Unravelling Students’ Choice of Course Modality and Flow Experience in Multi-Access University Courses in Relation to Interpersonal Personality Traits

Authors

DOI:

https://doi.org/10.18357/otessaj.2025.5.1.76

Keywords:

distance education, online learning, improving classroom teaching, teaching and learning strategies, multi-access learning, synchronous hybrid learning, merging modalities

Abstract

Recent developments have led institutions into a transition towards more flexible educational models, such as synchronous hybrid education, i.e., having both on-site and remote students at the same time or multi-access education also providing asynchronous access. It is assumed that these new models can enhance accessibility for learners with diverse learning needs, creating opportunities for inclusive education. However, prior research investigating the relationship between student choice of course modality and personality, and the effect of this choice of delivery mode on affective learning outcomes remains underexplored. The current study filled this gap by exploring student choice behaviour regarding course modality, examining the influence of interpersonal personality traits on these choices, and assessing the impact of course modality on students’ flow experiences. This research builds upon prior research on synchronous hybrid education, digital personalized learning, personality, and flow. Our study shows evidence for the significant relation between degree of introversion–extraversion and the choice of course modality, with more introverted students tending to prefer the remote setting compared to the on-campus setting. Moreover, the findings confirmed the influence of course modality on flow experiences. In this respect, our study contributes to the research on personalized learning by showing that current technological evolutions provide choices about where students learn, in addition to what and how they learn. This creates a new dimension of adaptivity, opening possibilities for inclusive education, yet also adding new challenges.

References

Abbassi, M., Abbassi, W., Fenouillet, F., & Naceur, A. (2021). Validation of the flow scale related to physical education in Arabic language. Advances in Physical Education, 11(02), 246–260. https://doi.org/10.4236/ape.2021.112020

Abdelmalak, M. M. M., & Parra, J. L. (2018). Case study of HyFlex course design. In R. C. Sharma (Ed.), Innovative applications of online pedagogy and course design (pp. 298–317). IGI Global. https://doi.org/10.4018/978-1-5225-5466-0.ch015

Ahmad, N., & Abdulkarim, H. (2019). The Impact of flow experience and personality type on the intention to use Virtual World. International Journal of Human-Computer Interaction, 35(12), 1074–1085. https://doi.org/10.1080/10447318.2018.1509500

Augustine, A. A., & Hemenover, S. H. (2012). Extraversion, social interaction, and affect repair. In N. M. Seel (Ed.), Encyclopedia of the sciences of learning (1st ed., pp. 1253–1255). Springer US. https://doi.org/10.1007/978-1-4419-1428-6_1744

Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1). https://doi.org/10.18637/jss.v067.i01

Baumann, N. (2012). Autotelic personality. In S. Engeser (Ed.), Advances in flow research (pp. 165–186). Springer New York. https://doi.org/10.1007/978-1-4614-2359-1_9

Basham, J. D., Hall, T. E., Carter, R. A., & Stahl, W. M. (2016). An operationalized understanding of personalized learning. Journal of Special Education Technology, 31(3), 126–136. https://doi.org/10.1177/0162643416660835

Bell, J., Sawaya, S., & Cain, W. (2014). Synchromodal classes: Designing for shared learning experiences between face-to-face and online students. International Journal of Designs for Learning, 5(1), 68-82. https://doi.org/10.14434/ijdl.v5i1.12657

Beatty, B. (2007). Transitioning to an online world: Using HyFlex courses to bridge the gap. EdMedia + Innovate Learning. https://www.learntechlib.org/primary/p/25752/

Beatty, B. (2019). Hybrid-flexible course design. EdTech Books. https://doi.org/10.59668/33

Biasutti, M. (2011). Flow and optimal experience. In M. A. Runco & S. R. Pritzker (Eds.), Encyclopedia of creativity (2nd ed., pp. 522–528). Elsevier. https://doi.org/10.1016/B978-0-12-375038-9.00099-6

Bower, M., Dalgarno, B., Kennedy, G. E., Lee, M. J. W., & Kenney, J. (2015). Design and implementation factors in blended synchronous learning environments: Outcomes from a cross-case analysis. Computers and Education, 86, 1–17. https://doi:10.1016/j.compedu.2015.03.006

Bozkurt, A. (2022). A retro perspective on blended/hybrid learning: Systematic review, mapping and visualization of the scholarly landscape. Journal of Interactive Media in Education, 1. https://doi.org/10.5334/jime.751

Bredow, C. A., Roehling, P. V., Knorp, A. J., & Sweet, A. M. (2021). To flip or not to flip? A meta-analysis of the efficacy of flipped learning in higher education. Review of Educational Research, 91(6), 878–918. https://doi.org/10.3102/2F00346543211019122

Cain, W., Sawaya, S. & Bell, J. (2013). Innovating the Hybrid Small Group Model in a Synchromodal Learning Environment. In J. Herrington, A. Couros & V. Irvine (Eds.), Proceedings of EdMedia 2013--World Conference on Educational Media and Technology (pp. 1333-1339). Victoria, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved from https://www.learntechlib.org/primary/p/112129/.

Chapman, R. (2020). Defining neurodiversity for research and practice. In H. Rosqvist, N. Chown, & A. Stenning (Eds.), Neurodiversity Studies (1st ed., pp. 218-220). Routledge. https://doi.org/10.4324/9780429322297-21

Cheng, A. W., Rizkallah, S., & Narizhnaya, M. (2020). Individualism vs. collectivism. In B. J. Carducci, C. S. Nave, J. S. Mio, & R. E. Riggio (Eds.), The Wiley encyclopedia of personality and individual differences (Vol. 4, pp. 287–297). Wiley. https://doi.org/10.1002/9781118970843.ch313

Cohen, A., Nørgård, R.T., & Mor, Y. (2020). Hybrid learning spaces––Design, data, didactics. British Journal of Educational Technology, 51(4), 1039–1044. https://doi.org/10.1111/bjet.12964

Clayton, K., Blumberg, F., & Auld, D. P. (2010). The relationship between motivation, learning strategies and choice of environment whether traditional or including an online component. British Journal of Educational Technology, 41(3), 349–364. https://doi.org/10.1111/j.1467-8535.2009.00993.x

Costa, P. T., & McCrae, R. R. (1995). Domains and facets: Hierarchical personality assessment using the revised NEO personality inventory. Journal of Personality Assessment, 64(1), 21–50. https://doi.org/10.1207/s15327752jpa6401_2

Csikszentmihalyi, M. (1975). Beyond boredom and anxiety (1st ed.). Jossey-Bass. https://psycnet.apa.org/record/2000-12701-000

Delle Fave, A., & Bassi, M. (2016). Flow and psychological selection. In L. Harmat, F. Ø. Andersen, F. Ullén, J. Wright, & G. Sadlo (Eds.), Flow experience (pp. 3–19). Springer International Publishing. https://doi.org/10.1007/978-3-319-28634-1_1

Fabian, K., Smith, S., & Taylor-Smith, E. (2024). Being in two places at the same time: A future for hybrid learning based on student preferences. TechTrends. https://doi.org/10.1007/s11528-024-00974-x

Fenwick, T., Edwards, R., & Sawchuk, P. (2011). Emerging approaches to educational research: Tracing the socio-material. Routledge. https://doi.org/10.4324/9780203817582

Gruppen, L. D., Irby, D. M., Durning, S. J., & Maggio, L. A. (2019). Conceptualizing learning environments in the health professions. Academic Medicine, 94(7), 969–974. https://doi.org/10.1097/ACM.0000000000002702

Heller, K., Bullerjahn, C., & Von Georgi, R. (2015). The relationship between personality traits, flow-experience, and different aspects of practice behavior of amateur vocal students. Frontiers in Psychology, 6(DEC), 1–15. https://doi.org/10.3389/fpsyg.2015.01901

Heutte, J., Fenouillet, F., Martin-Krumm, C., Gute, G., Raes, A., Gute, D., Bachelet, R., & Csikszentmihalyi, M. (2021). Optimal experience in adult learning: Conception and validation of the flow in education scale (EduFlow-2). Frontiers in Psychology, 12, 1–12. https://doi.org/10.3389/fpsyg.2021.828027

Heutte, J., Kaplan, J., & Martin-Krumm, C. (2016). The EduFlow model: A contribution toward the study of optimal learning environments. In L. Harmat, F. Ørsted Andersen, F. Ullén, J. Wright, & G. Sadlo (Eds.), Flow experience: Emperical research and applications (pp. 127–143). Springer International Publishing. https://doi.org/10.1007/978-3-319-28634-1

Hünermund, P., & Louw, B. (2023). On the nuisance of control variables in causal regression analysis. Organizational Research Methods, 28(1), 138–151. https://doi.org/10.1177/10944281231219274

Irvine, V. (2009). The Emergence of Choice in “Multi-Access” Learning Environments: Transferring Locus of Control of Course Access to the Learner. In G. Siemens & C. Fulford (Eds.), Proceedings of ED-MEDIA 2009--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 746-752). Honolulu, HI, USA: Association for the Advancement of Computing in Education (AACE). Retrieved from https://www.learntechlib.org/primary/p/31583/

Irvine, V., Code, J., & Richards, L. (2013). Realigning higher education for the 21st-century learner through multi-access learning. MERLOT Journal of Online Learning and Teaching, 9(2). https://www.proquest.com/scholarly-journals/realigning-higher-education-21st-century-learner/docview/1500422332/se-2

Irvine, V. (2020). The landscape of merging modalities. EDUCAUSE Review, 55(4). https://er.educause.edu/articles/2020/10/the-landscape-of-merging-modalities

Liu, T., & Csikszentmihalyi, M. (2020). Flow among introverts and extraverts in solitary and social activities. Personality and Individual Differences, 167(June), 110197. https://doi.org/10.1016/j.paid.2020.110197

McCormack, M. (2023). 2023 Students and technology report: Flexibility, choice, and equity in the student experience. Research report. Boulder, CO: EDUCAUSE. https://www.educause.edu/ecar/research-publications/2023/students-and-technology-report-flexibility-choice-and-equity-in-the-student-experience/empowering-students-to-choose

McCrae, R. R., & Costa, P. T. (2008a). Empirical and theoretical status of the five-factor model of personality traits. In G. J. Boyle, G. Matthews, & D. H. Saklofske (Eds.), The SAGE handbook of personality theory and assessment (pp. 273–294). SAGE Publications Inc. https://doi.org/10.4135/9781849200462.n13

McCrae, R. R., & Costa, P. T. (2008b). The five-factor theory of personality. In O. P. John, R. W. Robins, & A. Pervin. Lawrence (Eds.), Handbook of personality: Theory and research (3rd ed., pp. 159–181). The Guilford Press.

McKellar, S. E., & Wang, M. (2023). Adolescents’ daily sense of school connectedness and academic engagement: Intensive longitudinal mediation study of student differences by remote, hybrid, and in-person learning modality. Learning and Instruction, 83, 101659. https://doi.org/10.1016/J.LEARNINSTRUC.2022.101659

McPartlan, P., Rutherford, T., Rodriguez, F., Shaffer, J. F., & Holton, A. (2021). Modality motivation: Selection effects and motivational differences in students who choose to take courses online. The Internet and Higher Education, 49, 100793. https://doi.org/10.1016/j.iheduc.2021.100793

Mesurado, B., & de Minzi, M. C. R. (2013). Child’s personality and perception of parental relationship as correlates of optimal experience. Journal of Happiness Studies, 14(1), 199–214. https://doi.org/10.1007/s10902-012-9324-8

Mentzer, N., Mammadova, E., Koehler, A., Mohandas, L., & Farrington, S. (2024). Analyzing the impact of basic psychological needs on student academic performance: A comparison of post-pandemic interactive synchronous hyflex and pre-pandemic traditional face-to-face instruction. Educational Technology Research and Development. https://doi.org/10.1007/s11423-024-10417-2

Moon, Y. J., Kim, W. G., & Armstrong, D. J. (2014). Exploring neuroticism and extraversion in flow and user generated content consumption. Information and Management, 51(3), 347–358. https://doi.org/10.1016/j.im.2014.02.004

Nakamura, J., & Csikszentmihalyi, M. (2014). The concept of flow. In M. Csikszentmihalyi (Ed.), Flow and the foundations of positive psychology (1st ed., pp. 239–263). Springer Netherlands. https://doi.org/10.1007/978-94-017-9088-8_16

Olčar, D. (2019). Personality traits as predictors of domain specific flow proneness. The European Proceedings of Social & Behavioural Sciences, 86–99. https://doi.org/10.15405/epsbs.2019.11.7

O’Neill, K., Lopes, N., Nesbit, J., Reinhardt, S., & Jayasundera, K. (2021). Modeling undergraduates’ selection of course modality: A large sample, multi-discipline study. The Internet and Higher Education, 48, 100776. https://doi.org/10.1016/j.iheduc.2020.100776

Park, J. O., Lee-Jayaram, J., Sato, E., Eto, Y., Kahili-Heede, M., Hirayama, K., & Berg, B. W. (2023). A scoping review of remote facilitation during simulation-based healthcare education. BMC Medical Education, 23(1), 592. https://doi.org/10.1186/s12909-023-04551-3

Patrick, S., Kennedy, K., & Powell, A. (2013). Mean what you say: Defining and integrating personalized, blended and competency education. https://eric.ed.gov/?id=ED561301

Peifer, C., & Tan, J. (2021). The psychophysiology of flow experience. In C. Peifer & S. Engeser (Eds.), Advances in flow research (2nd ed., pp. 191–230). Springer Cham. https://doi.org/10.1007/978-3-030-53468-4_8

Pelletier, K., Robert, J., Muscanell, N., McCormack, M, Reeves, J., Arbino, N., Grajek, S.,

Birdwell, T., Liu, D., Mandernach, J., Moore, A., Porcaro, A., Rutledge, R., Zimmern, J., (eds.) (2023). EDUCAUSE Horizon Report: 2023 Higher Education Edition. https://library.educause.edu/resources/2023/5/2023-educause-horizon-report-teaching-and-learning-edition

Raes, A., Detienne, L., Windey, I., & Depaepe, F. (2020a). A systematic literature review on synchronous hybrid learning: gaps identified. Learning Environments Research, 23(3). https://doi.org/10.1007/s10984-019-09303-z

Raes, A. (2022). Exploring Student and Teacher Experiences in Hybrid Learning Environments: Does Presence Matter? Postdigital Science and Education, 4(1), 138–159. https://doi.org/10.1007/S42438-021-00274-0/FIGURES/6

Raes, A., Vanneste, P., Pieters, M., Windey, I., van den Noortgate, W., & Depaepe, F. (2020b). Learning and instruction in the hybrid virtual classroom: An investigation of students’ engagement and the effect of quizzes. Computers & Education, 143, 103682. https://doi.org/10.1016/J.COMPEDU.2019.103682

Ross, S. R., & Keiser, H. N. (2014). Autotelic personality through a five-factor lens: Individual differences in flow-propensity. Personality and Individual Differences, 59, 3–8. https://doi.org/10.1016/j.paid.2013.09.029

Schmidt, J. A. (2010). Flow in education. In P. Peterson, E. Baker, & B. McGaw (Eds.), International encyclopedia of education (3rd ed., pp. 605–611). Elsevier. https://doi.org/10.1016/B978-0-08-044894-7.00608-4

Shernoff, D. J., Sannella, A. J., Schorr, R. Y., Sanchez-Wall, L., Ruzek, E. A., Sinha, S., & Bressler, D. M. (2017). Separate worlds: The influence of seating location on student engagement, classroom experience, and performance in the large university lecture hall. Journal of Environmental Psychology, 49, 55–64. https://doi.org/10.1016/j.jenvp.2016.12.002

Sjoberg, D. (2021). ggsankey (0.0.99999). https://github.com/davidsjoberg/ggsankey

Snow, R. (1989). Aptitude-treatment interaction as a framework for research on individual differences in learning. In P. L. Ackerman, R. J. Sternberg, & R. Glaser (Eds.), Learning and individual differences. W.H. Freeman.

Soto, C. J., & John, O. P. (2017). The next big five inventory (BFI-2): Developing and assessing a hierarchical model with 15 facets to enhance bandwidth, fidelity, and predictive power. Journal of Personality and Social Psychology, 113(1), 117–143. https://doi.org/10.1037/pspp0000096

Szeto, E. (2014). A comparison of online/face-to-face students’ and instructor’s experiences: Examining blended synchronous learning effects. Procedia - Social and Behavioral Sciences, 116, 4250–4254. https://doi.org/10.1016/j.sbspro.2014.01.926

Tian, Y., Bian, Y., Han, P., Wang, P., Gao, F., & Chen, Y. (2017). Physiological signal analysis for evaluating flow during playing of computer games of varying difficulty. Frontiers in Psychology, 8(JUL). https://doi.org/10.3389/fpsyg.2017.01121

Tse, D. C. K., Nakamura, J., & Csikszentmihalyi, M. (2021). Living well by “flowing’ well: The indirect effect of autotelic personality on well-being through flow experience. Journal of Positive Psychology, 16(3), 310–321. https://doi.org/10.1080/17439760.2020.1716055

Ullén, F., Harmat, L., Theorell, T., & Madison, G. (2016). Flow and individual differences – A phenotypic analysis of data from more than 10,000 twin individuals. In L. Harmat, F. O. Andersen, F. Ullén, J. Wright, & G. Sadlo (Eds.), Flow experience (pp. 267–288). Springer International Publishing. https://doi.org/10.1007/978-3-319-28634-1_17

UNESCO. (2020). Covid-19 response - hybrid learning (Issue July). https://unesdoc.unesco.org/ark:/48223/pf0000373767?posInSet=3%26queryId=b40003f4-2249-4974-84e4-acb9bc32fcf9

Vandewaetere, M., & Clarebout, G. (2014). Advanced technologies for personalized learning, instruction, and performance. In J. M. Spector, M. D. Merril, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (4th ed., pp. 425–437). Springer New York. https://doi.org/10.1007/978-1-4614-3185-5_34

Van Schoors, R., Elen, J., Raes, A., & Depaepe, F. (2021). An overview of 25 years of research on digital personalised learning in primary and secondary education: A systematic review of conceptual and methodological trends. British Journal of Educational Technology, 52(5), 1798–1822. https://doi.org/10.1111/bjet.13148

Vrijdags, A., Merlier, B., & Combe, M. (2020). Professional attitudes continuum questionnaire (PACQ) - Technical manual.

Wagner, M., Pishtari, G., & Ley, T. (2023). Here or there? Differences of on-site and remote students’ perceptions of usability, social presence, engagement, and learning in synchronous hybrid classrooms. In O. Viberg, I. Jivet, P. J. Muñoz-Merino, M. Perifanou, & T. Papathoma (Eds.), Responsive and sustainable educational futures: Vol. 14200 LNCS (pp. 446–458). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-42682-7_30

Walkington, C., & Bernacki, M. L. (2019). Personalizing algebra to students’ individual interests in an intelligent tutoring system: Moderators of impact. International Journal of Artificial Intelligence in Education, 29(1), 58–88. https://doi.org/10.1007/s40593-018-0168-1

Wang, H., & Lee, K. (2020). Getting in the flow together: The role of social presence, perceived enjoyment and concentration on sustainable use intention of mobile social network game. Sustainability, 12(17). https://doi.org/10.3390/SU12176853

Zeng, L. M., & Bridges, S. M. (2022). Factors that affect student choice of course modality and learning environment during COVID-19 in an Asian context. Proceedings of the 15th International Conference on Computer-Supported Collaborative Learning, 503–504.

Zeng, L. M., & Bridges, S. M. (2023). The effect of conceptions of learning and prior online course experiences on students’ choice of learning spaces for synchronous online learning during COVID-19. Australasian Journal of Educational Technology, 2023(3), 17–34. https://doi.org/10.14742/ajet.8345

Zydney, J. M., McKimmy, P., Lindberg, R., & Schmidt, M. (2019). Here or there instruction: Lessons learned in implementing innovative approaches to blended synchronous learning. TechTrends, 63(2), 123–132. https://doi.org/10.1007/s11528-018-0344-z

Downloads

Published

2025-10-22

How to Cite

Buseyne, S., & Raes, A. (2025). Unravelling Students’ Choice of Course Modality and Flow Experience in Multi-Access University Courses in Relation to Interpersonal Personality Traits. The Open/Technology in Education, Society, and Scholarship Association Journal, 5(1), 1–32. https://doi.org/10.18357/otessaj.2025.5.1.76

Issue

Section

Research Articles