Exploring the Interplay of Distance Education, Learning Styles, and Emotional Experiences in High School Students: A Structural Equation Modeling Perspective

Document Type : Original Article


1 Department of Psychology, Payame Noor University (PNU), Tehran, Iran

2 Department of Educational Sciences, Payame Noor University (PNU), Tehran, Iran


Background: Distance education is an opportunity to overcome the limitations of face-to-face education and has provided the idea of education for everyone and everywhere. The current study aimed to examine the correlation between distance education and learning styles, incorporating the mediating influence of emotional experiences among high school students.
Methods: The research methodology was correlation type. The statistical population comprised all the first-year high school students in Shiraz City during the academic year spanning November 2023 to 2022, with a sample size of 300 individuals selected through convenience sampling. The research tools included Kolb’s Learning Styles Questionnaire, Sekou and Samson’s Distance Space Questionnaire, and Pekrun et al.’s Emotional Experiences Questionnaire. The data analysis involved utilizing Pearson’s correlation coefficient, path analysis, and structural equation modeling through SPSS V26 and Amos V24 software.
Results: The results of the present study showed a significant and positive correlation between learning styles and positive emotions. The coefficients indicated a significant correlation between positive emotions with concrete experience (r=0.21, P=0.01), reflective observation (r=-0.25, P=0.01), conceptualization (r=0.18, P=0.02), and concrete experience (r=0.32), (P=0.01). Negative emotions showed a weak correlation with objective experience (r=-0.19, P=0.02) and observation of reflection (r=-0.21, P=0.01), while no significant relationship was found between negative emotions and the abstract conceptualization learning style (r=0.07, P=0.09). There was also a significant correlation between learning styles and distance education. There was a negative correlation between distance education and objective experience (r=-0.18, P=0.02), while there were positive correlations with reflective observation (r=0.35, P=0.01), abstract conceptualization (r=0.42, P=0.01), and another positive correlation with reflective observation (r=0.29, P=0.03).
Conclusion: The results showed that positive emotions can help improve distance education even when the student’s learning style is objective experience or active experimentation.


Akram Malekzadeh (Google Scholar)


  1. AlAteeq, D. A., Aljhani, S., & AlEesa, D. (2020). Perceived stress among students in virtual classrooms during the COVID-19 outbreak in KSA. Journal of Taibah University Medical Sciences, 15(5), 398–403. doi:10.1016/j.jtumed.2020.07.004.
  2. Martínez-López FJ, Infante-Moro A, García-Ordaz M, Infante-Moro JC, Gallardo-Pérez J. A longitudinal analysis of the use of videoconferences in the Spanish company: its potential for virtual training. In 2021 XI International Conference on Virtual Campus (JICV). 2021, 30:1-3. IEEE. doi:10.1109/JICV53222.2021.9600372.
  3. Fisher WW, Luczynski KC, Hood SA, Lesser AD, Machado MA, Piazza CC. Preliminary findings of a randomized clinical trial of a virtual training program for applied behavior analysis technicians. Research in Autism Spectrum Disorders. 2014; 1;8(9):1044-54. doi:10.1016/j.rasd.2014.05.002.
  4. Shernoff ES, Von Schalscha K, Gabbard JL, Delmarre A, Frazier SL, Buche C, Lisetti C. Evaluating the usability and instructional design quality of Interactive Virtual Training for Teachers (IVT-T). Educational Technology Research and Development. 2020; 68:3235-62.
  5. Gabajova G, Furmannova B, Medvecka I, Grznar P, Krajčovič M, Furmann R. Virtual training application by use of augmented and virtual reality under university technology enhanced learning in Slovakia. Sustainability. 2019;11(23):6677. doi: 10.3390/su11236677.
  6. Abich IV J, Parker J, Murphy JS, Eudy M. A review of the evidence for training effectiveness with virtual reality technology. Virtual Reality. 2021; 25(4):919-33. A review of the evidence for training effectiveness with virtual reality technology. doi:10.1007/s10055-020-00498-8
  7. Radhakrishnan U, Koumaditis K, Chinello F. A systematic review of immersive virtual reality for industrial skills training. Behavior & Information Technology. 2021;40(12):1310-39. doi: 10.1080/0144929X.2021.1954693.
  8. Kukharenko V M, Oleinik T. Open distance learning for teachers (Doctoral dissertation). Ukraine National Technical University; 2019.
  9. Barbera E. Quality in virtual education environments. British Journal of Educational Technology. 2004; 35(1): 13-20. doi:10.1111/j.1467-8535.2004.00364.x.
  10. Costa RD, Souza GF, Valentim RA, Castro TB. The theory of learning styles applied to distance learning. Cognitive Systems Research. 2020; 64:134-45. doi: 10.1016/j.cogsys.2020.08.004.
  11. Holmberg B. Distance education: A survey and bibliography. London: Kogan Page, 1977.
  12. Peters, O. Die didaktische Struktur des Fernunterrichts. Untersuchungen zu einer industrialisierten Form des Lehrens and Lernens. Weinheim: Beltz; 1973.
  13. Keegan DJ. On defining distance education. Distance education. 1980;1(1):13-36. doi: 10.1080/0158791800010102.
  14. Keefe JW. Assessing Student Learning Style. In J. W. Keefe (Ed.), Student learning styles and Brain Behaviors. Reston, VA: National Association of Secondary School Principals; 1982.
  15. Kolb D. Learning style inventory: self-scoring inventory and interpretation booklet. Englewood.1984;37. https://www.scirp.org/reference/ReferencesPapers?ReferenceID=1690677.
  16. Moussa N. The importance of learning styles in education. Institute for Learning Styles Journal. 2014;1(2):19-27.
  17. Pashler H, McDaniel M, Rohrer D, Bjork R. Learning styles: Concepts and evidence. Psychological science in the public interest. 2008;9(3):105-19. doi: 10.1111/j.1539-6053.2009.01038.x.
  18. Hosseini N, Najafi N, Minaiyan S, Razavi Sh, Azar A, Seyedkazem M. Investigating learning styles based on Kolb’s theory in students of the first course of business management in Iran University of Medical Sciences. New achievements in humanities studies. 2022; 45(4): 98-113. [In Persian].
  19. Kolb D. Experiential Learning: Experience as the Source of Learning and Development. Englewood Cliffs, NJ: Prentice Hall; 2005.
  20. Kolb D A. The Kolb learning style inventory. Boston, MA: Hay Resources Direct; 2007.
  21. Wolf C. Weaver: Towards’ learning style-based e-learning in computer science education. In Proceedings of the fifth Australasian Conference on Computing Education, 2003; 20; 273-279.
  22. Honey P, Alonso C, Domingo J, Domingo J. Los estilos de aprendizaje: procedimientos de diagnóstico y mejora. España, Bilbao: Ediciones El Mensajero. 1994.
  23. Habibi R, Setyohadi DB, Santoso KI. Student learning styles and emotional tendencies detection based on Twitter. In2017 4th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE) 2017;18: 239-243. doi:10.1109/ICITACEE.2017.8257710.
  24. Li L, Gow ADI, Zhou J. The role of positive emotions in education: A neuroscience perspective. Mind, Brain, and Education, 2020; 14(3): 220-234. doi: 10.1111/mbe.12244.
  25. Kosciw JG, Palmer NA, Kull RM, Greytak EA. The effect of negative school climate on academic outcomes for LGBT youth and the role of in-school supports. Journal of School Violence. 2013; 12(1):45-63. doi:10.1080/15388220.2012.732546.
  26. Furlong MJ, You S, Renshaw TL, O’Malley MD, Rebelez J. Preliminary development of the Positive Experiences at School Scale for elementary school children. Child Indicators Research. 2013;6:753-75.
  27. Lotz ROY, Lee L. Sociability, school experience, and delinquency. Youth & Society,199; 31(2), 199-223. doi:10.1177/0044118X99031002004.
  28. Tamada MM, de Magalhaes, Netto JF, de Lima DP. Predicting and reducing dropout in virtual learning using machine learning techniques: A systematic review. In 2019 IEEE Frontiers in Education Conference (FIE) 2019;16:1-9. doi: 10.1109/FIE43999.2019.9028545.
  29. D’Errico F, Paciello M, Cerniglia L. When emotions enhance students’ engagement in e-learning processes. Journal of e-Learning and Knowledge Society. 2016; 12(4).
  30. Dhawan S, Online learning: A panacea in the time of COVID-19 crisis. Journal of educational technology systems. 2020;49(1):5-22. doi: 10.1177/0047239520934018.
  31. Petrie C. Spotlight: Quality education for all during COVID-19 crisis United Nations.2020. https://hundred.org/en/collections/quality-education-for-all-duringcoronavirus.
  32. Cardinas-Flamiano BG A, Return to Complete Face to Face Learning: Level of Students’ Academic Excitement and Challenges. Asian Journal of Research in Education and Social Sciences. 2022; 4(1): 317-327.
  33. Son C, Hegde S, Smith A, Wang X, Sasangohar F. Effects of COVID-19 on college students’ mental health in the United States: Interview survey study. Journal of medical internet research. 2020;22(9):e21279. https://preprints.jmir.org/preprint/21279.
  34. Baltà-Salvador R, Olmedo-Torre N, Peña M, Renta-Davids A I. Academic and emotional effects of online learning during the COVID-19 pandemic on engineering students. Education and information technologies. 2021;26(6):7407-7434. doi:10.1007/s10639-021-10593-1. PubMed PMID: 34108843. PMCID: PMC8179070.
  35. Kline RB. Principles and practice of structural equation modeling. Guilford publications. 2015; 8.
  36. Saekow A, Samson D. E-learning Readiness of Thailand’s Universities Comparing to the USA’s Cases. International Journal of e-Education, e-Business, e-Management and e-Learning. 2011; 1(2): 126. doi: 10.7763/IJEEEE.2011.V1.20.
  37. Yzidi S, Mohammadzadeh A, Rajab A. Investigating the relationship between learning styles, personality traits and students’ academic performance, Shahid University’s scientific-research bimonthly, 14th year, new period. 2006; 27 [In Persian].
  38. Pekrun R., Goetz T., Titz W, Perry R P. Academic emotions in students’ self-regulated learning and achievement: A program of quantitative and qualitative research. Educational Psychologist. 2002; 37: 91-106. doi:10.1207/S15326985EP3702_4.
  39. Nikdel F. Examining the relationship between perception of the classroom environment and motivational beliefs (goal orientation and academic self-concepts) with academic emotions and self-directed learning: the mediating role of academic emotions. PhD Thesis in Psychology, Kharazmi University; 2013 [In Persian].
  40. Sabbaghi S, Rabiei N, Sadeghi H. The relationship between the use of virtual social networks in educational interactions during the Covid-19 crisis and the academic performance of students with regard to the mediating role of the quality of learning experiences. Journal of Sabzevar University of Medical Sciences. 2022; 29(4): 475-484 [Persian].
  41. Farajollahi, Mehran, Zarrabian, Forozan, Zare, Azadeh. Design and development of web-based interactive education, Tehran: Payam Noor University Press; 2016.
  42. Talkhabi M, Bagheri Noaparast K, Bozorgi A, Sahafi L, Mohammadi A. The Coherence between Cognition and Emotion in Education. Advances in Cognitive Sciences 2016; 18 (3):68-79. http://icssjournal.ir/article-1-505-fa.html
  43. Noteborn, G., Carbonell, K. B., Dailey-Hebert, A., & Gijselaers, W. The role of emotions and task significance in virtual education. The internet and higher education, 2012; 15(3), 176-183.
  44. Aballay, L. N., Aciar, S. V., & Collazos, C. A. Emotions for virtual learning environments. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 2021; 16(3), 215-224.