Research on educational technologies continues to be predominantly shaped by Western research traditions and learning theories (Bulfin et al., 2013; Hew et al., 2019). In addition, much of the extant empirical evidence originates from so-called WEIRD countries (Henrich et al., 2010), meaning western, educated, industrialized, rich, and democratic contexts. This pattern is also visible in recent work on learning analytics (Baek & Doleck, 2024) and bibliometric studies in human–computer interaction (Linxen et al., 2021). Drawing back on empirical research on artificial intelligence in higher education as an example, the presented mapping review (Sutton et al., 2019) examines the extent to which this field remains influenced by WEIRD publications. Following the PRISMA guidelines for systematic reviews (Page et al., 2021), the authors developed an extensive search string and applied pre-determined inclusion and exclusion criteria. Studies were included if they were primary studies that addressed students in tertiary education, clearly focused on AI in higher education, implemented a (quasi)experimental study design, incorporated a distinct method section, and were written in languages that were translatable by DeepL. Following the rigorous application of exclusion criteria during multiple rounds of screening titles and abstracts, as well as the full texts, 249 studies were deemed eligible for inclusion and data extraction. The preliminary results of this review indicate that publication structures have shifted, with almost one third of studies originating from China. However, most studies do not report participant characteristics, raising doubts about whether this geographic shift necessarily reflects more inclusive research practices. The presentation will discuss these findings and their implications for both future research and the responsible use of AI in education.

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