Operational Readiness for AI Driven Learning: Examining the Inter-play of Self-Assessed Competence, Usage Patterns and Trust

Abstract

Since the release of generative AI systems in autumn 2022, AI use in academic contexts has gained relevance worldwide. Developing AI-related competencies has emerged as an educational task within the field of learning technologies aimed at enhancing learning outcomes. Against this background, the DigiTaKS*-project investigates how usage patterns, trust in AI, and self-assessed AI compe-tencies are interrelated and how these factors influence students’ operational readiness to integrate AI-driven applications into their learning processes. We frame this presented approach as an idea that can be adapted to different regions and educational systems. This contribution presents findings from a questionnaire study conducted among bachelor’s students in Humanities and Social Sciences at a German university (N = 70). Results indicate that usage, trust, and self-assessed AI competence are closely intertwined and significantly predict opera-tional readiness to integrate AI into academic learning processes. These findings highlight the need for structured educational approaches that systematically foster these interrelated dimensions. In response, the Open Educational Resource (OER) “ComDigiS*” was developed within the project DigiTaKS* to systematically promote reflective, competence-oriented, and equitable AI integration in academic contexts. It conceptualizes AI as a form of machine intelligence and supports in-teracting with AI across different cognitive levels from understanding and apply-ing to critically reflecting thereby fostering a holistic set of AI-use competencies for students. However, the paper presents student AI practices based on ques-tionnaire results and the Open Educational Resource ComDigiS* for promoting (AI) competence development.  Grounded in a European setting, the study pro-poses an approach intended for context-sensitive adaptation across diverse edu-cational systems. While the study is grounded in a European higher-education context, it explicitly acknowledges the situatedness of its concepts. This opens a perspective on how the proposed heuristic can be adapted to diverse educational settings across regions, such as educational contexts across the African conti-nent.