Mobile Learning in Business English its Effect to South American Students’ Learning Styles in the COVID 19 Pandemic Era: Its Economic Implications

Authors

  • Joel Alanya-Beltran Universidad Tecnológica del Perú, Peru
  • Jeidy Panduro-Ramirez Universidad Tecnológica del Perú, Peru

DOI:

https://doi.org/10.25115/eea.v39i12.6394

Keywords:

mobile learning, education, COVID-19

Abstract

The adoption of M-learning and perceptual learning style preferences of South American EFL learners in a business English course were studied empirically. A descriptive correlational research design was used in this study. Data were gathered from 125 South American EFL students who were carefully sampled among a total of 184 students with mobile phones enrolled in a business English classes of selected South American university. The Mobile Learning Questionnaire (MLQ) and Perceptual Learning Style Preference Questionnaire were used in the study (PLSPQ). The data revealed that students in a business English course have a high level of M-learning adoption. It was discovered that respondents favor visual learning, group learning, individual learning, tactile learning, and auditory learning, with kinesthetic learning receiving the least attention. When students are grouped by gender and age, test results show that male respondents had stronger appeal to the utility, acceptability, enjoyment, facilitating conditions, and behavioral intention of M-learning than female respondents. Regardless of their age, respondents acknowledged the benefits of using M-learning in their business English course. Similarly, when the respondents are grouped by gender, no significant differences in learning style preferences are detected. However, the younger respondents prefer group learning, whilst the older respondents prefer individual learning. Finally, a link was discovered between M-learning usage and students' preferred learning styles. The positive link implies that the more M-learning students use, the more learning style preferences they have for group, tactile, visual, auditory, kinesthetic, and group learning tasks. This paper discusses the theoretical and educational consequences.

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References

Abouzeid, E., Fouad, S., Wasfy, N. F., Alkhadragy, R., Hefny, M., & Kamal, D. (2021). Influence of Personality Traits and Learning Styles on Undergraduate Medical Students’ Academic Achievement. Advances in Medical Education and Practice, 12, 769.

Al-Azawei, A., & Alowayr, A. (2020). Predicting the intention to use and hedonic motivation for mobile learning: A comparative study in two Middle Eastern countries. Technology in Society, 62, 101325.

Al-Emran, M., Mezhuyev, V., & Kamaludin, A. (2020). Towards a conceptual model for examining the impact of knowledge management factors on mobile learning acceptance. Technology in Society, 61, 101247.

Asongu, S. A., Adegboye, A., Ejemeyovwi, J., & Umukoro, O. (2021). The mobile phone technology, gender inclusive education and public accountability in Sub-Saharan Africa. Telecommunications Policy, 45(4), 102108.

Barrafrem, K., Västfjäll, D., & Tinghög, G. (2020). Financial well-being, COVID-19, and the financial better-than-average-effect. Journal of Behavioral and Experimental Finance, 28, 100410.

Bernacki, M. L., Greene, J. A., & Crompton, H. (2020). Mobile technology, learning, and achievement: Advances in understanding and measuring the role of mobile technology in education. Contemporary Educational Psychology, 60, 101827.

Chen, C. C., & Huang, P. H. (2020). The effects of STEAM-based mobile learning on learning achievement and cognitive load. Interactive Learning Environments, 1-17.

Chtourou, M. S., & Souiden, N. (2010). Rethinking the TAM model: time to consider fun. Journal of Consumer Marketing.

Crompton, H., & Burke, D. (2018). The use of mobile learning in higher education: A systematic review. Computers & Education, 123, 53-64.

Elsalem, L., Al-Azzam, N., Jum'ah, A. A., Obeidat, N., Sindiani, A. M., & Kheirallah, K. A. (2020). Stress and behavioral changes with remote E-exams during the Covid-19 pandemic: A cross-sectional study among undergraduates of medical sciences. Annals of Medicine and Surgery, 60, 271-279.

Fisher, R. A. (1992). Statistical methods for research workers. In Breakthroughs in statistics (pp. 66-70). Springer, New York, NY.

Ge, Z. G. (2021). Does mismatch between learning media preference and received learning media bring a negative impact on Academic performance? An experiment with e-learners. Interactive Learning Environments, 29(5), 790-806.

Islam, M. J. (2011). Language learning style preferences: Bangladeshi EFL learners. Harvest: Jahangirnagar Studies in Language and Literature, 26, 59-76.

Jossan, K. S., Gauthier, A., & Jenkinson, J. (2021). Cultural implications in the acceptability of game-based learning. Computers & Education, 174, 104305.

Kalloo, V., & Mohan, P. (2012). Correlating questionnaire data with actual usage data in a mobile learning study for high school mathematics. Electronic Journal of e-Learning, 10(1), pp76-89.

Khampirat, B. (2021). The Impact of Work-Integrated Learning and Learning Strategies on Engineering Students’ Learning Outcomes in Thailand: A Multiple Mediation Model of Learning Experiences and Psychological Factors. IEEE Access, 9, 111390-111406.

Khan, A. I., Al-Shihi, H., Al-Khanjari, Z. A., & Sarrab, M. (2015). Mobile Learning (M-Learning) adoption in the Middle East: Lessons learned from the educationally advanced countries. Telematics and Informatics, 32(4), 909-920.

Khedr, A. E., Idrees, A. M., & Alsheref, F. K. (2019). A Proposed Framework to Explore Semantic Relations for Learning Process Management. International Journal of e-Collaboration (IJeC), 15(4), 46-70.

Laksana, D. N. L. (2021). Implementation of online learning in the pandemic covid-19: Student perception in areas with minimum internet access. Journal of Education Technology, 4(4), 502-509.

Magulod Jr, G. C. (2019). Learning styles, study habits and academic performance of Filipino University students in applied science courses: Implications for instruction. JOTSE: Journal of Technology and Science Education, 9(2), 184-198.

Martin, A. (2020). How to optimize online learning in the age of coronavirus (COVID-19): A 5-point guide for educators. UNSW Newsroom, 53(9), 1-30.

Muñoz, V. A., Carby, B., Abella, E. C., Cardona, O. D., López-Marrero, T., Marchezini, V., ... & Wisner, B. (2020). Success, innovation and challenge: school safety and disaster education in South America and the Caribbean. International journal of disaster risk reduction, 44, 101395.

Mussa, I. H. (2020). Mobile Learning adoption in the Middle East: Limitations, Challenges and Features of the Mobile Devices. Int. J. Contemp. Manag. Inf. Technol, 1(1), 30-36.

Mutambara, D., & Bayaga, A. (2021). Determinants of mobile learning acceptance for STEM education in rural areas. Computers & Education, 160, 104010.

Naciri, A., Baba, M. A., Achbani, A., & Kharbach, A. (2020). Mobile learning in Higher education: Unavoidable alternative during COVID-19. Aquademia, 4(1), ep20016.

Navarro, O., Sanchez-Verdejo, F., Anguita, J., & Gonzalez, A. (2020). Motivation of university students towards the use of information and communication technologies and their relation to learning styles. International Journal of Emerging Technologies in Learning (iJET), 15(15), 202-218.

Oyelere, S. S., Suhonen, J., Shonola, S. A., & Joy, M. S. (2016, October). Discovering students mobile learning experiences in higher education in Nigeria. In 2016 IEEE Frontiers in Education Conference (FIE) (pp. 1-7). IEEE.

Qureshi, M. I., Khan, N., Hassan Gillani, S. M. A., & Raza, H. (2020). A Systematic Review of Past Decade of Mobile Learning: What we Learned and Where to Go. International Journal of Interactive Mobile Technologies, 14(6).

Ranjeeth, S., Latchoumi, T. P., & Paul, P. V. (2020). Role of gender on academic performance based on different parameters: Data from secondary school education. Data in brief, 29, 105257.

Saikat, S., Dhillon, J. S., Wan Ahmad, W. F., & Jamaluddin, R. (2021). A Systematic Review of the Benefits and Challenges of Mobile Learning during the COVID-19 Pandemic. Education Sciences, 11(9), 459.

Sitar‐Tăut, D. A. (2021). Mobile learning acceptance in social distancing during the COVID‐19 outbreak: The mediation effect of hedonic motivation. Human Behavior and Emerging Technologies, 3(3), 366-378.

Talan, T. (2020). The Effect of Mobile Learning on Learning Performance: A Meta-Analysis Study. Educational Sciences: Theory and Practice, 20(1), 79-103.

Talwar, M., Talwar, S., Kaur, P., Tripathy, N., & Dhir, A. (2021). Has financial attitude impacted the trading activity of retail investors during the COVID-19 pandemic?. Journal of Retailing and Consumer Services, 58, 102341.

Tan, T. H., & Liu, T. Y. (2004, August). The mobile-based interactive learning environment (MOBILE) and a case study for assisting elementary school English learning. In IEEE International Conference on Advanced Learning Technologies, 2004. Proceedings. (pp. 530-534). IEEE

Taufina, T., Chandra, C., & Kharisma, A. (2019, October). Technology integration in thematic learning to welcome the era of the industrial revolution 4.0 in elementary schools. In Proceeding International Seminar of Primary Education (Vol. 2).

Tkachuk, V., Yechkalo, Y., Semerikov, S., Kislova, M., & Hladyr, Y. (2020, October). Using mobile ict for online learning during covid-19 lockdown. In International Conference on Information and Communication Technologies in Education, Research, and Industrial Applications (pp. 46-67). Springer, Cham.

Turri, J. (2020). A Peculiar and Perpetual Tendency: An Asymmetry in Knowledge Attributions for Affirmations and Negations. Erkenntnis, 1-14.

Yuan, Y. P., Tan, G. W. H., Ooi, K. B., & Lim, W. L. (2021). Can COVID-19 pandemic influence experience response in mobile learning?. Telematics and Informatics, 64, 101676.

Additional Files

Published

2021-11-26