Krashen’s Input Hypothesis in Technology-Enhanced and AI-Assisted Language Learning Environments: A Systematic Review
Abstract
This systematic review examines the integration of Krashen’s Input Hypothesis within technology-enhanced and AI-assisted language learning environments over the past decade (2018–2025). As digital tools and artificial intelligence become increasingly central to English as a Foreign Language (EFL) instruction, understanding how theoretical constructs like "comprehensible input" (i+1) and the "affective filter" are operationalized is crucial. Following a systematic selection process from the Web of Science (WoS) database, 12 empirical studies were analyzed based on their research foci, participant demographics, technological tools, and methodological designs. The findings reveal a significant shift from static web-based platforms to dynamic, AI-driven, and immersive environments, such as virtual reality and generative AI agents. Results indicate that while technology effectively facilitates multimodal and personalized input, research remains heavily weighted toward quantitative and mixed methods designs, with a notable absence of qualitative inquiry. Furthermore, most studies focus on undergraduate populations in Asian and Middle Eastern contexts. This review identifies critical research gaps, including the need for longitudinal studies on input comprehension processes rather than just output gains.
Keywords
Input Hypothesis, Artificial Intelligence, Second Language Acquisition, Technology-Enhanced Learning, Systematic Review, EFL
How to Cite
Artul, B., (2026) “Krashen’s Input Hypothesis in Technology-Enhanced and AI-Assisted Language Learning Environments: A Systematic Review ”, Journal of Second Language Acquisition and Teaching (JSLAT) 32, 43–78. doi: https://doi.org/10.2458/jslat.10536
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