Résumés
Abstract
This article examines the impact of personality traits, learning styles, gender, and online course factors (course difficulty, group affiliation, provided materials, etc.) in the academic success of students taking online courses and their overall success rate through traditional classes. Students’ performance in the online learning environment is still a new perception, and a fair numbers of details are still unknown, in stark contrast to the details known in regard to traditional learning methods. Different types of learners respond differently to online and traditional courses. A case study was performed in which students were asked to attend two online courses, with different difficulty levels, during one semester. One-way analysis of variance was used to determine which factors are significant for the academic performance of students taking online courses, as well as for their overall academic success. Findings from the case study indicate that female students score slightly better, course difficulty has impact on test results, emotional students are more susceptible to online environments, and learning styles are more difficult to identify in online classes.
Keywords:
- online education,
- character traits,
- learning styles,
- academic success,
- gender
Parties annexes
Bibliography
- Allen, I. E., & Seaman, J. (2011). Going the distance: Online education in the United States, 2011. Sloan Consortium. https://files.eric.ed.gov/fulltext/ED529948.pdf
- Allen, I. E., & Seaman, J. (2017). Digital compass learning: Distance education enrollment report 2017. Babson Survey Research Group. https://files.eric.ed.gov/fulltext/ED580868.pdf
- Altanopoulou, P., & Tselios, N. (2018). Big Five personality traits and academic learning in wiki-mediated collaborative activities: Evidence from four case studies. International Journal of Distance Education Technologies, 16(3), 81-92. https://doi.org/10.4018/ijdet.2018070105
- Bao, W. (2020). COVID ‐ 19 and online teaching in higher education: A case study of Peking University. Human Behavior and Emerging Technologies, 2(2), 113-115. https://doi.org/10.1002/hbe2.191
- Beer, C., Clark, K., & Jones, D. (2010). Indicators of engagement. In C. H. Steel, M. Keppell, P. Gerbic, & S. Housego (Eds.), Curriculum, technology and transformation for an unknown future: Proceedings ascilite Sydney 2010 (pp. 75-86). http://ascilite.org.au/conferences/sydney10/procs/Beer-full.pdf
- Bonk, C. J., Lee, M. M., Reeves, T. C., & Reynolds, T. H. (Eds.). (2015). MOOCs and open education around the world. Routledge. https://doi.org/10.4324/9781315751108
- Bozkurt, A. (2019). From distance education to open and distance learning: A holistic evaluation of history, definitions, and theories. In Handbook of research on learning in the age of transhumanism (pp. 252-273). IGI Global. https://doi.org/10.4018/978-1-5225-8431-5.ch016
- Clark, J. T. (2020). Distance education. In E. Iadanza (Ed.), Clinical engineering handbook (2nd ed., pp. 410-415). Academic Press. https://doi.org/10.1016/b978-0-12-813467-2.00063-8
- Crawford, J., Butler-Henderson, K., Rudolph, J., Malkawi, B., Glowatz, M., Burton, R., Magni, P. A., & Lam, S. (2020). COVID-19: 20 countries’ higher education intra-period digital pedagogy responses. Journal of Applied Learning & Teaching, 3(1), 1-20. https://doi.org/10.37074/jalt.2020.3.1.7
- Cronje, Johannes C. (2018) Learning 3.0: Rhizomatic implications for blended learning. In K. Persichitte, A. Suparman, & M. Spector (Eds.), Educational technology to improve quality and access on a global scale (pp. 9-20). Springer. https://doi.org/10.1007/978-3-319-66227-5_2
- Cuadrado-García, M., Ruiz-Molina, M. E., & Montoro-Pons, J. D. (2010). Are there gender differences in e-learning use and assessment? Evidence from an interuniversity online project in Europe. Procedia-Social and Behavioral Sciences, 2(2), 367-371. https://doi.org/10.1016/j.sbspro.2010.03.027
- Costa Jr, P. T., & McCrae, R. R. (1992). Four ways five factors are basic. Personality and Individual Differences, 13(6), 653-665. https://doi.org/10.1016/0191-8869(92)90236-i
- Davies, R. S., & West, R. E. (2018). Technology integration in schools. In J. Spector, M. Merrill, J. Elen, & M. Bishop (Eds.), Handbook of research on educational communications and technology (pp. 841-853). Springer. https://doi.org/10.1007/978-1-4614-3185-5_68
- Diseth, Å. (2013). Personality as an indirect predictor of academic achievement via student course experience and approach to learning. Social Behavior and Personality: An International Journal, 41(8), 1297-1308. https://doi.org/10.2224/sbp.2013.41.8.1297
- Downes, S. (2020). Recent work in connectivism. European Journal of Open, Distance and E-Learning, 22(2), 113-132. https://doi.org/10.2478/eurodl-2019-0014
- Essien, A. M. (2015). Effectiveness of cooperative learning methodology in improving students’ learning attitudes towards English language. International Journal of Arts & Sciences, 8(2), 119-127. http://www.universitypublications.net/ijas/0802/html/DE4C352.xml
- Faulconer, E. K., Griffith, J. C., Wood, B. L., Acharyya, S., & Roberts, D. L. (2018). A comparison of online and traditional chemistry lecture and lab. Chemistry Education Research and Practice, 19(1), 392-397. https://doi.org/10.1039/c7rp00173h
- Figlio, D. N., Rush, M., & Yin, L. (2010). Is it live or is it Internet? Experimental estimates of the effects of online instruction on student learning (Working Paper 16089). National Bureau of Economic Research. https://doi.org/10.3386/w16089
- Fleming, N. D. (1987). VARK inventory. Retrieved January, 20, 2003 https://vark-learn.com/introduction-to-vark/the-vark-modalities/
- Fleming, N., & Baume, D. (2006). Learning styles again: VARKing up the right tree! Educational Developments, 7(4), 4-7. https://www.vark-learn.com/wp-content/uploads/2014/08/Educational-Developments.pdf
- Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64-71. https://doi.org/10.1007/s11528-014-0822-x
- Geng, S., Law, K. M., & Niu, B. (2019). Investigating self-directed learning and technology readiness in blending learning environment. International Journal of Educational Technology in Higher Education, 16(1), Article 17. https://doi.org/10.1186/s41239-019-0147-0
- Glazier, R. A., Hamann, K., Pollock, P. H., & Wilson, B. M. (2020). Age, gender, and student success: Mixing face-to-face and online courses in political science. Journal of Political Science Education, 16(2), 142-157. https://doi.org/10.1080/15512169.2018.1515636
- Harvey, H. L., Parahoo, S., & Santally, M. (2017). Should gender differences be considered when assessing student satisfaction in the online learning environment for millennials? Higher Education Quarterly, 71(2), 141-158. https://doi.org/10.1111/hequ.12116
- Henderikx, M., Kreijns, K., Castano Munoz, J., & Kalz, M. (2019). Factors influencing the pursuit of personal learning goals in MOOCs. Distance Education, 40(2), 187-204. https://doi.org/10.1080/01587919.2019.1600364
- Howie, D. (2011). Teaching students thinking skills and strategies: A framework for cognitive education in inclusive settings. Jessica Kingsley Publishers. https://www.ibs.it/teaching-students-thinking-skills-strategies-libro-inglese-dorothy-howie/e/9781843109501
- Husmann, P. R., & O’Loughlin, V. D. (2019). Another nail in the coffin for learning styles? Disparities among undergraduate anatomy students’ study strategies, class performance, and reported VARK learning styles. Anatomical sciences education, 12(1), 6-19. https://doi.org/10.1002/ase.1777
- Icekson, T., Kaplan, O., & Slobodin, O. (2020). Does optimism predict academic performance? Exploring the moderating roles of conscientiousness and gender. Studies in Higher Education, 45(3), 635-647. https://doi.org/10.1080/03075079.2018.1564257
- Idrizi, E., Filiposka, S., & Trajkovik, V. (2018, September). Character traits in online education: Case study. In S. Kalajdziski & N. Ackovska (Eds) ICT 2018: ICT Innovations 2018. Engineering and Life Sciences (pp. 247-258). Springer, Cham. https://doi.org/10.1007/978-3-030-00825-3_21
- Idrizi, E., & Filiposka, S. (2018). VARK learning styles and online education: Case Study. Learning, 5-6. https://www.researchgate.net/publication/327869001_VARK_Learning_Styles_and_Online_Education_Case_Study
- Ilgaz, H., & Gulbahar, Y. (2017). Why do learners choose online learning: The learners’ voices. International Association for Development of the Information Society. https://eric.ed.gov/?id=ED579379
- Kara, M., Erdoğdu, F., Kokoç, M., & Cagiltay, K. (2019). Challenges faced by adult learners in online distance education: A literature review. Open Praxis, 11(1), 5-22. https://doi.org/10.5944/openpraxis.11.1.929
- Keller, H., & Karau, S. J. (2013). The importance of personality in students’ perceptions of the online learning experience. Computers in Human Behavior, 29(6), 2494-500. https://doi.org/10.1016/j.chb.2013.06.007
- Kirschner, P. A. (2017). Stop propagating the learning styles myth. Computers & Education, 106, 166-171. https://doi.org/10.1016/j.compedu.2016.12.006
- Komarraju, M., Karau, S. J., Schmeck, R. R., & Avdic, A. (2011). The Big Five personality traits, learning styles, and academic achievement. Personality and Individual Differences, 51(4), 472-477. https://doi.org/10.1016/j.paid.2011.04.019
- Köseoglu, Y. (2016). To what extent can the Big Five and learning styles predict academic achievement. Journal of Education and Practice, 7(30), 43-51. https://files.eric.ed.gov/fulltext/EJ1118920.pdf
- McCarty, C., Bennett, D., & Carter, S. (2013). Teaching college microeconomics: Online vs. traditional classroom instruction. Journal of Instructional Pedagogies, 11. https://eric.ed.gov/?id=EJ1097170
- Mirza, M. A., & Khurshid, K. (2020). Impact of VARK learning model at tertiary level education. International Journal of Educational and Pedagogical Sciences, 14(5), 359-366. https://publications.waset.org/10011198/impact-of-vark-learning-model-at-tertiary-level-education
- Nakayama, M., Mutsuura, K., & Yamamoto, H. (2017). Effectiveness of student’s note-taking activities and characteristics of their learning performance in two types of online learning. International Journal of Distance Education Technologies, 15(3), 47-64. https://doi.org/10.4018/ijdet.2017070104
- Noroozi, O., Hatami, J., Bayat, A., van Ginkel, S., Biemans, H. J., & Mulder, M. (2018). Students’ online argumentative peer feedback, essay writing, and content learning: Does gender matter? Interactive Learning Environments, 6, 698-712. https://doi.org/10.1080/10494820.2018.1543200
- Page, J., Meehan-Andrews, T., Weerakkody, N., Hughes, D. L., & Rathner, J. A. (2017). Student perceptions and learning outcomes of blended learning in a massive first-year core physiology for allied health subjects. Advances in Physiology Education, 41(1), 44-55. https://doi.org/10.1152/advan.00005.2016
- Poropat, A. E. (2009). A meta-analysis of the five-factor model of personality and academic performance. Psychological Bulletin, 135(2), 322-338. https://doi.org/10.1037/a0014996
- Redecker, C., Leis, M., Leendertse, M., Punie, Y., Gijsbers, G., Kirschner, P., Stoyanov, S., & Hoogveld, B. (2011). The future of learning: Preparing for change. Publications Office of the European Union. https://doi.org/10.2791/64117
- Rice, M. F., Lowenthal, P. R., & Woodley, X. (2020). Distance education across critical theoretical landscapes: Touchstones for quality research and teaching. Distance Education, 41(3), 319-325. https://doi.org/10.1080/01587919.2020.1790091
- Sandu, M. (2019). Investigating personality traits and intelligence as predictors of academic performance and academic motivation. [Doctoral dissertation, National College of Ireland]. Semantic Scholar. https://www.semanticscholar.org/paper/Investigating-Personality-Traits-and-Intelligence-Sandu/ce27950afc1482a94d002c515994a77a4e0f99f0
- Seaman, J. E., Allen, I. E., & Seaman, J. (2018). Grade increase: Tracking distance education in the United States. Babson Survey Research Group. https://eric.ed.gov/?id=ED580852
- Siemens, G., Gašević, D., & Dawson, S. (2015). Preparing for the digital university: A review of the history and current state of distance, blended, and online learning. https://doi.org/10.13140/RG.2.1.3515.8483
- Simonson, M., Zvacek, S. M., & Smaldino, S. (2019). Teaching and learning at a distance: Foundations of distance education (7th ed.). IAP.
- Stojilović, M., Filiposka, S., Krsteska, A., Vidosavljević, A., Janev, V., & Vraneš, S. (2012). Students’ perception of IT curricula and career opportunities in Serbia and Macedonia. In A. Béraud, A. S. Godfroy, & K. Michel (Eds.), GIEE 2011: Gender and Interdisciplinary Education for Engineers (pp. 241-253). SensePublishers. https://doi.org/10.1007/978-94-6091-982-4_18
- Talebian, S., Mohammadi, H. M., & Rezvanfar, A. (2014). Information and communication technology (ICT) in higher education: Advantages, disadvantages, conveniences and limitations of applying e-learning to agricultural students in Iran. Procedia-Social and Behavioral Sciences, 152, 300-305. https://doi.org/10.1016/j.sbspro.2014.09.199
- Tawfik, Y., Samy Eldeeb, M., & Elwy, E. (2017). Behaviourism, cognitivism and constructivism paradigm for teaching and learning. University of Greenwich. http://central-library.msa.edu.eg:8009/xmlui/handle/123456789/2706
- Toquero, C. M. (2020). Challenges and opportunities for higher education amid the COVID-19 pandemic: The Philippine context. Pedagogical Research, 5(4). https://doi.org/10.29333/pr/7947
- Tseng, K. C., & Chu, S. Y. (2010). Traditional versus online courses, efforts, and learning performance. The Journal of Human Resource and Adult Learning, 6(1), 115-121. http://www.hraljournal.com/Page/14%20Kuang-Cheng%20Tseng.pdf
- Uliaszek, A. A., Al-Dajani, N., Sellbom, M., & Bagby, R. M. (2019). Cross-validation of the demoralization construct in the Revised NEO Personality Inventory. Psychological Assessment, 31(2), 159-166. https://doi.org/10.1037/pas0000655
- Wu, F., & Lai, S. (2019). Linking prediction with personality traits: A learning analytics approach. Distance Education, 40(3), 330-349. https://doi.org/10.1080/01587919.2019.1632170
- Wu, J. Y., & Cheng, T. (2019). Who is better adapted in learning online within the personal learning environment? Relating gender differences in cognitive attention networks to digital distraction. Computers & Education, 128, 312-329. https://doi.org/10.1016/j.compedu.2018.08.016
- Zhang, X., Chen, G., & Xu, B. (2020). The influence of group Big-Five personality composition on student engagement in online discussion. International Journal of Information and Education Technology, 10(10), 744-750. https://doi.org/10.18178/ijiet.2020.10.10.1452