1 INTRODUCTION

The COVID-19 pandemic has posed substantial challenges for education worldwide. Massive school closures in over 200 countries have displaced approximately 1.6 billion learners, equivalent to over 94% of the student population worldwide.1, 2 The crisis propelled academic institutions to shift to other learning platforms, such as distance learning and online education, as an immediate solution.1, 3 However, reports have revealed that a sizeable portion of the academic sector has been unprepared to meet the demands of this bold, futuristic direction.4, 5

The Sultanate of Oman responded robustly to contain the spread of the virus by instituting national quarantine and lockdown measures. Since March 15, 2020, schools at all levels have been physically closed and shifted to emergency remote teaching (ERT). Essentially an immediate remedy to a crisis situation, ERT comprises an urgent albeit temporary solution to provide remote methods of delivering instruction until the emergency subsides.6 In response to the exigent nature of the transition, administrators and educators across the country transitioned to the online platform, adopting videoconferencing, videorecording of lectures, and synchronous and asynchronous online discussions. Alternative strategies for clinical and laboratory experiences such as posting clinical case scenarios for comprehensive discussion and uploading available videos covering nursing procedures were implemented. In contrast, before the pandemic, nursing schools all over the country had relied primarily on traditional face-to-face teaching. Thrusting students into fully online education has been a unique and extraordinary solution to an unanticipated situation. Traditional versus online education platforms feature completely different structures, contexts, requirements, preparations, and demands.7 Moreover, success in online learning requires students to have a high degree of self-direction and motivation.8

Self-directed learning (SDL) goes by the principle of adult learning. The literature employs various terms for this educational method, including student-centered learning, self-instruction, self-teaching, prescriptive learning, and individualized learning.9 Meanwhile, learning styles (LS) represent an individual learner's preferred set of cognitive and behavioral feedback concerning a learning task.10 LS influence learners' motivation and attitude to learn and may affect their academic performance.10 In the area of healthcare education, nurse educators are key players in helping nursing students develop their readiness and skills for SDL through the prudent exercise of control and a teaching method designed to meet students' needs and LS.11, 12

2 LITERATURE

The demand for lifelong learning and SDL skills in the nursing curriculum has expanded considerably, as seen by the current integration of these concepts into the overall nursing program, program registration, and accreditation processes.13 Nursing schools have made efforts to integrate SDL into the nursing curriculum, as exemplified by the inclusion of problem-based learning, team-based learning, simulations, hands-on clinical experience, reflective journals, and case studies, as well as the emergence of online learning.13, 14

Furthermore, as a vital element in the development of life-long learning, SDL is an integral skill of the 21st-century nurse professional.15 Mounting evidence has strongly linked SDL with enhanced learning outcomes and academic performance in nursing students14, 16 as well as ensuring adequate preparation of nursing students for their future role as healthcare professionals.9, 11 Nursing students who have high SDL skills tend to exhibit better learning and studying strategies, such as the ability to deduce the most relevant information, relate previous learning with current knowledge, master test-taking skills, and enjoy a more optimistic attitude.17 Furthermore, their awareness of their own learning process puts nursing students in a better position to initiate and plan for future learning.9 In view of the essential nature of SDL, teaching and learning strategies that use this approach must be deliberately incorporated into the nursing curriculum.11, 14

To date, many studies have examined SDL and LS among students in higher education, including those enrolled in nursing programs.11, 18-20 However, studies evaluating how LS is associated with SDL readiness among student nurses are scarce. Accordingly, this study, set in Oman, explored nursing students' readiness for SDL, their LS, and the association of their demographic variables and LS with their SDL. The current global situation, where many nursing schools are employing an online learning platform, has compelled students to exercise self-direction in their learning, making this study's potential contribution more valuable than ever. To the best of the authors' knowledge, this study is the first that links students' demographics and LS with SDL within the realm of nursing education during the COVID-19 pandemic, thus contributing new knowledge on this relevant topic.

3 METHODS

This study followed a descriptive, cross-sectional approach using online data collection. Typically employing population-based surveys taken at a single point in time, such a design describes the predominant characteristics of phenomena as well as the association between or among the variables under study.21 Hence, this approach is highly suited to shed light on the study topic of inquiry.

3.1 Samples and settings

Nursing students from three institutions of higher education in Oman were recruited to participate in the study. The study's inclusion criteria required each eligible student to (1) be currently registered in a nursing institution, (2) be a full-time student, and (3) have consented to participate in the study. Power analysis using the G power program showed that the minimum required sample size was 172 to achieve 80% power (where effect size was 0.10 and α = 0.05). This estimated effect size offered an adequate sample to identify significant correlations between the study variables. The online questionnaire was sent to 350 students, and 236 students responded (response rate = 67%) during a 2-month data collection period from June to July 2020, 2 months shortly after the commencement of ERT through online learning at the onset of COVID19-related school closure.

3.2 Instruments

Data were collected using a three-part online questionnaire. The first section inquired about the nursing students' demographic characteristics. The second and third sections consisted of the following two psychometrically valid scales, used with the permission of the original authors.

Self-Directed Learning Readiness Scale for Nursing Education (SDLRSNE).22 This scale consists of 40 items where the respondents indicate their degree of agreement or disagreement in describing their own characteristics using a 5-point Likert scale (5 = strongly agree and 1 = strongly disagree) for each item. The items on the scale are categorized into three subscales: self-management (13 items), desire for learning (12 items), and self-control (15 items). Four negatively worded items are reverse-scored. A total score greater than 150 implies readiness for SDL. According to previous research, the validity of the SDLRSNE was primarily established by a Delphi technique among a panel of experts, and the scale was determined to have an internal consistency reliability value of 0.924.22 In this study, Cronbach's alpha for the internal consistency of the scale was α = 0.87, and the subscales ranged from 0.88 to 0.95.

Learning Style Scales (LSS).23 As a relatively new tool, the LSS was psychometrically tested among Muslim nursing students in Iran and Malaysia. This normative scale consists of 22 items scored with a 6-point Likert scale (6 = strongly agree and 1 = strongly disagree) that identifies students' LS as solitary (2 items) versus sociable (2 items), competitive (3 items), imaginative (4 items), perceptive (7 items), or analytical (4 items). The scale has demonstrated excellent face and content validity, according to an expert panel, as well as internal consistency reliability, with Cronbach's α of ≥0.80 and ≥0.70 for its subscales.23 In the current study, Cronbach's alpha for the internal consistency of the scale was α = 0.90, and the values for the subscales ranged from 0.75 to 0.94. The LSS is short, simple, and easy to use. The current study's objectives, along with the similarity of the sample characteristics in terms of religion, culture, and geographical proximity as well as the challenges of online data collection during a lockdown, made the LSS seem well-suited for this study.

3.3 Data collection and ethical considerations

Ethical clearance was obtained from the main author's research and ethics committee [CON/NF/2020/13] and, subsequently, from each study site's respective research ethics committee. Data collection was conducted through an online questionnaire using Google Forms. An email communication containing the full disclosure of respondents' rights as participants, the purpose and nature of the study, and the benefits and risks that could be derived from the study results was sent to all eligible respondents. Completion and submission of the survey form indicated each participant's consent. The principal investigator had exclusive control and access to the online survey database. No personal identifiers were requested from the respondents.

3.4 Data analysis

The collected data were analyzed using SPSS version 25.24 A univariate descriptive statistical analysis was used to analyze independent variables. Mean scores were calculated for the students' overall SDL readiness and its subscales. For LS, items corresponding to a specific style were grouped, and cumulative mean scores were calculated. Additionally, Pearson's chi-squared test, a t-test, and ANOVA were conducted to identify relationships between the relevant variables (bivariate analysis). Multiple linear regression was used to determine the association of students' demographic variables and LS with their SDL. Data analysis was set at a 95% confidence interval and statistical significance of p < 0.05.

4 RESULTS

A total of 236 out of 350 students completed the online survey (response rate = 67%). The participating students' ages ranged from 18 to 37 years, with a mean age of 21 (SD = 3.02). Most of the participants were female (85.2%), single (94.9%), and currently enrolled in the BSN degree (83.9%). Less than half (41.9%) indicated being at a first-year level. More than a third reported a semester GPA between 3.0 and 3.49 (39.4%) and a cumulative GPA between 2.5 and 2.99 (33.1%), and most had never been on probation status (CGPA or SGPA <2.0) (82.2%) (Table 1).

Table 1. Students' characteristics (n = 236) Variables Category Mean SD Age (range: 18–37) 21.44 3.02 N % Gender Male 35 14.8 Female 201 85.2 Academic degree Diploma in Nursing 13 5.5 Bachelor of Science in Nursing 198 83.9 Bridging Program 25 10.6 Year level Year 1 99 41.9 Year 2 29 12.3 Year 3 35 14.8 Year 4 37 15.7 Year 5 26 11 Year 6 10 4.2 Semester GPA <2.0 8 3.4 2.00–2.49 33 14 2.50–2.99 63 26.7 3.0–3.49 93 39.4 >3.5 39 16.5 Cumulative GPA <2.0 6 2.5 2.00–2.49 41 17.4 2.50–2.99 78 33.1 3.0–3.49 73 30.9 >3.5 38 16.1 Probation status Yes 42 17.8 No 194 82.2 Marital status Single 224 94.9 Married 12 5.1 Note: Year Level: Nursing program in Oman starts with a mandatory 1 year-Foundation Program where students learn English, mathematics, computer and general study skills (Year 1). After which, they are admitted into their respective nursing programs. Diploma in Nursing (DN) spans 3 years (Year 2–4); Bachelor of Science in Nursing (BSN) lasts 5 years (Year 2–6); and Bridging Program lasts 2 years (Year 5–6). The Bridging Program is offered only to students who have completed the DN program and aspire to continue their studies to the BSN level. Abbreviation: GPA, grade point average.

The mean scale score in the SDLRSNE was 149.58 (SD = 29.07). Out of 236 students, 147 (62%) scored >150. The mean scores for the SDLRSNE subscales were as follows: self-management = 46.85 (SD = 8.56), desire for learning = 45.94 (SD = 9.71), and self-control = 56.79 (SD = 11.96). The LS that obtained higher means were perceptive LS (mean = 4.7) and imaginative LS (mean = 4.54), while analytical LS (mean = 4.29) and sociable LS (mean = 3.96) obtained the lowest means (Table 2).

Table 2. Students' SDL readiness and LS Scale/subscales Mean SD Overall SDL readiness 149.58 29.07 Self-management 46.85 8.56 Desire for Learning 45.94 9.71 Self-control 56.79 11.96 Learning styles Solitary 4.32 1.41 Sociable 3.96 1.45 Competitive 4.47 1.18 Imaginative 4.54 1.19 Perceptive 4.70 1.21 Analytical 4.29 1.19 Abbreviations: LS, learning styles; SDL, self-directed learning.

Bivariate analysis revealed a significant relationship between students' SDL readiness and their SGPA (F = 5.31, p = 0.001), CGPA (F = 3.45, p = 0.008), and probation status (t = −2.73, p = 0.008). Moreover, all LS correlated positively and significantly with the SDL (all p < 0.001). However, no significant relationship emerged between students' SDL and their age, gender, academic degree, year level, marital status, area of residence, monthly family income, leadership assignment in academic-related activities, participation in extracurricular activities, and leadership assignment in extracurricular activities (Table 3).

Table 3. Association between students' SDL, their demographics and LS Variables Category Mean SD Statistical test p value Age r = 0.048 0.46 Gender 142.57 28.46 t = −1.575 0.122 150.81 29.07 Academic degree 140.85 21.31 F = 0.694 0.501 149.83 29.77 152.20 26.93 Year level 150.86 28.43 F = 2.326 0.06 150.14 22.41 139.77 36.45 143.81 24.67 161.04 33.28 161.30 10.67 Semester GPA 131.50 28.14 F = 5.31 0.001 132.52 35.03 2 < 3,4,5* 150.67 26.57 152.04 29.95 160.13 16.47 Cumulative GPA 123.83 30.07 F = 3.45 0.008 146.68 31.23 3 < 4* 144.26 27.93 157.53 26.63 152.45 29.62 Probation status 136.24 36.20 t = −2.73 0.008 152.47 26.52 1 < 2 Marital status 150.38 28.34 t = 1.356 0.199 134.83 38.96 Area of residence 149.51 26.99 t = 0.03 0.972 149.65 30.85 Monthly income 146.46 29.97 F = 0.67 0.643 150.88 31.24 155.54 21.70 142.07 32.89 147.42 26.48 155.67 21.98 Assigned as leader in academic-related activities 144.54 28.27 F = 0.65 0.640 151.17 29.60 151.42 28.33 152.11 24.80 147.23 44.95 Participation in extracurricular activities 151.89 26.68 F = 1.80 0.120 148.89 28.60 150.79 31.09 132.71 34.97 165.00 9.64 Assigned as leader in extracurricular activities 152.06 25.67 F = 0.70 0.614 147.67 31.30 144.55 36.23 144.43 32.16 154.33 18.82 Solitary LS r = 0.620 0.001 Sociable LS r = 0.276 0.001 Competitive LS r = 0.687 0.001 Imaginative LS r = 0.733 0.001 Perceptive LS r = 0.753 0.001 Analytical LS r = 0.592 0.001 Abbreviations: LS, learning styles; SDL, self-directed learning. * p < 0.05.

Table 4 displays the results of the hierarchical regression analyses. Variables that significantly correlated with SDL in the bivariate analysis were clustered into two groups (students' demographic variables and LS) and entered into the h