Obstacles of Online Learning Facing Nursing Students after the COVID-19 Pandemic

Background After the COVID-19 pandemic, the online style of instruction started to replace the traditional style in Jordan. Aims This study aims to (1) assess the nursing students' perceived obstacles to online learning in Jordan; (2) explore significant relationships between participants' characteristics and their perceived obstacles; and (3) assess for significant differences in the perceived obstacles based on participants' characteristics. Methods A cross-sectional, descriptive design was utilized in this study. A convenient sample of 325 nursing students responded to a self-reported questionnaire utilizing Google Forms. Both descriptive and inferential statistics were used to analyze the dataset using the SPSS software. Results The mean scores of the obstacles to online learning were 2.94 (SD = 0.95) for the academic obstacles subscale, 2.90 (SD = 0.83) for the technological obstacles subscale, and 3.25 (SD = 1.00) for the administrative obstacles subscale. Significant associations were found between participants' characteristics and perceived obstacles to online learning. For instance, the type of university was significantly associated with academic (r = −0.32, p < 0.01), technological (r = −0.21, p < 0.01), and administrative obstacles (r = −0.32, p < 0.01). Furthermore, significant differences were found in the perceived obstacles based on the participants' demographic and studentship-related characteristics. Conclusions According to their perceptions of online learning, nursing students in Jordan face three types of obstacles: academic, technical, and administrative. Decision-makers should intervene to enhance the online learning experience by overcoming the reported obstacles.


Introduction
Over the last two decades, online teaching has begun to spread in higher education, especially in the United States [1].Despite the immense advancements in teaching technologies and Internet access, traditional teaching remains the dominant style of instruction in universities worldwide [2][3][4].Te reason behind this domination could be that faceto-face teaching has several advantages such as the high and immediate interaction between students and teachers, the less distractive environment, and socialization between students and teachers and between students themselves, especially in the small lecture halls.However, face-to-face teaching has several disadvantages including traveling costs and time rigidity [5].
In 2019, the coronavirus disease (COVID-19) started to spread around the world causing millions of deaths [6].Terefore, the World Health Organization (WHO) recommended governments around the world to implement rapid responses to the COVID-19 pandemic [7].In response to WHO recommendations, governments restricted traveling, closed airports, applied social distancing measures [8], and used online teaching as an alternative to face-to-face teaching [3].
Indeed, the recent pandemic has tipped the scales and driven higher education institutions to adopt the online style of instruction [2,4,5,[9][10][11][12].Despite its advantages, such as time fexibility [4,5] and lower costs [4,11], the online style of instruction has faced many hurdles [2,4].Tese hurdles include poor Internet access [4,9], lack of student and teacher coaching [13], a disruptive household setting [2,14], and scarce digital backing [11,15], which are the most pressing issues confronted by teachers and students.Te root cause for these barriers could be the unexpected and unplanned use as a result of the COVID-19 pandemic [11].
Following the epidemic, a lot of colleges around the world embraced the blended/online style of instruction [10].Te blended style of instruction is described as a mixture of conventional and electronic teaching [16,17].Tis kind of teaching gives students the freedom of electronic learning while still allowing them to connect with their peers and teachers in a typical classroom setting [16,18].Another rationale for using this approach is to stay up to date with the emerging trend of combining electronic and traditional instruction [18,19].However, there are some issues that institutions should keep in mind when introducing the hybrid approach.First is ensuring that the quality of blended courses is comparable to that of traditional courses.Second, universities must ensure that students and instructors have access to the necessary resources, training, and support to succeed in integrating the blended style [3,20,21].
Te negative attitude towards online teaching and lack of previous experience in online teaching should not be overlooked [11].Some of the reported obstacles in online teaching are related to session control such as controlling student participation [11].Another study found that students feel stressed, complain of poor sound clarity, and fail to learn in the home atmosphere [15].
According to a Saudi Arabian study, obstacles facing both students and teachers in online teaching can be academic, technical, or managerial.Academic obstacles for teachers include the time needed to prepare online teaching materials, the absence of communication with students, and the time needed to prepare online exams.Academic obstacles for students include the absence of communication with teachers, unavailability of time needed to complete the online course requirements, and unapproachable online course materials.Technical obstacles for teachers include a lack of technical backing, unavailable technological requirements and training, and the difcult use of online teaching software.For students, technical obstacles include the difcult use of online teaching software, and the unavailable technological requirements, training, and technical backing.Managerial obstacles for teachers include poor managerial reassurance, weak Internet access, negative criticism, and poor online teaching infrastructure.For students, managerial obstacles include weak Internet access, negative criticism, and poor online teaching infrastructure [9].
To date, the immature technical infrastructure of online teaching is a key obstacle, especially in third-world countries such as Jordan.For example, statistical reports indicate that the percentage of Internet users in Jordan is only 66% compared with 91% of United States inhabitants and 98% of Saudi Arabia inhabitants [22,23].Due to such circumstances, online teaching is still at its beginning at Jordanian universities.Taking into consideration these inputs, obstacles that hinder online teaching in Jordan are expected to be more impactful.A Jordanian study assessed students' perceived barriers to online teaching before the COVID-19 pandemic [24] and found that students were concerned about online teaching infrastructure and efectiveness, and whether they were delighted to use it.Furthermore, the case is even more complicated with health sciences teaching such as nursing teaching.Te reason behind this particularity is that nursing students need to demonstrate practical skills and undergo clinical training [13,[25][26][27].
Jordan is one of the developing Middle Eastern countries that incorporated the online style of instruction in higher education institutions after the COVID-19 pandemic [28].Despite the immense advancements in teaching technologies and Internet access around the world, students started to face several obstacles in using online learning during and after the COVID-19 pandemic [9,29].It is essential for universities to carefully consider these obstacles and develop strategies to overcome them.
In Jordan, obstacles to online learning facing nursing students are not yet well understood whether they are academic, administrative, or technical.To the best of our knowledge, no study yet has addressed the obstacles of online learning among nursing students, particularly in Jordan.Tis means that the current study is the frst Jordanian study to evaluate difculties facing online learning among nursing students.Knowing these obstacles might help decision-makers in higher education to ease the way of online learning by making appropriate laws.Tus, the main aim of this study was to identify obstacles to online learning facing nursing students after the COVID-19 pandemic in Jordan.Te second aim was to search for signifcant relationships between participants' characteristics and perceived obstacles to online learning.Te third aim of this study was to look for signifcant variances in the perceived obstacles to online learning based on participants' characteristics.

Sample.
Te sample was selected conveniently by using the snowball technique in which researchers invited nursing students at Jerash University to participate in this study.Ten, the invited participants were asked to invite nursing students from other universities in Jordan.To reduce the potential bias with our convenient sample, the researchers targeted key traits for our target population (nursing 2 Te Scientifc World Journal students in Jordan).Tese traits included gender, year of study, type of university (public/private), and type of study (regular undergraduate students/diploma-to-bachelor bridging students).To avoid these traits being underrepresented, the researchers were keen to invite students from diferent academic levels.For example, the researchers selected students from basic and advanced courses to represent new and old students, respectively.In addition, two of the research teams who work at the governmental universities did the same at their institutions to represent the targeted traits.
To guarantee a satisfactory statistical power, a priori sample size calculation was performed using G * Power software 3.1 [30].Using the t-test approach/Wilcoxon-Mann-Whitney test with a medium efect size, signifcance set at 0.05, and power at 0.95, a sample size of 184 was needed.However, the post hoc analysis showed that our fnal sample with 325 participants provided a power of 0.99.

Data Collection.
In this study, data were collected online using Google Forms ® in the period between 17 January and 31 March 2023.A link to the questionnaire was created and shared with the potential participants at Jordanian universities.Tose students who agreed to participate in this study were voluntarily asked to fll out a validated questionnaire.To reduce the potential selection bias by using Google Forms ® , the researchers distributed the link through mul- tiple channels to reach diferent groups and represent different participants' traits.Te channels included WhatsApp ® , Facebook ® , and e-mail addresses.

Instrument.
Participants responded to a group of demographics and studentship-related characteristics, and a validated questionnaire on obstacles to online learning.Tis instrument is a validated questionnaire composed of 11 Likert items (5 strongly agree and 1 strongly disagree) measuring three dimensions namely: academic (three items), technological (fve items), and administrative obstacles (three items) of online learning [9].According to Ja'ashan [9], Cronbach's alpha for the instrument was 0.8.

Ethical Consideration.
As this study involved human subjects, ethical approval was obtained from the Institutional Review Board (IRB) at Jerash University according to the decision no.3/4/2022/2023.Regarding the instrument use, permission was obtained from the instrument creator.Voluntary participation and free withdrawal from the study were ensured on the study's coversheet.

Data Analysis.
Te Statistical Package for the Social Sciences (SPSS) software was used in the data analysis.After downloading our data from Google Forms as an Excel sheet, the data were copied to the SPSS, cleaned, and coded.First, Kolmogorov-Smirnov and Shapiro-Wilk tests were used to check whether the data were normally distributed and to select statistical tests accordingly.
Kolmogorov-Smirnov and Shapiro-Wilk tests showed that the three subscales' data were nonnormally distributed and that the overall score's data were normally distributed.To normalize our data by removing the outliers, the square root transformation technique was used.As it did not work, we used nonparametric statistics.
Statistical tests included frequencies and percentages for categorical variables such as gender and marital status.In addition, mean and standard deviation were used to describe participants' scores on the outcome variables (academic, technological, and administrative obstacles and overall score).Spearman's correlation was used to fnd the significant relationships among variables.
To look for signifcant diferences in the outcome variables based on participants' demographic and studentshiprelated characteristics, the Mann-Whitney test (for variables with two groups) and the Kruskal-Wallis test (for variables with three or more groups) were used.A p value of less than 0.05 was considered statistically signifcant.

Scale Reliability.
In this study, the internal consistency of Cronbach's alpha coefcient was used to assess the reliability of the questionnaire.According to the results of the scales, Cronbach's alpha coefcient for the scale used was 0.872.However, Cronbach's alpha coefcient for the three subscales was 0.653 for the academic subscale, 0.776 for the technological subscale, and 0.777 for the administrative subscale.

Participants' Characteristics and Scores on Outcome
Variables.Tis study collected data from 325 participants in Jordan, of which 226 (69.5%) were female, 245 (75.4%) were single, and 220 (67.7%) were from private universities.Regarding their geographical regions, 203 (62.5%) were from the northern region, 112 (34.5%) were from the middle region, and 10 (3.1%) were from the southern region.Table 1 shows more details on participants' characteristics such as the study program, number of family members, family income, living place, study year, available Internet, and available electronic devices.
Regarding the participants' scores on the outcome variables, the mean overall score was 3.0 (±0.78).On the subscales, the lowest mean score was on the technological subscale (2.90 ± 0.83) and the highest mean score was on the administrative subscale (3.25 ± 1.0).

Correlations among Study Variables.
As shown in Table 2, Spearman's correlation coefcients showed signifcant associations among the participants' demographic and studentship characteristics and their scores on the outcome variables.For instance, signifcant associations were found among available Internet options and available electronic devices with participants' scores on the academic and administrative subscales, as well as with the overall score.Also, participants' living style was associated with their score on the technological subscale and the overall score.In addition, Te Scientifc World Journal ( (10) (1) Gender  4, the results revealed no signifcant diferences in the subscales' mean rank scores based on participants' gender.However, signifcant diferences were found based on the study program and type of university.Participants in the bridging program showed lower mean rank scores on the three subscales than those in the regular program.In addition, participants from private universities demonstrated lower mean rank scores on the three subscales than those from governmental universities.Te Kruskal-Wallis test was used to fnd variations in the subscales' mean rank scores based on participants' characteristics in three or more groups.Results showed no signifcant diferences in the subscales' mean rank scores based on total family income, geographical region, or study year.Nevertheless, results showed signifcant differences in the subscales' mean rank scores based on marital status, number of family members, living place, available Internet, and available electronic devices.For instance, married participants demonstrated the lowest mean rank scores on the two subscales (technological and administrative subscales) than their counterparts.On the academic subscale, they scored lower mean rank than single participants and higher mean rank than divorced/ married participants.
Based on the number of family members, the only subscale that showed signifcant diferences in the mean rank scores was the academic subscale.Tose participants with less than fve family members showed lower mean rank scores than those with fve to nine family members.Interestingly, participants with 10 or more family members showed the lowest mean rank scores.
Participants living alone or with their families showed lower mean rank scores than those living in university dormitories or with their colleagues/friends on the three subscales (academic, technological, and administrative subscales).
Participants with no Internet access at their homes showed the highest mean rank scores than their counterparts, on the three subscales.Interestingly, participants with more than two sources on the Internet showed higher mean rank scores on the three subscales than those with one source.
Participants who have laptops showed the lowest mean rank scores on the three subscales than participants with mobile phones, tablets, or even desktop computers, as shown in Table 5.

Discussion
Tis study aimed to assess the students' perceived levels of academic, technical, and administrative obstacles to online learning facing nursing students in Jordan.Our results showed that the lowest mean score was on the technological subscale.Tis means that participants face low levels of technological obstacles.Tis fnding can be explained by technological literacy, especially among educated people such as university students [31].However, two items (ffth and seventh items) within the technological subscale had the highest mean score than other items within the same subscale.Tese items are related to a lack of technological support and a lack of training courses provided by the institution, and this matches an Indian study about the obstacles of online teaching during the last pandemic [32].
On the other hand, the highest mean score was on the administrative subscale.Tis means that the administrative obstacles are the biggest obstacles hindering online learning among the participants.Te three items of the administrative subscale (ninth to eleventh items) showed relatively high mean scores.Tese items are related to problems with Internet access, negative comments on online learning, and inadequate infrastructure.Our explanation for this result might be the high bureaucracy in the third-world countries such as Jordan [33].Our fndings were diferent from those found in a Saudi study [9]; in their study, the highest mean score was for technological obstacles and the lowest mean score was for academic obstacles.Tese diferences can be secondary to the diferent samples as they studied university students in the English department or to the diferent technological and academic abilities between Saudi and Jordanian universities.
Regarding the academic obstacles, the mean score of this subscale occupied the middle rank between the technological and administrative obstacle subscales.Within the academic subscale, two items (the frst and second items) had relatively high mean scores.Tese items are related to the lack of interaction between students and teaching staf and the lack of time required to have exams/assignments.Tis fnding can be explained by the nature of online learning which usually limits the teacher-student interaction [5].

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Te Scientifc World Journal Te second aim of this study was to explore signifcant relationships among participants' demographic and studentship-related characteristics with perceived academic, technical, and administrative obstacles.Tis study showed signifcant associations between available Internet options and available electronic devices with participants' scores on the academic and administrative subscales, as well as with the overall score.Tis result refects the well-known vital role of technology availability in facilitating online learning [9,10].
In addition, our results showed signifcant relationships among the type of university (private or governmental) and the three subscales as well as the overall score.Tese signifcant relationships can be explained by several explanations.For instance, the diferent learning management systems used in each university might be diferent from each other in terms of simplicity.Another explanation is the higher academic level of students at governmental universities than at private universities.Furthermore, training on how to use these systems is also diferent between private and governmental universities [34].
Tis study aimed to examine signifcant diferences in the perceived academic, technical, and administrative obstacles based on participants' demographic and studentshiprelated characteristics.Our results showed higher mean ranks for the three subscales and a higher mean for the overall score among students in bachelor programs than those in bridging programs.Tis fnding looks logical as students in bridging programs are more experienced in online learning than their counterparts.In Jordan, students with a 2-year diploma can obtain a bachelor's degree through 2-year bridging programs.Tus, students in bridging programs were enrolled in a college, experienced in online learning, and are more intellectually mature than students in bachelor programs.Tis can make online learning among bridging students easier than their counterparts.Tis fnding is supported by an Egyptian study which found that fourth-year students face the least difculty in online learning [35].
Regarding the type of university, governmental university students showed higher mean ranks for the three subscales and a higher mean for the overall score among    [34].In addition, our fndings can be explained by the diferent economic classes of the students' families.In other words, relatively rich families send their children to private universities and provide them with technological means and Internet access.On the other hand, poor families might not be able to ofer technological aid and send their children to government universities.Furthermore, it is believed that studying at private universities is much easier than at governmental universities and fewer requirements reduce the challenges.Tis fnding is diferent from a Pakistani study which found no signifcant diferences between public and private universities [36].Tis diference might be related to the diferent economic strengths between Jordan, which is a middle-income country, and Pakistan, which is a low-income country [37].
In terms of marital status and living place, married students and those living with their families showed the lowest mean ranks for the three subscales and the lowest mean for the overall score than single students and those living far from their families.Tis result can be explained by the care and support the students receive from their spouses or families, compared with their single or living-alone counterparts.Tis explanation is supported by a systematic review which found that peer and family support is linked with student doggedness in distance education programs [38].Tis fnding might stress the importance of student family support during their studies.
Although this study has a good sample size, the results of this study are limited by several factors.For instance, the cross-sectional design and relatively homogenous sample can limit the generalization of results.Furthermore, the obstacles of online learning were studied only from the student's perspective without assessing teachers' perspectives.Future studies may study the obstacles of online learning internationally and assess teachers' perspectives.

Conclusion
Online learning has become an integral part of nursing learning around the world.However, there are still many obstacles that stand in the way of online learning in the nursing feld.Participants of the current study faced several obstacles hindering their online learning.Tese obstacles could either be administrative, technological, or academic.Universities' academic decision-makers and stakeholders are advised to intervene to turn these obstacles into enablers.Interventions can primarily include orientation programs upon entrance and continuous training programs to guide nursing students on how to use online learning software.In addition, organizing social activities and encouraging the exchange of experiences could be benefcial, especially for students living far from their families.Furthermore, fnancial support could help students overcome technological obstacles if they are able to obtain the needed devices and Internet access.Finally, universities might make a borrowing system to provide electronic devices for needy students during their study period.

Table 2 :
Correlations among study variables (N �

Table 3 :
Overall score diferences based on participants' characteristics.

Table 4 :
Mann-Whitney test for subscale diferences based on participants' characteristics.

Table 5 :
Continued.Tis fnding means that students at governmental universities in Jordan face more obstacles than those at private universities.Tis result can be explained by the higher quality of support provided by private universities than by government universities, as found by another study about factors that infuence online learning in private universities