A Study of Higher Education Students’ Expectations toward 21st-Century Blended Learning and the Influence of the Big Five Personality Traits

Main Article Content

Nurseeta Phoesalae
Nuttaporn Lawthong

Abstract

The purposes of this study were (1) to investigate higher education students’ expectations toward blended learning, and (2) to examine differences in these expectations according to personal factors and the Big Five personality traits. The sample consisted of 650 undergraduate students from Prince of Songkla University, Pattani Campus, selected through multi-stage sampling. The research instruments included the 21st-Century Blended Learning Expectation Scale for Undergraduate Students and the Big Five Inventory–2 Extra Short Form (BFI-2-XS), both of which were validated for content validity and reliability. Data were analyzed using chi-square statistics and the standard error of the difference between observed and expected frequencies. The results indicated that (1) the majority of students expected the Rotation Model of blended learning, in which assessment serves as a mechanism to support and enhance learning. They anticipated three to five assessment opportunities per semester and preferred feedback delivered through either cohort feedback or individual feedback channels. The most expected feedback type was general and facilitative elaborated feedback. Furthermore, students expected their learning outcomes to be evaluated using a criterion-referenced assessment approach. (2) Students with different personal factors and personality traits exhibited distinct expectations regarding certain aspects of blended learning.

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How to Cite
Phoesalae, N. ., & Lawthong, N. . (2025). A Study of Higher Education Students’ Expectations toward 21st-Century Blended Learning and the Influence of the Big Five Personality Traits. Journal of Inclusive and Innovative Education, 9(3), 111–128. retrieved from https://so01.tci-thaijo.org/index.php/cmujedu/article/view/283389
Section
Research Article

References

Abdulkader, F. (2024). Understanding blended learning from students’ perspectives: Challenges and opportunities in Saudi undergraduate settings. English Language Teaching, 17(4), 1–13.

Abubakar, B., & Adetimirin, A. (2015). Influence of computer literacy on postgraduates' use of e-resources in Nigerian university libraries. Library Philosophy and Practice (e-journal), 1230, 1-17.

Alkış, N., & Taşkaya Temizel, T. (2018). The impact of individual differences on e-learning participation through LMSs in higher education. Education and Information Technologies, 23(6), 2445–2468.

Arambewela, R., & Hall, J. (2009). An empirical model of international student satisfaction. Asia Pacific Journal of Marketing and Logistics, 21(4), 555–569.

Attali, Y., & Powers, D. (2010). Immediate feedback and opportunity to revise answers to open-ended questions. Educational and Psychological Measurement, 70(1), 22–35.

Bandura, A. (1977). Social learning theory. Englewood Cliffs: Prentice Hall.

Berenson, R., Boyles, G., & Weaver, A. (2008). Emotional intelligence as a predictor for success in online learning. International Review of Research in Open and Distributed Learning, 9(2), 1–17.

Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta‐analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243–1289.

Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74.

Brookhart, S. M. (2013). How to create and use rubrics for formative assessment and grading. Alexandria, VA: Association for Supervision & Curriculum Development (ASCD).

Costa, Jr, P. T., & McCrae, R. R. (1992). Revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI): Professional manual. Odessa, FL: Psychological Assessment Resources, Inc.

Evans, C. (2013). Making sense of assessment feedback in higher education. Review of Educational Research, 83(1), 70–120.

García-Aracil, A. (2009). European graduates’ level of satisfaction with higher education. Higher Education, 57(1), 1–21.

Green, J., Nelson, G., Martin, A. J., & Marsh, H. W. (2015). The causal ordering of self-concept and academic motivation and its effect on academic achievement. International Journal of Educational Research, 65, 1–11.

Kay, R., et al. (2014). The impact of STEM experience on student technology acceptance. Computers & Education, 75, 28–37.

Kintu, M. J., Zhu, C., & Kagambe, E. (2017). Blended learning effectiveness: The relationship between student characteristics, design features and outcomes. International Journal of Educational Technology in Higher Education, 14(7), 1-20.

Komarraju, M., et al. (2011). The Big Five personality traits, learning styles, and academic achievement. Personality and Individual Differences, 51(4), 472–477.

Lipko-Speed, A., Dunlosky, J., & Rawson, K. A. (2014). Does testing with feedback help grade-school children learn key concepts in science?. Journal of Applied Research in Memory and Cognition, 3(3), 171-176.

Mammadov, S. (2021). Big Five personality traits and academic performance: A meta-analysis. Journal of Personality, 89(2), 222–238.

Masantia, J. (2017). Chuthaphon Masantia. (2017). The development of a computer-based testing system with immediate feedback for learners with different ability levels: An application of the continuous response Rasch model (Doctoral dissertation). Faculty of Education, Chulalongkorn University).

McCrae, R. R., & Costa, P. T., Jr. (1999). In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (pp.139–153). New York: Guilford Press.

McCrae, R. R., & Costa, P. T., Jr. (2003). Personality in adulthood: A five-factor theory perspective (2nd ed.). New York: Guilford Press.

McCrae, R. R., & Costa, P. T., Jr. (2008). In O. P. John, R. W. Robins, & L. A. Pervin (Eds.), Handbook of personality: Theory and research (pp. 159–181). New York: Guilford Press.

Mofrad, L. (2020). The role of personality traits and learning styles in predicting the academic motivation of Iranian EFL students in blended learning environments. Journal of Language and Education, 6(2), 123–133.

Panadero, E., Jonsson, A., & Botella, J. (2017). Effects of self-assessment on self-regulated learning and self-efficacy: A meta-analysis. Educational Research Review, 22, 74–98.

Pekrun, R., Cusack, A., Murayama, K., Elliot, A. J., & Thomas, K. (2014). The power of anticipated feedback: Effects on students' achievement goals and achievement emotions. Learning and Instruction, 29, 115-124.

Phoesalae, N., & Lawthong, N. (2025). The Development of a Multidimensional Forced-Choice Situational Judgment Test for Assessing Undergraduate Students’ Expectations Toward Blended Learning in the 21st Century. Journal of Educational Measurement Mahasarakham University, 31(2).[in Thai]

Radloff, A., & Coates, H. (2010). Doing more for learning: Enhancing engagement and outcomes. Australasian Student Engagement Report. Camberwell, VIC: Australian Council for Educational Research (ACER).

Rust, R. T., & Oliver, R. L. (1994). In R. T. Rust & R. L. Oliver (Eds.), Service quality: New directions in theory and practice (pp. 1–19). New York: SAGE Publications.

Salleh, F. I. M., Baharum, H. I., & Shamsudin, S. (2017). Comparative study between flipped learning and flex model in English as second language classroom. Advanced Science Letters, 23(4), 2663–2666.

Singh, H., et al. (2018). Use of technology in science education: A review. Journal of Science Education and Technology, 27(5), 412–423.

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.

Staker, H., & Horn, M. B. (2012). Classifying K-12 Blended Learning. Mountain View, CA: Innosight Institute.

Varadwaj, P. K. (2017). Predicting students’ academic performance using Big Five personality traits and learning styles in a blended learning context. International Journal of Educational Research and Technology, 8(2), 18–26.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge: Harvard University Press.

Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology, 10, 3087(1)-3087(14).

Yastıbaş, G. Ç., & Yastıbaş, A. E. (2015). The effect of peer feedback on writing anxiety in Turkish EFL (English as a foreign language) students. Procedia-Social and Behavioral Sciences, 199, 530-538.

Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70.