37.2022, Calls: Language Learning & Technology - "Special Issue: Robot-Assisted Language Learning" (Jrnl)

Tue Jun 9 10:05:02 UTC 2026

LINGUIST List: Vol-37-2022. Tue Jun 09 2026. ISSN: 1069 - 4875.

Subject: 37.2022, Calls: Language Learning & Technology - "Special Issue: Robot-Assisted Language Learning" (Jrnl)

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Date: 07-Jun-2026
From: Language Learning & Technology Managing Editor [llt at hawaii.edu]
Subject: Language Learning & Technology - "Special Issue: Robot-Assisted Language Learning" (Jrnl)

Journal: Language Learning & Technology
Issue: Robot-Assisted Language Learning
Call Deadline: 01-Sep-2026

Guest Editors: Ali Derakhshan, Golsetan University, Iran, and Haoran
Xie, Lingnan University, Hong Kong SAR
Language learning is a crucial skill in our increasingly globalized
world, where communication across cultures and languages is more
important than ever (Chen et al., 2021). Traditional methods of
language education, while effective, often lack the interactivity that
modern technology can provide (Derakhshan & Zhang, 2024; Fathi et al.,
2024; Zhao & Lai, 2023). Robot-Assisted Language Learning (RALL) has
emerged as a promising approach to address these gaps by leveraging
advancements in robotics and artificial intelligence (Derakhshan &
Ghiasvand, 2024; Derakhshan et al., 2025; Derakhshan, Teo, Saeedy
Robat, et al., 2024; Huang et al., 2023; Engwall & Lopes, 2022; Lee &
Lee, 2021, 2022; Teo et al., 2022; Van den Berghe et al., 2021). RALL
encompasses the use of robots equipped with language learning software
to aid in the teaching and learning process (Ao & Yu, 2022; Engwall et
al., 2021; Khazaie & Derakhshan, 2024). These robots can interact with
learners in dynamic and engaging ways (Lee & Lee, 2022), providing
immediate feedback and creating a more immersive learning environment
(Chen et al., 2022; Derakhshan, Teo, & Khazaie, 2024; Engwall et al.,
2022). In response to the increasing interest in harnessing the
potential of robots in language education, this special issue seeks to
explore the recent advances in RALL and identify future directions for
research and implementation.
The rationale for this special issue stems from the need to address
the gaps in the pertinent literature. While there is a growing body of
research on the use of technology in language learning (e.g., Chen,
2022; Chun et al., 2016; Hoi, 2020; Huh & Lee, 2020; Zhang & Zou,
2022), studies specifically focusing on the integration of robots in
educational settings remain limited. Existing literature often
emphasizes the theoretical potential of RALL without providing
sufficient empirical evidence on its effectiveness. Furthermore, many
studies lack a comprehensive analysis of the pedagogical, technical,
and ethical dimensions of RALL. There is a need for research that not
only showcases successful implementations of RALL but also critically
examines the challenges and limitations associated with its use. This
special issue aims to fill these gaps by providing a platform for
scholars to present original research, case studies, and meta-analyses
that offer a holistic view of robots and their untapped potential in
language education.
The proposed special issue aligns seamlessly with Language and
Learning Technology’s esteemed readership as it exemplifies the
applications of educational technology and applied linguistics to
problems of foreign language teaching and learning. The integration of
robotics, AI, and language learning represents a complex system that
requires a multidisciplinary approach to understand and optimize. The
esteemed readers of Language and Learning Technology will find value
in the innovative applications of systems methodologies in RALL, as
well as the discussions on how to design, implement, and evaluate
these systems effectively to optimize foreign language teaching and
learning. The special issue will also appeal to those interested in
the broader implications of emerging technologies in language
education and the potential for these technologies to transform
traditional learning paradigms.
While we suggest the following themes as a foundation for submissions,
we also enthusiastically welcome studies that investigate novel
constructs, pioneering frameworks, and unexplored avenues beyond the
themes listed below:
Advances in Robot-Assisted Language Learning (RALL) Approaches
- Novel RALL systems and their impact on language learning outcomes
- Integrating artificial intelligence and machine learning into RALL
- Multimodal interaction and feedback in RALL environments
- Personalized and adaptive RALL for individualized learning
Effectiveness of RALL in Language Learning
- Empirical studies on the effectiveness of RALL in improving language
skills (e.g., speaking, listening, reading, and writing)
- Comparative analyses of RALL and traditional language learning
method
- Factors influencing the effectiveness of RALL, such as learner
characteristics and cultural contexts
Psycho-emotional Aspects of RALL
-Investigating the impact of RALL on learners’ classroom emotions and
overall well-being
-The role of robots in enhancing language learners’ motivation and
academic engagement
RALL in Diverse Educational Contexts
- Implementing RALL in elementary, secondary, and higher education
settings
- Exploring the use of RALL in language learning for specific purposes
(e.g., business, medicine, tourism)
- Challenges and best practices for integrating RALL into different
educational systems
Future Trends and Directions in RALL
- Emerging technologies and their potential impact on RALL (e.g.,
augmented reality, brain-computer interfaces)
- Ethical considerations and privacy concerns in RALL
- Interdisciplinary collaborations and the future of RALL research
Guidelines for Authors:
For author guidelines for the full manuscripts, please refer to LLT
submission guidelines.
Abstracts for this special issue Call for Papers should be no more
than 500 words and should describe the study’s aim, methodology,
findings related to L2 learning outcomes, and how these findings can
be used in classroom contexts to enhance L2 teaching and learning with
technology. To be considered for this special issue, which will appear
in volume 32, issue 2 in June of 2028, please submit a title and a
500-word abstract through this online form (https://go.hawaii.edu/iqQ)
by September 1, 2026.
Publication Schedule:
June 1, 2026: Call for papers
September 1, 2026: Submission deadline for abstracts
October 1, 2026: Invitation for authors to submit full manuscripts
March 1, 2027: Submission of the first drafts of full manuscripts
November 1, 2027: Submission of revised manuscripts
June 1, 2028: Publication of final manuscripts in the special issue
For Further Information:
Please contact the Managing Editor at llt at hawaii.edu with questions.
References:
Ao, Y., & Yu, Z. (2022). Exploring the relationship between
interactions and learning performance in robot‐assisted language
learning. Education Research International, 2022(1), Article 1958317.
https://doi.org/10.1155/2022/1958317
Chen, X., Zou, D., Xie, H., & Cheng, G. (2021). Twenty years of
personalized language learning. Educational Technology & Society,
24(1), 205–222.
Chen, Y. C. (2022). Effects of technology-enhanced language learning
on reducing EFL learners’ public speaking anxiety. Computer Assisted
Language Learning, 37(4), 789–813.
https://doi.org/10.1080/09588221.2022.2055083
Chen, Y. L., Hsu, C. C., Lin, C. Y., & Hsu, H. H. (2022).
Robot-assisted language learning: Integrating artificial intelligence
and virtual reality into English tour guide practice. Education
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Chun, D., Kern, R., & Smith, B. (2016). Technology in language use,
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Derakhshan, A., & Ghiasvand, F. (2024). Is ChatGPT an evil or an angel
for second language education and research? A phenomenographic study
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Applied Linguistics, 34(4), 1246–1264.
https://doi.org/10.1111/ijal.12561
Derakhshan, A., Teo, T., & Khazaie, S. (2025). Investigating the
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Derakhshan, A., Teo, T., & Khazaie, S. (2024). Is game-based language
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Derakhshan, A., Teo, T., Saeedy Robat, E., Janebi Enayat, M., &
Jahanbakhsh, A. A. (2024). Robot-assisted language earning: A
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https://doi.org/10.3102/00346543241247227
Derakhshan, A., & Zhang, L. J. (2024). Applications of
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Engwall, O., & Lopes, J. (2022). Interaction and collaboration in
robot-assisted language learning for adults. Computer Assisted
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https://doi.org/10.1080/09588221.2020.1799821
Engwall, O., Cumbal, R., Lopes, J., Ljung, M., & Månsson, L. (2022).
Identification of low-engaged learners in robot-led second language
conversations with adults. ACM Transactions on Human-Robot Interaction
(THRI), 11(2), 1–33. https://doi.org/10.1145/3503799
Engwall, O., Lopes, J., & Åhlund, A. (2021). Robot interaction styles
for conversation practice in second language learning. International
Journal of Social Robotics, 13(2), 251–276.
https://doi.org/10.1007/s12369-020-00635-y
Fathi, J., Rahimi, M., & Derakhshan, A. (2024). Improving EFL
learners’ speaking skills and willingness to communicate via
artificial intelligence-mediated interactions. System, 121, Article
103254. https://doi.org/10.1016/j.system.2024.103254
Hoi, V. N. (2020). Understanding higher education learners’ acceptance
and use of mobile devices for language learning: A Rasch-based path
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https://doi.org/10.1016/j.compedu.2019.103761
Huang, X., Zou, D., Cheng, G., Chen, X., & Xie, H. (2023). Trends,
research issues and applications of artificial intelligence in
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https://doi.org/10.30191/ETS.202301_26(1).0009
Huh, K., & Lee, J. (2020). Fostering creativity and language skills of
foreign language learners through SMART learning environments:
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https://doi.org/10.1093/elt/ccab041
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learning environments for young English learners (pp. 167–206).
Routledge.

Linguistic Field(s): Applied Linguistics

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