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All Journal Journal of Research on English and Language Learning (J-REaLL) JOI Jurnal Gladiator Lentera Negeri JRTI (Jurnal Riset Tindakan Indonesia)
Kristian Burhan
Universitas Negeri Padang
Religion Humanities Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Effectiveness of immersive virtual reality interventions for l2 english oral communication: a systematic review Kristian Burhan
Lentera Negeri Vol. 7 No. 1 (2026): Lentera Negeri
Publisher : Indonesian Institute For Counseling, Education and Therapy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/993850

Abstract

Speaking is one of the most demanding skills for English learners, who often lack authentic, low-anxiety opportunities to practise oral communication. This systematic review synthesises empirical evidence on immersive virtual reality (VR) for L2 English speaking and oral communication. Following PRISMA 2020, searches of Scopus, PubMed, and ScienceDirect identified 948 records; after 11 duplicates were removed, 937 records were screened, 162 full texts were assessed, and 24 empirical studies published between 2021 and 2025 were included. Eligible studies examined English-speaking or oral-communication outcomes in EFL/ESL/ESP learners using immersive VR and were appraised with the Mixed Methods Appraisal Tool (MMAT 2018). Because the included studies differed substantially in design, outcomes, instruments, and reporting, findings were synthesised narratively and thematically rather than pooled statistically. The corpus was dominated by mixed-methods and quasi-experimental studies and was concentrated in Asian higher-education contexts. Across the 24 studies, confidence, willingness to communicate, and engagement showed the most consistently positive descriptive pattern, whereas effects on measured oral proficiency and speaking anxiety were mixed. The evidence therefore supports task-based, scaffolded, and socially supported VR use, while cautioning against equating positive perceptions with demonstrated proficiency gains. Formal inter-rater agreement statistics were not recorded in the original review and are identified as a methodological limitation.
Effects of AI-generated feedback on l2 writing: a PRISMA 2020 systematic review of performance, revision, and engagement outcomes Kristian Burhan
JRTI (Jurnal Riset Tindakan Indonesia) Vol. 11 No. 1 (2026): JRTI (Jurnal Riset Tindakan Indonesia)
Publisher : IICET (Indonesian Institute for Counseling, Education and Therapy)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/30036973000

Abstract

Generative artificial intelligence (GenAI) tools can provide immediate feedback during second-language (L2) writing, but evidence on their effects across writing outcomes remains fragmented. This PRISMA 2020 systematic review synthesized peer-reviewed empirical studies published from 2023 to 2025 that examined GenAI-generated feedback for English writing in EFL/ESL contexts. Searches of Scopus, PubMed, and ScienceDirect identified 1,106 records; after 12 duplicates were removed, 1,094 records were screened, 71 full texts were assessed, and 20 studies met the eligibility criteria. Eligible studies were experimental, quasi-experimental, mixed-methods, qualitative, or design-based investigations reporting writing performance, revision, feedback engagement/literacy, or AI-feedback accuracy. Because study designs, writing tasks, outcome measures, and reported statistics were heterogeneous, statistical meta-analysis and pooled effect-size estimation were not conducted; findings were synthesized thematically and by effect direction. The evidence indicates that GenAI feedback most consistently supports local accuracy, lexical development, revision activity, and learner engagement, whereas effects on syntactic complexity, higher-order composing, and long-term retention are mixed or conditional. Comparative evidence generally supports a complementary model in which AI provides rapid, high-volume local feedback and teachers address global structure, disciplinary expectations, contextual appropriateness, and affective support. Key limitations of the evidence base include short intervention periods, small samples, heterogeneous measurement, limited longitudinal evidence, and uneven geographic representation. Future research should preregister screening procedures, use independent double screening with agreement statistics, report extractable effect sizes and delayed post-tests, and examine equity, transfer, and hybrid AI-human feedback models.
Generative AI in second-language writing: a systematic review of learning, feedback, and literacy outcomes Kristian Burhan
JRTI (Jurnal Riset Tindakan Indonesia) Vol. 10 No. 4 (2025): JRTI (Jurnal Riset Tindakan Indonesia)
Publisher : IICET (Indonesian Institute for Counseling, Education and Therapy)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/30036974000

Abstract

The diffusion of generative artificial intelligence (AI) has challenged assumptions about how English L2 writing is taught, supported, and assessed. This systematic literature review synthesised peer-reviewed empirical evidence on generative AI in English L2 writing, focusing on pedagogical transformation, feedback and assessment, and academic literacy. Following PRISMA 2020, searches of Scopus, PubMed, and ScienceDirect identified 912 records. After duplicate removal and eligibility screening, 18 empirical studies published between 2023 and 2025 were included, although the search window covered 2020-2025. The eligible studies were appraised with the Mixed Methods Appraisal Tool (MMAT 2018), with 14 meeting at least 4 of 5 criteria under the manuscript's descriptive appraisal rubric and four scoring 3.0-3.5; none was excluded solely on quality. Owing to substantial heterogeneity in designs and outcomes, findings were synthesised narratively and no quantitative meta-analysis was attempted. Evidence indicates that generative AI can improve surface-level accuracy, revision activity, and selected language or self-regulatory outcomes, while effects on higher-order rhetorical and critical competencies remain inconsistent. AI is most defensible as a teacher-guided complement, with continuing concerns about academic integrity, over-reliance, assessment validity, and equity. The review identifies priorities for longitudinal, multi-model, and multi-site research.
Co-Authors - Rudyanto Anisa Sholiha Mia Edmizal, Eval Febrian, Mario Helfany Amsa Ifdil Ifdil Indra Hanafi Indri Astuti Jeki Haryanto Juanda Putra M. Arie Desman Muhammad Ghaluh Sari, Suci Nanda Septia Dina Fernanda Sherly Franchisca Yendrizal, Yendrizal Yogi Arnaldo Putra