Rethinking the effects of performance expectancy and effort expectancy on new technology adoption: Evidence from Moroccan nursing students

Abstract

Clinical practice is a part of the integral learning method in nursing education. The use of information and communication technologies (ICT) in clinical learning is highly encouraged among nursing students to support evidence-based nursing and student-centered learning. Through the information-processing lens of the mindsponge theory, this study views performance expectancy (or perceived usefulness) and effort expectancy (or perceived ease of use) as results of subjective benefit and cost judgments determining the students’ ICT using intention for supporting clinical learning, respectively. Therefore, the study examines whether effort expectancy moderates the relationship between performance expectancy and the intention to use ICT among Moroccan nursing students. The Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset of 702 Moroccan nursing students. We found that nursing students’ performance expectancy is positively associated with the intention to adopt ICT and social media, while effort expectancy positively moderates this relationship. Moreover, the model with effort expectancy as the moderator was discovered to have a significantly larger weight than the model with effort expectancy as the direct predictor, validating our information-processing reasoning. This study provides a new perspective on the interplay between the benefit and cost perceptions of ICT use to support clinical learning methods in nursing education. Moreover, given the limited education resources, especially in developing countries like Morocco, we recommend nursing education and training prioritize communicating the benefits of ICTs and social media over ease of use. Doing so would help improve the effectiveness and efficiency of nursing education and training while lowering costs.

Author Profiles

Sari Ni Putu Wulan Purnama
Widya Mandala Surabaya Catholic University
Dan Li
Pepperdine University (PhD)
2 more

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2023-11-28

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