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My research interests include English language learning, Technology-assisted language learning, and student motivation. I plan to start with investigating the current status and perspectives of EFL undergraduate students in South Korea on using mobile- or web-based software for their English language learning. Then, I want to investigate EFL undergraduate students in the United States to see if there are any similarities or differences between EFL undergraduate students in South Korea and those in the US regarding the usage of mobile- or web-based language learning software and its impact on student motivation. I have two major goals at this point. One is to find certain features of language learning software that motivate or de-motivate EFL students. Based on the findings, I also intend to develop and test a software design to enhance EFL students' motivation and achievement in English language learning.

Technology-assisted language learning
& student motivation

According to the British Council (2013), English is now spoken by approximately 1.75 billion people. Crystal (2012) also stated that English is the most widely taught language in over 100 countries. Given that the number of English language learners (ELLs) has increased exponentially, many studies have investigated the second or foreign language acquisition of ELLs (Cooper & McIntyre, 1996; Albiladi & Alshareef, 2019). Particularly, the current study will focus on English as a foreign language (EFL) learners among the ELLs, who study English outside the English-speaking countries. This is partly because there has been relatively limited research on the unique learning experiences of EFLs from different non-English-speaking countries. 

In recent years, there has also been a line of research that focuses particularly on technology-assisted language learning (Godwin-Jones, 2017; Xu & Warschauer, 2020a; Chen, 2016), such as mobile-assisted language learning (MALL) or computer-assisted language learning (CALL), as technology has emerged and has been integrated into diverse learning environments. In addition, the advancement of technology also allowed learners to develop their own learning experiences outside of formal educational settings in various contexts of informal learning environments (Zheng, 2019; Terras & Ramsay, 2012). Accordingly, there has been an increase in studies that focused on improving learners’ motivation to persist in technology-assisted language learning (Kondo et al., 2012; Todaka, 2017).

In terms of motivation, Self-determination theory (SDT) has been adopted as a framework in recent studies as it provides a theoretical foundation for understanding student motivation. This theory offers empirical support for the basic psychological needs of human beings, which facilitates students’ autonomous motivation; needs of perceived competence, autonomy, and relatedness (Deci & Ryan, 2012). Social contexts around individuals affect the satisfaction of these basic psychological needs and the types of motivation (Deci & Ryan, 2012). Research has indicated that technology-assisted learning supports each element of basic psychological needs, and thus, enhances student motivation (Huang et al., 2019; Jeno et al., 2019; Chiu, 2021).  In this study, we will explore how technology-assisted learning, MALL and CALL, affect the motivation of EFL learners in South Korea.

Purpose of the current study

The purpose of this study is to explore EFL undergraduate students’ usage of mobile- and web-based software for language learning in South Korea. This study aims to assess elements that facilitate or impede students' language learning by looking into usage patterns and features of language learning software that students currently use. Moreover, the impact of MALL and CALL will be explored from the perspective of student motivation.

Research questions

RQ 1. Which mobile- or web-based software do current undergraduate EFL learners in South Korea use for their English language learning?

RQ 2. How are current undergraduate EFL learners in South Korea using mobile- or web-based software for their English language learning?

RQ 3. What features of mobile- and web-based software motivate undergraduate EFL learners in South Korea?

RQ 4. What features of mobile- and web-based software de-motivate undergraduate EFL learners in South Korea?

Methods

We will recruit 50-100 undergraduate student participants in South Korea to conduct a survey. Those who are 18 years old or older and have been studying English as a foreign language will be eligible to participate in this study. Survey questions will include which mobile- or web-based software students are currently using for their English language learning, if any. We will then conduct a follow-up interview with individual students who are willing to participate. Interview questions will include how they think about certain software they are currently using for their English language learning. 

References

Albiladi, W. S., & Alshareef, K. K. (2019). Blended learning in English teaching and learning: A review of the current literature.

Journal of Language Teaching and Research, 10(2), 232-238. http://dx.doi.org/10.17507/jltr.1002.03

British Council. (2013, 8 27). The English effect. The English effect.

https://www.britishcouncil.org/sites/default/files/english-effect-report-v2.pdf

Chen, X. (2016). Evaluating language-learning mobile apps for second-language learners. Journal of Educational Technology

Development and Exchange, 9(2). https://doi.org/10.18785/jetde.0902.03

Cooper, P., & McIntyre, D. (1996). Effective teaching and learning: Teachers’ and students’ perspectives.

McGraw-Hill Education (UK).

Chiu, T. K. F. (2021). Student engagement in K-12 online learning amid COVID-19: A qualitative approach from a self-

determination theory perspective. Interactive Learning Environment. https://doi.org/10.1080/10494820.2021.1926289

Crystal, D. (2012). English as a global language (2nd ed.). Cambridge University Press.

http://dx.doi.org/10.1017/CBO9781139196970

Deci, E. L., & Ryan, R. M. (2012). Motivation, personality, and development within embedded social contexts:  An overview of

self-determination theory. In R. M. Ryan (Ed.), Oxford library of psychology. The Oxford handbook of human motivation (pp.  85–107). Oxford University Press.

Godwin-Jones, R. (2017). Smartphones and language learning. Language Learning & Technology, 21(2), 3–17. 

https://llt.msu.edu/issues/june2017/emerging.pdf

Huang, Y. C., Backman, S. J., Backman, K. F., McGuire, F. A., & Moore, D. (2019). An investigation of motivation and experience

in virtual learning environments: A self-determination theory. Education and Information Technologies, 24(1), 591–611. https://doi.org/10.1007/s10639-018-9784-5

Jeno, L. M., Vandvik, V., Eliassen, S., & Grytnes, J. A. (2019). Testing the novelty effect of an m-learning tool on internalization

and achievement: A self-determination theory approach. Computers and Education, 128, 398–413. https://doi.org/10.1016/j.compedu.2018.10.008

Kondo, M., Ishikawa, Y., Smith, C., Sakamoto, K., Shimomura, H., & Wada, N. (2012). Mobile assisted language learning in

university EFL courses in Japan: Developing attitudes and skills for self-regulated learning. ReCall, 24(2), 169-187. https://doi.org/10.1017/S0958344012000055

Terras, M. M., & Ramsay, J. (2012). The five central psychological challenges facing effective mobile learning: A psychological

perspective on mobile learning. British Journal of Educational Technology, 43(5), 820-832. https://doi.org/10.1111/j.1467-8535.2012.01362.x

Todaka, Y. (2017). How to motivate de-motivated  Japanese college EFL learners. European Journal of English Language

Teaching, 2(4). https://doi.org/10.5281/ZENODO.823789

Xu, Y., & Warschauer, M. (2020, June). A content analysis of voice-based apps on the market for early literacy development. In

Proceedings of the Interaction Design and Children Conference (pp. 361-371). https://doi.org/10.1145/3392063.3394418

Zheng, L., Zhang, X., & Gyasi, J. F. (2019). A literature review of features and trends of technology-supported collaborative

learning in informal learning settings from 2007 to 2018. Journal of Computers in Education, 6(4), 529-561. https://doi.org/10.1007/s40692-019-00148-2

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