Quigley, M., Bradley, A., Playfoot, D., & Harrad, R. (2022). Personality traits and stress perception as predictors of students’ online engagement during the COVID-19 pandemic. Personality and Individual Differences, 194, 111645. https://doi.org/10.1016/j.paid.2022.111645
  45. R Core Team. R: A Language and environment for statistical computing. Version 4.1. Available online: https://cran.r-project.org (R packages retrieved from CRAN snapshot 2023-04-07). (Accessed on 1 January 2022).
  46. Radu, M.-C., Schnakovszky, C., Herghelegiu, E., Ciubotariu, V.-A., & Cristea, I. (2020). The impact of the COVID-19 pandemic on the quality of educational process: A student survey. International Journal of Environmental Research and Public Health, 17(21), 7770. https://doi.org/10.3390/ijerph17217770
  47. Rasskazova, E.I., & Soldatova, G.U. (2022). Psychological and user activity predictors of attitude toward learning in students during digitalization of education in pandemic. Psychology. Journal of Higher School of Economics, 19(1), 26–44. (In Russ.) https:// doi.org/10.17323/1813-8918-2022-1-26-44
  48. Revelle, W., & Condon, D.M. (2019). Reliability from α to ω: A tutorial. Psychological Assessment, 31(12), 1395–1411. https://doi.org/10.1037/pas0000754
  49. Rivers, D.J. (2021). The role of personality traits and online academic self-efficacy in acceptance, actual use and achievement in Moodle. Education and Information Technologies, 26(4), 4353–4378. https://doi.org/10.1007/s10639-021-10478-3
  50. Rivers, D.J. (2022). Stress mediates the relationship between personality and the affordance of socially distanced online education. Human Behavior and Emerging Technologies, 2022, 1–12. https://doi.org/10.1155/2022/9719729
  51. Rizun, M., & Strzelecki, A. (2020). Students’ acceptance of the COVID-19 impact on shifting higher education to distance learning in Poland. International Journal of Environmental Research and Public Health, 17(18), 6468. https://doi.org/10.3390/ijerph17186468
  52. Romero Martínez, S.J., Ordóñez-Camacho, X.G., Guillen-Gamez, F.D., & Bravo Agapito, J. (2020). Attitudes towards technology among distance education students: Validation of an explanatory model. Online Learning, 24(2), 59–75. https://doi.org/10.24059/olj.v24i2.2028
  53. Rosen, L.D., Whaling, K., Carrier, L.M., Cheever, N.A., & Rokkum, J. (2013). The media and technology usage and attitudes scale: An empirical investigation. Computers in Human Behavior, 29(6), 2501–2511. https://doi.org/10.1016/j.chb.2013.06.006
  54. Rosli, M.S., Saleh, N.S., Md. Ali, A., & Abu Bakar, S. (2022). Self-determination theory and online learning in university: Advancements, future direction and research gaps. Sustainability, 14(21), 14655. https://doi.org/10.3390/su142114655
  55. Selwyn, N. (1997). Students’ attitudes toward computers: Validation of a computer attitude scale for 16–19 education. Computers & Education, 28(1), 35–41. https://doi.org/ 10.1016/s0360-1315(96)00035-8
  56. Soldatova, G.U., & Nestik, T.A. (2016). Technophiles and technophobes. Deti v informatsionnom obshchestve, (25), 20–29. (In Russ.)
  57. Soldatova, G.U., & Rasskazova, E.I. (2018). Brief and screening versions of the Digital Competence Index: Verification and application possibilities. National Psychological Journal, (3), 47–56. (In Russ.) https://doi.org/10.11621/npj.2018.0305
  58. Sorokova, M.G., Odintsova, M., & Radchikova, N.P. (2021). Scale for assessing university digital educational environment (AUDEE Scale). Psychological Science and Education, 26(2), 52–65. (In Russ.) https://doi.org/10.17759/pse.2021260205
  59. Staller, N., Großmann, N., Eckes, A., Wilde, M., Müller, F.H., & Randler, C. (2021). Academic self-regulation, chronotype and personality in university students during the remote learning phase due to COVID-19. Frontiers in Education, 6, 681840. https://doi.org/ 10.3389/feduc.2021.681840
  60. Svenningsson, J., Höst, G., Hultén, M., & Hallström, J. (2022). Students’ attitudes toward technology: Exploring the relationship among affective, cognitive and behavioral components of the attitude construct. International Journal of Technology and Design Education, 32(3), 1531–1551. https://doi.org/10.1007/s10798-021-09657-7
  61. The jamovi project. jamovi. (Version 2.4). Available online: https://www.jamovi.org (accessed on 16 March 2022).
  62. Tzafilkou, K., Perifanou, M., & Economides, A.A. (2021). Development and validation of a students’ remote learning attitude scale (RLAS) in higher education. Education and Information Technologies, 26(6), 7279–7305. https://doi.org/10.1007/s10639-021-10586-0
  63. VandenBos, G.R. (Ed.). (2015). APA dictionary of psychology (2nd ed.). Washington: American Psychological Association. https://doi.org/10.1037/14646-000
  64. Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
  65. Vladova, G., Ullrich, A., Bender, B., & Gronau, N. (2021). Students’ acceptance of technology-mediated teaching – How it was influenced during the COVID-19 pandemic in 2020: A study from Germany. Frontiers in Psychology, 12, 636086. https://doi.org/10.3389/fpsyg.2021.636086

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