By
1ONUGU,
Priscilla Afor Ph.D, 2AWESU,
Funso Gabriel & 3BAKARE, Mayowa
Department
of English, Directorate of General Studies, Federal School of Surveying,
Oyo.State Nigeria
Corresponding Author’s email & Phone No: priscyudy@gmail.com 08134568013
Abstract
Technological
innovation, such as Artificial Intelligence, is rapidly developing to make
lives universally easier and is poised to transform the way people interact
with one another, enhancing communication skills, learning, vision,
problem-solving, language comprehension and logical reasoning. This study investigates Artificial intelligence outcomes on language communication
stimulus; its strengths and drawbacks towards developing receptive language
skills for efficient teaching and learning. Albert Bandura’s (1977) Social Learning
Theory which posits that learning can take place through observation, imitation
and modelling was adopted as theoretical framework. Two hundred (200)
questionnaires containing fifteen (15) testable questions each were purposively
administered to the study sample representing fifty percent (50%) of the
School’s entire students. The statistical methods of mean and percentages were
applied to analyse the data of this study using descriptive survey design.
Results of the data analysis reveals that majority of the study sample agreed
that adopting and using AI in learning language in the Federal School of
Surveying, Oyo will be more advantageous as indicated by 73.9% of the students’
responses to the questionnaire. It concludes on the premise that AI provides fresh insights that inform
and shape approaches to improving language teaching and learning. The study is
therefore recommending the adoption of Artificial Intelligence to support language
learning in the nation’s institutions of higher learning. Thus, policymakers need to imperatively
develop comprehensive and contextually relevant strategies for the effective
integration of AI into classroom practices, in order to enhance pedagogical
approaches and maximise teaching
efficacy and learning outcomes.
Keywords: Artificial Intelligence, Teaching, Learning, Language,
Communication
Background to the Study
Language is essential for social relationships because it
allows for effective communication. Language facilitates communication which is
a transactional activity between individuals, communities, and countries with
the purpose of exchanging and imparting through speaking, writing and using
some other medium (Oduola, 2020). According to Banegas, Beltrán-Palanques, and Salas (2023), Hakim, Efriyanti, Zasrianita, and Astari, (2022) and Burns, Teaching, Aberdeen, and Psychology (2011), having strong
language abilities entails being able to communicate effectively and comprehend
others. Consequently, Lan, Liu and Baranwal
(2020) opine that the most common language in the world is English. It is
widely utilised for employment, commerce, travel, conversation and
international connectivity, making it the universal language of communication.
Therefore, improving both active (speaking and writing) and passive (listening
and reading) language communication skills is the goal of teaching and learning
English language.
Grabe and Stoller (2002) posit that a student must become
proficient in speaking, listening, reading and writing in order to master the
English language. However, there is a lot of barriers that learners must
overcome, in order to learn and communicate in English across linguistic and
cultural boundaries (Renandya and Widodo, 2016). To aid learners
and overcome these barriers, teachers
make efforts to look for strategies to support students' successes. In light of
this, Artificial Intelligence (AI) is being used as a tool to assist English
language Teaching and Learning (ELT/L), offering fresh approaches and chances
to overcome obstacles, broaden and improve learning (Baranwal, 2022). AI is playing an
increasingly significant role in language teaching and learning through
individualised learning, natural language processing, intelligent content
creation and data-driven insights.
Statement of the Problem
AI has become more prevalent in recent years, and many
studies have examined the application of AI and its vast potentials in a
variety of fields, including technology and medicine. However, few have
examined how AI affects the development of communication skills, how it can
alter motivation and the capacity to develop receptive language skills, and its
drawbacks. For instance, Odunaya (2023) investigated the Transformative
Impact of Artificial Intelligence (AI) on Curriculum Implementation in Nigerian
Tertiary Institutions. The study, explores the multifaceted contributions
of AI across various stages of curriculum development and execution and shows
that AI technologies, including machine learning and natural language
processing, play a pivotal role in enhancing educational practices. Okunade (2023) studied the Role
of Artificial Intelligence in Teaching of Science Education in Secondary
Schools in Nigeria, examining how AI technologies might improve the overall
quality and efficacy in teaching science subjects may lead to better results
for secondary school students. Also, Atoi (2024) investigated the Impact
of Artificial Intelligence on the English Language use and Communication Skills
of Selected Nigerian University Undergraduates. Findings from the study reveal
that artificial intelligence impacted greatly on the language and communication
skills of Nigerian undergraduates both positively and negatively, particularly
on their vocabulary and grammar. Nwaokugha and Abiakwu (2024) investigated the Prospects of Using Artificial
Intelligence in Teaching and Learning in Educational Institutions in Nigeria.
It has answers to issues and challenges in education as one of the studies’
findings. However, these studies created a lacuna which the present is set to
fill because none of them explored the adoption, use and challenges of applying
AI in learning language skills towards effective teaching and learning in the
Federal School of Surveying, Oyo.
Aim and Objectives
This study investigates
Artificial intelligence
outcomes on language communication stimulus, its strengths and drawbacks
towards developing receptive language skills for efficient teaching and
learning.
Its specific objectives are to:
1.
identify areas where AI can apply in teaching
and learning language skills;
2.
discuss the merits of AI adoption in teaching
and learning language skills; and
3.
examine the demerits of AI adoption in
teaching and learning language skills.
Significance of the Study
This study is significant because it will provide helpful
insights for both practitioners and scholarly audiences. Teachers will acquire
a point of reference for incorporating AI into English instruction, covering
pedagogical strategies and links to language communication abilities. The study
will also identify obstacles, allowing teachers to deal with problems, avoid abuses
and comprehend constraints. Policy makers, funders and educational leaders can
use this research to promote evidence-based practice and policy.
Review of Relevant Literature
An Overview of Artificial Intelligence (AI)
AI is a branch of
computer science which involves developing computer programmes to complete
tasks which would otherwise require human intelligence (Mohammed, 2019). The term Artificial Intelligence was originally coined by the American
physicist John McCarthy in 1955. He defines it as “the science and engineering
of making intelligent machines” (McCarthy 1955, p.1). It is the ability to hold two different ideas in mind at
the same time and still retain the ability to function (Singh, Mishra and Sagar, 2013). Systems that exhibit intelligent behaviour by analysing
their surroundings and acting somewhat independently to accomplish
predetermined objectives are referred to as artificially intelligent (Boucher,
2020). In addition, Akinwalere and Ivanov (2022) describe artificial
intelligence as a technological innovation that is committed to making the
lives of human beings easier, while Bostrum (2017) writes that the rapidly developing field of artificial intelligence
has the potential to completely change how people interact with one another.
Learning, vision, problem-solving, language comprehension and logical reasoning
can all be addressed by artificial intelligence algorithms (Mohammed, 2019).
Artificial
Intelligence in Language Teaching and Learning
AI has emerged as a powerful tool in the field of language
teaching and learning, transforming the way teachers and learners interact with
language learning materials and resources (Godwin-Jones, 2019). Lo (2023) reveals that numerous
acronyms are frequently linked to different subtleties and historical patterns
when scholars and professionals concentrate their efforts on the planning and
execution of teaching and learning English language proficiency. For instance, Computer-Assisted Language
Learning (CALL) and Mobile- Assisted Language Learning (MALL) focus on the
technology used in learning English Language as a Second Language (ESL),
English for Speakers of Other Languages (ESOL) and English as a Foreign
Language (EFL) (Lo 2023).
This study investigates the outcomes
of artificial intelligence on language communication stimuli, with particular
emphasis on its strengths and drawbacks in the development of receptive
language skills for effective teaching and learning. Therefore, in line with
this aim, it is crucial to note that while AI tools demonstrate significant
potential for English Language Teaching and Learning (ELT/L), their pedagogical
affordances are best realised when educators and learners possess a clear
understanding of the available technologies and how both pedagogical and
andragogical approaches can be appropriately aligned with them.
Artificial intelligence systems
offer diverse affordances tailored to specific users and instructional
objectives. Notably, AI technologies are capable of processing vast amounts of
data, utilising natural language modalities like speaking, listening and
writing as well as adhering to established linguistic conventions and patterns.
These capabilities directly support the development of receptive language
skills which this study seeks to investigate. Furthermore, the portability,
universality, sharing ability and individuality of mobile devices have
facilitated their widespread adoption in English Language Teaching and Learning
(ELT/L) contexts (Ma, 2021). The integration of speech synthesis, big data and
intelligent systems into mobile-based AI applications has further promoted
language outcomes (Luo and Cheng, 2020).
Despite these strengths, such
systems only approximate human interaction and remain inherently limited. For
example, AI-powered voice assistants provide continuous conversational engagement
through human-like voices and diverse English dialects (Dixon and Tang, 2020),
thereby stimulating language input. However, their inability to fully replicate
human communicative competence highlights the drawbacks that this study actually
explores, particularly in relation to the development of receptive language.
Merits
of Adoption and Using Artificial Intelligence in English Language Teaching and Learning (ELT/L)
A key merit of AI adoption
and use in language teaching is personalised learning. AI-powered language
learning platforms can tailor instruction and content to individual learners’
needs, abilities and preferences. By collecting data on learners’ performance,
AI algorithms can identify areas of weaknesses and provide targeted exercises
and materials to address those specific areas. This personalised approach
enhances the learning experience, allowing learners to progress at their own
pace and focus on areas that require more attention. AI is used in ELT/L for the development of
speaking, writing and reading skills which supports Rusmiyanto, Huriati, Fitriani, Tyas, Rofi’i, and ‘Sari (2023) perspective on the four cardinal areas where the use of AI
can enhance communication skills in language teaching and learning environments
to include: speaking, listening, reading and writing.
Furthermore, Vincent-Lancrin
and Vlies (2020, p. 9), are of the view that “AI features such as speech
recognition, analysis and pronunciation correction, can help supplement
teachers in the teaching of foreign languages.” AI can facilitate language
learning through Natural Language Processing (NLP) techniques. NLP also enables
AI systems to understand and generate human language, making it possible for
learners to engage in interactive conversations and receive instant feedback. AI enables students to rehearse speaking in a customised and
encouraging setting. With these advanced Natural Language
Processing (NLP) capabilities and interactive conversational features,
AI-powered tools and applications provide learners with unique opportunities to
practice and improve their speaking abilities. AI can be beneficial in
developing speaking skills with the availability of virtual language tutors and
conversational chatbots. These AI-based conversational agents can engage
learners in interactive conversations, simulating real-life language
interactions. Learners can practise speaking in a comfortable and
non-judgmental environment, where they can experiment with language, receive
instant feedback, and refine their pronunciation and fluency.
By providing speech recognition
systems, chatbots, virtual tutors and language learning applications, learners
are made to engage in immersive language learning experiences. Therefore, real-time
feedback, adaptive testing and customised content, among other features
provided by these technologies, have the potential to improve language
learners' communication skills and hasten the process of language acquisition. AI
is beneficial in teaching or learning writing skills. Two areas that emerged
for AI use in writing were related to vocabulary learning and grammar. When students have access to neural machine
translation programmes, it resulted greatly in their vocabulary improvement,
especially when specialised or unambiguous expressions are involved (Lo, 2023).
AI grammar checkers are yet another
popular application of AI in communication. AI is used to achieve good
reading skills. This is made possible through the use of gaming systems. Zheng, Bischoff, and Gilliland (2015) observe how vocabulary
learning in reading occurs during gaming quest-play, mediated in English when
students, used avatars, semiotic resources imbued in the game World of Warcraft
(WoW). Zheng and colleagues posit that students have opportunities to learn
vocabulary and understand meaning via games beyond what a textbook or classroom
can provide, by contextualising often decontextualised vocabulary. AI is used in World of Warcraft to supply that context by incorporating
AI characters (that is characters that are not controlled by humans) and
pathfinding navigation algorithms that create a dynamic and captivating world.
Demerits of Artificial Intelligence
Adoption in English Language Teaching and Learning (ELT/L)
The lack of emotion in AI has been observed by researchers
utilising AI with ELT/L (Annamalai et al., 2023). While AI can
appear to be showing emotions, such as text describing feelings and avatars
showing facial expressions, AI does not have the capacity to feel emotions and AI systems may struggle with the tones of language, such as
humour, irony or cultural context, which can affect their ability to provide
accurate feedback. In other words, AI systems can only mimic text and expressions,
and may not always capture the full
range of linguistic tones, cultural context or non-verbal communication cues
that are essential for effective spoken communication. Therefore, human
interaction and feedback from language instructors remain vital in providing
learners with a comprehensive understanding of spoken language and guiding them
in overcoming specific challenges.
Technology breakdowns, limited capabilities, fear and
standardising language are also some issues teachers and learners encounter
while using AI. Technology breakdowns include technical malfunctions, poor
connectivity and incorrect answers provided by the AI, largely due to its limited
capabilities, especially when users require more advanced functionality.
Theoretical Framework
This study adopts
Albert Bandura’s (1977) Social Learning
Theory which was articulated by the psychologist Albert Bandura in 1977. It
emphasises that learning occurs not
just by a one-on-one teacher/learner encounter but through
observation, imitation and modelling, within a social context. The key
principles of the theory include
observational learning, which asserts that individuals acquire new behaviours
by seeing others and the repercussions of their actions. Modeling denotes the
process by which individuals replicate behaviours exhibited by role models they
see as credible, authoritative, or appealing. Reinforcement and punishment
clarify that learning is shaped by incentives and sanctions, whether directly
encountered or vicariously viewed in others. Cognitive processes highlight the
significance of internal mental activity, including attention, retention,
reproduction, and motivation, in enhancing the learning and execution of
learned behaviours. Therefore, Albert Bandura’s (1977) Social Learning Theory can suffice when
using Artificial Intelligence (AI) in teaching and learning for effective
communication skill through observational learning and AI simulations. This is
seen when AI tools, such as virtual tutors, chatbots and role-playing
simulations are used to model effective communication behaviours.
Methodology
The descriptive
survey design was used for this study. Two hundred (200) students representing
fifty percent (50%) of the students in the Federal School of Surveying, Oyo
were randomly selected for the study. From the aforementioned, a hundred and
fifty (150) male students and fifty (50) female students all from National
Diploma I (NDI), National Diploma II (NDII) and Higher National Diploma 1
(HNDI) classes respectively offering language and communication skills were
sampled. A total of two hundred (200)
questionnaires containing fifteen (15) testable questions each were purposively
administered to the study sample to investigate how the adoption and use of
Artificial Intelligence (AI) can either be advantageous or disadvantageous in
teaching and learning language communication skills in Higher Institutions. A
reliability scale of above 1.5 was obtained indicating a positive inclination
towards agreement using Likert Scale. The statistical methods were applied to
analyse the data using mean and percentages.
Data Presentation, Analysis, Discussion
and Findings
Participants
responses were subjected to frequency distribution and percentages. The results
are presented in the table below.
Table 1: Distribution of the Responses of Students to Questionnaires on AI
Adoption and Use
|
AGREE |
INDIFFERENT/NEUTRAL |
DISAGREE |
TOTAL RESPONSES |
|
2217 |
358 |
425 |
3000 |
|
73.9% |
11.93% |
14.17% |
100% |
Results of the
data analysis of this study reveals that majority of the study sample agreed
that adopting and using AI in learning language in the Federal School of
Surveying, Oyo will be more advantageous as indicated by 73.9% of the students’
responses to the questionnaire. By implication, AI provides fresh approaches to
improve learning language. It is also discovered that 14.17% of the
participants’ responses to the questionnaire disagreed to the adoption and use
AI in language learning in the Federal School of Surveying, Oyo. On the other
hand, 11.93% of the students were indifferent as attested by their responses.
The findings confirm that AI use in teaching and learning language skills for
effective communication will be of immense benefit if it is adopted as part of
the School’s curriculum. This claim is obviously supported by the percentages
of the respondents who either disagreed or were indifferent to the questions
asked.
Conclusion
This study emphasises the necessity of educating English
language instructors on AI and how to utilise its numerous advantages when
working with English language learners. The
use of AI in improving communication skills has the potential to revolutionise
the way students enhance their skills. By providing immediate feedback,
simulating conversation partners, and supporting cross-cultural communication,
AI can help students improve their listening, reading, speaking and writing
skills in engaging and effective ways. As AI technology continues to advance,
it will be exciting to see how it can be integrated into the classroom to
support students learning outcomes. AI has been recognised as a potential tool
to improve learning and teaching. It
provides fresh approaches to improving language acquisition, particularly
through individualised and controlled practice. AI technology is used to
provide language learning support for students. AI-based platforms and tools
offer interactive exercises, real-time feedback and adaptive content delivery
based on the learner’s needs and proficiency level.
Recommendations
This study provides a platform for other researchers to
investigate on how Artificial Intelligence
can
be adopted to support language learning in the nation’s institutions of higher
learning. Future researchers should further
explore other dimensions AI can be applied in learning communication skills in
order to reaffirm the evidence of this present one. Policy makers, funders and educational leaders can use
this research to promote evidence-based practice and policy with in order to enhance pedagogical approaches and maximise teaching efficacy and
learning outcomes.
References
Akinwalere, S. N. and Ivanor,
V. T. (2022). Artificial intelligence in higher education: Challenges and
opportunities. Border Crossing, 12(1), 1-15
Annamalai, N., Eltahir, M. E.,
Zyoud, S. H., Soundrarajan, D., Zakarneh, B., and Al Salhi, N. R. (2023).
Exploring english language learning via chabot: A case study from a self-determination
theory perspective. Computers and Education: Artificial Intelligence, 5,100148.
https:// doi. org/ 10. 1016/j. caeai. 2023. 100148
Atoi
N.N. (2024). Language and communication implication of artificial intelligence
on selected Nigerian University Undergraduates: in Unizik Journal of Arts and
Humanities Vol. 25, No. 1, https://dx.doi.org/10.431//ujahv25il.5
Bandura, A. (1977). Social learning theory. Englewood
Cliffs, NJ: Prentice-Hall.
Banegas, D. L.,
Beltrán-Palanques, V., and Salas, A. (2023). Language teacher educators’
identity construction through teaching and supporting action research: A trio
ethnographic Study. RELC Journal. https://doi.org/10.1177/00336882231212855
Baranwal, D. (2022). A
systematic review of exploring the potential of teachable agents in English
learning. Pedagogical Research, 7(1). https:// doi. org/ 10. 29333/ pr/ 11553
Boucher, P. (2020). Artificial
intelligence: How does it work, why does it matter, and what can we do about
it?” Think Tank European Parliament. https://doi.org/10.2861/44572
Bostrum, N. (2017). Superintelligence: Paths, Dangers,
Strategies. Oxford University Press
Burns, S., Teaching, L.,
Aberdeen, T., and Psychology, E. (2011). Deanna Book_Review-Burns 12.1[1].
Canadian Journal of Action Research, 12(1), 45-46.https://doi.org/10.33524/cjar.v12i1.5
Dizon, G., and Tang, D. (2020).
Intelligent personal assistants for autonomous second language learning: An
investigation of Alexa. JALT CALL Journal, 16(2), 107–120. https:// doi. org/ 10. 29140/ jaltc
all. V1. 6n2. 273
Godwin-Jones,
R. (2019). Emerging technologies: AI in language learning. Language Learning & Technology, 23(3), 1-17.
https://www.lltjournal.org
Grabe, W. P., and Stoller, F. L. (2002). Teaching and researching
reading. Pearson Education. https:// doi.
org/ 10. 4324/ 97813 15833743
Hakim, M. A. R., Efriyanti, N.,
Zasrianita, F., and Astari, A. R. N. (2022). English teachers’ creativity in preparing and managing
teaching-learning media during covid-19
pandemic for junior high school students indonesia. What Covid-19 Pandemic has
altered english teacher's teaching practice, 25-38
Lan,
P.-S., Liu, M.C., and Baranwal, D. (2020). Applying contracts and online
communities to promote pupil self-regulation
in English learning at the primary-school level. Interactive Learning
Environments, 31(1), 468-479. https://doi.org/10.1080/10494820.2020.1789674
Lo, S. (2023). Neural machine translation in EFL classrooms:
Learners' vocabulary improvement, immediate
vocabulary retention and delayed vocabulary retention. Computer-Assisted Language Learning, 1–20. https:// doi. org/
10. 1080/ 09588 221. 2023.2207603
Ma, G. (2021). The current
situations of mobile assisted language learning. In J. MacIntyre, J. .Zhao, and
X. Ma (Eds.), Proceedings of the International Conference on Machine Learning and Big Data Analytics for
IoT Security and Privacy (pp. 675–679). Springer. https://doi. org/ 10. 1007/
978- 3-
030- 62746 - 1_ 99 McCarthy,
J., Minsky, M. L., Rochester, N., and C. E. Shannon, C. E. (1955). A Proposal for the Dartmouth Summer research project on artificial intelligence
http://wwwfor-mal.stanford.edu/jmc/history/dartmouth/dartmouth.html [Google Scholar]
Mohammed, Z. (2019). Artificial intelligence
definition, ethics and standards. Electronics and communication: Law, Standards
and Practice. British University in Egypt.
Nwaokugha,
D.O. and Abiaukwu, O. F. (2024). Prospects of using artificial intelligence in
teaching and learning in educational institutions in Nigeria: In International
Journal of Innovative Social &
Science Educational Research12(4):182-192
Odunaya, M.O. (2023). Impact of
artificial intelligence in curriculum development in Nigerian tertiary institutions.
In Journal of Educational Research, vol. 12, No. 2013
Oduola,
M.O. (2020). English Language and
communication skills for tertiary levels. Abila Crown Publishers, Ibadan.
Okunade,
A.I. (2024). The role of artificial intelligence in teaching of science education
in secondary schools in Nigeria, European Journal of Computer Science and
Information Technology,12,
(1).57-67
Rich,
S. (2021). Back to the future: An examination of Graddol’s trends of English
and the implications for the
future. [unpublished internal report]. British Council
Renandya,
W.A. and Widodo, H.P. (2016). English language teaching today. Springer,
Switzerland.
https://doi.org/10.1007/978-3-319-38834-2
Rusmiyanto, R., Huriati, N.,
Fitriani, N., Tyas, N.K., Rofi’i, A., and Sari, M.N. (2023). The role of
artificial intelligence (AI) in developing English language learners'
communication skills. Journal on Education, 06(01), 750- 757. https://doi.org/10.31004/joe.v6i1.2990
Singh, G., Mishra, A., and Sagar, D. (2013). An overview of
artificial intelligence. SBIT Journal
of Science and Technology 2(1), 1-4.
Vincent-Lancrin, S. and Vlies, R.
(2020). Trustworthy artificial intelligence (AI) in education: Promises and
challenges. Organisation for Economic Co-operation and Development Working
Papers #218, 1-18. https://doi.org/10.1787/19939019
Zheng, D., Bischoff, M., and
Gilliland, B. (2015). Vocabulary learning in massively multiplayer online
games: Context and action before words. Educational Technology Research and
Development, 63, 771–790. https:// doi. org/ 10. 1007/ s1142 3- 015-
9387
This article is published in ALQALAM: A Journal of Language and Literary Studies, FUGUS, Volume 1, Issue 2 - June 2026
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