Beyond digital-native assumptions: A systematic integrative review of Generation Z teachers and learners in English language education

Erna Iftanti; Umniyati Ris’ah

doi:10.70376/jerp.v4i2.457

Authors

Erna Iftanti English Department, Universitas Islam Negeri Sayyid Ali Rahmatullah Tulungagung, Indonesia https://orcid.org/0000-0001-6913-3125
Umniyati Ris’ah English Department, Universitas Islam Negeri Sayyid Ali Rahmatullah Tulungagung, Indonesia https://orcid.org/0009-0005-3739-8803

DOI:

https://doi.org/10.70376/jerp.v4i2.457

Keywords:

Generation Z English teachers, English language teaching, teacher professional identity, digital pedagogy, generative artificial intelligence

Abstract

Generation Z is increasingly being discussed as both a teacher cohort and learner population in English-language education amid the expansion of digital platforms and generative artificial intelligence. However, evidence is distributed across teacher- and learner-focused studies, creating the risk that findings about learners may be attributed to teachers from the same cohort. This systematic integrative review examined teacher professionalism, pedagogy, technology use, learner experience, and implementation conditions, while maintaining a distinction between direct teacher evidence and contextual learner evidence. Searches completed on 19 May 2026 covered Dimensions, Google Scholar, ERIC, GARUDA, publisher websites, and DOI registries. Forty-one articles with resolvable DOIs were retained in the evidence maps. Directed qualitative content analysis and study-level methodological flags were applied to 40 full texts comprising 12 teacher-focused and 28 contextual studies. The evidence base was recent and geographically uneven: 35 articles were published between 2023 and 2026 and 13 were situated in Indonesia. In the core studies, Generation Z English teachers were represented as developing professionals negotiating identity, authority, resilience, and digital agency, rather than as uniformly competent digital natives. Technology and engagement frequently co-occurred in studies describing relevant, interactive, and learner-centred tasks, but this pattern did not establish effects on engagement or language learning. Reported uses of generative AI include material preparation, feedback, and personalisation, accompanied by concerns about accuracy, dependence, integrity, and human oversight. As 28 studies relied primarily on self-report or perception evidence, claims regarding effectiveness remain limited. The synthesis organises recurring implications into an equity-sensitive framework that connects professional identity and early career resilience, ELT-specific digital pedagogy, critical AI literacy with human oversight, and institutional support. Its originality lies in separating teachers from learner evidence, treating generation as a situated context rather than a causal explanation, and connecting ethical digital transformation with sustainable teacher capacity.

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