Generative AI Confidence Modeling in Nursing Education Based on Interpretable Machine Learning: An Analytical Framework for Structured Questionnaire Data

Basit Raza; Samina Rajper; Hidayat Shaikh; Zahid Hussain Shar; Sadaf Bibi; Iqra Hyder; Sadia Bibi

Author(s)

Basit Raza Aror University of Art,Architecture, Design & Heritage,

Samina Rajper Aror University of Art,Architecture, Design & Heritage,

Hidayat Shaikh Aror University of Art,Architecture, Design & Heritage,

Zahid Hussain Shar Aror University of Art,Architecture, Design & Heritage,

Sadaf Bibi Aror University of Art,Architecture, Design & Heritage,

Iqra Hyder Aror University of Art,Architecture, Design & Heritage,

Sadia Bibi Sukkur IBA University University Country:,,Pakistan

Abstract

With the rapid penetration of Generative Artificial Intelligence (GenAI) into education and healthcare practice, learners' "confidence in using" these tools is gradually becoming a key variable influencing effective application, sustained adoption, and risk control. Existing research largely remains at the level of descriptive statistics or qualitative discussions, lacking quantitative modeling methods that can simultaneously characterize the combined effects of "training experience-familiarity-confidence in using" and have a reproducible process. Therefore, this paper proposes an interpretable machine learning analysis framework for nursing education scenarios. Variables such as training exposure, GenAI familiarity, tool usage, learning experience, and self-rated confidence are collected based on an online questionnaire; after data cleaning and privacy protection, feature engineering is used to unify key variables into modelable inputs, and "confidence" is predicted and explained through both regression and classification paths. This paper emphasizes using transparent and interpretable models as a strong baseline, and combines cross-validation and visualization analysis to output actionable educational recommendations, providing data-driven evidence for curriculum design, tiered training, and capacity building.

Publication Details

Page(s) 73-76

DOI DOI not available

Published Journal: Journal of Information & Communication Technology (JICT), Volume: 19, Issue: 2, Year: 2025

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Keywords

learning analytics, AI Literacy, Generative Artificial Intelligence, Questionnaire Data Analysis, Nursing education, Explainable Machine Learning

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