Machine and Deep Learning as Perceived by Academic Teaching Staff at Faculty of Nursing in Assuit University

Mohamed Ahmed, Hanaa; Mohamed Abd Allah, Samah; Abd Allah Abozeid, Hanan; Melek Labieb, Martha

doi:10.21608/ejhc.2025.420756

Machine and Deep Learning as Perceived by Academic Teaching Staff at Faculty of Nursing in Assuit University

Document Type : Original Article

Authors

¹ Assistant Professor of Nursing Administration, Faculty of Nursing- Assuit University, Egypt.

² Professor of Nursing Administration, Faculty of Nursing- Assuit University, Egypt.

³ Assistant Professor of Gerontogical Nursing, Faculty of Nursing- Assuit University, Egypt.

⁴ Lecturer of Gerontogical Nursing, Faculty of Nursing- Assuit University, Egypt.

10.21608/ejhc.2025.420756

Abstract

This study investigated the perception of machine and deep learning among academic teaching staff at Assiut University's Faculty of Nursing. Defining machine learning as a subset of artificial intelligence and deep learning as multi-layered neural networks, the study employed a descriptive cross-sectional design. A convenience sample of teaching and assistant teaching staff completed questionnaires about their personal and job characteristics, as well as their understanding of machine and deep learning. The results showed a significant difference in perception: The vast majority of assistant teaching staff reported satisfactory understanding, compared to more than half of teaching staff reporting unsatisfactory understanding (P=0.001). The study concluded that assistant teaching staff demonstrated a significantly higher level of satisfaction and understanding of machine and deep learning compared to teaching staff, with statistically significant differences across all measured dimensions. The researchers recommended implementing educational programs for professors and assistant professors to improve their knowledge of these technologies, and for educational institutions to use this information to inform hiring, training, and evaluation practices, as well as the application of these technologies in the teaching process.

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