General Guidelines for Contributors
AI Policy | Articles | Research Syntheses | Forum on Technology in Practice | Reviews | Submission Process |Review Process | IRIS
AI Policy for Submissions
1. Define scope clearly
Specify that the policy covers generative LLM tools (e.g., ChatGPT, Gemini) and Machine Translation tools used to translate non-English data (e.g., interviews or participant responses) for inclusion in the manuscript, and AI-powered literature discovery/screening tools (e.g., Elicit, Semantic Scholar) used to identify candidate studies, as detailed in the Translation and Literature review provision below, and excludes grammar checkers, plagiarism detectors, and citation managers.
2. Permitted use with transparency
AI may assist with the following tasks, but all uses must be disclosed in the manuscript. This list is not exhaustive and all submitted articles will be considered on a case-by-case basis.
- Literature review assistance (authors may use AI for searching and classifying previous work, but may not use AI to generate the literature review)
- Data analysis
- Data visualization (authors may use AI to produce charts, graphs, and other visualizations derived from verified data using reproducible methods, but may not use AI to generate primary experimental imagery)
- Authors may use AI to assist with the analysis of human-collected data, including writing analysis code or scripts for research methods (e.g., R scripts, Jupyter notebooks), provided this use is disclosed, but may not misrepresent AI-assisted analysis as manual human analysis.
- Language editing
- Translation- if AI is used to translate non-English data (e.g., interviews or participant responses) for the manuscript, authors must disclose the following in the Methods section:
- the name and version of the tool used;
- the language pair;
- the human review process (e.g., verification by the author(s)’ own bilingual expertise, a co-author, or a professional translation service). Raw AI translations must not be used without such verification.
- Language editing (grammar, clarity, cohesion, register): AI-assisted edits must not add new content, alter citations, or change the meaning of the author's original text; all suggested edits must be reviewed and confirmed by the author(s).
- Code and prompts/instruments assistance: authors may use AI to assist in developing research instruments (e.g., 'vibecoded' survey or testing applications) used to collect data, provided this use is disclosed and the resulting instrument is verified by the authors for accuracy and fitness for purpose.
3. Prohibited uses
- Authorship: Generative AI must not be credited as an author under any circumstances.
- Manuscript Generation: The submission of work that was wholly or extensively generated by AI but is declared as being written by the author is prohibited and considered unethical.
4. Require disclosure and citation
- Authors must state which tool and version was used (or, for tools without discrete version numbers, the access date) and how (i.e., authors must provide details clarifying the scope and level of AI use), including the prompt(s) used or a representative summary thereof where the interaction involved multiple iterative exchanges, to support replicability of the reported process.
- A sample is provided for authors’ information:
“The authors used Claude (Sonnet 4.5, Anthropic, accessed March–June 2026) and Elicit (accessed April 2026) at two stages of manuscript preparation. Claude was used for language editing of the Introduction, Methods, and Discussion sections after the full draft had been written by the authors. Prompts were of the form: "Improve the clarity, cohesion, and academic register of the following paragraph. Do not add new content, alter citations, or change the meaning. Flag any sentences whose meaning is unclear rather than rewriting them speculatively." All suggested edits were reviewed sentence-by-sentence by the first author and accepted, modified, or rejected. Elicit was used during the scoping stage of the literature review to identify candidate studies on data-driven learning and secondary school EFL contexts, using queries such as "empirical studies of data-driven learning with secondary school EFL learners, 2015–2025." All studies surfaced by Elicit were independently retrieved from their original sources, read in full, and screened against the inclusion criteria described in Section 3.1; Elicit's summaries were not cited or paraphrased in the manuscript. Neither tool was used to generate research questions, design the study, analyze data, interpret findings, or draft original argumentation. The authors take full responsibility for the accuracy and integrity of all content in the final manuscript. No participant data or unpublished materials were shared with either tool.”
5. Affirm author responsibility
Authors are fully responsible for the accuracy, integrity, and ethics of all content, including any AI-assisted portions. Authors will verify that **each** cited reference is accurate, complete, and corresponds to a genuine source, and that it appropriately supports the claims and ideas for which it is cited. The journal has a zero-tolerance policy toward fabricated or non-existent references, regardless of how they were generated.
6. Consequences of misuse.
Any failure to adhere to these guidelines may result in:
- Manuscript rejection: The manuscript will be rejected without the possibility of resubmission.
- Retraction: If inappropriate AI use is discovered post-publication — including undisclosed AI-generated content, misrepresentation of AI assistance as the author's own work, or any other breach of the AI use provisions set out in this policy — the publisher reserves the right to retract the publication.
Articles
- LLT publishes articles of up to 8,500 words that present an empirical study or an original framework (e.g., novel conceptual or theoretical ideas) linking second language acquisition theory, previous research, and language learning and teaching practices that utilize technology. Prioritized are articles that provide and discuss data and analysis of language learning or language teaching outcomes. Articles containing only descriptions of software, pedagogical procedures, or those presenting results of small or limited surveys without providing systematic empirical data and analysis on language learning or language teaching outcomes or processes will not be considered.
- General guidelines are available for conducting CALL research (see LLT editors’ Research Workshop slides) and for reporting on both quantitative and qualitative research (see LLT Research Guidelines).
- Manuscripts that have already been published, are being considered for publication elsewhere, or have been previously rejected by LLT will not be considered. Authors who submit a manuscript simultaneously to multiple journals will be banned from submissions to LLT for a two-year period. If your submission is part of a larger study or if you have used the same data in whole or in part in other papers published or under review, you must write a cover letter stating where the paper is published/under review and describing how the current submission to LLT makes a different and distinct contribution to the field.
- Submitted manuscripts that contain substantial portions of the author(s)' own work that has been published in other venues are considered self plagiarism and will not be considered. Authors will be banned from submissions to LLT for a two-year period.
- Submitted manuscripts that contain substantial portions of others' work that have been published are considered plagiarism, and authors who submit plagiarized work will be banned from publishing in LLT.
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Authors who use AI tools in the writing of their manuscript, production of images or graphical elements of the paper, or in the collection and analysis of data, must be transparent in disclosing in the Materials and Methods (or similar section) of the paper how the AI tool was used and which tool was used. Authors are fully responsible for the content of their manuscript, even those parts produced by an AI tool, and are thus liable for any breach of publication ethics.
Research Syntheses
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LLT publishes research syntheses of up to 8,500 words (same as regular research papers) but excluding references and appendices. Research syntheses provide a critical overview of empirical research in a given subfield of CALL. The syntheses must be comprehensive but focused by capturing ground-breaking studies that have defined the particular subfield. Syntheses must also show the impact of CALL research and its applications to language learning and teaching. Click
here to see the Call for Papers for these types of articles (they were previously referred to as "systematic reviews and meta-analyses").
Forum on Technology in Practice
The integration of technology into language teaching and learning has become the norm in recent years. It is therefore more important than ever for practitioners and researchers to share those pedagogical practices that work well and those that do not, identify practical challenges in technology integration and evaluate its impact. The Technology in Practice (TIP) Forum aims to provide a space for language teachers and teacher educators to reflect on their pedagogies, with a focus on the intersection of education and computer-assisted language learning (CALL).
In particular, the TIP Forum publishes pedagogically oriented articles that describe the implementation of a CALL-based technology, task, activity, or assessment for a specific purpose related to language teaching or teacher education. Submissions are welcomed from those who work in a diversity of contexts (e.g., K-12, higher education, or professional contexts).
The audience for the TIP Forum includes graduate students, practitioners, and teacher educators. Notably, the Forum places pedagogy at the forefront, meaning that contributions are intended to provide practical descriptions and insights. To facilitate this, submissions are encouraged to follow the guidelines below. The TIP forum accepts manuscripts on a rolling basis, similar to traditional manuscript submissions.
Guidelines for Authors (submitting to Technology in Practice):
- Word length: Initial submissions should not exceed 5,000 words (including references, but not including any appendices).
- Citations: Authors are encouraged not to exceed 15 references.
- Sections of the manuscript: Submissions typically contain the following five sections: 1. Introduction, 2. Instructional Context, 3. Description of Teaching Practices, 4. Practical Benefits and Challenges, and 5. Lessons Learned.
- Introduction - Open by explaining the aims of the pedagogical practice. For example, is it a tool/activity/assessment that you are highlighting in this Forum article? Why are you highlighting it (i.e., for what purpose)? If any existing or related research exists, be sure to briefly justify its use.
- Instructional Context - Explain information about your teaching context, such as the location, the age of the learners, their proficiency level, and information regarding student and/or instructor access to technology, etc. What problem did the introduction of the technology aim to tackle, or what new opportunity was it used to achieve?
- Description of Teaching Practices - Explain in detail how you instituted the tool/activity/assessment in your context. Include any tables or figures that may help readers better understand what you did and how you did it.
- Practical Benefits and Challenges - Reflect on some of the benefits you observed while adopting the tool/activity/assessment (e.g., aspects of student engagement, learning, etc.). Additionally, report some of the issues you encountered and how you dealt with them. These can be challenges you faced as a teacher and/or challenges students faced when engaging with the tool/activity/assessment. Your discussion of the benefits and challenges may stem from your observations as a teacher, or they may come from informal discussions with students. (Note: In this section, you should not integrate any formal data sources or statistical analyses which commonly appear in empirical research papers).
- Lessons Learned - Close the piece by providing readers with a few practical tips or takeaways to consider when implementing the tool/activity/assessment in the future.
- Language use/proofreading: Prior to submission, authors should ensure that a) they have carefully proofread their work, or b) their work has been proofread by a professional familiar with academic English.
Prior to drafting a manuscript, prospective authors are strongly encouraged to review articles that have been published in the TIP Forum, as they can serve as useful templates and mentor texts. Examples include:
Gracia, E. (2025). Teaching ESL pronunciation to international teaching assistants with the ELSA Speak app. Language Learning & Technology, 29(1), 1-13. https://www.lltjournal.org/item/1223/
Hu, H., Du, K., Hashim, H. U., & Hashim, H. (2025). Educational escape rooms for French grammar: A technology-in-practice approach. Language Learning & Technology, 29(1), 1-15. https://www.lltjournal.org/item/1188/
Finally, authors are also encouraged to contact the TIP Forum editor to discuss whether their topic is a potential fit for the Forum. Editor contact: Matt Kessler (kesslerm@usf.edu).
Media Reviews (currently on hiatus)
- LLT has published reviews of professional books and software related to the use of technology in language learning, teaching, and testing but has temporarily suspended these reviews.
- LLT does not accept unsolicited reviews.
Submission process
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Review process
All articles go through a two-step review process:
- Internal Review. The editors first review each manuscript to see if it meets the basic requirements (i.e., that it reports on original research or presents an original framework linking previous research, second language acquisition theory, and teaching practices), and that it is of sufficient quality to merit external review. Manuscripts that do not meet these requirements and are principally descriptions of classroom practices or software are not sent out for further review. The internal review generally takes about 8 days. Following the internal review, authors are notified of the results.
- External Review. Submissions which meet the basic requirements are then sent out for double blind peer review by a minimum of 2 experts in the field. The external review takes approximately 2-3 months. Following the external review, the authors are sent copies of the external reviewers’ comments and are notified as to the decision (accept, resubmit for review (major revisions required and a new external review will be conducted), revisions required (minor revisions required), decline/reject).
IRIS
LLT encourages authors to consider uploading their data collection materials to the IRIS database. IRIS is an online repository for data collection materials used for second language research. This includes data elicitation instruments such as interview and observation schedules, language tests and stimuli, pictures, questionnaires, software scripts, url links, word lists, teaching intervention activities, amongst many other types of materials used to elicit data. Please see http://www.iris-database.org for more information and to upload. Any questions, or the materials themselves, may be sent to iris@iris-database.org. When your article has been formally accepted for publication, your instrument(s) can be uploaded to the IRIS database with an 'in press' reference. The IRIS team will add page numbers to the reference once they are available.
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