ArticleScientific reports2026
Faculty perceptions of AI for personalized instruction and learning facilitation in higher education.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
This study examines university faculty members' perceptions of how artificial intelligence (AI) supports personalized instruction and facilitates learning opportunities in higher education. Given the exploratory nature of AI-based pedagogical practices, a qualitative, interpretive design was employed to capture instructors' lived experiences and meaning-making processes. Semi-structured interviews were conducted with 12 faculty members from two Iranian universities, selected through purposive maximum-variation sampling. Data were analyzed using inductive thematic analysis in MAXQDA 22, and trustworthiness was strengthened through double-coding (Cohen's κ = 0.82), member checking, expert review, and an audit trail. Two overarching themes emerged: (1) personalized course content and (2) facilitation of learning opportunities. Faculty perceived AI as capable of diagnosing learner profiles, adapting instructional materials, generating individualized feedback, and supporting self-paced and competency-based learning pathways. They also viewed AI as a facilitator that enhances access to resources, strengthens interaction and collaboration, and enables predictive academic guidance. Importantly, these findings represent instructors' perceptions rather than empirically verified learning outcomes. Participants emphasized the need for ethical governance, content accuracy, and institutional readiness, highlighting mechanisms such as Retrieval-Augmented Generation (RAG) to ensure reliable AI outputs. Overall, the study provides a contextualized understanding of AI as a multifaceted pedagogical partner in higher education and identifies the conditions necessary for its responsible and effective integration into teaching and learning.
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