Systematic Literature Review Artificial Intelligence Readiness Assessment of Prospective Vocational Teachers Informatics using Artificial Intelligence Application in Education for Sustainable Development Erlangga, Ana, Isma Widiaty, Dwi Novial Al-Husaeni, Tatang Mulyana
Universitas Pendidikan Indonesia
Abstract
Assessing the technical skill readiness of prospective vocational teachers is crucial for evaluating the quality of graduates from higher education institutions, especially in terms of computer Artificial Intelligence Readiness skills that align with industry requirements. This systematic literature review focuses on the research surrounding the evaluation of prospective vocational teachers readiness in Artificial Intelligence, specifically through the use of artificial intelligence (AI)-based assessment methods. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted a thorough search of studies published between 2015 and 2025 across the Scopus, Web of Science, and IEEE Xplore databases. From an initial pool of 250 records, we screened for relevance, methodological quality, and full-text availability, ultimately including 42 studies in our final analysis. The review identified three primary AI approaches: (1) The general status of research trends on AI readiness in education in the annual distribution of publications and citations of research on the application of ai in AI readiness, and (2) The trends and impacts of AI implementation in measuring AI readiness in education evolve from the research theme development path. These findings highlight the importance of AI readiness in supporting AI implementation in education, which can improve the quality of learning and enrich educational experiences globally.
