Artificial Intelligence and Gamification Literacy in Higher Education Language Learning: Insights from a Gamified Diagnostic Test

The rapid integration of artificial intelligence (AI) and gamification into higher education has transformed approaches to teaching, learning, and assessment. This study introduced and validated a case-based gamified diagnostic test for language education. The test was designed to measure students’ literacy in AI, gamification, and ethical–pedagogical competence in English as a foreign language (EFL) learning contexts. A purposive sample of 227 undergraduate pre-service teachers from Zh.A. Tashenev University (Kazakhstan) participated in the study. A mixed-methods research design was used, integrating quantitative data from gamified diagnostics and qualitative insights from a post-test group discussion with students. The diagnostic instrument, implemented on the Wayground gamified platform, incorporated adaptive scoring, leaderboards, real-time feedback, and progress visualization to foster engagement and reflective learning. Quantitative data included performance indicators (total score, accuracy, completion time), while qualitative reflections captured students’ motivation, ethical awareness, and perceptions of usability. Results reveal moderate to high literacy levels across all domains, with the highest scores in ethical awareness (M = 74.19, SD = 24.01). ANOVA results confirmed significant differences in accuracy across readiness levels (F(2,224) = 634.36, p < .001). Strong correlations among AI literacy, gamification literacy, and ethical awareness (r = .73–.94, p < .01) demonstrated the interconnected nature of cognitive, motivational, and ethical dimensions. The findings support the main hypothesis that gamified diagnostics can enhance digital pedagogical competence by combining engagement, ethical reflection, and data-driven learning. The study offers a replicable framework for integrating responsible AI and gamification training in higher education.