Sophia University Junior College Division Faculty Journal
第 45 号, 2024, 127-137

Research Note

Exploring Generative AI Tools for English
Language Learning: Student Adoption andPerceptions
Bradley Irwin
Abstract
This study examines the adoption and perception of generative AI, specifically
ChatGPT, as a study tool among university students in Japan. With a focus on
preliminary data, it seeks to elucidate students’ awareness, current use, and potential
future utilization of generative AI in their academic pursuits. The research utilizes
a survey methodology to gather quantitative data from 101 students, revealinghigh awareness but varied adoption rates. While many students do not currently
use ChatGPT in their studies, a significant majority express an intention to do so,
anticipating benefits such as time-saving and improved research capabilities. Factors
influencing non-use include concerns about accuracy and ethical implications. This
paper contributes to the discourse on AI in education, highlighting the nuanced student
perspectives and the need for ongoing research to navigate the rapidly evolving AI
landscape in educational settings.

Introduction
The integration of Artificial Intelligence (AI) in education has witnessed substantial
recent growth, leading to innovative tools and methodologies that aim to enhance
the learning experience. Among these innovations, generative AI (herein referred toas GenAI) is emerging as a prominent player, demonstrating a remarkable ability togenerate human-like text responses. The rapid advancement of GenAI has introduced
opportunities, as well as challenges, in language education.
Despite this advancement, there is a noticeable gap in understanding how
university students are incorporating these AI tools into their academic endeavors,
especially in non-Western educational contexts (Crompton & Burke, 2023). The research
described in this paper seeks to bridge this gap, aiming to shed light on the extent towhich Japanese university students are aware of and utilize, GenAI in their studies.

─ 127 ─Bradley Irwin

The specific objectives of this research are multifaceted. Primarily, it seeks todetermine the level of awareness and usage of GenAI among university students,
providing insight into how these tools are impacting their academic lives. Additionally,
the study aims to identify the various purposes for which students currently use, or
intend to use, GenAI, exploring a range of applications from study aid to research
assistance. A critical aspect of this research is to uncover the factors that influence
students’ decisions to adopt or refrain from using this technology, delving into theperceptions, attitudes, and external influences that play a role in these decisions. Lastly,
the study investigates the potential impact of GenAI on students’ learning experiences
and outcomes, striving to understand how these tools can shape and influence theiracademic journeys.
By exploring these dimensions, this research aims to contribute valuable insights
to the ongoing discourse surrounding the adoption of GenAI in education, providing
a nuanced understanding of student perceptions and usage in a Japanese university
setting.

Background and Literature Review
2.1 Generative AI in Language Learning
Generative AI, particularly models like GPT (Generative Pre-trained Transformer),has revolutionized numerous fields, including natural language processing and machinelearning. Its application in language learning has garnered significant attention,
demonstrating the potential to aid language acquisition, provide instant feedback, andcreate interactive and personalized learning experiences (Hou, 2020; Tan et al., 2023;
Ulla et al., 2023). GenAI, especially large language models such as OpenAI’s GPT-3.5,
are now being explored for their capacity to not only impact the learning and teachingprocess but also to empower researchers in the field of language education (Pack &Maloney, 2023). According to Cambridge English (2023), the rapid development of GenAI
is set to significantly enhance the effectiveness and accessibility of language education.

2.2 Adoption of AI Tools in Education
The adoption of AI tools in educational settings has been subject to extensive
research (Yanhua, 2020). Studies have shown a variety of factors influencing students’
willingness to utilize these technologies, ranging from perceived usefulness and ease ofuse, to trust in the technology and individual attitudes toward AI (Zhang & Aslan, 2021;

─ 128 ─

Exploring Generative AI Tools for English Language Learning: Student Adoption and Perceptions

Wang et al. 2021; Kizilcec, 2023). Despite the potential of AI-based adaptive learning
platforms to transform educational practices, their adoption in schools has been slower
than anticipated, which raises questions about the factors influencing this adoption
and the extent to which these factors affect teachers’ engagement with the technology(Cukurova et al., 2023).

2.3 ChatGPT in Academic Settings
ChatGPT, as a specific instance of GenAI, has found its way into academic settings,
assisting students in tasks such as essay writing, researching, and studying. Researchon its impact has been emerging, with studies examining how students perceive thesetools and the extent to which they integrate them into their academic practices (Bringula,2023; Kohnke et al., 2023; Malik et al., 2023). The motivations driving academics toadopt ChatGPT vary, with considerations of academic integrity playing a significant
role in adoption behavior (Bin-Nashwan, 2023). Furthermore, the potential benefits andchallenges of using ChatGPT in higher education settings, particularly its effects onteaching, learning, research, and student assessment, are under investigation (Fütterer
et al., 2023).

2.4 Cultural and Contextual Factors
Cultural and contextual factors play a significant role in technology adoption.
Riberio (2020) notes that UNESCO has pinpointed challenges teachers encounter with
AI comprehension and integration into teaching, shedding light on the cultural andsituational aspects that impact the adoption of AI tools. In the Japanese educational
context, studies have explored the integration of technology in classrooms, revealing
unique challenges and opportunities (Stout & Yamauchi, 2012; Mitomo, 2020; Tanaka& Saito, 2021). However, research specific to AI tool adoption in Japan is still limited,highlighting a gap this study aims to address.

2.5 Potential Impact on Learning Outcomes
The impact of GenAI tools on learning outcomes is a critical area of investigation.
Preliminary studies have shown both positive and negative effects, depending on factors
such as the implementation method, student engagement, and the nature of the task at
hand (Semerikov et al., 2021). The integration of AI in education has been associatedwith a paradigm shift in teaching and learning, offering unparalleled opportunities
as well as complex challenges (Alasadi & Baiz, 2023). Chiu (2023) identified GenAI─ 129 ─Bradley Irwin

technologies as playing multiple roles in education across learning, teaching,assessment, and administration domains. Moreover, Relmasira et al. (2023) encourage
educators to seize the opportunity to prepare students to leverage GenAI in meaningful
ways and to experiment creatively with its use in educational settings.

Methodology
3.1 Research Design
The primary aim of this study is to explore the adoption, usage, and perceptionsof GenAI tools, specifically ChatGPT, among English language learners at Japanese
universities. To achieve this, a survey methodology was employed, providing a
structured yet flexible means of gathering quantitative data on students’ awareness,
usage patterns, and attitudes towards these tools.

3.2 Data Collection
Data was collected through Google Forms, a widely used platform for creating anddistributing surveys. The survey was comprised of 23 questions (9 multiple-choice and
14 Likert-scale), designed to capture a comprehensive view of the students’ interactions
and perceptions of GenAI. To ensure clarity and accessibility, the questions were
provided in both English and Japanese, minimizing language barriers and enhancing
the validity of the responses. The survey questions and responses were translated by the
researcher (with the aid of machine translation) and checked for accuracy by a Japanesecolleague.
Participants were assured of their anonymity, and participation was made entirely
optional, fostering an environment where respondents could provide honest and accurate
answers. The nature of the data collected was self-assessment, relying on participants’
self-reported knowledge, behaviors, and attitudes.

3.3 Participants
The survey garnered participation from 101 university students resulting in 97
complete and usable responses. Responses were collected from students majoringin English, global communication, or international relations from universities in
Kanagawa, Tokyo, and Shizuoka. Although the participants’ exact demographics were
not provided, most responses likely originated from first and second-year students,
given that the surveys were predominantly disseminated among those year groups.
Additionally, the diversity in responses suggests a range of experiences and perspectives

─ 130 ─

Exploring Generative AI Tools for English Language Learning: Student Adoption and Perceptions

concerning generative AI tools.

3.4 Survey Questions
The survey comprised a series of multiple-choice questions, designed to address
various aspects of the students’ engagement with GenAI. The questions focused on:•	Awareness and initial exposure to GenAI (specifically ChatGPT) and similar
tools (DALL-E2, Speechify, Midjourney, etc.).
•

Usage of GenAI in academic studies, including purposes and frequency.

•

Factors influencing the decision to use or not use generative AI.

•

Anticipated future use and perceived benefits of AI in education.

Participants were also given the option to provide their own answers under ‘other’for questions where predefined options may not have fully captured their experiences or
opinions.

Preliminary Findings
4.1 Awareness and Initial Exposure
The survey data indicates a high level of awareness of GenAI tools among
participants, with 94.8% of the respondents acknowledging that they have heard of
ChatGPT specifically. The initial exposure to this tool is primarily through online news
(54.3%) and social media (28.7%), highlighting the significant role of digital channels
in disseminating information about AI technology. Recommendations from instructors(6.2%), peers (5.8%), and advertisements (5.0%) accounted for the remaining ways thatstudents first became familiar with the technology.

4.2 Usage in Academic Studies
Despite the high level of awareness, a majority of the students (60.8%) reported
that they do not use GenAI tools for their academic studies, including subjects beyond
language learning. This suggests a discrepancy between awareness and actual usage,
raising questions about the factors that influence adoption.

4.3 Purposes for Using ChatGPT
ChatGPT usage for academic purposes among students varies, primarily for
research and information gathering (70.0%), idea generation (47.5%), and writing
skills enhancement (35.0%). A minority (7.5%) also practice conversation with the tool,─ 131 ─Bradley Irwin

reflecting its wide-ranging utility. (Multiple responses to usage were permitted.)

4.4 Factors Influencing Non-Usage
For students who refrain from using ChatGPT in their studies, concerns aboutaccuracy and reliability (47.3%) were the most prominent factors, followed by ethicalconcerns (31.7%) and perceived usefulness (28.6%). Ease of use was a factor for a smaller
portion of students (12.7%), suggesting that the tool’s user-friendliness is not a major
barrier to adoption.

4.5 Frequency of Use
The frequency of usage among the students is skewed towards the lower end, with
60.8% never using GenAI for their studies, 20.2% using it rarely, and 17.0% occasionally.
Only a small percentage (2.0%) reported using GenAI very frequently.

4.6 Future Use and Anticipated Benefits
Looking ahead, 68.0% of the students anticipate using ChatGPT or similar GenAI
tools for their academic studies in the future. The envisioned uses include research andinformation gathering (72.3%), generating ideas (60.0%), and improving writing skills(40.0%). The specific benefits students anticipate from using these tools in the future are
predominantly time-saving (62.0%), improved research and information retrieval (54.3%),
and an enhanced understanding of academic content (41.3%). (Again, participants wereallowed to select all answers that they believed applied to their future potential use of
AI in educational settings.)

Discussion
5.1 Awareness and Initial Exposure
The high level of awareness of GenAI-powered tools among university students inJapan indicates a high level of dissemination of information through digital channels.
This is evident from the 94.8% of participants who have heard of or used ChatGPT,
primarily learning about them through online news and social media. This widespreadawareness, however, does not directly translate into usage for academic purposes,
suggesting that mere awareness might not be sufficient to drive adoption.

5.2 Adoption and Usage in Academia
The study reveals a notable gap between awareness and actual use of GenAI in─ 132 ─

Exploring Generative AI Tools for English Language Learning: Student Adoption and Perceptions

academic settings, with over 60.0% of students not utilizing these tools for their studies.
This disjunction raises critical questions about the factors influencing adoption andhow they might be addressed to encourage the constructive use of AI tools in education.
The reasons for not using these tools, including concerns about its accuracy, reliability,
perceived usefulness, and ethical considerations, offer valuable insights into thechallenges associated with its adoption.
Although outside the scope of this research, it has been observed that there isno unified policy among universities regarding the ethical use of GenAI. While someadministrations actively encourage educators to explore its use in classrooms, otherinstitutions have issued blanket bans. These varied stances may lead to confusion
among students about whether or not using AI in their studies may lead to accusationsof academic misconduct.

5.3 Purposes and Frequency of Use
For the minority of students who do use GenAI, the purposes are diverse, ranging
from research and information gathering to improving writing skills. However, thefrequency of use is skewed towards rare usage, highlighting a potential area for further
exploration and understanding. Identifying the factors that influence the frequency of AI
tool use can provide important insights into their role in academic practices.

5.4 Future Prospects and Anticipated Benefits
Looking forward, a significant portion of students (68.0%) foresee themselves using
GenAI or similar tools in their future studies, anticipating benefits such as time-saving,
improved research and information retrieval, and enhanced understanding of academic
content. This perspective indicates that future adoption patterns may be influenced byovercoming present obstacles and improving the perceived value of these tools.

5.5 Potential Limitations of the Study
While this study provides important insights into the adoption and perception of
GenAI among university students in Japan, several limitations must be acknowledged.
First, the study’s reliance on self-reported data may lead to biases in the responses, as
students might overestimate their awareness or underreport their usage due to social
desirability or ethical concerns. Additionally, the sample size of 101 participants, while
offering a glimpse into the students’ perspectives, may not be sufficiently representativeof the wider student population in Japan. This limits the generalizability of the findings.

─ 133 ─Bradley Irwin

Another potential limitation is the rapidly evolving nature of GenAI technology.
The findings of this study, while current, may quickly become outdated as new
advancements in AI are continuously being made, potentially altering the landscapeof AI in education. Furthermore, the cultural and linguistic specificity of the study,
focusing solely on university students in Japan, means that the findings might not apply
to students in different cultural or educational contexts. Lastly, the study’s focus on
GenAI tools in language learning contexts might have overlooked broader applications ofthese technologies in other academic disciplines, which could offer different insights into
student adoption and perceptions.

Conclusion
This preliminary report has explored the current state of adoption, usage, andperceptions of GenAI among university students in Japan, shedding light on the complex
interplay between awareness, usage patterns, and influencing factors. The findings
reveal a range of opportunities and challenges, indicating that more research andexploration are required to understand the role of AI-powered tools in academic settings.
As the field of GenAI continues to evolve, understanding the factors that influence
student adoption and usage becomes increasingly crucial. By addressing the concerns
about accuracy, reliability, and ethical implications, and enhancing the perceived
usefulness of these tools, there is potential to transform the academic landscape,fostering a more seamless integration of AI-powered tools in educational settings.
This study serves as a stepping stone toward a comprehensive understanding of
the role of GenAI in education, providing insights that can inform future research,
policy, and practice. However, due to the rapidly evolving nature of AI technology, it
is important to emphasize the need for continuous data collection and observation in
future research. As AI tools like ChatGPT evolve and become more integrated into
educational settings, student behaviors, attitudes, and perceptions are likely to shiftcorrespondingly. Repeated studies, ideally at regular intervals, will be instrumental intracking these changes and understanding the long-term implications of AI integrationin education.
An ongoing research effort is crucial not only for understanding changes in GenAI
usage in education but also for identifying emerging trends and challenges that students
might face as they adapt to new technologies. By continually collecting data, researchersand educators can stay ahead of these changes, ensuring that their strategies, policies,
and practices evolve in tandem with the technology and the needs of the students.

─ 134 ─

Exploring Generative AI Tools for English Language Learning: Student Adoption and Perceptions

Furthermore, longitudinal studies would allow for a more comprehensive
understanding of how the use of AI in education impacts student learning outcomes overtime. This could include aspects such as academic performance, engagement, motivation,and the development of critical thinking and problem-solving skills. Understanding
these impacts will be key to optimizing the use of AI in educational contexts andensuring that these tools serve as beneficial aids in the learning process rather than as
mere novelties.

References
Alasadi, E. A., & Baiz, C. R. (2023). Generative AI in education and research:
Opportunities, concerns, and solutions. Journal of Chemical Education, 100(8),2965-2971.
Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023). Use of ChatGPT in academia:
Academic integrity hangs in the balance. Technology in Society, 75. https://doi.
org/10.1016/j.techsoc.2023.102370
Bringula, R. (2023). What do academics have to say about ChatGPT? A text mining
analytics on the discussions regarding ChatGPT on research writing. AI and Ethics,
1-13. https://link.springer.com/article/10.1007/s43681-023-00354-w
Cambridge English. (2023). Generative AI for English. Cambridge Assessment English.
https://www.cambridgeenglish.org/english-research-group/generative-ai-for-english/
Chiu, T. K. (2023). The impact of Generative AI (GenAI) on practices, policies andresearch direction in education: a case of ChatGPT and Midjourney. Interactive
Learning Environments, 1-17.
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: thestate of the field. International Journal of Educational Technology in Higher
Education, 20(1), 1-22.
Cukurova, M., Miao, X., & Brooker, R. (2023, June). Adoption of Artificial Intelligencein schools: Unveiling factors influencing teachers’ engagement. In International
Conference on Artificial Intelligence in Education (pp. 151-163). Cham: Springer
Nature Switzerland.
Fütterer, T., Fischer, C., Alekseeva, A., Chen, X., Tate, T., Warschauer, M., & Gerjets,
P. (2023). ChatGPT in education: Global reactions to AI innovations. https://www.
researchsquare.com/article/rs-2840105/v1
Hou, Y. (2020). Foreign language education in the era of Artificial Intelligence. In:
Atiquzzaman, M., Yen, N., Xu, Z. (Eds.). Big Data Analytics for Cyber-Physical─ 135 ─Bradley Irwin

System in Smart City. BDCPS 2019. Advances in Intelligent Systems andComputing, 1117. Springer, Singapore. https://doi.org/10.1007/978-981-15-25681_128
Hyangeun Ji, Insook Han & Yujung Ko (2023). A systematic review of conversational AI
in language education: focusing on the collaboration with human teachers. Journalof Research on Technology in Education, 55(1), 48-63. https://doi.org/10.1080/153915
23.2022.2142873
Kizilcec, R. F. (2023). To advance AI use in education, focus on understanding educators.
International Journal of Artificial Intelligence in Education, 1-8.
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching andlearning. RELC Journal, 52(2), 537-550. 
https://doi.org/10.1177/00336882231162868.
Malik, A., Khan, M. L., & Hussain, K. (2023). How is ChatGPT transforming academia?
Examining its impact on teaching, research, assessment, and learning. SSRN, 1-34.
http://dx.doi.org/10.2139/ssrn.4413516
Mitomo, H. (2020). Utilization of ICT in elementary and secondary education in Japan:
Its policies and effects. Telecommunications policies of Japan, 239-266.
Pack, A., & Maloney, J. (2023). Using Generative Artificial Intelligence for language
education research: Insights from using OpenAI’s ChatGPT. TESOL Quarterly,
57(4), 1571-1582.
Relmasira, S. C., Lai, Y. C., & Donaldson, J. P. (2023). Fostering AI literacy inelementary science, technology, engineering, art, and mathematics (STEAM)
Education in the age of Generative AI. Sustainability, 15(18), 13595. https://doi.
org/10.3390/su151813595
Ribeiro, R. (2020, March 9). AI In English Language Learning. World of Better Learning.
https://www.cambridge.org/elt/blog/2020/03/09/artificial-intelligence-englishlanguage-learning
Semerikov, S. O., Striuk, A. M., & Shalatska, H. M. (2021). AI-assisted language
education: critical review. Educational Dimension, 4, 1–7. https://doi.org/10.31812/
ed.623
Stout, M., & Yamauchi, M. (2012). Researching ICT integration in Japanese EFL
classrooms. The Language Teacher, 36(3), 38-40.
Tan, S. C., Chen, W., & Chua, B. L. (2023). Leveraging generative artificial intelligencebased on large language models for collaborative learning. Learning: Research andPractice, 1-10.

─ 136 ─

Exploring Generative AI Tools for English Language Learning: Student Adoption and Perceptions

Tanaka, S., & Saito, E. (2021). Examining the barriers experienced by EFL teachers
when implementing technology in senior secondary schools in Japan: a selfstudy. Practice, 3(2), 96-109.
Ulla, M. B., Perales, W. F., & Busbus, S. O. (2023). ‘To generate or stop generating
response’: Exploring EFL teachers’ perspectives on ChatGPT in English language
teaching in Thailand. Learning: Research and Practice, 9(2), 168-182.
Wang, Y., Liu, C., & Tu, Y. F. (2021). Factors affecting the adoption of AI-based
applications in higher education. Educational Technology & Society, 24(3), 116-129.
Yanhua, Z. (2020, June). The application of artificial intelligence in foreign language
teaching. In 2020 International Conference on Artificial Intelligence and Education(ICAIE) (pp. 40-42). IEEE.
Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future
directions. Computers and Education: Artificial Intelligence, 2, 1-11.

─ 137 ─