To date, research has not examined the mediating mechanism of ease of use and emotional reaction on the short-term focus of resistance to change and behavior intention to participate in technology-based course activities.
ObjectivesThe study compares resistance to tech-based learning changes in younger and older nursing students and examines how ease of use and emotional reaction mediate between a short-term focus of resistance to change and intentional behavior to participate in technology-based course activities.
MethodsThe researcher recruited 218 nursing students from the School of Health Sciences for a cross-sectional survey. Participants voluntarily completed the online survey, consisting of four sections: perceived ease of use, behavioral intention to use technology, resistance to change scale, and background characteristics. The survey was analyzed using Model 6 via Process software, and ethical considerations such as informed consent and confidentiality were maintained.
ResultsThe study found that younger nursing students had a more robust emotional response to changes in technology-enhanced learning, and older students were more cognitively rigid. The study also found statistically significant serial multiple mediations of emotional response and perceived ease of use in the relationship between short-term focus and intended behavior.
ConclusionsThe study highlights the importance of considering learner diversity, including age, in designing technology-based learning programs and the role of ease of use and emotional reaction as mediating factors in determining students’' behavioral intention to participate. The findings contribute to the literature on inclusive education and the relationship between resistance to change, ease of use, and intention behaviors in technology-based learning.
Section snippetsBackgroundThe pandemic caused by COVID-19 has taken many lives and incurred various costs worldwide, with education being among the sectors most severely affected (Ciotti et al., 2020; Pokhrel & Chhetri, 2021). The COVID-19 pandemic has significantly impacted learning, teaching methods, and real-world applications in academic institutions. The shift from traditional to online learning presents new difficulties, such as balancing flexibility with self-directed learning and promoting student engagement in
Literature reviewThe RTC concept discussed in this paper relies on the comprehensive RTC model based on a person's personality. The model consists of four key elements of resistance: Routine-seeking, Emotional reaction, Cognitive rigidity, and Short-term focus (Oreg et al., 2008). Students' routine-seeking behavior, i.e., their inclination to stick to routines, was evaluated (the behavioral aspect). Emotional reaction refers to change capturing the students' discomfort in facing changes, and the short-term
Study designThe study used a cross-sectional design with a convenience sample.
Participants and procedureThe researcher recruited 218 students from the Nursing Department at the School of Health Sciences, Ariel University, Israel, as participants, representing a response rate of 62 %. The inclusion criteria for subjects comprised of nursing students enrolled in a recognized B.Sc. nursing program that used technology-based learning in their programs. Exclusion criteria included students not enrolled in a nursing program and
ResultsThe average age of the study participants was 27 years, with a standard deviation of 6.35. On average, they reported using 0.71 technologies for learning, with a standard deviation of 1.17, and identified 1.14 benefits of technology use in education, with a standard deviation of 1.49. For frequencies and percentages of participants' background characteristics, see Table 1.
Table 1 illustrates that most participants were female, single, Jewish (all), and in their first year of study, with a
DiscussionThe study strives to compare resistance to tech-based learning changes in younger and older nursing students. It examines how ease of use and emotional reaction mediate between a short-term focus of resistance to change and intentional behavior to participate in technology-based course activities.
First, it was found that younger nursing students presented a more robust emotional response to changes in technology-enhanced learning than their older counterparts; they tend to feel stressed and
ConclusionIn conclusion, the study provides insight into the differences in resistance to technology-based learning changes among younger and older nursing students. The study's findings can also be used to inform policies and practices in nursing education, such as providing more support and resources for older nursing students who may have more difficulty adapting to technology-based learning.
The study also demonstrates the critical role of ease of use and emotional reaction as mediating factors in
Limitations and recommendations for future researchThe study was conducted with a limited sample of 218 nursing students from a specific of health sciences. Future research could benefit from more extensive and more diverse samples regarding background characteristics, to enhance the generalizability of the findings. Using a cross-sectional survey might limit the ability to establish causal relationships between variables. Longitudinal studies (examining the study model multiple times) could provide more insights into the dynamic nature of the
Implications for nursing educationNursing educators and institutions could consider the following implications. To optimize nursing education, it is crucial to implement targeted support systems for younger and older students, including tailored resources, workshops, and mentorship programs to alleviate stress related to technology-enhanced learning. The findings underscore the importance of considering emotional reactions and perceived ease of use in understanding the dynamics of resistance to technological changes in
Author contributionsGizell Green conducted all research stages.
FundingThis research received no external funding.
Institutional Review Board statementThis study was conducted according to ethical guidelines and approved by the Institutional Review Board (IRB) of Ariel University.
Informed consent statementInformed consent was obtained from all research participants involved in the study.
GuarantorGizell Green.
Declaration of competing interestThe authors declare no conflicts of interest.
AcknowledgmentsThis research is the result of research conducted at the university.
References (41)M.K. Hsu et al.Computer attitude, statistics anxiety and self-efficacy on statistical software adoption behavior: An empirical study of online MBA learnersComputers in Human Behavior
(2009)
F.C. Tung et al.Nursing students’ behavioral intention to use online courses: A questionnaire surveyInternational Journal of Nursing Studies
(2008)
L. Carter et al.The utilization of e-government services: Citizen trust, innovation, and acceptance factorsInformation Systems Journal
(2005)
A. Chayomchai et al.Factors affecting acceptance and use of online technology in Thai people during COVID-19 quarantine timeManagement Science Letters
(2020)
M. Ciotti et al.The COVID-19 pandemicCritical Reviews in Clinical Laboratory Sciences
(2020)
E. Crisol Moya et al.University students’ emotions when using E-portfolios in virtual education environmentsSustainability (Switzerland)
(2021)
S.J. DanielEducation and the COVID-19 pandemicProspects
(2020)
F.D. DavisPerceived usefulness, perceived ease of use, and user acceptance of information technologyMIS Quarterly: Management Information Systems
(1989)
J.C. Diedericks et al.Resistance to change, work engagement and psychological capital of academics in an open distance learning work environmentSA Journal of Human Resource Management
(2019)
D. DuongAlpha, Beta, Delta, Gamma: What’s important to know about SARS-CoV-2 variants of concern?CMAJ : Canadian Medical Association journal = journal de l’Association medicale canadienne
(2021)
M. Dyehouse et al.Examining the relationship between resistance to change and undergraduate engineering students’ environmental knowledge and attitudesStudies in Higher Education
(2017)
L. Espino-Díaz et al.Analyzing the impact of COVID-19 on education professionals. Toward a paradigm shift: ICT and neuroeducation as a binomial of actionSustainability (Switzerland)
(2020)
J.J. Gross et al.Emotion and aging: Experience, expression, and controlPsychology and Aging
(1997)
A. HayesIntegrating mediation and moderation analysis: Fundamentals using PROCESS(2013)
N. Jahangir et al.The role of perceived usefulness , perceived ease of use , security and privacy , and customer attitude to engender customer adaptation in the context of electronic bankingAfrican Journal of Business Management
(2008)
G. Kouri et al.The Greek resistance to change scale: A further validationInternational Journal of Caring Sciences
(2020)
F. Kunze et al.Age, resistance to change, and job performanceJournal of Managerial Psychology
(2013)
P. LaiThe literature review of technology adoption models and theories for the novelty technologyJournal of Information Systems and Technology Management
(2017)
S. Laumer et al.User personality and resistance to mandatory information systems in organizations: A theoretical model and empirical test of dispositional resistance to changeJournal of Information Technology
(2016)
J. Liu et al.Mediation analysis in nursing research: A methodological reviewContemporary Nurse
(2016)
View full text© 2023 Published by Elsevier Inc.
Comments (0)