Adaptive AI Integration in Higher Education: Validating the AAIIF Framework for Faculty Adoption and Pedagogical Transformation

DOI

10.2991/978-2-38476-599-7_3How to use a DOI?

Keywords

Adaptive AI Integration Framework (AAIIF); Generative AI; Faculty Development; Technology Acceptance; UTAUT-2; Behavioral Intention; Pedagogical Self-Efficacy; AI Literacy; Quasi-Experimental Design; Human-AI Collaboration; Iterative Design Cycle

Abstract

Generative AI arrived in higher education after late-2022 large language model releases—and existing technology-adoption models weren’t built for it. We close the gap with the Adaptive AI Integration Framework (AAIIF). AAIIF runs in five stages—context assessment, pedagogical alignment, adaptive design, implementation and support, reflective iteration—with ethics threaded through every stage. We tested it in a single-group pre/post quasi-experiment: sixty-four faculty at a Romanian public university across STEM, social sciences, and humanities. The twelve-week hybrid program combined four synchronous workshops, asynchronous resources, peer groups, and individual mentoring. Outcomes came from the AAIIF-Faculty Questionnaire (AAIIF-FQ)—thirty-eight items adapted from UTAUT-2, nine constructs, seven-point Likert. Cycle adherence tracked output quality (r = 0.73, p < 0.001). Behavioral-intention gains hit medium-to-large (Cohen’s d 0.5–0.8). Prior AI experience moderated outcomes—novices benefited most from critical AI-literacy training; experienced users hit ceiling effects. Discipline mattered. A chemistry instructor focused on verifying AI-generated lab examples in thermodynamics, language faculty on cultural verification in second-language teaching, engineering on ethical reasoning around circuit-design prompts. Career stage shaped the arc: junior faculty climbed faster; senior colleagues went further on self-efficacy. The evidence backs AAIIF as a context-aware tool that lifts faculty uptake and AI literacy.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits any noncommercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if you modified the licensed material. You do not have permission under this license to share adapted material derived from this chapter or parts of it.

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TY  - CONF
AU  - Oana-Adriana Ticleanu
AU  - Nicolae Constantinescu
PY  - 2026
DA  - 2026/07/31
TI  - Adaptive AI Integration in Higher Education: Validating the AAIIF Framework for Faculty Adoption and Pedagogical Transformation
BT  - Proceedings of the International Conference on Management and Entrepreneurial Leadership for K-12 Education Excellence (LEADK12 2026)
PB  - Atlantis Press
SP  - 19
EP  - 41
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-599-7_3
DO  - 10.2991/978-2-38476-599-7_3
ID  - Ticleanu2026
ER  -