online classes research

How Effective Is Online Learning? What the Research Does and Doesn’t Tell Us

Editor’s Note: This is part of a series on the practical takeaways from research.

The times have dictated school closings and the rapid expansion of online education. Can online lessons replace in-school time?

Clearly online time cannot provide many of the informal social interactions students have at school, but how will online courses do in terms of moving student learning forward? Research to date gives us some clues and also points us to what we could be doing to support students who are most likely to struggle in the online setting.

The use of virtual courses among K-12 students has grown rapidly in recent years. Florida, for example, requires all high school students to take at least one online course. Online learning can take a number of different forms. Often people think of Massive Open Online Courses, or MOOCs, where thousands of students watch a video online and fill out questionnaires or take exams based on those lectures.

In the online setting, students may have more distractions and less oversight, which can reduce their motivation.

Most online courses, however, particularly those serving K-12 students, have a format much more similar to in-person courses. The teacher helps to run virtual discussion among the students, assigns homework, and follows up with individual students. Sometimes these courses are synchronous (teachers and students all meet at the same time) and sometimes they are asynchronous (non-concurrent). In both cases, the teacher is supposed to provide opportunities for students to engage thoughtfully with subject matter, and students, in most cases, are required to interact with each other virtually.

Coronavirus and Schools

Online courses provide opportunities for students. Students in a school that doesn’t offer statistics classes may be able to learn statistics with virtual lessons. If students fail algebra, they may be able to catch up during evenings or summer using online classes, and not disrupt their math trajectory at school. So, almost certainly, online classes sometimes benefit students.

In comparisons of online and in-person classes, however, online classes aren’t as effective as in-person classes for most students. Only a little research has assessed the effects of online lessons for elementary and high school students, and even less has used the “gold standard” method of comparing the results for students assigned randomly to online or in-person courses. Jessica Heppen and colleagues at the American Institutes for Research and the University of Chicago Consortium on School Research randomly assigned students who had failed second semester Algebra I to either face-to-face or online credit recovery courses over the summer. Students’ credit-recovery success rates and algebra test scores were lower in the online setting. Students assigned to the online option also rated their class as more difficult than did their peers assigned to the face-to-face option.

Most of the research on online courses for K-12 students has used large-scale administrative data, looking at otherwise similar students in the two settings. One of these studies, by June Ahn of New York University and Andrew McEachin of the RAND Corp., examined Ohio charter schools; I did another with colleagues looking at Florida public school coursework. Both studies found evidence that online coursetaking was less effective.

About this series

This essay is the fifth in a series that aims to put the pieces of research together so that education decisionmakers can evaluate which policies and practices to implement.

The conveners of this project—Susanna Loeb, the director of Brown University’s Annenberg Institute for School Reform, and Harvard education professor Heather Hill—have received grant support from the Annenberg Institute for this series.

To suggest other topics for this series or join in the conversation, use #EdResearchtoPractice on Twitter.

Read the full series here .

It is not surprising that in-person courses are, on average, more effective. Being in person with teachers and other students creates social pressures and benefits that can help motivate students to engage. Some students do as well in online courses as in in-person courses, some may actually do better, but, on average, students do worse in the online setting, and this is particularly true for students with weaker academic backgrounds.

Students who struggle in in-person classes are likely to struggle even more online. While the research on virtual schools in K-12 education doesn’t address these differences directly, a study of college students that I worked on with Stanford colleagues found very little difference in learning for high-performing students in the online and in-person settings. On the other hand, lower performing students performed meaningfully worse in online courses than in in-person courses.

But just because students who struggle in in-person classes are even more likely to struggle online doesn’t mean that’s inevitable. Online teachers will need to consider the needs of less-engaged students and work to engage them. Online courses might be made to work for these students on average, even if they have not in the past.

Just like in brick-and-mortar classrooms, online courses need a strong curriculum and strong pedagogical practices. Teachers need to understand what students know and what they don’t know, as well as how to help them learn new material. What is different in the online setting is that students may have more distractions and less oversight, which can reduce their motivation. The teacher will need to set norms for engagement—such as requiring students to regularly ask questions and respond to their peers—that are different than the norms in the in-person setting.

Online courses are generally not as effective as in-person classes, but they are certainly better than no classes. A substantial research base developed by Karl Alexander at Johns Hopkins University and many others shows that students, especially students with fewer resources at home, learn less when they are not in school. Right now, virtual courses are allowing students to access lessons and exercises and interact with teachers in ways that would have been impossible if an epidemic had closed schools even a decade or two earlier. So we may be skeptical of online learning, but it is also time to embrace and improve it.

A version of this article appeared in the April 01, 2020 edition of Education Week as How Effective Is Online Learning?

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Published: 25 January 2021

Online education in the post-COVID era

Barbara B. Lockee 1

Nature Electronics volume 4 , pages 5–6 ( 2021 ) Cite this article

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Science, technology and society

The coronavirus pandemic has forced students and educators across all levels of education to rapidly adapt to online learning. The impact of this — and the developments required to make it work — could permanently change how education is delivered.

The COVID-19 pandemic has forced the world to engage in the ubiquitous use of virtual learning. And while online and distance learning has been used before to maintain continuity in education, such as in the aftermath of earthquakes 1 , the scale of the current crisis is unprecedented. Speculation has now also begun about what the lasting effects of this will be and what education may look like in the post-COVID era. For some, an immediate retreat to the traditions of the physical classroom is required. But for others, the forced shift to online education is a moment of change and a time to reimagine how education could be delivered 2 .

Looking back

Online education has traditionally been viewed as an alternative pathway, one that is particularly well suited to adult learners seeking higher education opportunities. However, the emergence of the COVID-19 pandemic has required educators and students across all levels of education to adapt quickly to virtual courses. (The term ‘emergency remote teaching’ was coined in the early stages of the pandemic to describe the temporary nature of this transition 3 .) In some cases, instruction shifted online, then returned to the physical classroom, and then shifted back online due to further surges in the rate of infection. In other cases, instruction was offered using a combination of remote delivery and face-to-face: that is, students can attend online or in person (referred to as the HyFlex model 4 ). In either case, instructors just had to figure out how to make it work, considering the affordances and constraints of the specific learning environment to create learning experiences that were feasible and effective.

The use of varied delivery modes does, in fact, have a long history in education. Mechanical (and then later electronic) teaching machines have provided individualized learning programmes since the 1950s and the work of B. F. Skinner 5 , who proposed using technology to walk individual learners through carefully designed sequences of instruction with immediate feedback indicating the accuracy of their response. Skinner’s notions formed the first formalized representations of programmed learning, or ‘designed’ learning experiences. Then, in the 1960s, Fred Keller developed a personalized system of instruction 6 , in which students first read assigned course materials on their own, followed by one-on-one assessment sessions with a tutor, gaining permission to move ahead only after demonstrating mastery of the instructional material. Occasional class meetings were held to discuss concepts, answer questions and provide opportunities for social interaction. A personalized system of instruction was designed on the premise that initial engagement with content could be done independently, then discussed and applied in the social context of a classroom.

These predecessors to contemporary online education leveraged key principles of instructional design — the systematic process of applying psychological principles of human learning to the creation of effective instructional solutions — to consider which methods (and their corresponding learning environments) would effectively engage students to attain the targeted learning outcomes. In other words, they considered what choices about the planning and implementation of the learning experience can lead to student success. Such early educational innovations laid the groundwork for contemporary virtual learning, which itself incorporates a variety of instructional approaches and combinations of delivery modes.

Online learning and the pandemic

Fast forward to 2020, and various further educational innovations have occurred to make the universal adoption of remote learning a possibility. One key challenge is access. Here, extensive problems remain, including the lack of Internet connectivity in some locations, especially rural ones, and the competing needs among family members for the use of home technology. However, creative solutions have emerged to provide students and families with the facilities and resources needed to engage in and successfully complete coursework 7 . For example, school buses have been used to provide mobile hotspots, and class packets have been sent by mail and instructional presentations aired on local public broadcasting stations. The year 2020 has also seen increased availability and adoption of electronic resources and activities that can now be integrated into online learning experiences. Synchronous online conferencing systems, such as Zoom and Google Meet, have allowed experts from anywhere in the world to join online classrooms 8 and have allowed presentations to be recorded for individual learners to watch at a time most convenient for them. Furthermore, the importance of hands-on, experiential learning has led to innovations such as virtual field trips and virtual labs 9 . A capacity to serve learners of all ages has thus now been effectively established, and the next generation of online education can move from an enterprise that largely serves adult learners and higher education to one that increasingly serves younger learners, in primary and secondary education and from ages 5 to 18.

The COVID-19 pandemic is also likely to have a lasting effect on lesson design. The constraints of the pandemic provided an opportunity for educators to consider new strategies to teach targeted concepts. Though rethinking of instructional approaches was forced and hurried, the experience has served as a rare chance to reconsider strategies that best facilitate learning within the affordances and constraints of the online context. In particular, greater variance in teaching and learning activities will continue to question the importance of ‘seat time’ as the standard on which educational credits are based 10 — lengthy Zoom sessions are seldom instructionally necessary and are not aligned with the psychological principles of how humans learn. Interaction is important for learning but forced interactions among students for the sake of interaction is neither motivating nor beneficial.

While the blurring of the lines between traditional and distance education has been noted for several decades 11 , the pandemic has quickly advanced the erasure of these boundaries. Less single mode, more multi-mode (and thus more educator choices) is becoming the norm due to enhanced infrastructure and developed skill sets that allow people to move across different delivery systems 12 . The well-established best practices of hybrid or blended teaching and learning 13 have served as a guide for new combinations of instructional delivery that have developed in response to the shift to virtual learning. The use of multiple delivery modes is likely to remain, and will be a feature employed with learners of all ages 14 , 15 . Future iterations of online education will no longer be bound to the traditions of single teaching modes, as educators can support pedagogical approaches from a menu of instructional delivery options, a mix that has been supported by previous generations of online educators 16 .

Also significant are the changes to how learning outcomes are determined in online settings. Many educators have altered the ways in which student achievement is measured, eliminating assignments and changing assessment strategies altogether 17 . Such alterations include determining learning through strategies that leverage the online delivery mode, such as interactive discussions, student-led teaching and the use of games to increase motivation and attention. Specific changes that are likely to continue include flexible or extended deadlines for assignment completion 18 , more student choice regarding measures of learning, and more authentic experiences that involve the meaningful application of newly learned skills and knowledge 19 , for example, team-based projects that involve multiple creative and social media tools in support of collaborative problem solving.

In response to the COVID-19 pandemic, technological and administrative systems for implementing online learning, and the infrastructure that supports its access and delivery, had to adapt quickly. While access remains a significant issue for many, extensive resources have been allocated and processes developed to connect learners with course activities and materials, to facilitate communication between instructors and students, and to manage the administration of online learning. Paths for greater access and opportunities to online education have now been forged, and there is a clear route for the next generation of adopters of online education.

Before the pandemic, the primary purpose of distance and online education was providing access to instruction for those otherwise unable to participate in a traditional, place-based academic programme. As its purpose has shifted to supporting continuity of instruction, its audience, as well as the wider learning ecosystem, has changed. It will be interesting to see which aspects of emergency remote teaching remain in the next generation of education, when the threat of COVID-19 is no longer a factor. But online education will undoubtedly find new audiences. And the flexibility and learning possibilities that have emerged from necessity are likely to shift the expectations of students and educators, diminishing further the line between classroom-based instruction and virtual learning.

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EdTakeAways

How effective is online learning what the research does and doesn't tell us.

By Susanna Loeb

Students who struggle will likely struggle more online

The times have dictated school closings and the rapid expansion of online education. Can online lessons replace in-school time?

Susanna Loeb is a professor of education and of public affairs at Brown University and the director of the university's Annenberg Institute for School Reform. She studies education policy, and her interests include social inequality.

Promises and pitfalls of online education

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Eric bettinger and eric bettinger associate professor of economics of education - stanford graduate school of education, research associate - national bureau of economic research susanna loeb susanna loeb professor and faculty director - scale initiative, stanford university's graduate school of education, founder and executive director - national student support accelerator.

June 9, 2017

12 min read

Executive Summary

Online courses have expanded rapidly and have the potential to extend further the educational opportunities of many students, particularly those least well-served by traditional educational institutions. However, in their current design, online courses are difficult, especially for the students who are least prepared. These students’ learning and persistence outcomes are worse when they take online courses than they would have been had these same students taken in-person courses. Continued improvement of online curricula and instruction can strengthen the quality of these courses and hence the educational opportunities for the most in-need populations.

Online courses offer the promise of access regardless of where students live or what time they can participate, potentially redefining educational opportunities for those least well-served in traditional classrooms. Moreover, online platforms offer the promise, through artificial intelligence, of providing the optimal course pacing and content to fit each student’s needs and thereby improve educational quality and learning. The latest “intelligent” tutoring systems, for example, not only assess students’ current weaknesses, but also diagnose why students make the specific errors. These systems then adjust instructional materials to meet students’ needs. 1

Yet today these promises are far from fully realized. The vast majority of online courses mirror face-to-face classrooms with professors rather using technology to better differentiate instruction across students. As one new study that we completed with our colleagues Lindsay Fox and Eric Taylor shows, online courses can improve access, yet they also are challenging, especially for the least well-prepared students. These students consistently perform worse in an online setting than they do in face-to-face classrooms; taking online courses increases their likelihood of dropping out and otherwise impedes progress through college. 2

Online college courses are rapidly growing. One out of three college students now takes at least one course online during their college career, and that share has increased threefold over the past decade. 3 The potential for cost savings and the ease of scaling fuels ongoing investments in online education by both public and private institutions. 4 Online courses have grown in the K-12 sector as well. Florida, for example, requires each high school student to take at least one online course before graduation and the Florida Virtual School offers over 150 classes to students across the state. 5 An estimated 1.5 million K-12 students participated in some online learning in 2010, 6 and online learning enrollments are projected to grow in future years. 7

Non-selective and for-profit higher education institutions have expanded online course offerings particularly quickly. These institutions serve a majority of college-aged students, and these students typically have weaker academic preparation and fewer economic resources than students at other more selective colleges and universities. As such, their ability to provide useful course work, engage students, and build the skills necessary for economic success is particularly important. Their use of online coursework is promising to the extent that it can reach the most students in need and serve them well.

While online course-taking is both prevalent and growing, especially in non-selective higher education institutions, relatively little evidence has examined how taking a course online instead of in person affects student success in college. Our new study is the first of which we are aware to provide evidence on the effects of online courses at-scale at non-selective four-year colleges. It is also the first to assess the effects of online course taking at for-profit institutions. Nearly 2.4 million undergraduate students (full-time equivalent) enrolled at for-profit institutions during the 2011-12 academic year, and the sector granted approximately 18 percent of all associate degrees.

Our study uses data from DeVry University, a large for-profit college with an undergraduate enrollment of more than 100,000 students, 80 percent of whom are seeking a bachelor’s degree. The average DeVry student takes two-thirds of her courses online. The remaining one-third of courses meet in conventional in-person classes held at one of DeVry’s 102 physical campuses. The data include over 230,000 students enrolled in 168,000 sections of more than 750 different courses.

DeVry University’s approach to online education makes it particularly well suited for estimating the effects of taking online courses. Each DeVry course is offered both online and in-person, and each student enrolls in either an online section or an in-person section. Online and in-person sections are identical in most ways: both follow the same syllabus and use the same textbook; class sizes are approximately the same; both use the same assignments, quizzes, tests, and grading rubrics. Many professors teach both online and in-person courses. The contrast between online and in-person sections is primarily the mode of communication. In online sections, all interaction—lecturing, class discussion, group projects—occurs in online discussion boards, and much of the professor’s “lecturing” role is replaced with standardized videos. In online sections, participation is often asynchronous while in-person sections meet on campus at scheduled times. In short, DeVry online classes attempt to replicate traditional in-person classes, except that student-student and student-professor interactions are virtual and asynchronous.

Using variation in course-taking that arises both from changes in course offerings at particular campuses in a particular term and from variation across students in the distance that they have to travel to take in-person courses, we find that taking a course online reduces student grades by 0.44 points on the traditional four-point grading scale, approximately a 0.33 standard deviation decline relative to taking a course in-person (See Figure 1). To be more concrete, students taking the course in-person earned roughly a B- grade (2.8) on average while if they had taken it online, they would have earned a C (2.4). Additionally, taking a course online reduces a student’s GPA the following term by 0.15 points; and, if we look only at the next term GPA for courses in the same subject area or courses for which the course in question is a pre-requisite, we find larger drops of 0.42 points and 0.32 points respectively, providing evidence that students learned less in the online setting.

We also find that taking a course online, instead of in person, increases the probability that a student will drop out of school. In the semester after taking an online course, students are about 9 percentage points less likely to remain enrolled. This reduction is relative to an average of 88 percent of students remaining enrolled in the following term. Moreover, taking a course online reduces the number of credits that students who do reenroll take in future semesters. While this setting is quite different, we can compare the effects on online course taking to other estimates of effects of on college persistence. For example, the literature on financial aid often finds that $1000 in financial aid increases persistence rates by about three percentage points 8 and college mentorship increases persistence rates by five percentage points. 9

The negative effects of online course taking are concentrated in the lowest performing students. As shown in Figure 2, for students with below median prior GPA, the online classes reduce grades by 0.5 points or more, while for students with prior GPA in the top three deciles we estimate the effect as much smaller and, in fact, we cannot tell whether there is negative effect at all for this higher-achieving group. Thus, while online courses may have the potential to differentiate coursework to meet the needs of students with weaker incoming skills, current online courses, in fact, do an even worse job of meeting the needs of these students than do traditional in-person courses.

These analyses provide evidence that students in online courses perform substantially worse than students in traditional in-person courses and that experience in these online courses impact performance in future classes and their likelihood of dropping out of college as well. The negative effects of online course-taking are far stronger for students with lower prior GPA. The results are in line with prior studies of online education in other settings such as community colleges and highly competitive four-year institutions that also show that online courses yield worse average outcomes than in-person courses. 10

The current negative effect of online course taking relative to in-person course taking should not necessarily lead to the conclusion that online courses should be discouraged. On the contrary, online courses provide access to students who never would have the opportunity or inclination to take classes in-person. 11 As one indication, of the 5.8 million students taking online courses in the fall of 2014, 2.85 million took all of their courses online. 12 Moreover, advances in AI offer hope that future online courses can respond to the needs of students, meeting them where they are in their learning and engaging them in higher education even better than in-person courses are currently able to do. 13 Nonetheless, the tremendous scale and consistently negative effects of current offerings points to the need to improve these courses, particularly for students most at risk of course failure and college dropout.

The authors did not receive financial support from any firm or person with a financial or political interest in this article. They are currently not officers, directors, or board members of any organization with an interest in this article.

Graesser, Arthur C., Mark W. Conley, and Andrew Olney. 2012. “Intelligent tutoring systems.” In APA Educational Psychology Handbook, Vol. 3: Application to Learning and Teaching , edited by Karen. R. Harris, Steve Graham, and Tim Urdan. Washington, DC: American Psychological Association.
Bettinger, E., Fox, L., Loeb, S., & Taylor, E. (Forthcoming). Changing Distributions: How Online College Classes Alter Student and Professor Performance. American Economic Review .
Allen, I. Elaine, and Jeff Seaman. 2013. Changing Course: Ten Years of Tracking Online Education in the United States. Newburyport, MA: Sloan Consortium.
Deming, David J., Claudia Goldin, Lawrence F. Katz, and Noam Yuchtman. 2015. Can Online Learning Bend the Higher Education Cost Curve? American Economic Review, Papers & Proceedings, 105 (5):496-501.
Jacob, B., Berger, D. Hart, C. & Loeb, S. (Forthcoming). “Can Technology Help Promote Equality of Educational Opportunities?” In K. Alexander and S. Morgan (Editors), The Coleman Report and Educational Inequality Fifty Years Later. Russell Sage Foundation and William T. Grant Foundation: New York.
Wicks, Matthew. 2010. “A National Primer on K-12 Online Learning. Version 2.” Vienna, VA: International Association for K-12 Online Learning.
Watson, John, Amy Murin, Lauren Vashaw, Butch Gemin, and Chris Rapp. 2012. “Keeping Pace with K-12 Online Learning: An Annual Review of Policy and Practice 2011.” Durango, CO: Evergreen Education Group. And Picciano, Anthony G., Jeff Seaman, Peter Shea, and Karen Swan. 2012. “Examining the Extent and Nature of Online Learning in American K-12 Education: The Research Initiatives of the Alfred P. Sloan Foundation.” The Internet and Higher Education 15(2): 127-35.
Bettinger, Eric P. 2004. “How Financial Aid Affects Persistence.” In Caroline Hoxby (Ed.), College Choices: The Economics of Where to Go, When to Go, and How to Pay for It . University of Chicago Press.
Bettinger, Eric P., and Rachel B. Baker. 2013. “The Effects of Student Coaching: An Evaluation of a Randomized Experiment in Student Advising.” Educational Evaluation and Policy Analysis, 36 (1):3-19.
See for examples: Figlio, David, Mark Rush, and Lu Yin. 2013. “Is It Live or Is It Internet? Experimental Estimates of the Effects of Online Instruction on Student Learning.” Journal of Labor Economics, 31 (4):763-784; Couch, Kenneth A., William T. Alpert, and Oskar R. Harmon. 2014. “Online, Blended and Classroom Teaching of Economics Principles: A Randomized Experiment.” University of Connecticut Working Paper; Xu, Di, and Shanna Smith Jaggars. 2014. “Performance Gaps Between Online and Face-to-Face Courses: Differences Across Types of Students and Academic Subject Areas.” The Journal of Higher Education, 85 (5):633-659; Hart, Cassandra, Elizabeth Friedmann, and Michael Hill. 2014. “Online Course-Taking and Student Outcomes in California Community Colleges.” Working Paper; and Streich, Francie E. 2014. “Online and Hybrid Instruction and Student Success in College: Evidence from Community Colleges in Two States.” University of Michigan Working Paper.
See, for example, Joshua Goodman, Julia Melkers, and Amanda Pallais, “ Can Online Delivery Increase Access to Education? ” National Bureau of Economic Research working paper 22754, October 2016.
Online Report Card – Tracking Online Education in the United States , the 2015 Survey of Online Learning conducted by the Babson Survey Research Group and co-sponsored by the Online Learning Consortium (OLC), Pearson, StudyPortals, WCET and Tyton Partners.
See, for example, the Open Learning Initiative at Carnegie Mellon University.

Education Technology Higher Education

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Zachary Billot, Annie Vong, Nicole Dias Del Valle, Emily Markovich Morris

August 26, 2024

Brian A. Jacob, Cristina Stanojevich

Christine Apiot Okudi, Atenea Rosado-Viurques, Jennifer L. O’Donoghue

August 23, 2024

Study Protocol
Open access
Published: 26 August 2024

Learning effect of online versus onsite education in health and medical scholarship – protocol for a cluster randomized trial

Rie Raffing 1 ,
Lars Konge 2 &
Hanne Tønnesen 1

BMC Medical Education volume 24 , Article number: 927 ( 2024 ) Cite this article

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The disruption of health and medical education by the COVID-19 pandemic made educators question the effect of online setting on students’ learning, motivation, self-efficacy and preference. In light of the health care staff shortage online scalable education seemed relevant. Reviews on the effect of online medical education called for high quality RCTs, which are increasingly relevant with rapid technological development and widespread adaption of online learning in universities. The objective of this trial is to compare standardized and feasible outcomes of an online and an onsite setting of a research course regarding the efficacy for PhD students within health and medical sciences: Primarily on learning of research methodology and secondly on preference, motivation, self-efficacy on short term and academic achievements on long term. Based on the authors experience with conducting courses during the pandemic, the hypothesis is that student preferred onsite setting is different to online setting.

Cluster randomized trial with two parallel groups. Two PhD research training courses at the University of Copenhagen are randomized to online (Zoom) or onsite (The Parker Institute, Denmark) setting. Enrolled students are invited to participate in the study. Primary outcome is short term learning. Secondary outcomes are short term preference, motivation, self-efficacy, and long-term academic achievements. Standardized, reproducible and feasible outcomes will be measured by tailor made multiple choice questionnaires, evaluation survey, frequently used Intrinsic Motivation Inventory, Single Item Self-Efficacy Question, and Google Scholar publication data. Sample size is calculated to 20 clusters and courses are randomized by a computer random number generator. Statistical analyses will be performed blinded by an external statistical expert.

Primary outcome and secondary significant outcomes will be compared and contrasted with relevant literature. Limitations include geographical setting; bias include lack of blinding and strengths are robust assessment methods in a well-established conceptual framework. Generalizability to PhD education in other disciplines is high. Results of this study will both have implications for students and educators involved in research training courses in health and medical education and for the patients who ultimately benefits from this training.

Trial registration

Retrospectively registered at ClinicalTrials.gov: NCT05736627. SPIRIT guidelines are followed.

Peer Review reports

Medical education was utterly disrupted for two years by the COVID-19 pandemic. In the midst of rearranging courses and adapting to online platforms we, with lecturers and course managers around the globe, wondered what the conversion to online setting did to students’ learning, motivation and self-efficacy [ 1 , 2 , 3 ]. What the long-term consequences would be [ 4 ] and if scalable online medical education should play a greater role in the future [ 5 ] seemed relevant and appealing questions in a time when health care professionals are in demand. Our experience of performing research training during the pandemic was that although PhD students were grateful for courses being available, they found it difficult to concentrate related to the long screen hours. We sensed that most students preferred an onsite setting and perceived online courses a temporary and inferior necessity. The question is if this impacted their learning?

Since the common use of the internet in medical education, systematic reviews have sought to answer if there is a difference in learning effect when taught online compared to onsite. Although authors conclude that online learning may be equivalent to onsite in effect, they agree that studies are heterogeneous and small [ 6 , 7 ], with low quality of the evidence [ 8 , 9 ]. They therefore call for more robust and adequately powered high-quality RCTs to confirm their findings and suggest that students’ preferences in online learning should be investigated [ 7 , 8 , 9 ].

This uncovers two knowledge gaps: I) High-quality RCTs on online versus onsite learning in health and medical education and II) Studies on students’ preferences in online learning.

Recently solid RCTs have been performed on the topic of web-based theoretical learning of research methods among health professionals [ 10 , 11 ]. However, these studies are on asynchronous courses among medical or master students with short term outcomes.

This uncovers three additional knowledge gaps: III) Studies on synchronous online learning IV) among PhD students of health and medical education V) with long term measurement of outcomes.

The rapid technological development including artificial intelligence (AI) and widespread adaption as well as application of online learning forced by the pandemic, has made online learning well-established. It represents high resolution live synchronic settings which is available on a variety of platforms with integrated AI and options for interaction with and among students, chat and break out rooms, and exterior digital tools for teachers [ 12 , 13 , 14 ]. Thus, investigating online learning today may be quite different than before the pandemic. On one hand, it could seem plausible that this technological development would make a difference in favour of online learning which could not be found in previous reviews of the evidence. On the other hand, the personal face-to-face interaction during onsite learning may still be more beneficial for the learning process and combined with our experience of students finding it difficult to concentrate when online during the pandemic we hypothesize that outcomes of the onsite setting are different from the online setting.

To support a robust study, we design it as a cluster randomized trial. Moreover, we use the well-established and widely used Kirkpatrick’s conceptual framework for evaluating learning as a lens to assess our outcomes [ 15 ]. Thus, to fill the above-mentioned knowledge gaps, the objective of this trial is to compare a synchronous online and an in-person onsite setting of a research course regarding the efficacy for PhD students within the health and medical sciences:

Primarily on theoretical learning of research methodology and

Secondly on

◦ Preference, motivation, self-efficacy on short term

◦ Academic achievements on long term

Trial design

This study protocol covers synchronous online and in-person onsite setting of research courses testing the efficacy for PhD students. It is a two parallel arms cluster randomized trial (Fig. 1 ).

Consort flow diagram

The study measures baseline and post intervention. Baseline variables and knowledge scores are obtained at the first day of the course, post intervention measurement is obtained the last day of the course (short term) and monthly for 24 months (long term).

Randomization is stratified giving 1:1 allocation ratio of the courses. As the number of participants within each course might differ, the allocation ratio of participants in the study will not fully be equal and 1:1 balanced.

Study setting

The study site is The Parker Institute at Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Denmark. From here the courses are organized and run online and onsite. The course programs and time schedules, the learning objective, the course management, the lecturers, and the delivery are identical in the two settings. The teachers use the same introductory presentations followed by training in break out groups, feed-back and discussions. For the online group, the setting is organized as meetings in the online collaboration tool Zoom® [ 16 ] using the basic available technicalities such as screen sharing, chat function for comments, and breakout rooms and other basics digital tools if preferred. The online version of the course is synchronous with live education and interaction. For the onsite group, the setting is the physical classroom at the learning facilities at the Parker Institute. Coffee and tea as well as simple sandwiches and bottles of water, which facilitate sociality, are available at the onsite setting. The participants in the online setting must get their food and drink by themselves, but online sociality is made possible by not closing down the online room during the breaks. The research methodology courses included in the study are “Practical Course in Systematic Review Technique in Clinical Research”, (see course programme in appendix 1) and “Getting started: Writing your first manuscript for publication” [ 17 ] (see course programme in appendix 2). The two courses both have 12 seats and last either three or three and a half days resulting in 2.2 and 2.6 ECTS credits, respectively. They are offered by the PhD School of the Faculty of Health and Medical Sciences, University of Copenhagen. Both courses are available and covered by the annual tuition fee for all PhD students enrolled at a Danish university.

Eligibility criteria

Inclusion criteria for participants: All PhD students enrolled on the PhD courses participate after informed consent: “Practical Course in Systematic Review Technique in Clinical Research” and “Getting started: Writing your first manuscript for publication” at the PhD School of the Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.

Exclusion criteria for participants: Declining to participate and withdrawal of informed consent.

Informed consent

The PhD students at the PhD School at the Faculty of Health Sciences, University of Copenhagen participate after informed consent, taken by the daily project leader, allowing evaluation data from the course to be used after pseudo-anonymization in the project. They are informed in a welcome letter approximately three weeks prior to the course and again in the introduction the first course day. They register their consent on the first course day (Appendix 3). Declining to participate in the project does not influence their participation in the course.

Interventions

Online course settings will be compared to onsite course settings. We test if the onsite setting is different to online. Online learning is increasing but onsite learning is still the preferred educational setting in a medical context. In this case onsite learning represents “usual care”. The online course setting is meetings in Zoom using the technicalities available such as chat and breakout rooms. The onsite setting is the learning facilities, at the Parker Institute, Bispebjerg and Frederiksberg Hospital, The Capital Region, University of Copenhagen, Denmark.

The course settings are not expected to harm the participants, but should a request be made to discontinue the course or change setting this will be met, and the participant taken out of the study. Course participants are allowed to take part in relevant concomitant courses or other interventions during the trial.

Strategies to improve adherence to interventions

Course participants are motivated to complete the course irrespectively of the setting because it bears ECTS-points for their PhD education and adds to the mandatory number of ECTS-points. Thus, we expect adherence to be the same in both groups. However, we monitor their presence in the course and allocate time during class for testing the short-term outcomes ( motivation, self-efficacy, preference and learning). We encourage and, if necessary, repeatedly remind them to register with Google Scholar for our testing of the long-term outcome (academic achievement).

Outcomes are related to the Kirkpatrick model for evaluating learning (Fig. 2 ) which divides outcomes into four different levels; Reaction which includes for example motivation, self-efficacy and preferences, Learning which includes knowledge acquisition, Behaviour for practical application of skills when back at the job (not included in our outcomes), and Results for impact for end-users which includes for example academic achievements in the form of scientific articles [ 18 , 19 , 20 ].

The Kirkpatrick model

Primary outcome

The primary outcome is short term learning (Kirkpatrick level 2).

Learning is assessed by a Multiple-Choice Questionnaire (MCQ) developed prior to the RCT specifically for this setting (Appendix 4). First the lecturers of the two courses were contacted and asked to provide five multiple choice questions presented as a stem with three answer options; one correct answer and two distractors. The questions should be related to core elements of their teaching under the heading of research training. The questions were set up to test the cognition of the students at the levels of "Knows" or "Knows how" according to Miller's Pyramid of Competence and not their behaviour [ 21 ]. Six of the course lecturers responded and out of this material all the questions which covered curriculum of both courses were selected. It was tested on 10 PhD students and within the lecturer group, revised after an item analysis and English language revised. The MCQ ended up containing 25 questions. The MCQ is filled in at baseline and repeated at the end of the course. The primary outcomes based on the MCQ is estimated as the score of learning calculated as number of correct answers out of 25 after the course. A decrease of points of the MCQ in the intervention groups denotes a deterioration of learning. In the MCQ the minimum score is 0 and 25 is maximum, where 19 indicates passing the course.

Furthermore, as secondary outcome, this outcome measurement will be categorized as binary outcome to determine passed/failed of the course defined by 75% (19/25) correct answers.

The learning score will be computed on group and individual level and compared regarding continued outcomes by the Mann–Whitney test comparing the learning score of the online and onsite groups. Regarding the binomial outcome of learning (passed/failed) data will be analysed by the Fisher’s exact test on an intention-to-treat basis between the online and onsite. The results will be presented as median and range and as mean and standard deviations, for possible future use in meta-analyses.

Secondary outcomes

Motivation assessment post course: Motivation level is measured by the Intrinsic Motivation Inventory (IMI) Scale [ 22 ] (Appendix 5). The IMI items were randomized by random.org on the 4th of August 2022. It contains 12 items to be assessed by the students on a 7-point Likert scale where 1 is “Not at all true”, 4 is “Somewhat true” and 7 is “Very true”. The motivation score will be computed on group and individual level and will then be tested by the Mann–Whitney of the online and onsite group.

Self-efficacy assessment post course: Self-efficacy level is measured by a single-item measure developed and validated by Williams and Smith [ 23 ] (Appendix 6). It is assessed by the students on a scale from 1–10 where 1 is “Strongly disagree” and 10 is “Strongly agree”. The self-efficacy score will be computed on group and individual level and tested by a Mann–Whitney test to compare the self-efficacy score of the online and onsite group.

Preference assessment post course: Preference is measured as part of the general course satisfaction evaluation with the question “If you had the option to choose, which form would you prefer this course to have?” with the options “onsite form” and “online form”.

Academic achievement assessment is based on 24 monthly measurements post course of number of publications, number of citations, h-index, i10-index. This data is collected through the Google Scholar Profiles [ 24 ] of the students as this database covers most scientific journals. Associations between onsite/online and long-term academic will be examined with Kaplan Meyer and log rank test with a significance level of 0.05.

Participant timeline

Enrolment for the course at the Faculty of Health Sciences, University of Copenhagen, Denmark, becomes available when it is published in the course catalogue. In the course description the course location is “To be announced”. Approximately 3–4 weeks before the course begins, the participant list is finalized, and students receive a welcome letter containing course details, including their allocation to either the online or onsite setting. On the first day of the course, oral information is provided, and participants provide informed consent, baseline variables, and base line knowledge scores.

The last day of scheduled activities the following scores are collected, knowledge, motivation, self-efficacy, setting preference, and academic achievement. To track students' long term academic achievements, follow-ups are conducted monthly for a period of 24 months, with assessments occurring within one week of the last course day (Table 1 ).

Sample size

The power calculation is based on the main outcome, theoretical learning on short term. For the sample size determination, we considered 12 available seats for participants in each course. To achieve statistical power, we aimed for 8 clusters in both online and onsite arms (in total 16 clusters) to detect an increase in learning outcome of 20% (learning outcome increase of 5 points). We considered an intraclass correlation coefficient of 0.02, a standard deviation of 10, a power of 80%, and a two-sided alpha level of 5%. The Allocation Ratio was set at 1, implying an equal number of subjects in both online and onsite group.

Considering a dropout up to 2 students per course, equivalent to 17%, we determined that a total of 112 participants would be needed. This calculation factored in 10 clusters of 12 participants per study arm, which we deemed sufficient to assess any changes in learning outcome.

The sample size was estimated using the function n4means from the R package CRTSize [ 25 ].

Recruitment

Participants are PhD students enrolled in 10 courses of “Practical Course in Systematic Review Technique in Clinical Research” and 10 courses of “Getting started: Writing your first manuscript for publication” at the PhD School of the Faculty of Health Sciences, University of Copenhagen, Denmark.

Assignment of interventions: allocation

Randomization will be performed on course-level. The courses are randomized by a computer random number generator [ 26 ]. To get a balanced randomization per year, 2 sets with 2 unique random integers in each, taken from the 1–4 range is requested.

The setting is not included in the course catalogue of the PhD School and thus allocation to online or onsite is concealed until 3–4 weeks before course commencement when a welcome letter with course information including allocation to online or onsite setting is distributed to the students. The lecturers are also informed of the course setting at this time point. If students withdraw from the course after being informed of the setting, a letter is sent to them enquiring of the reason for withdrawal and reason is recorded (Appendix 7).

The allocation sequence is generated by a computer random number generator (random.org). The participants and the lecturers sign up for the course without knowing the course setting (online or onsite) until 3–4 weeks before the course.

Assignment of interventions: blinding

Due to the nature of the study, it is not possible to blind trial participants or lecturers. The outcomes are reported by the participants directly in an online form, thus being blinded for the outcome assessor, but not for the individual participant. The data collection for the long-term follow-up regarding academic achievements is conducted without blinding. However, the external researcher analysing the data will be blinded.

Data collection and management

Data will be collected by the project leader (Table 1 ). Baseline variables and post course knowledge, motivation, and self-efficacy are self-reported through questionnaires in SurveyXact® [ 27 ]. Academic achievements are collected through Google Scholar profiles of the participants.

Given that we are using participant assessments and evaluations for research purposes, all data collection – except for monthly follow-up of academic achievements after the course – takes place either in the immediate beginning or ending of the course and therefore we expect participant retention to be high.

Data will be downloaded from SurveyXact and stored in a locked and logged drive on a computer belonging to the Capital Region of Denmark. Only the project leader has access to the data.

This project conduct is following the Danish Data Protection Agency guidelines of the European GDPR throughout the trial. Following the end of the trial, data will be stored at the Danish National Data Archive which fulfil Danish and European guidelines for data protection and management.

Statistical methods

Data is anonymized and blinded before the analyses. Analyses are performed by a researcher not otherwise involved in the inclusion or randomization, data collection or handling. All statistical tests will be testing the null hypotheses assuming the two arms of the trial being equal based on corresponding estimates. Analysis of primary outcome on short-term learning will be started once all data has been collected for all individuals in the last included course. Analyses of long-term academic achievement will be started at end of follow-up.

Baseline characteristics including both course- and individual level information will be presented. Table 2 presents the available data on baseline.

We will use multivariate analysis for identification of the most important predictors (motivation, self-efficacy, sex, educational background, and knowledge) for best effect on short and long term. The results will be presented as risk ratio (RR) with 95% confidence interval (CI). The results will be considered significant if CI does not include the value one.

All data processing and analyses were conducted using R statistical software version 4.1.0, 2021–05-18 (R Foundation for Statistical Computing, Vienna, Austria).

If possible, all analysis will be performed for “Practical Course in Systematic Review Technique in Clinical Research” and for “Getting started: Writing your first manuscript for publication” separately.

Primary analyses will be handled with the intention-to-treat approach. The analyses will include all individuals with valid data regardless of they did attend the complete course. Missing data will be handled with multiple imputation [ 28 ] .

Upon reasonable request, public assess will be granted to protocol, datasets analysed during the current study, and statistical code Table 3 .

Oversight, monitoring, and adverse events

This project is coordinated in collaboration between the WHO CC (DEN-62) at the Parker Institute, CAMES, and the PhD School at the Faculty of Health and Medical Sciences, University of Copenhagen. The project leader runs the day-to-day support of the trial. The steering committee of the trial includes principal investigators from WHO CC (DEN-62) and CAMES and the project leader and meets approximately three times a year.

Data monitoring is done on a daily basis by the project leader and controlled by an external independent researcher.

An adverse event is “a harmful and negative outcome that happens when a patient has been provided with medical care” [ 29 ]. Since this trial does not involve patients in medical care, we do not expect adverse events. If participants decline taking part in the course after receiving the information of the course setting, information on reason for declining is sought obtained. If the reason is the setting this can be considered an unintended effect. Information of unintended effects of the online setting (the intervention) will be recorded. Participants are encouraged to contact the project leader with any response to the course in general both during and after the course.

The trial description has been sent to the Scientific Ethical Committee of the Capital Region of Denmark (VEK) (21041907), which assessed it as not necessary to notify and that it could proceed without permission from VEK according to the Danish law and regulation of scientific research. The trial is registered with the Danish Data Protection Agency (Privacy) (P-2022–158). Important protocol modification will be communicated to relevant parties as well as VEK, the Joint Regional Information Security and Clinicaltrials.gov within an as short timeframe as possible.

Dissemination plans

The results (positive, negative, or inconclusive) will be disseminated in educational, scientific, and clinical fora, in international scientific peer-reviewed journals, and clinicaltrials.gov will be updated upon completion of the trial. After scientific publication, the results will be disseminated to the public by the press, social media including the website of the hospital and other organizations – as well as internationally via WHO CC (DEN-62) at the Parker Institute and WHO Europe.

All authors will fulfil the ICMJE recommendations for authorship, and RR will be first author of the articles as a part of her PhD dissertation. Contributors who do not fulfil these recommendations will be offered acknowledgement in the article.

This cluster randomized trial investigates if an onsite setting of a research course for PhD students within the health and medical sciences is different from an online setting. The outcomes measured are learning of research methodology (primary), preference, motivation, and self-efficacy (secondary) on short term and academic achievements (secondary) on long term.

The results of this study will be discussed as follows:

Discussion of primary outcome

Primary outcome will be compared and contrasted with similar studies including recent RCTs and mixed-method studies on online and onsite research methodology courses within health and medical education [ 10 , 11 , 30 ] and for inspiration outside the field [ 31 , 32 ]: Tokalic finds similar outcomes for online and onsite, Martinic finds that the web-based educational intervention improves knowledge, Cheung concludes that the evidence is insufficient to say that the two modes have different learning outcomes, Kofoed finds online setting to have negative impact on learning and Rahimi-Ardabili presents positive self-reported student knowledge. These conflicting results will be discussed in the context of the result on the learning outcome of this study. The literature may change if more relevant studies are published.

Discussion of secondary outcomes

Secondary significant outcomes are compared and contrasted with similar studies.

Limitations, generalizability, bias and strengths

It is a limitation to this study, that an onsite curriculum for a full day is delivered identically online, as this may favour the onsite course due to screen fatigue [ 33 ]. At the same time, it is also a strength that the time schedules are similar in both settings. The offer of coffee, tea, water, and a plain sandwich in the onsite course may better facilitate the possibility for socializing. Another limitation is that the study is performed in Denmark within a specific educational culture, with institutional policies and resources which might affect the outcome and limit generalization to other geographical settings. However, international students are welcome in the class.

In educational interventions it is generally difficult to blind participants and this inherent limitation also applies to this trial [ 11 ]. Thus, the participants are not blinded to their assigned intervention, and neither are the lecturers in the courses. However, the external statistical expert will be blinded when doing the analyses.

We chose to compare in-person onsite setting with a synchronous online setting. Therefore, the online setting cannot be expected to generalize to asynchronous online setting. Asynchronous delivery has in some cases showed positive results and it might be because students could go back and forth through the modules in the interface without time limit [ 11 ].

We will report on all the outcomes defined prior to conducting the study to avoid selective reporting bias.

It is a strength of the study that it seeks to report outcomes within the 1, 2 and 4 levels of the Kirkpatrick conceptual framework, and not solely on level 1. It is also a strength that the study is cluster randomized which will reduce “infections” between the two settings and has an adequate power calculated sample size and looks for a relevant educational difference of 20% between the online and onsite setting.

Perspectives with implications for practice

The results of this study may have implications for the students for which educational setting they choose. Learning and preference results has implications for lecturers, course managers and curriculum developers which setting they should plan for the health and medical education. It may also be of inspiration for teaching and training in other disciplines. From a societal perspective it also has implications because we will know the effect and preferences of online learning in case of a future lock down.

Future research could investigate academic achievements in online and onsite research training on the long run (Kirkpatrick 4); the effect of blended learning versus online or onsite (Kirkpatrick 2); lecturers’ preferences for online and onsite setting within health and medical education (Kirkpatrick 1) and resource use in synchronous and asynchronous online learning (Kirkpatrick 5).

Trial status

This trial collected pilot data from August to September 2021 and opened for inclusion in January 2022. Completion of recruitment is expected in April 2024 and long-term follow-up in April 2026. Protocol version number 1 03.06.2022 with amendments 30.11.2023.

Availability of data and materials

The project leader will have access to the final trial dataset which will be available upon reasonable request. Exception to this is the qualitative raw data that might contain information leading to personal identification.

Abbreviations

Artificial Intelligence

Copenhagen academy for medical education and simulation

Confidence interval

Coronavirus disease

European credit transfer and accumulation system

International committee of medical journal editors

Intrinsic motivation inventory

Multiple choice questionnaire

Doctor of medicine

Masters of sciences

Randomized controlled trial

Scientific ethical committee of the Capital Region of Denmark

WHO Collaborating centre for evidence-based clinical health promotion

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Acknowledgements

We thank the students who make their evaluations available for this trial and MSc (Public Health) Mie Sylow Liljendahl for statistical support.

Open access funding provided by Copenhagen University The Parker Institute, which hosts the WHO CC (DEN-62), receives a core grant from the Oak Foundation (OCAY-18–774-OFIL). The Oak Foundation had no role in the design of the study or in the collection, analysis, and interpretation of the data or in writing the manuscript.

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Rie Raffing & Hanne Tønnesen

Copenhagen Academy for Medical Education and Simulation (CAMES), Centre for HR and Education, The Capital Region of Denmark, Copenhagen, 2100, Denmark

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Contributions

RR, LK and HT have made substantial contributions to the conception and design of the work; RR to the acquisition of data, and RR, LK and HT to the interpretation of data; RR has drafted the work and RR, LK, and HT have substantively revised it AND approved the submitted version AND agreed to be personally accountable for their own contributions as well as ensuring that any questions which relates to the accuracy or integrity of the work are adequately investigated, resolved and documented.

Corresponding author

Correspondence to Rie Raffing .

Ethics declarations

Ethics approval and consent to participate.

The Danish National Committee on Health Research Ethics has assessed the study Journal-nr.:21041907 (Date: 21–09-2021) without objections or comments. The study has been approved by The Danish Data Protection Agency Journal-nr.: P-2022–158 (Date: 04.05.2022).

All PhD students participate after informed consent. They can withdraw from the study at any time without explanations or consequences for their education. They will be offered information of the results at study completion. There are no risks for the course participants as the measurements in the course follow routine procedure and they are not affected by the follow up in Google Scholar. However, the 15 min of filling in the forms may be considered inconvenient.

The project will follow the GDPR and the Joint Regional Information Security Policy. Names and ID numbers are stored on a secure and logged server at the Capital Region Denmark to avoid risk of data leak. All outcomes are part of the routine evaluation at the courses, except the follow up for academic achievement by publications and related indexes. However, the publications are publicly available per se.

Competing interests

The authors declare no competing interests

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SAGE Open Nurs
v.10; Jan-Dec 2024
PMC11337188

Nursing Students’ Experiences and Challenges in Their Education During COVID 19 Pandemic: A Mixed-Method Study

Puvaneswari kanagaraj.

1 Department of Nursing, College of Applied Medical Sciences, University of Bisha, Bisha, Kingdom of Saudi Arabia

Judie Arulappan

2 Department of Maternal and Child Health, College of Nursing, Sultan Qaboos University, Al Khoudh, Muscat, Sultanate of Oman

Arpita Pradhan

3 Narayana Multi Specialty Hospital, Kolkata, West Bengal, India

* Current address: Durgapur City Hospital and Clinic Pvt. Limited, Durgapur, West Bengal, India.

Shimmaa Mansour Moustafa Mohammed

4 Faculty of Nursing, Zagazig University, Zagazig, Egypt

Associated Data

Supplemental material, sj-docx-1-son-10.1177_23779608241272484 for Nursing Students’ Experiences and Challenges in Their Education During COVID 19 Pandemic: A Mixed-Method Study by Puvaneswari Kanagaraj, Judie Arulappan, Arpita Pradhan and Shimmaa Mansour Moustafa Mohammed in SAGE Open Nursing

Supplemental material, sj-docx-2-son-10.1177_23779608241272484 for Nursing Students’ Experiences and Challenges in Their Education During COVID 19 Pandemic: A Mixed-Method Study by Puvaneswari Kanagaraj, Judie Arulappan, Arpita Pradhan and Shimmaa Mansour Moustafa Mohammed in SAGE Open Nursing

Introduction

The COVID-19 outbreak disrupted the nursing education across the world. The nursing students faced many challenges in their learning process.

The study explored the experiences and challenges faced by nursing students who had virtual education in India.

The study adopted an exploratory sequential mixed-methods design. The study was conducted as two phases. Phase 1: Qualitative data were collected using direct focus group interview with 18 students. Phase 2: Quantitative data were collected from 477 students using a Likert scale prepared by the investigators of the study on challenges experienced by nursing students on their education. The analysis was done using the descriptive and inferential statistics and thematic analysis.

Phase 1: The analyzed data produced seven themes and 10 sub-themes; (1) technical issues—a concern, (2) regular rhythm in educational training—but not complete, (3) stress and strain, (4) evaluation—a concern, (5) communication, (6) comfort zone, and (7) easy distraction. Phase 2: Majority of the students (54.71%) experienced high-level challenges with the nursing education during pandemic. The overall mean and SD of all the domain-wise challenges were 103.39 + 7.11 with the range from 30 to 150. The mean and SD with educational challenges were (20.27 + 3.04), environmental challenges (6.92 + 1.66), communication challenges (17.61 + 4.01), technical challenges (17.39 + 3.75), evaluation challenges (7.09 + 1.94), physical and mental challenges (20.47 + 4.33), career challenges (7.06 + 1.91), and financial challenges (6.61 + 2.1). The demographic variable gender ( P = 0.045) showed a statistically significant association with the challenges.

Considering the experiences and challenges faced by the nursing students, the nursing administrators shall design educational strategies to mitigate these challenges in nursing education during a pandemic.

Implication

Virtual nursing education offers flexibility in teaching and learning, self-paced learning opportunity, lower the costs, career advancement, comfortable learning environment, more opportunities for participation, easier to track documentation and improves skills in technology. Therefore, the challenges in virtual nursing education should be lessened to have successful teaching learning experiences.

Introduction/Background

The world faced unprecedented challenges during COVID-19 global pandemic ( World Health Organization, 2020 ). The pandemic changed the lives of people at different levels. Additionally, social distancing shaped the social relationship and behavior ( Kaveh et al., 2022 ). COVID-19 significantly strained the healthcare system. In addition, it affected the education in academic institutions and universities to a greater extent ( Dewart et al., 2020 ). As a preventive and control measure, all the schools, colleges, and universities were closed ( Mustafa, 2020 ). In April 2020, 94% of learners worldwide were affected by the pandemic, representing 1.58 billion children and youth in 200 countries ( De Giusti, 2020 ). Likewise, nursing education has undergone many radical changes both in developed and developing countries. The situation affected the learning opportunities of nursing students as their clinical placements were suspended and the face-to-face teaching moved into online teaching. Additionally, the pre-clinical activities such as laboratory and simulation-based teaching were affected due to social and organizational restrictions to limit unnecessary access and contact with others ( Tomietto et al., 2020 ).

To continue the teaching–learning activity, the academic institutions adopted various digital platforms including Zoom, Google meet, WebEx, Udemy, Edmodo, Google classroom, etc. ( Mishra et al., 2020 ). Moreover, web-based conferences were routinely organized by educational institutions during this pandemic ( Kaware, 2022 ). In addition, educational institutions have placed greater emphasis on ERP systems, library modules, fee modules, and examination modules. The virtual learning enhanced the comfort, accessibility, and encouraged remote learning ( Mukhtar et al., 2020 ). Similarly, the learners found it easy to access the online material, were able to record meetings and sessions and retrieve information ( Alsayed & Althaqafi, 2022 ). The faculty and students expressed that online education is useful during the COVID-19 pandemic; it was convenient, flexible, cost low, and encouraged self-learning ( Almahasees et al., 2021 ). Likewise, online education improved the flexibility, ability to teach large classes, increased interaction between the teachers and students and increased learning opportunities for the learners ( Hako, 2021 ). Ultimately, these educational technologies have had significant positive impact on the learning of the students. Additionally, it paves the way toward the blending of technology synchronously or asynchronously into education ( Thaheem et al., 2022 ).

Review of Literature

Although online education was beneficial to both the teachers and learners, it posed various challenges to the faculty and students ( Nimavat et al., 2021 ). Poor student attendance, loneliness, issues with internet connectivity and lack of information and technology skills were reported as challenges of online education ( Hako, 2021 ). The faculty and students indicated that efficacy of online teaching and learning is less effective than face–face teaching and learning. Moreover, online learning is ineffective for deaf and hard of hearing students. Likewise, online education is linked to lack of interaction and motivation, data privacy and security and technical issues ( Almahasees & Amin, 2021 ; Alsayed & Althaqafi, 2022 ). Furthermore, online education was inefficient in terms of maintaining academic integrity ( Mukhtar et al., 2020 ). The teachers reported difficulties in motivating the students without visual connection during online teaching ( Moustakas & Robrade, 2022 ). Also, Atout et al., (2022) reported lack of resources for the clinical learning, distracting home environment and challenging evaluation of learners as the barriers for virtual learning.

The challenges faced by the instructors includes transitional difficulties from offline to online teaching, communication barriers, changes in the teaching style and additional time and resources for preparation of teaching. The institutions experienced challenges such as need for additional training for faculty and students, technical and multimedia support, online counselling sessions for teachers and the need to have technical troubleshooting team. Students experienced challenges related to having technical skills to learn online, lack of readiness, network and speed issues, and lack of identity, interaction and participation. There were challenges related to content such as development of new material, regular assignments, multimedia tools, and checking assignments and sharing regular feedback with the students. Technological challenges included device suitability, network stability and speed, tools of conferencing software for online teaching and ease of use. Lastly, the motivational factors included lack of sense of job security, non-availability of salary on time, and lack of family support, mental and emotional support from colleagues and higher authorities ( Siddiquei & Kathpal, 2021 ).

To enhance the online teaching and learning, technical aptitude enhancement, resource management and utilization, time management, control over the learning environment and help seeking are essential ( Barrot et al., 2021 ). Furthermore, formal training for the teachers, and enhancement of psychosocial wellbeing of both the learners and teachers are necessary to curb the feelings of loneliness and isolation. Moreover, the nature of the problems related to the shift from face to face to online learning should be identified to combat these challenges ( Hako, 2021 ). In India, both the undergraduate and postgraduate students were badly affected during the COVID-19 pandemic and experienced many challenges with online education ( Joshi et al., 2020 ; Kamal & Illiyan, 2021 ; Muthuprasad et al., 2021 ; Pandit & Agrawal, 2022 ; Rannaware et al., 2022 ; Sengupta, 2022 ). However, very few studies explored the challenges encountered by the nursing students during the online learning ( Gaur et al., 2020a ; George et al., 2022 ; Kanagaraj et al., 2022 ; Lata & Kudi, 2022 ). Therefore, the authors decided to understand the experiences and challenges encountered by nursing students in their nursing education during the COVID-19 pandemic. We believe that the study finding will be beneficial to the educational authorities, curriculum developers, and policy makers to design appropriate measures and strategies to enhance effective learning both in nursing education and practice.

An exploratory sequential mixed-methods design was utilized in this study. The study integrated qualitative data into quantitative data to understand the experiences and challenges experienced by nursing students’ during the pandemic.

Research Setting

The study was conducted among nursing students of Narayana Hrudayalaya College of Nursing, Koshy's College of Nursing and Kirubanidhi College of Nursing, Bengaluru, Karnataka, India. These colleges initiated virtual classes from April 2020. Therefore, these colleges were selected as settings for the study.

The target population of the study included both Diploma and BSN students. The accessible population included both Diploma and BSN students studying in Narayana Hrudayalaya College of Nursing, Koshy's College of Nursing and Kirubanidhi College of Nursing, Bengaluru, Karnataka, India.

Sample, Sample Size, and Sampling Techniques

Three nursing colleges were conveniently selected for the study. In Phase 1, the researchers used purposive sampling technique to collect the qualitative data from six students in each college (Narayana Hrudayalaya College of Nursing, Koshy's College of Nursing and Kirubanidhi College of Nursing, Bengaluru, Karnataka, India). The data collection was done face to face. Thus, in total, 18 students participated in the focused group interview during phase I. For Phase 2, the sample size calculation was done based on the previous cross-sectional study ( Thapa et al., 2021 ). Having the expected proportion of challenges experienced by nursing students as 15%, with 95% confidence interval, and with the precision, the minimum required sample size was 400. In total, all the three nursing colleges had 654 students. Convenient sampling technique was used to collect the data in phase II.

Inclusion and Exclusion Criteria

The study included nursing students who were enrolled for Diploma and BSN program, exposed to online learning, and second, third, and fourth year nursing students. The study excluded those who were not willing to participate, and first year nursing students as they had limited exposure to the virtual theory and clinical classes, which may give a limited and inaccurate data. Considering the inclusion and exclusion criteria, 477 students participated in the study.

Description and Interpretation of Study Instrument

The instruments used in the study were prepared by the researchers of the study. The qualitative data collected during the first phase of the study was utilized in preparing the tool used for the quantitative phase of the study. It included four parts namely demographic variables, background variables, open-ended questions to explore the participant's experiences and challenges and Likert scale to assess the challenges.

Part 1 included the demographic variables of the participants including age, gender, course of study, year of study, residence, and place of attending online classes.

Part 2 comprised of the background variables such as gadgets used for attending online classes, source of internet, mode of theory classes taken during the last 6 months, mode of practical training, methods of teaching theory classes, audio visual aids used, and the virtual platform used.

Part 3 consisted of a questionnaire related to students’ experiences and challenges. It included 15 open-ended questions related to the aspects of theoretical learning, practical learning, study materials, teaching methodology, evaluation process, issues related to physical and mental health, issues related to technology and issues related to finance.

Lastly, Part 4 included a Likert scale on challenges having 30 questions with eight domains; educational challenges (six items), environmental challenges (two items), communication challenges (five items), technical challenges (five items), evaluation challenges (two items), physical challenges (six items), career challenges (two items), and financial challenges (two items). Dimensions were evaluated using 5-point Likert scale varying from strongly disagree (1), disagree (2), neutral (3), agree (4) and strongly agree (5). The total score ranges from 30 to 150. The domain-wise challenges were interpreted as 1–50 = low challenges, 51–100 = moderate challenges, 101–150 = high challenges. The instrument was prepared in English and no translations were done.

Reliability and Validity of the Tool

Content validity was obtained from eight experts in the field of nursing education. The calculated content validity index was 0.80. Pilot study was conducted with 10% of the study participants (42 students) to test the reliability of the tool before administering to the main study participants. Using Cronbach's alpha (inter-item reliability), the internal consistency assessed was 0.89, which is highly reliable. The participants participated in the pilot study were excluded from the main study.

Ethical Considerations

Ethical approval was obtained from the Research and Ethics Committee of Narayana Hrudayalaya College of Nursing (NHH/AEC-CL.2022-BI5 dated 22/3/2022), Kirubhanidhi College of Nursing (KCC/22/22 dated 04/3/2022), and Koshy's College of Nursing (KCN/15 dated 07/3/2022) and Institutional review board. After getting the ethical approvals, formal permission was obtained from the Head of Nursing colleges to collect data. The researchers explained the purpose of the study to the participants involved in both quantitative and qualitative data collection. The participants were informed that their participation in the study was voluntary. Since the participants were not forced to participate in the study, they were given the freedom to withdraw from the study at any time without any penalty. The participants signed the informed consent and responded to all the questions and returned the completed questionnaire. All the audio recordings were coded and password protected. It was explained to the participants that they were not exposed to any kind of risk. To keep the data anonymous, no identifying information was collected from the participants. The researchers maintained confidentiality of information throughout the study period. All the collected data were stored in a password protected file. Only, the investigators of the study had access to the data.

Data Collection (Qualitative Phase)

In Phase I of the study, three focus groups were selected using purposive sampling technique. Each group included six participants with a total of 18 nursing students. After getting the consent, the participants shared their experiences and challenges faced during their educational training in the pandemic. The interviews were conducted from 25/2/2022 to 25/3/2022 and each interview lasted for 1.30 h to 2 h. The first and third authors conducted the interview. The first author is a PhD and the third author is a BSN holder. The first author is an assistant professor and the third author is a staff nurse. Both of them were females. Both of them were trained in qualitative data collection. The researchers established rapport with the study participants. The researcher used 15 open-ended probing questions and the participants were given the freedom to express additional views and comments. All the interviews were conducted in person in the college and audio recorded with their consent. Focus group discussions were continued till the data saturation occurred. The transcripts were returned to the participants for their correction.

Data Collection (Quantitative Phase)

In Phase II, the quantitative data were collected using convenient sampling technique. The total number of students participated in the study were 477. The questionnaires were transferred to Google forms and were circulated to the students after explaining the objectives and getting the informed consent. The quantitative data were collected from 11/04/2022 to 20 /04/2022. The response rate was 72.9% (477) which included Narayana Hrudayalaya College of nursing (88 participants), Koshy's College of nursing (235 participants) and Kirubanidhi College of nursing (154 participants).

Data Analysis (Qualitative Phase)

The data were analyzed using thematic analysis. The collected data were transcribed and analyzed using Braun and Clarke's thematic analysis. Reflexive thematic analysis was performed in this study ( Clarke & Braun, 2017 ).

Data Analysis (Quantitative Phase)

The quantitative data were analyzed using descriptive and inferential statistics using SPSS version 22.

Credibility, Dependability, and Transferability

To ensure credibility of the data, the researcher strongly engaged with the focused group interviews by means of observation, documentation, and taking notes. Dependability was achieved through reviews and comments given by the research guide, who is the second author of the study who has full knowledge of the study design and methodology. The data collected from participants and the findings could be applicable to other contexts, situations, times, and populations and the study setting. It ensures transferability.

The researcher adhered to rigor by carefully collecting data via audio recordings and by taking field notes. Each focus group interview was transcribed immediately after the interview. The transcripts were given to the participants for cross-checking and approval. In addition to ensuring rigor through trustworthiness criteria, the authors followed mixed-methods research legitimation criteria by ensuring design quality, design suitability, within design consistency, design fidelity, and analytic adequacy ( Teddlie & Tashakkori, 2009 ).

Trustworthiness

Trustworthiness was established by using an unbiased approach in selecting the participants and by participant's being honest, clearly recorded, and accurately presented inputs. The transcriptions, coding, and themes–subthemes were discussed by the research team for their verification. Then based on the themes and subthemes the quantitative questionnaire was created by the researchers.

Phase 1 Qualitative Phase

Table 1 shows the frequency and percentage distribution of background variables of 18 participants who shared their experiences and challenges faced during their educational training in the pandemic. Table 2 shows the frequency and percentage distribution of participants’ background variables.

Table 1.

Frequency and Percentage Distribution of Demographic Variables of Nursing Students.

Demographic variables	Qualitative data		Quantitative data
	Frequency		Frequency
	Phase 1 ( = 18)	Percentage	Phase II ( = 477)	Percentage

18–23 years	16	88.9	432	90.6
23–29 years	2	11.1	45	9.4
Gender
Male	4	22.2	111	23.3
Female	14	77.8	366	76.7
Course
B.Sc. Nursing	14	77.8	331	69.4
GNM	4	22.2	146	30.6
Year of study
Second year	4	22.2	226	47.4
Third year	9	50	226	47.4
Fourth year	5	27.8	25	5.2
Residence
Urban	11	61.1	216	45.3
Semi-urban	2	11.1	113	23.7
Rural	5	27.8	148	31
From where you attended the online classes most of the time
Home	7	38.9	79	16.6
Hostel	11	61.1	398	83.4

Table 2.

Frequency and Percentage Distribution of Baseline Variables of Nursing Students.

Demographic variables	Qualitative data		Quantitative data
	Frequency		Frequency
	Phase 1 ( = 18)	Percentage	Phase II ( = 477)	Percentage
Gadget used for attending online classes (multiple choice)
Mobile	18	100	469	98.3
Laptop	2	11.11	52	10.9
Tablet	1	5.55	13	2.7
Desktop			4	0.8
Source of internet (multiple choice)
WiFi	3	16.66	87	18.2
LAN	-	-	1	0.2
Mobile data	18	100	451	94.5
Mode of theory classes taken for the last 6 months
Online	1	5.6	69	14.5
Offline	5	27.7	157	32.9
Both online and offline	12	66.7	251	52.6
Mode of the practical training
Online	1	5.6	50	10.5
Offline	7	38.9	289	60.6
Both online and offline	10	55.5	138	28.9
Methods of teaching used for theory classes (multiple choice)
Lecture cum discussion	18	100	451	94.5
Seminar	1	5.55	98	20.5
Role play	-	-	38	8
AV aids used (multiple options)
Power point presentation	17	94.4	445	93.3
Videos	7	38.9	218	45.7
White / Black board	-	-	88	18.4
Virtual platform used (multiple options)
Zoom	8	44.4	250	52.4
Google meet platform	10	55.6	286	60
Cisco	-	-	106	22.2
Web-ex	4	22.2	179	37.5

Experiences and Challenges Faced by the Nursing Students

In Phase 1, the experiences and challenges experienced by nursing students with their educational training during the pandemic were analyzed using thematic analysis. Table 3 reports seven themes and 10 sub-themes. The themes identified includes: (1) technical issues—a concern, (2) regular rhythm in educational training—but not complete, (3) stress and strain, (4) evaluation—a concern, (5) communication, (6) comfort zone, and (7) easy distraction. The sub-themes were: (1.1) problems with internet connectivity, (1.2) issues with the digital platform, (2.1) theoretical learning experience-better, (2.2) deficient practical skills, (3.1) physical stress, (3.2) mental stress, (4.1) unfair evaluation and lack of feedback, (5.1) decreased quality of communication, (6.1) very convenient, and (7.1) difficult to concentrate.

Table 3.

Themes and Subthemes of Experiences and Challenges Faced by Nursing Students.

S. no.	Themes	Sub-themes
	Technical issues—a concern	1.1. Problems with internet connectivity
	Technical issues—a concern	1.2. Issues with the digital platform
	Regular rhythm in educational training—but not complete	2.1. Theoretical learning experience-Better
	Regular rhythm in educational training—but not complete	2.2.Deficient practical skills
	Stress and strain	3.1.Physical stress
	Stress and strain	3.2.Mental stress
	Evaluation—a concern	4.1.Unfair evaluation
	Communication	5.1.Decreased quality of communication
	Comfort zone	6.1.Very convenient
	Easy distraction	7.1.Difficult to concentrate

Theme 1: Technical Issues: A Concern

Modern technology is progressive in all sectors. With this technology, it was possible to deliver training in all educational sectors including nursing education during COVID-19. Though it was helpful, technical problems interrupted the teaching–learning process. Most of the participants expressed their concern related to technical issues. It includes issues with internet connectivity, and issues with the digital platform.

Subtheme 1: Problems with Internet Connectivity

Constant network issues were an unavoidable fact for many students. Students could not be connected to the virtual class on time due to the internet connectivity issues and they had to miss attending the classes.

“Sometimes it keeps on showing error code and by the time I get connected the class is completed by the faculty” (5A).

Students stated that they faced technical and network issues while attending the classes.

“During online classes, we have faced a lot of technical and network issues” (2A).

In addition, fluctuations in the network connectivity were another technical issue faced by students and it affected the virtual learning of the students.

“I faced fluctuations in my network during a natural calamity in my place so I missed many classes during that time” (13A).

Subtheme 2: Issues with the Digital Platform

There are various platforms used to deliver online educational training. The participants expressed their difficulties as they had hitches in updating the digital platforms, and mentioned that the lack of experience in using the platforms affected their learning.

Digital platform did not work if the application is not updated on time. This was stated as below;

“If I did not update the app on time, it will not work” (1A).

Students faced problems in joining the virtual platform due to issues with the virtual platform.

“Sometimes I faced problems with joining with the virtual platform” (8A).

Lack of experience in using the virtual platform by both the faculty and student was another challenge stated by the students.

“Had struggle to join the meeting initially for both students and faculties because it was very new to us” (5A).

Students faced difficulties in submitting the assignments and answer sheets, as they did not have previous experience in submitting it through digital platforms.

“I struggled while submitting the answer sheets /assignment through digital platforms” (4A).

Theme 2: Regular Rhythm in Educational Training: But not Complete

Virtual education is a boon during pandemic. It took the education system in a rhythmic manner. Though the online lectures were beneficial, at times, students faced few challenges.

Subtheme 1: Online Theoretical Learning Experience

The students utilized the opportunities to learn from online classes with few challenges in attending online classes.

Commencement of online classes helped the students to have continuity in their studies. As the online classes were started on time immediately, it did not affect their theoretical learning.

“…It was not at all possible for the colleges to continue the offline classes so that the apex body instructed to start with online classes and it's good that we were in touch with our studies” (12A).

Different methods and techniques of teaching adopted during online classes enhanced interest in their learning.

“During online classes teacher used to teach with PPTs, and some good videos to make the session interesting. Sometimes they used to conduct lecture cum discussion. That time I was interested to listen to the class” (15A).

“I was interested to attend the online theory classes when teachers used to take a class by showing some videos related to theory content. It was good” (16A).

Students encountered issues with the storage of study materials as they had minimal storage space in their gadgets.

“Teachers used to send notes in PDF form in the mail or by WhatsApp. When I have storage issues in my gadgets, I deleted the content because of storage issues” (18A).

Subtheme 2: Deficient Practical Skills

Practical training is a major part of nursing profession. Students faced many challenges while attending online practical classes.

Most of the students stated that their theoretical learning through virtual mode was excellent. However, students felt that learning practical skills through direct clinical experience is rewarding than learning through virtual platform.

“…theory classes were very good. But in case of practical, like IV infusion, it was very easy to watch the procedure in a virtual platform, but it was very difficult to perform. I feel offline clinical exposure is better than online” (3A).

Students stated that they learnt basic nursing skills through direct clinical experience before the pandemic. However, the students lack confidence in performing the skills that they learnt through videos. The students felt nervous while performing the skills directly on the patients, as they did not get hands-on experience during virtual learning.

“…During my first-year clinical posting, I learnt basic procedure like vital signs checking, wound care, surgical dressing, etc with the direct clinical experience, suddenly everything goes on online, the faculty used to show us best videos. While watching videos I feel I can do. But when it's time to do directly, my hands were shivering and I was not confident. I feel offline exposure is better, we can get more exposure” (1A).

Huge gap in practical learning due to the pandemic affected the learning of the students. Thus, the students did not recommend online learning for learning the skills.

“I did not get adequate practical posting in my first year because of COVID-19. It continued with the second year too. So I have a huge gap with practical learning. For practical learning, online learning is not appropriate” (7A).

Theme 3: Stress and Strain

Prolonged online training affects the students’ physical as well as mental health. They felt more stressful.

Subtheme 1: Physical Stress

Students experienced physical symptoms such as strain in the eyes, neck pain, back pain and numbness in the legs due to prolonged usage of phone and sitting.

“I have to write my notes by seeing my phone. Every time I need to continuously see my mobile and make notes. It was straining my eyes and stressful for me” (16A).

“While attending online classes I used to keep my video on and listen to the class. Due to prolonged sitting, I have neck pain, eye strain also” (5A).

“I felt back pain and numbness in my leg while attending the online classes with prolonged sitting. I used to walk in between for some time to reduce the numbness” (12A).

Subtheme 2: Mental Stress

Students were anxious, as they could not complete the given tasks in online classes.

“I was anxious because I did not complete my task given in online classes, I was lazy” (4A).

As the students did not get practical experience in the clinical area, their confidence levels were low during the pandemic. Moreover, as the students did not get any opportunity to practice directly in the clinical area during the pandemic, they felt tensed and lacked confidence to directly practice on the patient after the pandemic.

“Due to lack of practice in clinical, my confidence had come down” (8A).

“I felt stressed out when I am thinking about my practical learning. I did not get adequate opportunity to practice” (10A).

“After lockdown when I came in the clinical setting, I was tensed about how I will handle the patient” (15A).

Theme 4: Evaluation: A Concern

Evaluation is the process of providing feedback to the students to improve themselves. The test, examination, assignment, and evaluation were new for the students and faculty during the pandemic and there were malpractice incidences by the students.

Sub-Theme 1 - Unfair Evaluation and Lack of Feedback

Students felt conducting exam using Google form as useful.

“Some faculties conducted few exams in Google Form, it was good because at that time I studied and attend the exam” (16A).

Malpractice in the online exam could be observed in the students during virtual learning.

“For the online exam, I never used to study because I can copy from PPT, my screenshots, or from Google and score good marks” (2A, 8A, 17A, 18A).

Students stated that they did not get proper feedback on their assignments.

“In my point of view, some faculties did not give us proper feedback on my assignment writing” (6A).

One student stated the unfair evaluation as the students copied scored well.

“I feel very bad when I write without copying and score very less marks; while the students who did malpractice scored well. So the evaluation was going very wrong” (4A).

Theme 5: Communication

It is necessary to build proper communication between the teachers and students to continue a smooth training session online. However, students felt that this distance learning created a communication gap between teachers and students.

Sub Theme 1- Decreased Quality of Communication

Limited and disrupted communication with the friends and teachers created distress in the students.

“It was not possible for me to communicate face to face with my friends and teachers during the online classes. It was quite distressing” (1A).

“Online class communication was the major problem. We could not communicate with faculties and peers like offline” (18A).

Students felt that they could not clarify their doubts with the faculty. However, faculty responded to their queries through WhatsApp and social media.

“If it comes to communication, it was very limited… During offline we can directly ask doubts to the faculty, but not now” (2A).

“During the online classes communication was not easy like face to face communication. But teachers were responding by WhatsApp and other social media after class time also” (6A).

Theme 6: Comfort Zone

Online classes were attended by the students either from hostel or home.

Subtheme 1: Very Convenient

Students felt comfortable staying home and attending online classes.

“It was convenient for me. Because I can stay at home, take care of my family and attend class also” (8A).

“For me, it was convenient, I got more time and can get up late to attend classes” (2A, 3A, 7A).

Students expressed that their transport expenses could be minimized, as they were not required to travel during the pandemic.

“I could save time. Even transport expenses could be minimized” (10A).

Theme 7: Distraction

Distraction was very high in online classes.

Sub-Theme 1: Difficult to Concentrate

Students were distracted during the online classes due to many notifications received from other online applications and disturbance from their siblings.

“As my internet is on I will get many notifications from other apps during class, it was a distraction for me” (4A, 9A, 11A).

“I attended online classes from my home only. I had disturbance from siblings, during my online classes” (7A, 16A).

Students themselves got distracted as they were using social media in between the online classes.

“I used to browse on Facebook, Instagram, YouTube, etc. during the online classes” (13A).

Phase 2: Quantitative Phase

Table 1 shows the frequency and percentage distribution of participant's demographic variables. Majority (90.6%) of the participants were in the age group between 18 and 23 years. Most of them were females (76.7%). 69.4% of the students were undergraduate (BSN) nursing students, while the rest were in Diploma nursing program. 47.4% of the participants were in their second and 47.4% were in their third year of study. Nearly half (45.3%) were from urban areas and 23.7 were from semi-urban areas, while the remaining (31%) were from rural areas. A large number (83.4%) of students attended the online classes from their hostels.

Table 2 outlines the frequency and percentage distribution of participants’ background variables. The results showed that the majority (98.3%) of the students used mobile phones to attend online classes. Most of them (94.5%) used the mobile data to have the internet connection. Almost half of the participants (52.6%) attended both online and offline classes. More than half (52.6%) of the participants had both online and offline practical exposure, and around 33% had offline clinical exposure. Most of the students (94.5%) attended lecture and discussion sessions. A huge number (93.3%) used power point presentation, and 45.7% of them used videos for teaching. Majority (60%) used Google Meet, while 52.4% used Zoom. The remaining used multiple platforms like Cisco, and Webex.

Figure 1 describes the frequency and percentage of distribution of level of challenges. It was classified as low, moderate, and high level of challenges. Majority of them (54.71%) experienced high-level challenges, 44.6% encountered moderate-level challenges, and the remaining experienced low-level challenges related to their nursing education during the pandemic.

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Frequency and Percentage Distribution of Challenges Faced by Nursing Students During Their Educational Training.

The domain-wise challenges with nursing education during pandemic were shown in Table 4 . The eight domains included educational challenges, environmental challenges, communication challenges, technical challenges, evaluation challenges, physical and mental challenges, career challenges, and financial challenges. The mean and standard deviations for educational challenges is (20.27 ± 3.04), environmental challenges (6.92 ± 1.66), communication challenges (17.61 ± 4.01), technical challenges (17.39 ± 3.75), evaluation challenges (7.09 ± 1.94), physical and mental challenges (20.47 ± 4.33), career challenges (7.06 ± 1.91), and financial challenges (6.61 ± 2.1). The overall mean and S.D. of all the domain was 103.39 ± 1 7.11 with the range from 30 to 150.

Table 4.

Assessment of Mean and Standard Deviation of Domain-Wise Challenges Faced by the Nursing Students n = 477.

Domain-wise challenges	Mean	Standard deviation	Range
Educational challenges	20.27	3.04	6–30
Environmental challenges	6.92	1.66	2–10
Communication challenges	17.61	4.01	5–25
Technical challenges	17.39	3.75	5–25
Evaluation challenges	7.09	1.94	2–10
Physical and mental challenges	20.47	4.33	6–30
Career challenges	7.06	1.91	2–10
Financial challenges	6.61	2.1	2–10
Total

Table 5 displays the item-wise challenges. The results of Educational Challenges indicated that almost 38.57% responded that they lack interest in learning. 15.93% either strongly agreed or agreed that face-to-face learning is very effective than E-learning. A larger portion (78.62%) of participants mentioned that the notes and lectures were inadequate. More than half of the participants (54.3%) agreed that virtual demonstration is not very effective for the practical patient care, and 61.21% mentioned that they lack confidence while taking care of patients. The participants provided similar responses during the qualitative phase of the study. The students lack confidence in performing the skills that they learnt through videos. Similarly, the students felt nervous while performing the skills directly on the patients, as they did not get hands-on experience during virtual learning. However, one third of the respondents (33.75%) expressed that they could learn the modern ways of handling patients through videos.

Table 5.

Item-Wise/Domain-Wise Analysis of Challenges Faced by Nursing Students.

S. no	Items	Strongly agree		Agree		Neutral		Disagree		Strongly disagree
S. no	Items	f	%	f	%	f	%	F	%	f	%

1	Lack of interest in learning	74	15.51	110	23.06	214	44.86	43	9.01	36	7.55
2	Face-to-face learning is more effective than E-learning	30	6.29	46	9.64	140	29.35	126	26.42	130	27.25
3	Notes/Lecture content are not adequate	224	46.96	151	31.66	72	15.09	16	3.35	14	2.94
4	Virtual demonstration is not very effective—practical patient care.	113	23.69	146	30.61	155	32.49	35	7.34	28	5.87
5	Lack of confidence while taking care of patients	162	33.96	130	27.25	117	24.53	44	9.22	24	5.03
6	Learnt modern ways of handling patients through videos.	56	11.74	105	22.01	185	38.78	80	16.77	51	10.69

7	Distracted very easily while attending online classes	142	29.77	139	29.14	133	27.88	38	7.97	25	5.24
8	My environment was very comfortable during pandemic to attend online classes	85	17.82	113	23.69	150	31.45	77	16.14	52	10.9

9	Difficulty in sharing my view with the teachers	83	17.4	141	29.56	169	35.43	55	11.53	29	6.08
10	Process of teacher–students interaction became passive.	74	15.51	145	30.4	197	41.3	48	10.06	13	2.73
11	Socializing with peer groups has decreased	109	22.85	167	35.01	151	31.66	27	5.66	23	4.82
12	Experience of loneliness without interacting much with peer groups.	115	24.11	155	32.49	151	31.66	32	6.71	24	5.03
13	Missed interaction with my seniors/college mates	94	19.71	138	28.93	167	35.01	43	9.01	35	7.34

14	Uncertain internet connection interrupts the learning process.	70	14.68	140	29.35	174	36.48	63	13.21	30	6.29
15	Teachers had difficulty in using technical aspects of the online platforms.	69	14.47	109	22.85	143	29.98	87	18.24	69	14.47
16	Good internet connection was there at my place.	140	29.35	148	31.03	125	26.21	38	7.97	26	5.45
17	Faced technical issues with learning platform /device.	114	23.9	151	31.66	146	30.61	37	7.76	29	6.08
18	Difficulty while submitting the answer sheets /assignment through digital platforms	140	29.35	144	30.19	122	25.58	44	9.22	27	5.66

19	Online evaluation may create irrational discrimination between students.	99	20.75	145	30.4	168	35.22	39	8.18	26	5.45
20	Evaluation/test conducted online was unfair	121	25.37	127	26.62	158	33.12	39	8.18	32	6.71

21	Experience of physical strain like headache, backache, neck pain, eye strain	147	30.82	149	31.24	158	23.27	43	9.01	27	5.66
22	I did not feel much mental stress	47	9.85	92	19.29	165	34.59	106	22.22	67	14.05
23	Developed insomnia	88	18.45	137	28.72	162	33.96	54	11.32	36	7.55
24	Addicted to phone due to prolonged using of phone other than learning purpose.	96	20.13	127	26.62	149	31.24	64	13.42	41	8.6
25	Regular life style has changed	125	26.21	146	30.61	148	31.03	38	7.97	20	4.19
26	Worry about online teaching applications that lack proper security system	99	20.75	131	27.46	160	33.54	55	11.53	32	6.71

27	Virtual practical training will affect my career as a registered nurse.	115	24.11	154	32.29	151	31.66	38	7.97	19	3.98
28	I may not be able to work as a skillful nurse	91	19.08	143	29.98	152	31.87	56	11.74	35	7.34

29	Extra money for my expenses for good internet package	149	31.24	128	26.83	126	26.42	40	8.39	34	7.13
30	Bought a new laptop/mobile/electric gadgets to attend virtual classes.	89	18.66	94	19.71	111	23.27	68	14.26	115	24.11

With regard to Environmental challenges , 41.51% expressed that they were comfortable with their home or hostel environment to attend online classes. However, more than half (58.91%) said that they were easily distracted while attending classes. Similar findings were seen in the qualitative phase of the study. Students were distracted during the online classes due to many notifications received from other online applications and disturbance from their siblings. Further, the students were distracted as they were using social media during the online class.

In terms of Communication challenges , almost half of them (46.96%) expressed that they had difficulty in sharing their view with the teachers, and 45.91% said that teacher–student interaction was passive. More than half (57.86%) of them expressed that peer group socialization has decreased, missed interaction (48.64%) with other college mates/seniors and experienced loneliness (56.6%) without interacting much with peer groups. Similar to these findings in the quantitative phase, in qualitative phase, the students mentioned that limited and disrupted communication with the friends and teachers created distress in the students. Moreover, the students could not clarify their doubts with the faculty.

Regarding Technical challenges , 44.03% had uncertain internet connection that interrupted the learning process. Around 37.32% expressed that the teachers had difficulty in using technical aspects of the online platforms initially. Around 39.63% had internet issues in their place. Almost 55.56% students faced technical issues with learning platform/device and around 59.54% had difficulty while submitting the answer sheets/assignment through digital platforms. Likewise, the qualitative findings revealed that the students faced technical and network issues while attending the classes. In addition, fluctuation in the network connectivity was another technical issue faced by students and it affected virtual learning. The participants expressed their concerns as they had difficulties in updating the digital platforms, and mentioned that the lack of experience in using the platforms affected their learning. Students faced difficulties in submitting the assignments and answer sheets, as they did not have previous experience in submitting it through digital platforms.

Related to Evaluation challenges , almost half of them (51.15%) mentioned that the online evaluation might create irrational discrimination between students with network issues, and 51.99% of them said that the evaluation/test conducted online was unfair. Consistent findings could be noted during the qualitative phase of study. Students mentioned that malpractice in the online exam occurred and it affected their grades. In addition, students stated that they did not get proper feedback on their assignments.

With respect to Physical and mental challenges , more than half 62.06% experienced physical strain like headache, backache, neck pain, and eye strain, 47.17% experienced insomnia, around 70.86% had mental stress, 46.75% got addicted to phone due to prolonged usage other than for learning purpose, 56.82% mentioned that the regular life style has changed, and lastly 48.21% were worried about the online teaching applications which lack proper security system. Likewise, same results are discovered in the qualitative phase of the study. Students experienced physical symptoms such as strain in the eyes, neck pain, back pain, and numbness in the legs due to prolonged sitting and continuous usage of phone. Additionally, students were anxious, as they could not complete the given tasks in online classes. Further, as the students did not get practical experience in the clinical area, their confidence levels were low and they felt tensed and lacked self-confidence to directly practice on the patients after the pandemic.

In terms of Career challenges , 56.4% agreed that virtual practical training may affect their career as a registered nurse, and 49.06% agreed that they may not be able to work as a skillful nurse with the virtual learning. Regarding Financial challenges , almost 58.07% agreed that extra money was spent for good internet package and 38.37% bought a new laptop/mobile/electric gadget to attend virtual classes.

With regard to association of demographic variables, only gender (χ 2 = 6.218, p = 0.045) has shown statistically significant association with problems or challenges faced by the nursing students during educational training in the pandemic at p < 0.05 level of significance.

During COVID-19 pandemic, face-to-face teaching and learning were converted to virtual learning and the clinical experiences were suspended to protect the students from the pandemic ( Agu et al., 2021 ). The experiences with the online classes were very new for the nursing students. Moreover, the online education became unavoidable and was a good choice for the faculty and students during this pandemic across the world. Even though, the students and teachers had a positive view of the technology, which helped in the teaching–learning process during pandemic, it posted many challenges ( Mousavizadeh, 2022 ).

We conducted a mixed-methods study to explore the experiences and challenges faced by nursing students in their education during COVID-19 in India. The study adopted an exploratory sequential mixed-methods design. The study was conducted as two phases; the qualitative data were collected during Phase I using focus group interview with the students. The qualitative data collected during the first phase of the study was utilized in preparing the tool for the quantitative phase of the study. The quantitative data were collected using a Likert scale prepared by the investigators of the study on challenges experienced by nursing students on their education. During Phase 1, the analyzed data produced seven themes and 10 sub-themes on the challenges. These themes produced during the qualitative phase further explained the challenges experienced by the nursing students in their education during COVID-19 pandemic in the quantitative phase.

Educational Challenges

Learning motivation encourages learners’ activities and directs and maintains their progress, allowing students to immerse themselves in learning ( Kim, 2020 ). However, virtual learning decreased students’ attention and interest in classes, which then decreased their motivation to learn ( Morfaki & Skotis, 2022 ). Likewise, in the current study most of the students expressed that they lost interest in their learning. Student's interest is very important for academic achievement, so different methods of teaching and learning need to be adopted in future to improve the learning among students during online education ( Mousavizadeh, 2022 ).

During COVID-19 pandemic, the medical and nursing institutions used learning management systems (LMS) and uploaded various reading materials, videos, quizzes, and presentations to encourage the engagement of students in asynchronous learning activities. In addition, online discussion forums were created to facilitate the virtual learning process ( Atwa et al., 2022 ). Some students preferred online learning as it provides structured learning materials and enables studying from home at their own pace and convenience ( Paechter et al., 2010 ; Zheng et al., 2021 ). However, most of the students in different studies conducted across the world preferred face-to-face learning for acquiring motor skills, for establishing interpersonal relationships, and for achieving student learning outcomes ( Arias et al., 2018 ; Faidley, 2021 ; Ramani & Deo, 2021 ; Lim et al., 2021 ). Similarly, Muthuprasad et al. (2021) advocated that the online mode of learning may not be a viable option for practical/skill-oriented courses and therefore hybrid/blended curriculum involving both face to face and online modes of learning shall be adopted by the institutions.

The faculty used different methods of teaching and audio visual aids to enhance the teaching–learning process during the pandemic ( Reimers et al., 2020 ). However, students in the present study mentioned that the notes/lecture content were inadequate. Similar findings were reported in other studies that the quality and effectiveness of lecture were low; and inconsistencies were observed in some professor's lecture during COVID-19 ( Cengiz et al., 2022 ; Dziurka et al., 2022 ; Mousavizadeh, 2022 ; Mukasa et al., 2021 ; Rohde et al., 2022 ). This warrants the educational institutions to monitor the quality of teaching delivered by the faculty to their students during this pandemic. In addition, the faculty should take self-initiatives for the professional empowerment ( Osmanovic Zajic et al., 2022 ).

The professional preparation of nurses involves many hours of practical and theoretical classes which is conducted face to face, which gives a real learning experience ( Dziurka et al., 2022 ). However, COVID-19 pandemic caused alterations, restrictions, limited clinical placements and simulation training in the campus ( Rohde et al., 2022 ). Thus, many nursing institutions adopted virtual theoretical and practical learning modes. Various studies across the world including the present study reported that virtual practical learning was inappropriate and ineffective in doing practical skills. Additionally, the nursing students lack confidence in taking care of the patients as they did not have hands on training ( Cengiz et al., 2022 ; Dziurka et al., 2022 ; Gheshlagh et al., 2022 ; Mukasa et al., 2021 ; Rohde et al., 2022 ; Wajid & Gedik, 2022 ). Therefore, in addition to direct face-to-face practical training in the clinical areas, more nursing simulations, virtual reality, artificial intelligence and telenursing should be utilized to enhance the practical learning of nursing students ( Dziurka et al., 2022 ).

Environmental Challenges

Student engagement during the virtual classes are very essential. The students are expected to actively participate, show positive conduct, self-regulated, display deep learning and understanding, and should demonstrate positive reactions to the learning environment, peers, and teachers ( Bond et al., 2020 ). However, students in the current study and many other studies were distracted very easily while attending online classes, which limited their learning during pandemic ( Bergdahl, 2022 ; Farrell & Brunton, 2020 ; Fazza & Mahgoub, 2021 ; Hollister et al., 2022 ). Therefore, more peer-to-peer conversations and faculty–student exchanges are recommended to enhance the engagement and learning during the pandemic.

Communication Challenges

Effective communication between the educator and the students enhances the learning experience and creates a positive learning environment. In addition, it improves the exchange of ideas, knowledge, and thought to fulfill the purpose of teaching and learning. However, ineffective communication creates frustration, impaired interpersonal relationships, and lack of motivation ( Alawamleh e al., 2020 ). In consistent to this study, the present participants had difficulty in sharing their view with the teachers, could not socialize with peer groups, and experienced loneliness. Furthermore, studies reported that impaired communication during online learning creates uncertainties and insufficiencies in learning ( Cengiz et al., 2022 ; Mousavizadeh, 2022 ; Mukasa et al., 2021 ). Thus, effective communication with the students should be streamlined for successful virtual learning ( Mukasa et al., 2021 ).

Technical Challenges

Online education can be effectively integrated in the nursing curriculum as it guarantees effective problem-based learning. However, the nursing colleges were not adequately prepared to effectively utilize the online teaching and learning in developing and under developed countries ( Molefe & Mabunda, 2022 ). Technical aptitude was lacking among the faculty and students, which posed various challenges ( Barrot et al., 2021 ). Moreover, technical challenges limited the satisfaction of students and faculty toward online teaching and learning ( Mahyoob, 2020 ). Furthermore, failure of internet services, website failures, problems in logging into the site disrupted the teaching–learning process during the pandemic ( Fuchs, 2022 ; Gaur et al., 2020b ). Similar to these studies, the present study participants mentioned that they experienced uncertain internet connection, faced technical issues with learning platform/device, and had difficulty while submitting the answer sheets /assignment through digital platforms. In addition, the teachers had difficulty in using technical aspects of the online platforms. This calls for improving the instructional design and pedagogical methods by training the faculty and students to utilize the digital platforms effectively, which might improve the motivation and engagement of faculty and students during the online education ( Aivaz & Teodorescu, 2022 ).

Evaluation Challenges

Significant changes in the teaching and learning during the pandemic created profound opportunities and threats. Stakeholders and students reported that the evaluation during online learning was biased and ineffective ( Krishnamurthy, 2020 ) and experienced uncertainty toward the examination ( Idris et al., 2021 ). Besides, online learning affects the test scores and grades, student outcomes, attitude, and overall satisfaction with learning ( Szopiński & Bachnik, 2022 ). In the same way, the students in the current study mentioned that the online evaluation created irrational discrimination between students and the evaluation conducted online was unfair. Therefore, standard setting in the evaluation is an essential step considering the learners and educator's perspective, which would improve the teaching–learning process ( Wasfy et al., 2021 ).

Physical and Mental Challenges

COVID-19 pandemic disproportionately affected the physical and mental health of students ( Ro et al., 2021 ). Students missed eating, did not participate in extracurricular activities, and experienced computer-related physical stress ( Idris et al., 2021 ). Likewise, students experienced increased stress due to homework, social isolation and lack of social interactions ( Rao & Rao, 2021 ). In congruent with these study findings, the participants in the present study experienced headache, backache, neck pain, eye strain, insomnia, and mental stress. The authors recommend addressing the physical and mental health issues of the students by promoting the utilization of physical, emotional, and mental health support programs ( Idris et al., 2021 ).

Career Challenges

COVID-19 pandemic impacted the career preference, career perspective, and ideal workplace ( Wang et al., 2022 ). In the same way, the students struggled with the career decision-making process during the pandemic ( Jemini-Gashi & Kadriu, 2022 ). Likewise, working students lost their jobs, which affected their lives, studies, and health ( Tsurugano et al., 2021 ). In line with these studies, students of the present study expressed that virtual practical training will affect their career as a registered nurse and they may not be able to work as a skillful nurse. This calls for the initiation of a structured and well-designed practical training program for the nursing students in the hospitals before their placement as a registered nurse in the clinical practice.

Financial Challenges

The pandemic put a number of students under financial strain, which severely affected their mental well-being ( Negash et al., 2021 ). Similarly, the university students were disproportionately affected by the economic consequences of the pandemic, which escalated the economic uncertainty ( Gewalt et al., 2022 ). The students who lost their economic resources during pandemic experienced higher prevalence of depressive symptoms ( Tancredi et al., 2022 ). Participants in the current study mentioned that they had to spend extra money for good internet package and bought a new laptop/mobile /electric gadget to attend virtual classes, which increased their economic burden. To counterbalance these economic challenges, financial aid schemes for students need to be made available to relieve distress and allow students to focus on their studies ( Gewalt et al., 2022 ).

Strengths and Limitations

The study findings are limited to only few nursing colleges in India. Therefore, the study findings may not be generalizable to other states of India. As the study population was not selected through probability sampling strategy, the representativeness of samples might be lacking in the current study. Moreover, the study instruments were prepared by the investigators of the study that did not undergo rigorous standardization process, which might limit the strength of the study. Based on the study findings, the institutions where the study was conducted should design strategies to mitigate the challenges to have effective teaching and learning.

Implications for Practice

Virtual nursing education can be improved by refining the content and delivery methods, training of nursing faculty to use online educational strategies, and by reducing the technical and environmental barriers. Hybrid and blended teaching–learning strategies may further improve the learning among nursing students.

Virtual education can be very successful if we address the challenges and experiences of the students by performing appropriate groundwork by upgrading the required hardware and software, teaching how to use the facilities, and developing innovative teaching techniques and standard protocols for virtual education.

Supplemental Material

Acknowledgments.

The authors thank the students and faculty members who participated in this study. The authors are thankful to the Deanship of Graduate Studies and Scientific Research at University of Bisha, Saudi Arabia for supporting this work through the Fast-Track Research Support Program. The authors would like to acknowledge the nursing students who have participated in the study. Special thanks to the administrators and faculty members of the institutions for their motivation and support during data collection.

Author Contributions: PK designed and conducted the study and wrote the initial draft of the manuscript. JA edited and added additional content and refined the manuscript. AP collected the data. SM edited the manuscript.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval: Ethical approval was obtained from the Research and Ethics Committee of Narayana Hrudayalaya College of Nursing (NHH/AEC-CL.2022-BI5 dated 22/3/2022), Kirubhanidhi College of Nursing (KCC/22/22 dated 04/3/2022), and Koshy's College of Nursing (KCN/15 dated 07/3/2022).

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors are thankful to the Deanship of Graduate Studies and Scientific Research at University of Bisha, Saudi Arabia for supporting this work through the Fast-Track Research Support Program.

ORCID iDs: Judie Arulappan https://orcid.org/0000-0003-2788-2755

Shimmaa Mansour Moustafa Mohammed https://orcid.org/0000-0002-2956-610X

Supplemental Material: Supplemental material for this article is available online.

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The effects of online education on academic success: A meta-analysis
According to the study of Bernard et al. ( 2004 ), this meta-analysis focuses on the activities done in online education lectures. As a result of the research, an overall effect size close to zero was found for online education utilizing more than one generation technology for students at different levels.
Online Education and Its Effective Practice: A Research Review
U ltimately, we organized. the findings into three major themes to answer our research questions, which included the evolu-. tion of online education, effective online teaching, and effective ...
Online education in the post-COVID era
Metrics. The coronavirus pandemic has forced students and educators across all levels of education to rapidly adapt to online learning. The impact of this — and the developments required to make ...
Impact of online classes on the satisfaction and performance of
The aim of the study is to identify the factors affecting students' satisfaction and performance regarding online classes during the pandemic period of COVID-19 and to establish the relationship between these variables. The study is quantitative in nature, and the data were collected from 544 respondents through online survey who were studying the business management (B.B.A or M.B.A) or ...
Review of Education
This systematic analysis examines effectiveness research on online and blended learning from schools, particularly relevant during the Covid-19 pandemic, and also educational games, computer-supported cooperative learning (CSCL) and computer-assisted instruction (CAI), largely used in schools but with potential for outside school.
Online Teaching in K-12 Education in the United States: A Systematic
The field of research on K-12 online education delivery and outcomes is an emerging area is growing considerably in the wake of the COVID-19 pandemic. This systematic literature review was conducted in response to the need to better understand the evidence-based practices within the research base that could guide the design and implementation ...
(PDF) The Effectiveness of Online Learning: Beyond No Significant
Nashville, TN 3720 3 USA. t [email protected]. Abstract. The physical "brick and mortar" classroom is starting to lose its monopoly as the place of. learning. The Internet has made ...
Online learning during COVID-19 produced ...
Research across disciplines has demonstrated that well-designed online learning can lead to students' enhanced motivation, satisfaction, and learning [1,2,3,4,5,6,7].]. A report by the U.S. Department of Education [], based on examinations of comparative studies of online and face-to-face versions of the same course from 1996 to 2008, concluded that online learning could produce learning ...
Effective online teaching and learning strategies: interdisciplinary
Higher Education has serious challenges regarding academic online teaching-learning-evaluation methods and tools. This study examined 980 students from diverse disciplines about their social ...
How Effective Is Online Learning? What the Research Does and Doesn't
Most of the research on online courses for K-12 students has used large-scale administrative data, looking at otherwise similar students in the two settings. One of these studies, by June Ahn of New York University and Andrew McEachin of the RAND Corp., examined Ohio charter schools; I did another with colleagues looking at Florida public ...
Online Learning: Challenges and Solutions for Learners and Teachers
The article presents some challenges faced by teachers and learners, supplemented with the recommendations to remove them. JEL Code: A20. The COVID-19 pandemic has led to an expansion in the demand for online teaching and learning across the globe. Online teaching and learning is attracting many students for enhanced learning experiences.
PDF Virtual Classrooms: How Online College Courses Affect Student
colleges, online courses have grown most rapidly and are central to the institutions' teaching strategy. Several other quasi-experimental studies examine two-year ... and availability of seats in in-person classes, respectively. A research design using 4 Using non-experimental methods, Brown and Liedholm (2002) and Coates et al. (2004) also ...
Full article: Online Education: Worldwide Status, Challenges, Trends
Many conferences and journals have had themes and special issues focusing on online education. Research related to online business education was first initiated in 1990s by Information Systems (IS) researchers like Alavi and Leidner (Citation 2001) focusing on technology-mediated learning (Alavi, Citation 1994; Alavi & Leidner, Citation 2001 ...
PDF Online Vs. Face-to-Face: A Comparison of Student Outcomes with ...
Online educational opportunities have blossomed as parents, students, college and university administrators and state and federal legislatures try to grapple with the problem of increasing education costs. The potential advantages of offering courses online are numerous: There is a perception that online classes are a more cost-
Promises and pitfalls of online education
Online Report Card - Tracking Online Education in the United States, the 2015 Survey of Online Learning conducted by the Babson Survey Research Group and co-sponsored by the Online Learning ...
Self-reported online science learning strategies of non-traditional
The relationship between learning strategies and academic success has been widely reported in the literature. The nature of student learning and the strategies students draw on when studying are ongoing areas of research for higher education institutions because 'equipping students with effective study strategies is vital to their educational success' (Miyatsu et al., 2018, p. 390).
Online assessment in the age of artificial intelligence
Online education, while not a new phenomenon, underwent a monumental shift during the COVID-19 pandemic, pushing educators and students alike into the uncharted waters of full-time digital learning. With this shift came renewed concerns about the integrity of online assessments. Amidst a landscape rapidly being reshaped by online exam/homework assistance platforms, which witnessed soaring ...
Learning effect of online versus onsite education in health and medical
The disruption of health and medical education by the COVID-19 pandemic made educators question the effect of online setting on students' learning, motivation, self-efficacy and preference. In light of the health care staff shortage online scalable education seemed relevant. Reviews on the effect of online medical education called for high quality RCTs, which are increasingly relevant with ...
Impact of online classes on the satisfaction and performance of
Online classes has encouraged me to develop my own academic interests as far as possible: 3.17: 0.76: 0.723: ... The present study results will help the educators increase the student's satisfaction and performance in online classes. The current research assists educators in understanding the different factors that are required for online ...
Best 6-Month Online Associate Degree Programs for 2024
Duration: A 6-month online associate degree can be completed in significantly less time compared to traditional programs, making it ideal for those seeking a fast-track educational path. Cost: Tuition for 6-month online associate degree programs ranges from $4,000 to $19,500, depending on the institution and program specialization.
HSCI 703 Quantitative Research Methods
Home Courses HSCI 703 August 26, 2024. Chat Live (800) 424-9595 ... A part one focus on the development of applying inferential statistics to health science research questions utilizing SPSS. ...
Omsk State Medical University
For the clinical training of the students, the University has affiliations with 33 hospitals and clinics in the city. Students are provided education with state-of-the-art infrastructure, including research labs and modern medical equipment. In a century-long time, more than 35,000 doctors have been trained at Omsk State Medical University.
Sustainable Development in Omsk, 2002-3 and 2005
Chapter 8 described how a three-person team from each of the distance-learning project’s four partner universities came to England early in 2001 for a course on developing distance-learning courses. Two of each team were distance-learning experts; the third was...
All 7 Universities in Omsk
Latest ranking updates related to universities in Omsk. 06 Mar, 2024: Scimago Institutions Rankings updated with Omsk State Technical University ranked highest among 3 listed universities in Omsk. 19 Oct, 2023: THE Times Higher Education, UK published most recent results of THE World University Rankings by Subject (Business and Economics).Omsk State Technical University achieves position 1001.
Courses/Training
1st NICPR-ECHO Online Course on Clinical Laboratory Management by ICMR-NICPR, Noida: July 9, 2024 : Aug. 28, 2024 : 391.75 KB: 3: DHR-sponsored 1-week training program on "Hands-on Training in HPV DNA Diagnostics" to be conducted by ICMR-NICPR, Noida (August 5-9, 2024) Aug. 5, 2024 : Aug. 9, 2024 : 425.44 KB
Nursing Students' Experiences and Challenges in Their Education During
Likewise, online education improved the flexibility, ability to teach large classes, ... Research Setting. The study was conducted among nursing students of Narayana Hrudayalaya College of Nursing, Koshy's College of Nursing and Kirubanidhi College of Nursing, Bengaluru, Karnataka, India. These colleges initiated virtual classes from April 2020.