essay on my online learning experience

Essays About Online Learning: Top 6 Examples And Prompts

If you are writing essays about online learning, you can start by reading some essay examples and prompts in this article. 

People often regard online learning as kids stuck at home, glued to their devices. However, there is so much more to it than this simplistic concept. Many parents may see it as an “easy way out” for students to slack off on their studies while still passing their classes, but online learning has not reached its full potential yet. 

It has dramatically impacted how education is handled globally, for better or worse. It has forced teachers to take on extra work , while students say it has helped reduce their stress levels. It is undoubtedly a contentious topic. 

If you need help writing an essay about online learning, here are some essay examples you can use for inspiration.

1. Disabled Students Urge Universities To Make Online Learning More Accessible by Lucia Posteraro

2. why are more and more students taking online classes by perry mullins, 3. the benefits of online learning: 7 advantages of online degrees by kelsey miller, 4. why is online learning important by clare scott, 5. is online learning as effective as face-to-face learning by kelli wilkins, 6. i’m a high school student. i don’t want online learning to end. by rory selinger, prompts on essays about online learning, 1. how has online learning affected you, 2. compare and contrast online and in-person classes., 3. what can you learn from an online setup, 4. what is the future of online learning, 5. which is better- online or face-to-face learning, 6. can online learning be sustained long-term.

“Autism may hinder the ability to follow complex conversations, especially with background noise – but Charli’s lectures did not have subtitles. Moreover, extensions for group projects were too short for her extenuating circumstances.’

Posteraro tells the stories of students who want online learning to be more accessible. For example, Charli, a student with autism, was greatly affected by the transition from in-person to online classes during the COVID-19 pandemic. Unfortunately, online learning has not catered to her special needs, so she urges schools to take action to make online education more inclusive. You might also be interested in these essays about knowledge .

“The result of taking online classes is that students who take them become more proficient and comfortable with using computers. Students can learn to connect with one another online and with information in meaningful and useful ways. With that said more and more students are taking online classes because it’s the best way to save money work at your own pace and not have to be stressed about going to class.”

In his essay, Mullins discusses why more students prefer online learning. First, it lessens expenses, as students learn from the comfort of their rooms. Second, it helps students avert the fear of talking to strangers face-to-face, helping them communicate better. 

“It’s clear, then, that learning online helps prepare professionals for this shift toward online work. Below, explore what online courses entail, explore seven key benefits, and get the advice you need to determine if online courses are right for you.”

Miller briefly explains what online learning is, then proceeds to discuss its advantages. These include a self-paced schedule, improved communication, and new technical skills. However, he reminds readers that everyone is different; regardless of the benefits, they should only choose online learning if they believe it will work for them.

“Boil it right down and the answer is simple: change is constant. You must move with it. The true beauty of online learning is that it lends itself perfectly to your lifestyle. By its very nature, it can fit around you. Also, no longer are we taught how to do a job, it’s usually a case of figuring it out for yourself—and that’s where online learning can amplify your skills.”

Scott presents the importance of online learning. Similar to Miller, she mentions self-paced, giving students new skills. However, the most important lesson is that change is constant. Online learning exemplifies this precept, and these skills help us move along.

“While both ways of learning have advantages and disadvantages, what is more effective is based off of the student themselves. Students can weigh the costs and benefits between online learning and face-to-face learning. They can decide for themselves what would be best for them. Online learning can be as effective as face-to-face learning if the student is committed to putting their time and effort to study alone.”

Wilkins questions the notion that online learning is inferior to a face-to-face classes. She begins by listing the benefits of online classes, including comfort and easier schedules, as with Miller and Scott. However, she also mentions its disadvantages, such as the possibility of students being distracted and a lack of bonding between classmates. But, of course, it’s all up to the student in the end: they should decide which type of education they prefer.

“One thing I hope people now realize is that education is not a one-size-fits-all model. While the self-disciplined nature of remote learning is not for everyone, it has allowed students like me to flourish unimpeded by the challenges presented by typical classroom settings.”

A 14-year-old student, Selinger wishes to continue her education online as schools return to physical classes amid the pandemic. She discusses the relief she feels from the lack of peer pressure, judgment, and a rigorous schedule. Controlling your study schedule relieves students of pressure, and Selinger believes this is optimal for success. She believes online learning opens a path to be better rather than to “return to normal.”

In this essay, you can write about your experience of online learning. Whether you have had online coursework from school or college or taken an online course for your own interests, we’ve all had some experience learning online. Discuss how you benefited from online learning and the challenges you faced. For a compelling essay, conduct interviews to back up your experience by showing others who felt the same way.

Create an exciting comparative essay between online and in-person learning. You can compare and contrast the experiences and show the positives and negatives of each. Start by making a list or Venn diagram, and organize your essay. Include the structure, advantages, and disadvantages of each method of learning. 

Online learning can teach you some skills to succeed in the real world. In this essay, write about the unique skills you can gain from online learning. Perhaps you learn valuable IT skills, virtual note-taking, and basic administrative skills. Then, look into how these skills can benefit you in future studies or when trying to step into a new career path. 

We have barely scratched the surface of technology. In this essay, look to the future and imagine how online education will look. Then, research up-and-coming online learning technologies and see what will come next. Will the development of more online learning technology benefit students? Look into this exciting topic for an engaging discussion.

For this topic, writing an excellent argumentative essay is easy. First, from research and your own experience, list the benefits and downsides of each type of learning and determine which is more effective. Then, you can use Google and the essay examples above to support your argument.  

Online learning is most commonly used for students who are ill or during situations such as a global pandemic. It is meant to be temporary; however, can schools stick to a completely-online method of instruction? Include some advantages and disadvantages of online learning in your essay.

Tip: If writing an essay sounds like a lot of work, simplify it. Write a simple 5 paragraph essay instead.

If you’re still stuck, check out our general resource of essay writing topics .

My Experience With Online Classes Essay

With the onset of Covid-19, students everywhere have had to adapt quickly and make an adjustment from traditional in-person classes to online education. I’ve been fortunate enough for my learning experience during this pandemic transition period not just be acceptable but enjoyable as well.

Write a Short Essay On My Experience With Online Classes during Pandemic

1. Introduction:

Despite the initial challenge of adjusting to a totally new format, I have embraced my experience with online learning. As time passed, it has become evident that there are many benefits to this mode of education , which can be especially helpful amidst trying times like these caused by COVID-19. Being able to tailor classes around my lifestyle and having access from anywhere in the world is invaluable for student success!

2. Body Paragraphs:

Online classes enabled me to learn and study from the comfort of my own home. I could avoid time-consuming commutes, conveniently access a range of learning materials, such as e-books and lectures online – all with an internet connection. Not only did this benefit my studies but also served to cultivate valuable skills like self-discipline and proper time management.

Despite its advantages, virtual learning posed some unique challenges. Namely, the lack of face-to-face interaction with teachers and peers made it difficult to ask questions or have meaningful group conversations. Additionally, technical issues such as slow internet connections and platform problems could impede lesson delivery at times.

3. Conclusion

My experiences with online classes have provided me with invaluable lessons, such as self-discipline and effective time management. While these courses bring advantages to the table in terms of convenience and accessibility, I hope that they will be used to supplement traditional learning rather than fully replace it.

Hello! Welcome to my Blog StudyParagraphs.co. My name is Angelina. I am a college professor. I love reading writing for kids students. This blog is full with valuable knowledge for all class students. Thank you for reading my articles.

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Students’ experience of online learning during the COVID‐19 pandemic: A province‐wide survey study

Lixiang yan.

1 Centre for Learning Analytics at Monash, Faculty of Information Technology, Monash University, Clayton VIC, Australia

Alexander Whitelock‐Wainwright

2 Portfolio of the Deputy Vice‐Chancellor (Education), Monash University, Melbourne VIC, Australia

Quanlong Guan

3 Department of Computer Science, Jinan University, Guangzhou China

Gangxin Wen

4 College of Cyber Security, Jinan University, Guangzhou China

Dragan Gašević

Guanliang chen, associated data.

The data is not openly available as it is restricted by the Chinese government.

Online learning is currently adopted by educational institutions worldwide to provide students with ongoing education during the COVID‐19 pandemic. Even though online learning research has been advancing in uncovering student experiences in various settings (i.e., tertiary, adult, and professional education), very little progress has been achieved in understanding the experience of the K‐12 student population, especially when narrowed down to different school‐year segments (i.e., primary and secondary school students). This study explores how students at different stages of their K‐12 education reacted to the mandatory full‐time online learning during the COVID‐19 pandemic. For this purpose, we conducted a province‐wide survey study in which the online learning experience of 1,170,769 Chinese students was collected from the Guangdong Province of China. We performed cross‐tabulation and Chi‐square analysis to compare students’ online learning conditions, experiences, and expectations. Results from this survey study provide evidence that students’ online learning experiences are significantly different across school years. Foremost, policy implications were made to advise government authorises and schools on improving the delivery of online learning, and potential directions were identified for future research into K‐12 online learning.

Practitioner notes

What is already known about this topic

• Online learning has been widely adopted during the COVID‐19 pandemic to ensure the continuation of K‐12 education.
• Student success in K‐12 online education is substantially lower than in conventional schools.
• Students experienced various difficulties related to the delivery of online learning.

What this paper adds

• Provide empirical evidence for the online learning experience of students in different school years.
• Identify the different needs of students in primary, middle, and high school.
• Identify the challenges of delivering online learning to students of different age.

Implications for practice and/or policy

• Authority and schools need to provide sufficient technical support to students in online learning.
• The delivery of online learning needs to be customised for students in different school years.

INTRODUCTION

The ongoing COVID‐19 pandemic poses significant challenges to the global education system. By July 2020, the UN Educational, Scientific and Cultural Organization (2020) reported nationwide school closure in 111 countries, affecting over 1.07 billion students, which is around 61% of the global student population. Traditional brick‐and‐mortar schools are forced to transform into full‐time virtual schools to provide students with ongoing education (Van Lancker & Parolin,  2020 ). Consequently, students must adapt to the transition from face‐to‐face learning to fully remote online learning, where synchronous video conferences, social media, and asynchronous discussion forums become their primary venues for knowledge construction and peer communication.

For K‐12 students, this sudden transition is problematic as they often lack prior online learning experience (Barbour & Reeves,  2009 ). Barbour and LaBonte ( 2017 ) estimated that even in countries where online learning is growing rapidly, such as USA and Canada, less than 10% of the K‐12 student population had prior experience with this format. Maladaptation to online learning could expose inexperienced students to various vulnerabilities, including decrements in academic performance (Molnar et al.,  2019 ), feeling of isolation (Song et al.,  2004 ), and lack of learning motivation (Muilenburg & Berge,  2005 ). Unfortunately, with confirmed cases continuing to rise each day, and new outbreaks occur on a global scale, full‐time online learning for most students could last longer than anticipated (World Health Organization,  2020 ). Even after the pandemic, the current mass adoption of online learning could have lasting impacts on the global education system, and potentially accelerate and expand the rapid growth of virtual schools on a global scale (Molnar et al.,  2019 ). Thus, understanding students' learning conditions and their experiences of online learning during the COVID pandemic becomes imperative.

Emerging evidence on students’ online learning experience during the COVID‐19 pandemic has identified several major concerns, including issues with internet connection (Agung et al.,  2020 ; Basuony et al.,  2020 ), problems with IT equipment (Bączek et al.,  2021 ; Niemi & Kousa,  2020 ), limited collaborative learning opportunities (Bączek et al.,  2021 ; Yates et al.,  2020 ), reduced learning motivation (Basuony et al.,  2020 ; Niemi & Kousa,  2020 ; Yates et al.,  2020 ), and increased learning burdens (Niemi & Kousa,  2020 ). Although these findings provided valuable insights about the issues students experienced during online learning, information about their learning conditions and future expectations were less mentioned. Such information could assist educational authorises and institutions to better comprehend students’ difficulties and potentially improve their online learning experience. Additionally, most of these recent studies were limited to higher education, except for Yates et al. ( 2020 ) and Niemi and Kousa’s ( 2020 ) studies on senior high school students. Empirical research targeting the full spectrum of K‐12students remain scarce. Therefore, to address these gaps, the current paper reports the findings of a large‐scale study that sought to explore K‐12 students’ online learning experience during the COVID‐19 pandemic in a provincial sample of over one million Chinese students. The findings of this study provide policy recommendations to educational institutions and authorities regarding the delivery of K‐12 online education.

LITERATURE REVIEW

Learning conditions and technologies.

Having stable access to the internet is critical to students’ learning experience during online learning. Berge ( 2005 ) expressed the concern of the divide in digital‐readiness, and the pedagogical approach between different countries could influence students’ online learning experience. Digital‐readiness is the availability and adoption of information technologies and infrastructures in a country. Western countries like America (3rd) scored significantly higher in digital‐readiness compared to Asian countries like China (54th; Cisco,  2019 ). Students from low digital‐readiness countries could experience additional technology‐related problems. Supporting evidence is emerging in recent studies conducted during the COVID‐19 pandemic. In Egypt's capital city, Basuony et al. ( 2020 ) found that only around 13.9%of the students experienced issues with their internet connection. Whereas more than two‐thirds of the students in rural Indonesia reported issues of unstable internet, insufficient internet data, and incompatible learning device (Agung et al.,  2020 ).

Another influential factor for K‐12 students to adequately adapt to online learning is the accessibility of appropriate technological devices, especially having access to a desktop or a laptop (Barbour et al., 2018 ). However, it is unlikely for most of the students to satisfy this requirement. Even in higher education, around 76% of students reported having incompatible devices for online learning and only 15% of students used laptop for online learning, whereas around 85% of them used smartphone (Agung et al.,  2020 ). It is very likely that K‐12 students also suffer from this availability issue as they depend on their parents to provide access to relevant learning devices.

Technical issues surrounding technological devices could also influence students’ experience in online learning. (Barbour & Reeves,  2009 ) argues that students need to have a high level of digital literacy to find and use relevant information and communicate with others through technological devices. Students lacking this ability could experience difficulties in online learning. Bączek et al. ( 2021 ) found that around 54% of the medical students experienced technical problems with IT equipment and this issue was more prevalent in students with lower years of tertiary education. Likewise, Niemi and Kousa ( 2020 ) also find that students in a Finish high school experienced increased amounts of technical problems during the examination period, which involved additional technical applications. These findings are concerning as young children and adolescent in primary and lower secondary school could be more vulnerable to these technical problems as they are less experienced with the technologies in online learning (Barbour & LaBonte,  2017 ). Therefore, it is essential to investigate the learning conditions and the related difficulties experienced by students in K‐12 education as the extend of effects on them remain underexplored.

Learning experience and interactions

Apart from the aforementioned issues, the extent of interaction and collaborative learning opportunities available in online learning could also influence students’ experience. The literature on online learning has long emphasised the role of effective interaction for the success of student learning. According to Muirhead and Juwah ( 2004 ), interaction is an event that can take the shape of any type of communication between two or subjects and objects. Specifically, the literature acknowledges the three typical forms of interactions (Moore,  1989 ): (i) student‐content, (ii) student‐student, and (iii) student‐teacher. Anderson ( 2003 ) posits, in the well‐known interaction equivalency theorem, learning experiences will not deteriorate if only one of the three interaction is of high quality, and the other two can be reduced or even eliminated. Quality interaction can be accomplished by across two dimensions: (i) structure—pedagogical means that guide student interaction with contents or other students and (ii) dialogue—communication that happens between students and teachers and among students. To be able to scale online learning and prevent the growth of teaching costs, the emphasise is typically on structure (i.e., pedagogy) that can promote effective student‐content and student‐student interaction. The role of technology and media is typically recognised as a way to amplify the effect of pedagogy (Lou et al.,  2006 ). Novel technological innovations—for example learning analytics‐based personalised feedback at scale (Pardo et al.,  2019 ) —can also empower teachers to promote their interaction with students.

Online education can lead to a sense of isolation, which can be detrimental to student success (McInnerney & Roberts,  2004 ). Therefore, integration of social interaction into pedagogy for online learning is essential, especially at the times when students do not actually know each other or have communication and collaboration skills underdeveloped (Garrison et al.,  2010 ; Gašević et al.,  2015 ). Unfortunately, existing evidence suggested that online learning delivery during the COVID‐19 pandemic often lacks interactivity and collaborative experiences (Bączek et al.,  2021 ; Yates et al.,  2020 ). Bączek et al., ( 2021 ) found that around half of the medical students reported reduced interaction with teachers, and only 4% of students think online learning classes are interactive. Likewise, Yates et al. ( 2020 )’s study in high school students also revealed that over half of the students preferred in‐class collaboration over online collaboration as they value the immediate support and the proximity to teachers and peers from in‐class interaction.

Learning expectations and age differentiation

Although these studies have provided valuable insights and stressed the need for more interactivity in online learning, K‐12 students in different school years could exhibit different expectations for the desired activities in online learning. Piaget's Cognitive Developmental Theory illustrated children's difficulties in understanding abstract and hypothetical concepts (Thomas,  2000 ). Primary school students will encounter many abstract concepts in their STEM education (Uttal & Cohen,  2012 ). In face‐to‐face learning, teachers provide constant guidance on students’ learning progress and can help them to understand difficult concepts. Unfortunately, the level of guidance significantly drops in online learning, and, in most cases, children have to face learning obstacles by themselves (Barbour,  2013 ). Additionally, lower primary school students may lack the metacognitive skills to use various online learning functions, maintain engagement in synchronous online learning, develop and execute self‐regulated learning plans, and engage in meaningful peer interactions during online learning (Barbour,  2013 ; Broadbent & Poon,  2015 ; Huffaker & Calvert, 2003; Wang et al.,  2013 ). Thus, understanding these younger students’ expectations is imperative as delivering online learning to them in the same way as a virtual high school could hinder their learning experiences. For students with more matured metacognition, their expectations of online learning could be substantially different from younger students. Niemi et al.’s study ( 2020 ) with students in a Finish high school have found that students often reported heavy workload and fatigue during online learning. These issues could cause anxiety and reduce students’ learning motivation, which would have negative consequences on their emotional well‐being and academic performance (Niemi & Kousa,  2020 ; Yates et al.,  2020 ), especially for senior students who are under the pressure of examinations. Consequently, their expectations of online learning could be orientated toward having additional learning support functions and materials. Likewise, they could also prefer having more opportunities for peer interactions as these interactions are beneficial to their emotional well‐being and learning performance (Gašević et al., 2013 ; Montague & Rinaldi, 2001 ). Therefore, it is imperative to investigate the differences between online learning expectations in students of different school years to suit their needs better.

Research questions

By building upon the aforementioned relevant works, this study aimed to contribute to the online learning literature with a comprehensive understanding of the online learning experience that K‐12 students had during the COVID‐19 pandemic period in China. Additionally, this study also aimed to provide a thorough discussion of what potential actions can be undertaken to improve online learning delivery. Formally, this study was guided by three research questions (RQs):

RQ1 . What learning conditions were experienced by students across 12 years of education during their online learning process in the pandemic period? RQ2 . What benefits and obstacles were perceived by students across 12 years of education when performing online learning? RQ3 . What expectations do students, across 12 years of education, have for future online learning practices ?

Participants

The total number of K‐12 students in the Guangdong Province of China is around 15 million. In China, students of Year 1–6, Year 7–9, and Year 10–12 are referred to as students of primary school, middle school, and high school, respectively. Typically, students in China start their study in primary school at the age of around six. At the end of their high‐school study, students have to take the National College Entrance Examination (NCEE; also known as Gaokao) to apply for tertiary education. The survey was administrated across the whole Guangdong Province, that is the survey was exposed to all of the 15 million K‐12 students, though it was not mandatory for those students to accomplish the survey. A total of 1,170,769 students completed the survey, which accounts for a response rate of 7.80%. After removing responses with missing values and responses submitted from the same IP address (duplicates), we had 1,048,575 valid responses, which accounts to about 7% of the total K‐12 students in the Guangdong Province. The number of students in different school years is shown in Figure  1 . Overall, students were evenly distributed across different school years, except for a smaller sample in students of Year 10–12.

The number of students in each school year

Survey design

The survey was designed collaboratively by multiple relevant parties. Firstly, three educational researchers working in colleges and universities and three educational practitioners working in the Department of Education in Guangdong Province were recruited to co‐design the survey. Then, the initial draft of the survey was sent to 30 teachers from different primary and secondary schools, whose feedback and suggestions were considered to improve the survey. The final survey consisted of a total of 20 questions, which, broadly, can be classified into four categories: demographic, behaviours, experiences, and expectations. Details are available in Appendix.

All K‐12 students in the Guangdong Province were made to have full‐time online learning from March 1, 2020 after the outbreak of COVID‐19 in January in China. A province‐level online learning platform was provided to all schools by the government. In addition to the learning platform, these schools can also use additional third‐party platforms to facilitate the teaching activities, for example WeChat and Dingding, which provide services similar to WhatsApp and Zoom. The main change for most teachers was that they had to shift the classroom‐based lectures to online lectures with the aid of web‐conferencing tools. Similarly, these teachers also needed to perform homework marking and have consultation sessions in an online manner.

The Department of Education in the Guangdong Province of China distributed the survey to all K‐12 schools in the province on March 21, 2020 and collected responses on March 26, 2020. Students could access and answer the survey anonymously by either scan the Quick Response code along with the survey or click the survey address link on their mobile device. The survey was administrated in a completely voluntary manner and no incentives were given to the participants. Ethical approval was granted by the Department of Education in the Guangdong Province. Parental approval was not required since the survey was entirely anonymous and facilitated by the regulating authority, which satisfies China's ethical process.

The original survey was in Chinese, which was later translated by two bilingual researchers and verified by an external translator who is certified by the Australian National Accreditation Authority of Translators and Interpreters. The original and translated survey questionnaires are available in Supporting Information. Given the limited space we have here and the fact that not every survey item is relevant to the RQs, the following items were chosen to answer the RQs: item Q3 (learning media) and Q11 (learning approaches) for RQ1, item Q13 (perceived obstacle) and Q19 (perceived benefits) for RQ2, and item Q19 (expected learning activities) for RQ3. Cross‐tabulation based approaches were used to analyse the collected data. To scrutinise whether the differences displayed by students of different school years were statistically significant, we performed Chi‐square tests and calculated the Cramer's V to assess the strengths of the association after chi‐square had determined significance.

For the analyses, students were segmented into four categories based on their school years, that is Year 1–3, Year 4–6, Year 7–9, and Year 10–12, to provide a clear understanding of the different experiences and needs that different students had for online learning. This segmentation was based on the educational structure of Chinese schools: elementary school (Year 1–6), middle school (Year 7–9), and high school (Year 10–12). Children in elementary school can further be segmented into junior (Year 1–3) or senior (Year 4–6) students because senior elementary students in China are facing more workloads compared to junior students due to the provincial Middle School Entry Examination at the end of Year 6.

Learning conditions—RQ1

Learning media.

The Chi‐square test showed significant association between school years and students’ reported usage of learning media, χ 2 (55, N  = 1,853,952) = 46,675.38, p  < 0.001. The Cramer's V is 0.07 ( df ∗ = 5), which indicates a small‐to‐medium effect according to Cohen’s ( 1988 ) guidelines. Based on Figure  2 , we observed that an average of up to 87.39% students used smartphones to perform online learning, while only 25.43% students used computer, which suggests that smartphones, with widespread availability in China (2020), have been adopted by students for online learning. As for the prevalence of the two media, we noticed that both smartphones ( χ 2 (3, N  = 1,048,575) = 9,395.05, p < 0.001, Cramer's V  = 0.10 ( df ∗ = 1)) and computers ( χ 2 (3, N  = 1,048,575) = 11,025.58, p <.001, Cramer's V  = 0.10 ( df ∗ = 1)) were more adopted by high‐school‐year (Year 7–12) than early‐school‐year students (Year 1–6), both with a small effect size. Besides, apparent discrepancies can be observed between the usages of TV and paper‐based materials across different school years, that is early‐school‐year students reported more TV usage ( χ 2 (3, N  = 1,048,575) = 19,505.08, p <.001), with a small‐to‐medium effect size, Cramer's V  = 0.14( df ∗ = 1). High‐school‐year students (especially Year 10–12) reported more usage of paper‐based materials ( χ 2 (3, N  = 1,048,575) = 23,401.64, p < 0.001), with a small‐to‐medium effect size, Cramer's V  = 0.15( df ∗ = 1).

Learning media used by students in online learning

Learning approaches

School years is also significantly associated with the different learning approaches students used to tackle difficult concepts during online learning, χ 2 (55, N  = 2,383,751) = 58,030.74, p < 0.001. The strength of this association is weak to moderate as shown by the Cramer's V (0.07, df ∗ = 5; Cohen,  1988 ). When encountering problems related to difficult concepts, students typically chose to “solve independently by searching online” or “rewatch recorded lectures” instead of consulting to their teachers or peers (Figure  3 ). This is probably because, compared to classroom‐based education, it is relatively less convenient and more challenging for students to seek help from others when performing online learning. Besides, compared to high‐school‐year students, early‐school‐year students (Year 1–6), reported much less use of “solve independently by searching online” ( χ 2 (3, N  = 1,048,575) = 48,100.15, p <.001), with a small‐to‐medium effect size, Cramer's V  = 0.21 ( df ∗ = 1). Also, among those approaches of seeking help from others, significantly more high‐school‐year students preferred “communicating with other students” than early‐school‐year students ( χ 2 (3, N  = 1,048,575) = 81,723.37, p < 0.001), with a medium effect size, Cramer's V  = 0.28 ( df ∗ = 1).

Learning approaches used by students in online learning

Perceived benefits and obstacles—RQ2

Perceived benefits.

The association between school years and perceived benefits in online learning is statistically significant, χ 2 (66, N  = 2,716,127) = 29,534.23, p  < 0.001, and the Cramer's V (0.04, df ∗ = 6) indicates a small effect (Cohen,  1988 ). Unsurprisingly, benefits brought by the convenience of online learning are widely recognised by students across all school years (Figure  4 ), that is up to 75% of students reported that it is “more convenient to review course content” and 54% said that they “can learn anytime and anywhere” . Besides, we noticed that about 50% of early‐school‐year students appreciated the “access to courses delivered by famous teachers” and 40%–47% of high‐school‐year students indicated that online learning is “helpful to develop self‐regulation and autonomy” .

Perceived benefits of online learning reported by students

Perceived obstacles

The Chi‐square test shows a significant association between school years and students’ perceived obstacles in online learning, χ 2 (77, N  = 2,699,003) = 31,987.56, p < 0.001. This association is relatively weak as shown by the Cramer's V (0.04, df ∗ = 7; Cohen,  1988 ). As shown in Figure  5 , the biggest obstacles encountered by up to 73% of students were the “eyestrain caused by long staring at screens” . Disengagement caused by nearby disturbance was reported by around 40% of students, especially those of Year 1–3 and 10–12. Technological‐wise, about 50% of students experienced poor Internet connection during their learning process, and around 20% of students reported the “confusion in setting up the platforms” across of school years.

Perceived obstacles of online learning reported by students

Expectations for future practices of online learning – RQ3

Online learning activities.

The association between school years and students’ expected online learning activities is significant, χ 2 (66, N  = 2,416,093) = 38,784.81, p < 0.001. The Cramer's V is 0.05 ( df ∗ = 6) which suggests a small effect (Cohen,  1988 ). As shown in Figure  6 , the most expected activity for future online learning is “real‐time interaction with teachers” (55%), followed by “online group discussion and collaboration” (38%). We also observed that more early‐school‐year students expect reflective activities, such as “regular online practice examinations” ( χ 2 (3, N  = 1,048,575) = 11,644.98, p < 0.001), with a small effect size, Cramer's V  = 0.11 ( df ∗ = 1). In contrast, more high‐school‐year students expect “intelligent recommendation system …” ( χ 2 (3, N  = 1,048,575) = 15,327.00, p < 0.001), with a small effect size, Cramer's V  = 0.12 ( df ∗ = 1).

Students’ expected online learning activities

Regarding students’ learning conditions, substantial differences were observed in learning media, family dependency, and learning approaches adopted in online learning between students in different school years. The finding of more computer and smartphone usage in high‐school‐year than early‐school‐year students can probably be explained by that, with the growing abilities in utilising these media as well as the educational systems and tools which run on these media, high‐school‐year students tend to make better use of these media for online learning practices. Whereas, the differences in paper‐based materials may imply that high‐school‐year students in China have to accomplish a substantial amount of exercise, assignments, and exam papers to prepare for the National College Entrance Examination (NCEE), whose delivery was not entirely digitised due to the sudden transition to online learning. Meanwhile, high‐school‐year students may also have preferred using paper‐based materials for exam practice, as eventually, they would take their NCEE in the paper format. Therefore, these substantial differences in students’ usage of learning media should be addressed by customising the delivery method of online learning for different school years.

Other than these between‐age differences in learning media, the prevalence of smartphone in online learning resonates with Agung et al.’s ( 2020 ) finding on the issues surrounding the availability of compatible learning device. The prevalence of smartphone in K‐12 students is potentially problematic as the majority of the online learning platform and content is designed for computer‐based learning (Berge,  2005 ; Molnar et al.,  2019 ). Whereas learning with smartphones has its own unique challenges. For example, Gikas and Grant ( 2013 ) discovered that students who learn with smartphone experienced frustration with the small screen‐size, especially when trying to type with the tiny keypad. Another challenge relates to the distraction of various social media applications. Although similar distractions exist in computer and web‐based social media, the level of popularity, especially in the young generation, are much higher in mobile‐based social media (Montag et al.,  2018 ). In particular, the message notification function in smartphones could disengage students from learning activities and allure them to social media applications (Gikas & Grant,  2013 ). Given these challenges of learning with smartphones, more research efforts should be devoted to analysing students’ online learning behaviour in the setting of mobile learning to accommodate their needs better.

The differences in learning approaches, once again, illustrated that early‐school‐year students have different needs compared to high‐school‐year students. In particular, the low usage of the independent learning methods in early‐school‐year students may reflect their inability to engage in independent learning. Besides, the differences in help seeking behaviours demonstrated the distinctive needs for communication and interaction between different students, that is early‐school‐year students have a strong reliance on teachers and high‐school‐year students, who are equipped with stronger communication ability, are more inclined to interact with their peers. This finding implies that the design of online learning platforms should take students’ different needs into account. Thus, customisation is urgently needed for the delivery of online learning to different school years.

In terms of the perceived benefits and challenges of online learning, our results resonate with several previous findings. In particular, the benefits of convenience are in line with the flexibility advantages of online learning, which were mentioned in prior works (Appana,  2008 ; Bączek et al.,  2021 ; Barbour,  2013 ; Basuony et al.,  2020 ; Harvey et al.,  2014 ). Early‐school‐year students’ higher appreciation in having “access to courses delivered by famous teachers” and lower appreciation in the independent learning skills developed through online learning are also in line with previous literature (Barbour,  2013 ; Harvey et al.,  2014 ; Oliver et al.,  2009 ). Again, these similar findings may indicate the strong reliance that early‐school‐year students place on teachers, while high‐school‐year students are more capable of adapting to online learning by developing independent learning skills.

Technology‐wise, students’ experience of poor internet connection and confusion in setting up online learning platforms are particularly concerning. The problem of poor internet connection corroborated the findings reported in prior studies (Agung et al.,  2020 ; Barbour,  2013 ; Basuony et al.,  2020 ; Berge,  2005 ; Rice,  2006 ), that is the access issue surrounded the digital divide as one of the main challenges of online learning. In the era of 4G and 5G networks, educational authorities and institutions that deliver online education could fall into the misconception of most students have a stable internet connection at home. The internet issue we observed is particularly vital to students’ online learning experience as most students prefer real‐time communications (Figure  6 ), which rely heavily on stable internet connection. Likewise, the finding of students’ confusion in technology is also consistent with prior studies (Bączek et al.,  2021 ; Muilenburg & Berge,  2005 ; Niemi & Kousa,  2020 ; Song et al.,  2004 ). Students who were unsuccessfully in setting up the online learning platforms could potentially experience declines in confidence and enthusiasm for online learning, which would cause a subsequent unpleasant learning experience. Therefore, both the readiness of internet infrastructure and student technical skills remain as the significant challenges for the mass‐adoption of online learning.

On the other hand, students’ experience of eyestrain from extended screen time provided empirical evidence to support Spitzer’s ( 2001 ) speculation about the potential ergonomic impact of online learning. This negative effect is potentially related to the prevalence of smartphone device and the limited screen size of these devices. This finding not only demonstrates the potential ergonomic issues that would be caused by smartphone‐based online learning but also resonates with the aforementioned necessity of different platforms and content designs for different students.

A less‐mentioned problem in previous studies on online learning experiences is the disengagement caused by nearby disturbance, especially in Year 1–3 and 10–12. It is likely that early‐school‐year students suffered from this problem because of their underdeveloped metacognitive skills to concentrate on online learning without teachers’ guidance. As for high‐school‐year students, the reasons behind their disengagement require further investigation in the future. Especially it would be worthwhile to scrutinise whether this type of disengagement is caused by the substantial amount of coursework they have to undertake and the subsequent a higher level of pressure and a lower level of concentration while learning.

Across age‐level differences are also apparent in terms of students’ expectations of online learning. Although, our results demonstrated students’ needs of gaining social interaction with others during online learning, findings (Bączek et al.,  2021 ; Harvey et al.,  2014 ; Kuo et al.,  2014 ; Liu & Cavanaugh,  2012 ; Yates et al.,  2020 ). This need manifested differently across school years, with early‐school‐year students preferring more teacher interactions and learning regulation support. Once again, this finding may imply that early‐school‐year students are inadequate in engaging with online learning without proper guidance from their teachers. Whereas, high‐school‐year students prefer more peer interactions and recommendation to learning resources. This expectation can probably be explained by the large amount of coursework exposed to them. Thus, high‐school‐year students need further guidance to help them better direct their learning efforts. These differences in students’ expectations for future practices could guide the customisation of online learning delivery.

Implications

As shown in our results, improving the delivery of online learning not only requires the efforts of policymakers but also depend on the actions of teachers and parents. The following sub‐sections will provide recommendations for relevant stakeholders and discuss their essential roles in supporting online education.

Technical support

The majority of the students has experienced technical problems during online learning, including the internet lagging and confusion in setting up the learning platforms. These problems with technology could impair students’ learning experience (Kauffman,  2015 ; Muilenburg & Berge,  2005 ). Educational authorities and schools should always provide a thorough guide and assistance for students who are experiencing technical problems with online learning platforms or other related tools. Early screening and detection could also assist schools and teachers to direct their efforts more effectively in helping students with low technology skills (Wilkinson et al.,  2010 ). A potential identification method involves distributing age‐specific surveys that assess students’ Information and Communication Technology (ICT) skills at the beginning of online learning. For example, there are empirical validated ICT surveys available for both primary (Aesaert et al.,  2014 ) and high school (Claro et al.,  2012 ) students.

For students who had problems with internet lagging, the delivery of online learning should provide options that require fewer data and bandwidth. Lecture recording is the existing option but fails to address students’ need for real‐time interaction (Clark et al.,  2015 ; Malik & Fatima,  2017 ). A potential alternative involves providing students with the option to learn with digital or physical textbooks and audio‐conferencing, instead of screen sharing and video‐conferencing. This approach significantly reduces the amount of data usage and lowers the requirement of bandwidth for students to engage in smooth online interactions (Cisco,  2018 ). It also requires little additional efforts from teachers as official textbooks are often available for each school year, and thus, they only need to guide students through the materials during audio‐conferencing. Educational authority can further support this approach by making digital textbooks available for teachers and students, especially those in financial hardship. However, the lack of visual and instructor presence could potentially reduce students’ attention, recall of information, and satisfaction in online learning (Wang & Antonenko,  2017 ). Therefore, further research is required to understand whether the combination of digital or physical textbooks and audio‐conferencing is appropriate for students with internet problems. Alternatively, suppose the local technological infrastructure is well developed. In that case, governments and schools can also collaborate with internet providers to issue data and bandwidth vouchers for students who are experiencing internet problems due to financial hardship.

For future adoption of online learning, policymakers should consider the readiness of the local internet infrastructure. This recommendation is particularly important for developing countries, like Bangladesh, where the majority of the students reported the lack of internet infrastructure (Ramij & Sultana,  2020 ). In such environments, online education may become infeasible, and alternative delivery method could be more appropriate, for example, the Telesecundaria program provides TV education for rural areas of Mexico (Calderoni,  1998 ).

Other than technical problems, choosing a suitable online learning platform is also vital for providing students with a better learning experience. Governments and schools should choose an online learning platform that is customised for smartphone‐based learning, as the majority of students could be using smartphones for online learning. This recommendation is highly relevant for situations where students are forced or involuntarily engaged in online learning, like during the COVID‐19 pandemic, as they might not have access to a personal computer (Molnar et al.,  2019 ).

Customisation of delivery methods

Customising the delivery of online learning for students in different school years is the theme that appeared consistently across our findings. This customisation process is vital for making online learning an opportunity for students to develop independent learning skills, which could help prepare them for tertiary education and lifelong learning. However, the pedagogical design of K‐12 online learning programs should be differentiated from adult‐orientated programs as these programs are designed for independent learners, which is rarely the case for students in K‐12 education (Barbour & Reeves,  2009 ).

For early‐school‐year students, especially Year 1–3 students, providing them with sufficient guidance from both teachers and parents should be the priority as these students often lack the ability to monitor and reflect on learning progress. In particular, these students would prefer more real‐time interaction with teachers, tutoring from parents, and regular online practice examinations. These forms of guidance could help early‐school‐year students to cope with involuntary online learning, and potentially enhance their experience in future online learning. It should be noted that, early‐school‐year students demonstrated interest in intelligent monitoring and feedback systems for learning. Additional research is required to understand whether these young children are capable of understanding and using learning analytics that relay information on their learning progress. Similarly, future research should also investigate whether young children can communicate effectively through digital tools as potential inability could hinder student learning in online group activities. Therefore, the design of online learning for early‐school‐year students should focus less on independent learning but ensuring that students are learning effective under the guidance of teachers and parents.

In contrast, group learning and peer interaction are essential for older children and adolescents. The delivery of online learning for these students should focus on providing them with more opportunities to communicate with each other and engage in collaborative learning. Potential methods to achieve this goal involve assigning or encouraging students to form study groups (Lee et al.,  2011 ), directing students to use social media for peer communication (Dabbagh & Kitsantas,  2012 ), and providing students with online group assignments (Bickle & Rucker,  2018 ).

Special attention should be paid to students enrolled in high schools. For high‐school‐year students, in particular, students in Year 10–12, we also recommend to provide them with sufficient access to paper‐based learning materials, such as revision booklet and practice exam papers, so they remain familiar with paper‐based examinations. This recommendation applies to any students who engage in online learning but has to take their final examination in paper format. It is also imperative to assist high‐school‐year students who are facing examinations to direct their learning efforts better. Teachers can fulfil this need by sharing useful learning resources on the learning management system, if it is available, or through social media groups. Alternatively, students are interested in intelligent recommendation systems for learning resources, which are emerging in the literature (Corbi & Solans,  2014 ; Shishehchi et al.,  2010 ). These systems could provide personalised recommendations based on a series of evaluation on learners’ knowledge. Although it is infeasible for situations where the transformation to online learning happened rapidly (i.e., during the COVID‐19 pandemic), policymakers can consider embedding such systems in future online education.

Limitations

The current findings are limited to primary and secondary Chinese students who were involuntarily engaged in online learning during the COVID‐19 pandemic. Despite the large sample size, the population may not be representative as participants are all from a single province. Also, information about the quality of online learning platforms, teaching contents, and pedagogy approaches were missing because of the large scale of our study. It is likely that the infrastructures of online learning in China, such as learning platforms, instructional designs, and teachers’ knowledge about online pedagogy, were underprepared for the sudden transition. Thus, our findings may not represent the experience of students who voluntarily participated in well‐prepared online learning programs, in particular, the virtual school programs in America and Canada (Barbour & LaBonte,  2017 ; Molnar et al.,  2019 ). Lastly, the survey was only evaluated and validated by teachers but not students. Therefore, students with the lowest reading comprehension levels might have a different understanding of the items’ meaning, especially terminologies that involve abstract contracts like self‐regulation and autonomy in item Q17.

In conclusion, we identified across‐year differences between primary and secondary school students’ online learning experience during the COVID‐19 pandemic. Several recommendations were made for the future practice and research of online learning in the K‐12 student population. First, educational authorities and schools should provide sufficient technical support to help students to overcome potential internet and technical problems, as well as choosing online learning platforms that have been customised for smartphones. Second, customising the online pedagogy design for students in different school years, in particular, focusing on providing sufficient guidance for young children, more online collaborative opportunity for older children and adolescent, and additional learning resource for senior students who are facing final examinations.

CONFLICT OF INTEREST

There is no potential conflict of interest in this study.

ETHICS STATEMENT

The data are collected by the Department of Education of the Guangdong Province who also has the authority to approve research studies in K12 education in the province.

Supporting information

Supplementary Material

ACKNOWLEDGEMENTS

This work is supported by the National Natural Science Foundation of China (62077028, 61877029), the Science and Technology Planning Project of Guangdong (2020B0909030005, 2020B1212030003, 2020ZDZX3013, 2019B1515120010, 2018KTSCX016, 2019A050510024), the Science and Technology Planning Project of Guangzhou (201902010041), and the Fundamental Research Funds for the Central Universities (21617408, 21619404).

SURVEY ITEMS

Yan, L , Whitelock‐Wainwright, A , Guan, Q , Wen, G , Gašević, D , & Chen, G . Students’ experience of online learning during the COVID‐19 pandemic: A province‐wide survey study . Br J Educ Technol . 2021; 52 :2038–2057. 10.1111/bjet.13102 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

DATA AVAILABILITY STATEMENT

• Aesaert, K. , Van Nijlen, D. , Vanderlinde, R. , & van Braak, J. (2014). Direct measures of digital information processing and communication skills in primary education: Using item response theory for the development and validation of an ICT competence scale . Computers & Education , 76 , 168–181. 10.1016/j.compedu.2014.03.013 [ CrossRef ] [ Google Scholar ]
• Agung, A. S. N. , Surtikanti, M. W. , & Quinones, C. A. (2020). Students’ perception of online learning during COVID‐19 pandemic: A case study on the English students of STKIP Pamane Talino . SOSHUM: Jurnal Sosial Dan Humaniora , 10 ( 2 ), 225–235. 10.31940/soshum.v10i2.1316 [ CrossRef ] [ Google Scholar ]
• Anderson, T. (2003). Getting the mix right again: An updated and theoretical rationale for interaction . The International Review of Research in Open and Distributed Learning , 4 ( 2 ). 10.19173/irrodl.v4i2.149 [ CrossRef ] [ Google Scholar ]
• Appana, S. (2008). A review of benefits and limitations of online learning in the context of the student, the instructor and the tenured faculty . International Journal on E‐learning , 7 ( 1 ), 5–22. [ Google Scholar ]
• Bączek, M. , Zagańczyk‐Bączek, M. , Szpringer, M. , Jaroszyński, A. , & Wożakowska‐Kapłon, B. (2021). Students’ perception of online learning during the COVID‐19 pandemic: A survey study of Polish medical students . Medicine , 100 ( 7 ), e24821. 10.1097/MD.0000000000024821 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Barbour, M. K. (2013). The landscape of k‐12 online learning: Examining what is known . Handbook of Distance Education , 3 , 574–593. [ Google Scholar ]
• Barbour, M. , Huerta, L. , & Miron, G. (2018). Virtual schools in the US: Case studies of policy, performance and research evidence. In Society for information technology & teacher education international conference (pp. 672–677). Association for the Advancement of Computing in Education (AACE). [ Google Scholar ]
• Barbour, M. K. , & LaBonte, R. (2017). State of the nation: K‐12 e‐learning in Canada, 2017 edition . http://k12sotn.ca/wp‐content/uploads/2018/02/StateNation17.pdf [ Google Scholar ]
• Barbour, M. K. , & Reeves, T. C. (2009). The reality of virtual schools: A review of the literature . Computers & Education , 52 ( 2 ), 402–416. [ Google Scholar ]
• Basuony, M. A. K. , EmadEldeen, R. , Farghaly, M. , El‐Bassiouny, N. , & Mohamed, E. K. A. (2020). The factors affecting student satisfaction with online education during the COVID‐19 pandemic: An empirical study of an emerging Muslim country . Journal of Islamic Marketing . 10.1108/JIMA-09-2020-0301 [ CrossRef ] [ Google Scholar ]
• Berge, Z. L. (2005). Virtual schools: Planning for success . Teachers College Press, Columbia University. [ Google Scholar ]
• Bickle, M. C. , & Rucker, R. (2018). Student‐to‐student interaction: Humanizing the online classroom using technology and group assignments . Quarterly Review of Distance Education , 19 ( 1 ), 1–56. [ Google Scholar ]
• Broadbent, J. , & Poon, W. L. (2015). Self‐regulated learning strategies & academic achievement in online higher education learning environments: A systematic review . The Internet and Higher Education , 27 , 1–13. [ Google Scholar ]
• Calderoni, J. (1998). Telesecundaria: Using TV to bring education to rural Mexico (Tech. Rep.). The World Bank. [ Google Scholar ]
• Cisco . (2018). Bandwidth requirements for meetings with cisco Webex and collaboration meeting rooms white paper . http://dwz.date/dpbc [ Google Scholar ]
• Cisco . (2019). Cisco digital readiness 2019 . https://www.cisco.com/c/m/en_us/about/corporate‐social‐responsibility/research‐resources/digital‐readiness‐index.html#/ (Library Catalog: www.cisco.com). [ Google Scholar ]
• Clark, C. , Strudler, N. , & Grove, K. (2015). Comparing asynchronous and synchronous video vs. text based discussions in an online teacher education course . Online Learning , 19 ( 3 ), 48–69. [ Google Scholar ]
• Claro, M. , Preiss, D. D. , San Martín, E. , Jara, I. , Hinostroza, J. E. , Valenzuela, S. , Cortes, F. , & Nussbaum, M. (2012). Assessment of 21st century ICT skills in Chile: Test design and results from high school level students . Computers & Education , 59 ( 3 ), 1042–1053. 10.1016/j.compedu.2012.04.004 [ CrossRef ] [ Google Scholar ]
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences . Routledge Academic. [ Google Scholar ]
• Corbi, A. , & Solans, D. B. (2014). Review of current student‐monitoring techniques used in elearning‐focused recommender systems and learning analytics: The experience API & LIME model case study . IJIMAI , 2 ( 7 ), 44–52. [ Google Scholar ]
• Dabbagh, N. , & Kitsantas, A. (2012). Personal learning environments, social media, and self‐regulated learning: A natural formula for connecting formal and informal learning . The Internet and Higher Education , 15 ( 1 ), 3–8. 10.1016/j.iheduc.2011.06.002 [ CrossRef ] [ Google Scholar ]
• Garrison, D. R. , Cleveland‐Innes, M. , & Fung, T. S. (2010). Exploring causal relationships among teaching, cognitive and social presence: Student perceptions of the community of inquiry framework . The Internet and Higher Education , 13 ( 1–2 ), 31–36. 10.1016/j.iheduc.2009.10.002 [ CrossRef ] [ Google Scholar ]
• Gašević, D. , Adesope, O. , Joksimović, S. , & Kovanović, V. (2015). Externally‐facilitated regulation scaffolding and role assignment to develop cognitive presence in asynchronous online discussions . The Internet and Higher Education , 24 , 53–65. 10.1016/j.iheduc.2014.09.006 [ CrossRef ] [ Google Scholar ]
• Gašević, D. , Zouaq, A. , & Janzen, R. (2013). “Choose your classmates, your GPA is at stake!” The association of cross‐class social ties and academic performance . American Behavioral Scientist , 57 ( 10 ), 1460–1479. [ Google Scholar ]
• Gikas, J. , & Grant, M. M. (2013). Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media . The Internet and Higher Education , 19 , 18–26. [ Google Scholar ]
• Harvey, D. , Greer, D. , Basham, J. , & Hu, B. (2014). From the student perspective: Experiences of middle and high school students in online learning . American Journal of Distance Education , 28 ( 1 ), 14–26. 10.1080/08923647.2014.868739 [ CrossRef ] [ Google Scholar ]
• Kauffman, H. (2015). A review of predictive factors of student success in and satisfaction with online learning . Research in Learning Technology , 23 . 10.3402/rlt.v23.26507 [ CrossRef ] [ Google Scholar ]
• Kuo, Y.‐C. , Walker, A. E. , Belland, B. R. , Schroder, K. E. , & Kuo, Y.‐T. (2014). A case study of integrating interwise: Interaction, internet self‐efficacy, and satisfaction in synchronous online learning environments . International Review of Research in Open and Distributed Learning , 15 ( 1 ), 161–181. 10.19173/irrodl.v15i1.1664 [ CrossRef ] [ Google Scholar ]
• Lee, S. J. , Srinivasan, S. , Trail, T. , Lewis, D. , & Lopez, S. (2011). Examining the relationship among student perception of support, course satisfaction, and learning outcomes in online learning . The Internet and Higher Education , 14 ( 3 ), 158–163. 10.1016/j.iheduc.2011.04.001 [ CrossRef ] [ Google Scholar ]
• Liu, F. , & Cavanaugh, C. (2012). Factors influencing student academic performance in online high school algebra . Open Learning: The Journal of Open, Distance and e‐Learning , 27 ( 2 ), 149–167. 10.1080/02680513.2012.678613 [ CrossRef ] [ Google Scholar ]
• Lou, Y. , Bernard, R. M. , & Abrami, P. C. (2006). Media and pedagogy in undergraduate distance education: A theory‐based meta‐analysis of empirical literature . Educational Technology Research and Development , 54 ( 2 ), 141–176. 10.1007/s11423-006-8252-x [ CrossRef ] [ Google Scholar ]
• Malik, M. , & Fatima, G. (2017). E‐learning: Students’ perspectives about asynchronous and synchronous resources at higher education level . Bulletin of Education and Research , 39 ( 2 ), 183–195. [ Google Scholar ]
• McInnerney, J. M. , & Roberts, T. S. (2004). Online learning: Social interaction and the creation of a sense of community . Journal of Educational Technology & Society , 7 ( 3 ), 73–81. [ Google Scholar ]
• Molnar, A. , Miron, G. , Elgeberi, N. , Barbour, M. K. , Huerta, L. , Shafer, S. R. , & Rice, J. K. (2019). Virtual schools in the US 2019 . National Education Policy Center. [ Google Scholar ]
• Montague, M. , & Rinaldi, C. (2001). Classroom dynamics and children at risk: A followup . Learning Disability Quarterly , 24 ( 2 ), 75–83. [ Google Scholar ]
• Montag, C. , Becker, B. , & Gan, C. (2018). The multipurpose application Wechat: A review on recent research . Frontiers in Psychology , 9 , 2247. 10.3389/fpsyg.2018.02247 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Moore, M. G. (1989). Editorial: Three types of interaction . American Journal of Distance Education , 3 ( 2 ), 1–7. 10.1080/08923648909526659 [ CrossRef ] [ Google Scholar ]
• Muilenburg, L. Y. , & Berge, Z. L. (2005). Student barriers to online learning: A factor analytic study . Distance Education , 26 ( 1 ), 29–48. 10.1080/01587910500081269 [ CrossRef ] [ Google Scholar ]
• Muirhead, B. , & Juwah, C. (2004). Interactivity in computer‐mediated college and university education: A recent review of the literature . Journal of Educational Technology & Society , 7 ( 1 ), 12–20. [ Google Scholar ]
• Niemi, H. M. , & Kousa, P. (2020). A case study of students’ and teachers’ perceptions in a finnish high school during the COVID pandemic . International Journal of Technology in Education and Science , 4 ( 4 ), 352–369. 10.46328/ijtes.v4i4.167 [ CrossRef ] [ Google Scholar ]
• Oliver, K. , Osborne, J. , & Brady, K. (2009). What are secondary students’ expectations for teachers in virtual school environments? Distance Education , 30 ( 1 ), 23–45. 10.1080/01587910902845923 [ CrossRef ] [ Google Scholar ]
• Pardo, A. , Jovanovic, J. , Dawson, S. , Gašević, D. , & Mirriahi, N. (2019). Using learning analytics to scale the provision of personalised feedback . British Journal of Educational Technology , 50 ( 1 ), 128–138. 10.1111/bjet.12592 [ CrossRef ] [ Google Scholar ]
• Ramij, M. , & Sultana, A. (2020). Preparedness of online classes in developing countries amid covid‐19 outbreak: A perspective from Bangladesh. Afrin, Preparedness of Online Classes in Developing Countries amid COVID‐19 Outbreak: A Perspective from Bangladesh (June 29, 2020) .
• Rice, K. L. (2006). A comprehensive look at distance education in the k–12 context . Journal of Research on Technology in Education , 38 ( 4 ), 425–448. 10.1080/15391523.2006.10782468 [ CrossRef ] [ Google Scholar ]
• Shishehchi, S. , Banihashem, S. Y. , & Zin, N. A. M. (2010). A proposed semantic recommendation system for elearning: A rule and ontology based e‐learning recommendation system. In 2010 international symposium on information technology (Vol. 1, pp. 1–5).
• Song, L. , Singleton, E. S. , Hill, J. R. , & Koh, M. H. (2004). Improving online learning: Student perceptions of useful and challenging characteristics . The Internet and Higher Education , 7 ( 1 ), 59–70. 10.1016/j.iheduc.2003.11.003 [ CrossRef ] [ Google Scholar ]
• Spitzer, D. R. (2001). Don’t forget the high‐touch with the high‐tech in distance learning . Educational Technology , 41 ( 2 ), 51–55. [ Google Scholar ]
• Thomas, R. M. (2000). Comparing theories of child development. Wadsworth/Thomson Learning. United Nations Educational, Scientific and Cultural Organization. (2020, March). Education: From disruption to recovery . https://en.unesco.org/covid19/educationresponse (Library Catalog: en.unesco.org)
• Uttal, D. H. , & Cohen, C. A. (2012). Spatial thinking and stem education: When, why, and how? In Psychology of learning and motivation (Vol. 57 , pp. 147–181). Elsevier. [ Google Scholar ]
• Van Lancker, W. , & Parolin, Z. (2020). Covid‐19, school closures, and child poverty: A social crisis in the making . The Lancet Public Health , 5 ( 5 ), e243–e244. 10.1016/S2468-2667(20)30084-0 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wang, C.‐H. , Shannon, D. M. , & Ross, M. E. (2013). Students’ characteristics, self‐regulated learning, technology self‐efficacy, and course outcomes in online learning . Distance Education , 34 ( 3 ), 302–323. 10.1080/01587919.2013.835779 [ CrossRef ] [ Google Scholar ]
• Wang, J. , & Antonenko, P. D. (2017). Instructor presence in instructional video: Effects on visual attention, recall, and perceived learning . Computers in Human Behavior , 71 , 79–89. 10.1016/j.chb.2017.01.049 [ CrossRef ] [ Google Scholar ]
• Wilkinson, A. , Roberts, J. , & While, A. E. (2010). Construction of an instrument to measure student information and communication technology skills, experience and attitudes to e‐learning . Computers in Human Behavior , 26 ( 6 ), 1369–1376. 10.1016/j.chb.2010.04.010 [ CrossRef ] [ Google Scholar ]
• World Health Organization . (2020, July). Coronavirus disease 2019 (COVID‐19): Situation Report‐164 (Situation Report No. 164). https://www.who.int/docs/default‐source/coronaviruse/situation‐reports/20200702‐covid‐19‐sitrep‐164.pdf?sfvrsn$=$ac074f58$_$2
• Yates, A. , Starkey, L. , Egerton, B. , & Flueggen, F. (2020). High school students’ experience of online learning during Covid‐19: The influence of technology and pedagogy . Technology, Pedagogy and Education , 9 , 1–15. 10.1080/1475939X.2020.1854337 [ CrossRef ] [ Google Scholar ]

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How to Write Stanford’s “Excited About Learning” Essay

This article was written based on the information and opinions presented by Johnathan Patin-Sauls and Vinay Bhaskara in a CollegeVine livestream. You can watch the full livestream for more info.

What’s Covered:

Choosing an idea vs. an experience, learning for the sake of learning, learning as a means to other ends, be specific.

Stanford University’s first essay prompt asks you to respond to the following:

“ The Stanford community is deeply curious and driven to learn in and out of the classroom. Reflect on an idea or experience that makes you genuinely excited about learning. (100-250 words)”

For this short answer question, your response is limited to a maximum of 250 words. In this article, we will discuss considerations for choosing to write about an idea or experience, ways to demonstrate a love or enthusiasm for learning, and why you should be as specific. For more information and guidance on writing the application essays for Stanford University, check out our post on how to write the Stanford University essays .

Regardless of if you choose either an idea or experience that makes you genuinely excited about learning as a topic, there are a few considerations for each.  

Most people gravitate towards writing about an idea. One challenge that arises with an idea-focused essay is that applicants who are passionate about an idea often become hyper focused on explaining the idea but neglect to connect this idea to who they are as a person and why this idea excites them. 

When writing about an experience, it is important to strike a balance between describing the experience and analyzing the impact of the experience on you, your goals, and your commitment to learning.

This essay question allows you to expand on your joy for learning and your genuine curiosity. Stanford is searching for students who are naturally curious and enjoy the process of learning and educating themselves. For example, a compelling essay could begin with a riveting story of getting lost while hiking the Appalachian Trail and describing how this experience led to a lifelong passion for studying primitive forms of navigation. 

There is a strong tendency among applicants to write about formal academic coursework, however, the most compelling essays will subvert expectations by taking the concept of learning beyond the classroom and demonstrating how learning manifests itself in unique contexts in your life.

If you’re someone for whom learning is a means to other ends, it is important that you convey a sense of genuine enthusiasm and purpose beyond, “I want to go to X school because it will help me get Y job for Z purpose.” You may be motivated to attend college to obtain a certain position and make a comfortable income, however these answers are not necessarily what admissions officers are looking for. Instead, it can be helpful to relate an idea or experience to something more personal to you.

Academic & Professional Trajectory

Consider relating the idea or experience you choose to a major, degree program, research initiative, or professor that interests you at Stanford. Then go beyond the academic context to explain how the idea or experience ties into your future career. 

For instance, if you are interested in the concept of universal health care, then you might describe your interest in applying to public health programs with faculty that specialize in national health care systems. You might then describe your long term career aspirations to work in the United States Senate on crafting and passing health care policy.

Personal Values & Experiences

Another way to tie the ideas in this essay back to a more personal topic is to discuss how the idea or experience informs who you are, how you treat others, or how you experience the world around you. 

You could also focus on an idea or experience that has challenged, frustrated, or even offended you, thereby reinforcing and further justifying the values you hold and your worldview.

Community Building & Social Connectedness

You may also explore how this idea or experience connects you to a particular community by helping you understand, build, and support members of the community. Stanford is looking to find students who will be engaged members of the student body and carry out the community’s core mission, values, and projects, so this essay can be an opportunity to highlight how you would contribute to Stanford. 

Be specific in your choice of idea or the way in which you describe an experience. For example, a response that focuses on the joys of learning philosophy is too broad to be particularly memorable or impactful. However, the mind-body problem looking at the debate concerning the relationship between thought and consciousness is a specific philosophical idea that lends itself to a rich discussion. 

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Lessons About Online Learning

By  Yoram Neumann and Edith Neumann

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In its infancy, online learning was viewed as a more accessible alternative for students unable to commit to the traditional higher education path. But in recent years online education has been gaining more acceptance. The most recent U.S. Department of Education data from fall 2014 indicate that 5.8 million students took at least one online course, with 2.85 million of them studying exclusively online. After thousands of online launches and millions of students, it is important to assess the advancement made in online learning as we look to further enhance online learning for future students.

Thirty years ago, we committed ourselves to a long-term program of research into higher education and how to improve it. Together, we have conducted several studies on student learning at colleges and universities.

Several factors emerged as determinants of students’ academic performance and related outcomes, such as retention, graduation, satisfaction and commitment toward their college or university. The four major predictors of student learning outcomes were:

• student engagement and involvement in a variety of activities aimed at different cognitive domains of learning;
• student-faculty contact, including faculty members’ helpfulness and accessibility -- as manifested through the immediacy of feedback and a concern for students and their problems;
• factors related to degree programs, including the integration and relevance of the various required and elective courses, as well as the quality of teaching focused on student learning and of academic advising; and
• learning opportunities beyond traditional courses, including opportunities to engage in self-directed learning and address critical issues in the course.

In addition to our interest in advancing policy-based knowledge in higher education, we have held leadership positions at several colleges and universities and have been involved in pioneering distance and online learning programs. In 1996, we developed a vision for a new online university in which all functions (academic, support, services and administrative) were directly linked to the development of a comprehensive online learning environment. We named it the Robust Learning Model , and all components of the model were designed to:

• enable systematic applications to all degree programs;
• be relevant for many groups of learners -- including adult and mobile learners;
• have a mechanism for accountability, transparency and quality assurance;
• use resources efficiently aimed at affordable tuition;
• develop a budget and resource-allocation plan based on projected enrollment growth and predefined quality improvements; and
• demonstrate a verifiable attainment of learning outcomes for students for each degree program.

The pedagogy included a completely interactive threaded discussion that allowed students to interact and engage with faculty members as well as each other. For each course, we introduced problem-based learning through case studies and project-based learning through a signature assignment. Self-reflection was included as part of the course as well as through a required essay at the end of the course. And when it came to assessment, the RLM was, to our knowledge, the first attempt to align institutional learning outcomes, program learning outcomes and course learning outcomes.

In 1998, we founded Touro University International, an independent branch campus of Touro College New York, using the RLM approach to online learning. It became a separately accredited institution and an academic and financial success. (Sold in 2007, it was later renamed Trident University International.)

Then, in 2012, we rejoined Touro in a new role of turnaround management for a division that it opened in 2008 named Touro University Worldwide. In the past four years, we have implemented a more advanced version of the RLM, based on our past experience with it and cloud and mobile technology, as well as on new developments in our conceptual map for an online university.

Throughout our two decades of experience, we have continued to improve the comprehensive learner-focused model using continuous assessment, experimentation and tests of new ideas and innovations. What have we learned about the factors in the online learning environment that directly or indirectly affect students’ learning performance?

Lessons Learned

• The major factor that consistently predicts successful performance outcomes is the student’s skill at learning to learn. By this we mean the student’s ability to persist in learning through an awareness of his or her learning needs, to effectively search for information and raise questions, to manage time to focus on learning, and to acquire or use support mechanisms to overcome challenges. Students with a high learning-to-learn ability will successfully prepare in advance how to progress and benefit from their learning experiences as well as persevere in finding the path to learning, despite adverse circumstances. We have continuously improved the learning model and the online learning environment by focusing  pedagogy, faculty-student interactions, student-to-student interactions, self-reflection and the variety of learning strategies and activities to support students in their improvement of this ability.
• Engagement in a variety of learning activities and assignments -- problem identification, problem solving, analytical tools, projects, reflective inquiry, discussions, critical thinking -- enhances learning outcomes when a component of self-assessment is added to each of those activities.
• Engagement in a variety of learning activities and assignments improves learning outcomes when the feedback received from the professor and/or other learners is immediate (less than 24 hours), constructive, substantial and (in case of professor feedback) guides students in how to strengthen their learning efficacy.
• The professor’s direct involvement in all facets of course development and management -- including design, instruction, meaningful and frequent interactions with the learners and assessment -- enhances student learning outcomes across all degree levels and programs. When the learning experience is divided (unbundled) among several segments, student learning outcomes are considerably lower. We have tried unbundling the learning process and have experimented with course developers and designers, teaching assistants, mentors, success coaches and a learning team, and we have always received inferior results compared to when a faculty member is fully involved in all facets of the course.
• Periodic course assessment and improvement based on self-reflection and peers’ and previous students’ comments can boost student learning outcomes. The key is to explicitly examine, for all courses across the institution, what worked well and what did not work previously for the same course.
• An eight-week session maximizes learning outcomes for adult learners (24 or older), compared to a four- or 12-week session. A 12-week session maximized learning outcomes for traditionally college-age students (23 or younger), compared to a four- or eight-week session.
• With all other learning activities and assignments remaining the same, courses without a problem-based learning component have resulted in lower learning outcomes compared with courses that include it.
• Similarly, courses without a project-based component, a threaded discussion or a self-reflective component result in lower learning outcomes compared with courses that include them.
• Students who receive either professors’ or peers’ constructive feedback at least twice a week substantially outperform those who do not.
• Students who perform mid-session self-assessment with the professor’s constructive feedback on that self-assessment outperform students who do not.
• Students who submit their learning assignment ahead of the deadline outperform students who wait until the last minute.
• Students who participate in precourse learning orientation activities (related to time planning, learning tips and a variety of supporting techniques) outperform students who do not.
• Students with high levels of student-faculty or student-to-student interactions in threaded discussions outperform students with lower levels of interactive learning.
• Students who received weekly tips directly from their professors encouraging them to take control of their learning activities outperform students who do not receive such tips. This finding led us to implement this practice as part of the threaded discussion.
• Students who can relate the signature assignment as well as the capstone to their work environment outperform students who cannot.
• Adding academic quality assurance -- staffed by an experienced senior faculty member who works collaboratively with all professors to study the lessons learned and implement the derived improvements into the online learning environment -- enhances student learning outcomes.
• When comparing online students using our model with students taking the same course with the same professor under the traditional classroom model, online students outperform their face-to-face counterparts.
• All the aforementioned factors that enhance learning outcomes also increase student retention rates as well as graduation rates, while reducing the time to degree across all degree levels and degree programs.

Of the various lessons that we have discussed in this piece, some are related to policy issues currently on the agenda of higher education and its future directions, such as MOOCs, competency-based education, the unbundling of the learning process and the like. Our lessons are based on the distinct learning model and web-based learning environment that we envisioned, developed and implemented -- and are important additions to the public discourse. That said, they are not intended to be the ultimate conclusion applied to all online learning environments, nor are they intended to end discussion of these important issues. As educators, it is our responsibility to continue to examine and improve how our students learn through online education.

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Capturing the benefits of remote learning

How education experts are applying lessons learned in the pandemic to promote positive outcomes for all students

Vol. 52 No. 6 Print version: page 46

• Schools and Classrooms
• Technology and Design

With schools open again after more than a year of teaching students outside the classroom, the pandemic sometimes feels like a distant memory. The return to classrooms this fall brings major relief for many families and educators. Factors such as a lack of reliable technology and family support, along with an absence of school resources, resulted in significant academic setbacks, not to mention stress for everyone involved.

But for all the downsides of distance learning, educators, psychologists, and parents have seen some benefits as well. For example, certain populations of students found new ways to be more engaged in learning, without the distractions and difficulties they faced in the classroom, and the general challenges of remote learning and the pandemic brought mental health to the forefront of the classroom experience.

Peter Faustino, PsyD, a school psychologist in Scarsdale, New York, said the pandemic also prompted educators and school psychologists to find creative new ways of ensuring students’ emotional and academic well-being. “So many students were impacted by the pandemic, so we couldn’t just assume they would find resources on their own,” said Faustino. “We had to work hard at figuring out new ways to connect with them.”

Here are some of the benefits of distance learning that school psychologists and educators have observed and the ways in which they’re implementing those lessons post-pandemic, with the goal of creating a more equitable, productive environment for all students.

Prioritizing mental health

Faustino said that during the pandemic, he had more mental health conversations with students, families, and teachers than ever. “Because COVID-19 affected everyone, we’re now having mental health discussions as school leaders on a daily and weekly basis,” he said.

This renewed focus on mental health has the potential to improve students’ well-being in profound ways—starting with helping them recover from the pandemic’s effects. In New York City, for example, schools are hiring more than 600 new clinicians, including psychologists , to screen students’ mental health and help them process pandemic-related trauma and adjust to the “new normal” of attending school in person.

Educators and families are also realizing the importance of protecting students’ mental health more generally—not only for their health and safety but for their learning. “We’ve been seeing a broader appreciation for the fact that mental health is a prerequisite for learning rather than an extracurricular pursuit,” said Eric Rossen, PhD, director of professional development and standards at the National Association of School Psychologists.

As a result, Rossen hopes educators will embed social and emotional learning components into daily instruction. For example, teachers could teach mindfulness techniques in the classroom and take in-the-moment opportunities to help kids resolve conflicts or manage stress.

Improved access to mental health resources in schools is another positive effect. Because of physical distancing guidelines, school leaders had to find ways to deliver mental health services remotely, including via online referrals and teletherapy with school psychologists and counselors.

Early in the pandemic, Faustino said he was hesitant about teletherapy’s effectiveness; now, he hopes to continue offering a virtual option. Online scheduling and remote appointments make it easier for students to access mental health resources, and some students even enjoy virtual appointments more, as they can attend therapy in their own spaces rather than showing up in the counselor’s office. For older students, Faustino said that level of comfort often leads to more productive, open conversations.

Autonomy as a key to motivation

Research suggests that when students have more choices about their materials and activities, they’re more motivated—which may translate to increased learning and academic success. In a 2016 paper, psychology researcher Allan Wigfield, PhD, and colleagues make the case that control and autonomy in reading activities can improve both motivation and comprehension ( Child Development Perspectives , Vol. 10, No. 3 ).

During the period of online teaching, some students had opportunities to learn at their own pace, which educators say improved their learning outcomes—especially in older students. In a 2020 survey of more than 600 parents, researchers found the second-most-valued benefit of distance learning was flexibility—not only in schedule but in method of learning.

In a recent study, researchers found that 18% of parents pointed to greater flexibility in a child’s schedule or way of learning as the biggest benefit or positive outcome related to remote learning ( School Psychology , Roy, A., et al., in press).

This individualized learning helps students find more free time for interests and also allows them to conduct their learning at a time they’re most likely to succeed. During the pandemic, Mark Gardner, an English teacher at Hayes Freedom High School in Camas, Washington, said he realized how important student-centered learning is and that whether learning happens should take precedence over how and when it occurs.

For example, one of his students thrived when he had the choice to do work later at night because he took care of his siblings during the day. Now, Gardner posts homework online on Sundays so students can work at their own pace during the week. “Going forward, we want to create as many access points as we can for kids to engage with learning,” he said.

Rosanna Breaux , PhD, an assistant professor of psychology and assistant director of the Child Study Center at Virginia Tech, agrees. “I’d like to see this flexibility continue in some way, where—similar to college—students can guide their own learning based on their interests or when they’re most productive,” she said.

During the pandemic, many educators were forced to rethink how to keep students engaged. Rossen said because many school districts shared virtual curricula during the period of remote learning, older students could take more challenging or interesting courses than they could in person. The same is true for younger students: Megan Hibbard, a teacher in White Bear Lake, Minnesota, said many of her fifth graders enjoyed distance learning more than in-person because they could work on projects that aligned with their interests.

“So much of motivation is discovering the unique things the student finds interesting,” said Hunter Gehlbach, PhD, a professor and vice dean at the Johns Hopkins School of Education. “The more you can facilitate students spending more time on the things they’re really interested in, the better.”

Going forward, Rossen hopes virtual curricula will allow students greater opportunities to pursue their interests, such as by taking AP classes, foreign languages, or vocational electives not available at their own schools.

Conversely, Hibbard’s goal is to increase opportunities for students to pursue their interests in the in-person setting. For example, she plans to increase what she calls “Genius Hours,” a time at the end of the school day when students can focus on high-interest projects they’ll eventually share with the class.

Better understanding of children's needs

One of the most important predictors of a child’s success in school is parental involvement in their education. For example, in a meta-analysis of studies, researchers linked parental engagement in their middle schoolers’ education with greater measures of success (Hill, N. E., & Tyson, D. F., Developmental Psychology , Vol. 45, No. 3, 2009).

During the pandemic, parents had new opportunities to learn about their kids and, as a result, help them learn. According to a study by Breaux and colleagues, many parents reported that the pandemic allowed them a better understanding of their child’s learning style, needs, or curriculum.

James C. Kaufman , PhD, a professor of educational psychology at the University of Connecticut and the father of an elementary schooler and a high schooler, said he’s had a front-row seat for his sons’ learning for the first time. “Watching my kids learn and engage with classmates has given me some insight in how to parent them,” he said.

Stephen Becker , PhD, a pediatric psychologist at Cincinnati Children’s Hospital Medical Center, said some parents have observed their children’s behavior or learning needs for the first time, which could prompt them to consider assessment and Individualized Education Program (IEP) services. Across the board, Gehlbach said parents are realizing how they can better partner with schools to ensure their kids’ well-being and academic success.

For example, Samantha Marks , PsyD, a Florida-based clinical psychologist, said she realized how much help her middle school daughter, a gifted and talented student with a 504 plan (a plan for how the school will offer support for a student’s disability) for anxiety, needed with independence. “Bringing the learning home made it crystal clear what we needed to teach our daughter to be independent and improve executive functioning” she said. “My takeaway from this is that more parents need to be involved in their children’s education in a healthy, helpful way.”

Marks also gained a deeper understanding of her daughter’s mental health needs. Through her 504 plan, she received help managing her anxiety at school—at home, though, Marks wasn’t always available to help, which taught her the importance of helping her daughter manage her anxiety independently.

Along with parents gaining a deeper understanding of their kids’ needs, the pandemic also prompted greater parent participation in school. For example, Rossen said his kids’ school had virtual school board meetings; he hopes virtual options continue for events like back-to-school information sessions and parenting workshops. “These meetings are often in the evening, and if you’re a single parent or sole caregiver, you may not want to pay a babysitter in order to attend,” he said.

Brittany Greiert, PhD, a school psychologist in Aurora, Colorado, says culturally and linguistically diverse families at her schools benefited from streamlined opportunities to communicate with administrators and teachers. Her district used an app that translates parent communication into 150 languages. Parents can also remotely participate in meetings with school psychologists or teachers, which Greiert says she plans to continue post-pandemic.

Decreased bullying

During stay-at-home orders, kids with neurodevelopmental disorders experienced less bullying than pre-pandemic (McFayden, T. C., et al., Journal of Rural Mental Health , No. 45, Vol. 2, 2021). According to 2019 research, children with emotional, behavioral, and physical health needs experience increased rates of bullying victimization ( Lebrun-Harris, L. A., et al., ), and from the U.S. Department of Education suggests the majority of bullying takes place in person and in unsupervised areas (PDF) .

Scott Graves , PhD, an associate professor of educational studies at The Ohio State University and a member of APA’s Coalition for Psychology in Schools and Education (CPSE), said the supervision by parents and teachers in remote learning likely played a part in reducing bullying. As a result, he’s less worried his Black sons will be victims of microaggressions and racist behavior during online learning.

Some Asian American families also report that remote learning offered protection against racism students may have experienced in person. Shereen Naser, PhD, an associate professor of psychology at Cleveland State University and a member of CPSE, and colleagues found that students are more comfortable saying discriminatory things in school when their teachers are also doing so; Naser suspects this trickle-down effect is less likely to happen when students learn from home ( School Psychology International , 2019).

Reductions in bullying and microaggressions aren’t just beneficial for students’ long-term mental health. Breaux said less bullying at school results in less stress, which can improve students’ self-esteem and mood—both of which impact their ability to learn.

Patricia Perez, PhD, an associate professor of international psychology at The Chicago School of Professional Psychology and a member of CPSE, said it’s important for schools to be proactive in providing spaces for support and cultural expression for students from vulnerable backgrounds, whether in culture-specific clubs, all-school assemblies that address racism and other diversity-related topics, or safe spaces to process feelings with teachers.

According to Rossen, many schools are already considering how to continue supporting students at risk for bullying, including by restructuring the school environment.

One principal, Rossen said, recently switched to single-use bathrooms to avoid congregating in those spaces once in-person learning commences to maintain social distancing requirements. “The principal received feedback from students about how going to the bathroom is much less stressful for these students in part due to less bullying,” he said.

More opportunities for special needs students

In Becker and Breaux’s research, parents of students with attention-deficit/hyperactivity disorder (ADHD), particularly those with a 504 plan and IEP, reported greater difficulties with remote learning. But some students with special learning needs—including those with IEPs and 504 plans—thrived in an at-home learning environment. Recent reporting in The New York Times suggests this is one reason many students want to continue online learning.

According to Cara Laitusis, PhD, a principal research scientist at Educational Testing Service ( ETS ) and a member of CPSE, reduced distractions may improve learning outcomes for some students with disabilities that impact attention in a group setting. “In assessments, small group or individual settings are frequently requested accommodations for some students with ADHD, anxiety, or autism. Being in a quiet place alone without peers for part of the instructional day may also allow for more focus,” she said. However, she also pointed out the benefits of inclusion in the classroom for developing social skills with peers.

Remote learning has improved academic outcomes for students with different learning needs, too. Marks said her seventh-grade daughter, a visual learner, appreciated the increase in video presentations and graphics. Similarly, Hibbard said many of her students who struggle to grasp lessons on the first try have benefited from the ability to watch videos over again until they understand. Post-pandemic, she plans to record bite-size lessons—for example, a 1-minute video of a long division problem—so her students can rewatch and process at their own rate.

Learners with anxiety also appreciate the option not to be in the classroom, because the social pressures of being surrounded by peers can make it hard to focus on academics. “Several of my students have learned more in the last year simply due to the absence of anxiety,” said Rosie Reid, an English teacher at Ygnacio Valley High School in Concord, California, and a 2019 California Teacher of the Year. “It’s just one less thing to negotiate in a learning environment.”

On online learning platforms, it’s easier for kids with social anxiety or shyness to participate. One of Gardner’s students with social anxiety participated far more in virtual settings and chats. Now, Gardner is brainstorming ways to encourage students to chat in person, such as by projecting a chat screen on the blackboard.

Technology has helped school psychologists better engage students, too. For example, Greiert said the virtual setting gave her a new understanding of her students’ personalities and needs. “Typing out their thoughts, they were able to demonstrate humor or complex thoughts they never demonstrated in person,” she said. “I really want to keep incorporating technology into sessions so kids can keep building on their strengths.”

Reid says that along with the high school students she teaches, she’s seen her 6-year-old daughter benefit from learning at her own pace in the familiarity of her home. Before the pandemic, she was behind academically, but by guiding her own learning—writing poems, reading books, playing outside with her siblings—she’s blossomed. “For me, as both a mother and as a teacher, this whole phenomenon has opened the door to what education can be,” Reid said.

Eleanor Di Marino-Linnen, PhD, a psychologist and superintendent of the Rose Tree Media School District in Media, Pennsylvania, says the pandemic afforded her district a chance to rethink old routines and implement new ones. “As challenging as it is, it’s definitely an exciting time to be in education when we have a chance to reenvision what schools have looked like for many years,” she said. “We want to capitalize on what we’ve learned.”

Further reading

Why are some kids thriving during remote learning? Fleming, N., Edutopia, 2020

Remote learning has been a disaster for many students. But some kids have thrived. Gilman, A., The Washington Post , Oct. 3, 2020

A preliminary examination of key strategies, challenges, and benefits of remote learning expressed by parents during the COVID-19 pandemic Roy, A., et al., School Psychology , in press

Remote learning during COVID-19: Examining school practices, service continuation, and difficulties for adolescents with and without attention-deficit/hyperactivity disorder Becker S. P., et al., Journal of Adolescent Health , 2020

Recommended Reading

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Student Reflections on Online Learning

Online education has changed significantly over the past year. Here we provide some feedback from students on what should continue as we engage in face-to-face instruction again and what should be left behind.

View a PDF version of this infographic.

What to keep from online learning

Assignment and participation flexibility: Help reduce student stress and increase accessibility by being flexible. For example, drop students' lowest assignment grades or create alternatives to graded synchronous participation.

Shorter lectures and breaks during lectures:  This can help maintain student engagement and help you to reduce burnout.

Keep your Canvas simple yet effective:  Help students by organizing files into folders, setting up weekly modules, and making sure to include all class Zoom links on Canvas.

Record your lectures:  This can make a world of difference for students in distant time zones and for when students have to miss a class due to health or other reasons. If you are concerned that recording lectures will result in less student participation, there are other ways to encourage student engagement.

What to leave from online learning

Focusing too much on "rigor":  Online education is fundamentally different from in-person instruction, so creating a rigorous learning environment will require different approaches. Focus on covering the most important material, and develop a backup plan, such as optional readings or asynchronous videos for the rest.

Big changes to courses:  Be sure to clearly set expectations at the beginning of the quarter and then be consistent with your expectations throughout the course. If an assignment or expectation does need to change, clearly communicate this to students.

What should stay for future in-person classes

Recorded lectures:  Students have given us feedback that lecture recordings are very helpful. However, recording lectures can sometimes be challenging depending on your situation. For a discussion of recommendations and policies regarding recording lectures and managing course absences see:

• Pre-recorded Instructional Video
• Live Online Lectures
• Strategies if Students are Unable to Attend in Person

Integrating Canvas fully into courses: Post the syllabus and other files. Have students submit assignments through Canvas.

Utilizing online tools:  For example, Poll Everywhere to replace clickers and Google Jamboards in place of whiteboards.

Flexibility and understanding: Help reduce student stress and promote mental health and well-being.

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ORIGINAL RESEARCH article

Insights into students’ experiences and perceptions of remote learning methods: from the covid-19 pandemic to best practice for the future.

• 1 Minerva Schools at Keck Graduate Institute, San Francisco, CA, United States
• 2 Ronin Institute for Independent Scholarship, Montclair, NJ, United States
• 3 Department of Physics, University of Toronto, Toronto, ON, Canada

This spring, students across the globe transitioned from in-person classes to remote learning as a result of the COVID-19 pandemic. This unprecedented change to undergraduate education saw institutions adopting multiple online teaching modalities and instructional platforms. We sought to understand students’ experiences with and perspectives on those methods of remote instruction in order to inform pedagogical decisions during the current pandemic and in future development of online courses and virtual learning experiences. Our survey gathered quantitative and qualitative data regarding students’ experiences with synchronous and asynchronous methods of remote learning and specific pedagogical techniques associated with each. A total of 4,789 undergraduate participants representing institutions across 95 countries were recruited via Instagram. We find that most students prefer synchronous online classes, and students whose primary mode of remote instruction has been synchronous report being more engaged and motivated. Our qualitative data show that students miss the social aspects of learning on campus, and it is possible that synchronous learning helps to mitigate some feelings of isolation. Students whose synchronous classes include active-learning techniques (which are inherently more social) report significantly higher levels of engagement, motivation, enjoyment, and satisfaction with instruction. Respondents’ recommendations for changes emphasize increased engagement, interaction, and student participation. We conclude that active-learning methods, which are known to increase motivation, engagement, and learning in traditional classrooms, also have a positive impact in the remote-learning environment. Integrating these elements into online courses will improve the student experience.

Introduction

The COVID-19 pandemic has dramatically changed the demographics of online students. Previously, almost all students engaged in online learning elected the online format, starting with individual online courses in the mid-1990s through today’s robust online degree and certificate programs. These students prioritize convenience, flexibility and ability to work while studying and are older than traditional college age students ( Harris and Martin, 2012 ; Levitz, 2016 ). These students also find asynchronous elements of a course are more useful than synchronous elements ( Gillingham and Molinari, 2012 ). In contrast, students who chose to take courses in-person prioritize face-to-face instruction and connection with others and skew considerably younger ( Harris and Martin, 2012 ). This leaves open the question of whether students who prefer to learn in-person but are forced to learn remotely will prefer synchronous or asynchronous methods. One study of student preferences following a switch to remote learning during the COVID-19 pandemic indicates that students enjoy synchronous over asynchronous course elements and find them more effective ( Gillis and Krull, 2020 ). Now that millions of traditional in-person courses have transitioned online, our survey expands the data on student preferences and explores if those preferences align with pedagogical best practices.

An extensive body of research has explored what instructional methods improve student learning outcomes (Fink. 2013). Considerable evidence indicates that active-learning or student-centered approaches result in better learning outcomes than passive-learning or instructor-centered approaches, both in-person and online ( Freeman et al., 2014 ; Chen et al., 2018 ; Davis et al., 2018 ). Active-learning approaches include student activities or discussion in class, whereas passive-learning approaches emphasize extensive exposition by the instructor ( Freeman et al., 2014 ). Constructivist learning theories argue that students must be active participants in creating their own learning, and that listening to expert explanations is seldom sufficient to trigger the neurological changes necessary for learning ( Bostock, 1998 ; Zull, 2002 ). Some studies conclude that, while students learn more via active learning, they may report greater perceptions of their learning and greater enjoyment when passive approaches are used ( Deslauriers et al., 2019 ). We examine student perceptions of remote learning experiences in light of these previous findings.

In this study, we administered a survey focused on student perceptions of remote learning in late May 2020 through the social media account of @unjadedjade to a global population of English speaking undergraduate students representing institutions across 95 countries. We aim to explore how students were being taught, the relationship between pedagogical methods and student perceptions of their experience, and the reasons behind those perceptions. Here we present an initial analysis of the results and share our data set for further inquiry. We find that positive student perceptions correlate with synchronous courses that employ a variety of interactive pedagogical techniques, and that students overwhelmingly suggest behavioral and pedagogical changes that increase social engagement and interaction. We argue that these results support the importance of active learning in an online environment.

Materials and Methods

Participant pool.

Students were recruited through the Instagram account @unjadedjade. This social media platform, run by influencer Jade Bowler, focuses on education, effective study tips, ethical lifestyle, and promotes a positive mindset. For this reason, the audience is presumably academically inclined, and interested in self-improvement. The survey was posted to her account and received 10,563 responses within the first 36 h. Here we analyze the 4,789 of those responses that came from undergraduates. While we did not collect demographic or identifying information, we suspect that women are overrepresented in these data as followers of @unjadedjade are 80% women. A large minority of respondents were from the United Kingdom as Jade Bowler is a British influencer. Specifically, 43.3% of participants attend United Kingdom institutions, followed by 6.7% attending university in the Netherlands, 6.1% in Germany, 5.8% in the United States and 4.2% in Australia. Ninety additional countries are represented in these data (see Supplementary Figure 1 ).

Survey Design

The purpose of this survey is to learn about students’ instructional experiences following the transition to remote learning in the spring of 2020.

This survey was initially created for a student assignment for the undergraduate course Empirical Analysis at Minerva Schools at KGI. That version served as a robust pre-test and allowed for identification of the primary online platforms used, and the four primary modes of learning: synchronous (live) classes, recorded lectures and videos, uploaded or emailed materials, and chat-based communication. We did not adapt any open-ended questions based on the pre-test survey to avoid biasing the results and only corrected language in questions for clarity. We used these data along with an analysis of common practices in online learning to revise the survey. Our revised survey asked students to identify the synchronous and asynchronous pedagogical methods and platforms that they were using for remote learning. Pedagogical methods were drawn from literature assessing active and passive teaching strategies in North American institutions ( Fink, 2013 ; Chen et al., 2018 ; Davis et al., 2018 ). Open-ended questions asked students to describe why they preferred certain modes of learning and how they could improve their learning experience. Students also reported on their affective response to learning and participation using a Likert scale.

The revised survey also asked whether students had responded to the earlier survey. No significant differences were found between responses of those answering for the first and second times (data not shown). See Supplementary Appendix 1 for survey questions. Survey data was collected from 5/21/20 to 5/23/20.

Qualitative Coding

We applied a qualitative coding framework adapted from Gale et al. (2013) to analyze student responses to open-ended questions. Four researchers read several hundred responses and noted themes that surfaced. We then developed a list of themes inductively from the survey data and deductively from the literature on pedagogical practice ( Garrison et al., 1999 ; Zull, 2002 ; Fink, 2013 ; Freeman et al., 2014 ). The initial codebook was revised collaboratively based on feedback from researchers after coding 20–80 qualitative comments each. Before coding their assigned questions, alignment was examined through coding of 20 additional responses. Researchers aligned in identifying the same major themes. Discrepancies in terms identified were resolved through discussion. Researchers continued to meet weekly to discuss progress and alignment. The majority of responses were coded by a single researcher using the final codebook ( Supplementary Table 1 ). All responses to questions 3 (4,318 responses) and 8 (4,704 responses), and 2,512 of 4,776 responses to question 12 were analyzed. Valence was also indicated where necessary (i.e., positive or negative discussion of terms). This paper focuses on the most prevalent themes from our initial analysis of the qualitative responses. The corresponding author reviewed codes to ensure consistency and accuracy of reported data.

Statistical Analysis

The survey included two sets of Likert-scale questions, one consisting of a set of six statements about students’ perceptions of their experiences following the transition to remote learning ( Table 1 ). For each statement, students indicated their level of agreement with the statement on a five-point scale ranging from 1 (“Strongly Disagree”) to 5 (“Strongly Agree”). The second set asked the students to respond to the same set of statements, but about their retroactive perceptions of their experiences with in-person instruction before the transition to remote learning. This set was not the subject of our analysis but is present in the published survey results. To explore correlations among student responses, we used CrossCat analysis to calculate the probability of dependence between Likert-scale responses ( Mansinghka et al., 2016 ).

Table 1. Likert-scale questions.

Mean values are calculated based on the numerical scores associated with each response. Measures of statistical significance for comparisons between different subgroups of respondents were calculated using a two-sided Mann-Whitney U -test, and p -values reported here are based on this test statistic. We report effect sizes in pairwise comparisons using the common-language effect size, f , which is the probability that the response from a random sample from subgroup 1 is greater than the response from a random sample from subgroup 2. We also examined the effects of different modes of remote learning and technological platforms using ordinal logistic regression. With the exception of the mean values, all of these analyses treat Likert-scale responses as ordinal-scale, rather than interval-scale data.

Students Prefer Synchronous Class Sessions

Students were asked to identify their primary mode of learning given four categories of remote course design that emerged from the pilot survey and across literature on online teaching: live (synchronous) classes, recorded lectures and videos, emailed or uploaded materials, and chats and discussion forums. While 42.7% ( n = 2,045) students identified live classes as their primary mode of learning, 54.6% ( n = 2613) students preferred this mode ( Figure 1 ). Both recorded lectures and live classes were preferred over uploaded materials (6.22%, n = 298) and chat (3.36%, n = 161).

Figure 1. Actual (A) and preferred (B) primary modes of learning.

In addition to a preference for live classes, students whose primary mode was synchronous were more likely to enjoy the class, feel motivated and engaged, be satisfied with instruction and report higher levels of participation ( Table 2 and Supplementary Figure 2 ). Regardless of primary mode, over two-thirds of students reported they are often distracted during remote courses.

Table 2. The effect of synchronous vs. asynchronous primary modes of learning on student perceptions.

Variation in Pedagogical Techniques for Synchronous Classes Results in More Positive Perceptions of the Student Learning Experience

To survey the use of passive vs. active instructional methods, students reported the pedagogical techniques used in their live classes. Among the synchronous methods, we identify three different categories ( National Research Council, 2000 ; Freeman et al., 2014 ). Passive methods (P) include lectures, presentations, and explanation using diagrams, white boards and/or other media. These methods all rely on instructor delivery rather than student participation. Our next category represents active learning through primarily one-on-one interactions (A). The methods in this group are in-class assessment, question-and-answer (Q&A), and classroom chat. Group interactions (F) included classroom discussions and small-group activities. Given these categories, Mann-Whitney U pairwise comparisons between the 7 possible combinations and Likert scale responses about student experience showed that the use of a variety of methods resulted in higher ratings of experience vs. the use of a single method whether or not that single method was active or passive ( Table 3 ). Indeed, students whose classes used methods from each category (PAF) had higher ratings of enjoyment, motivation, and satisfaction with instruction than those who only chose any single method ( p < 0.0001) and also rated higher rates of participation and engagement compared to students whose only method was passive (P) or active through one-on-one interactions (A) ( p < 0.00001). Student ratings of distraction were not significantly different for any comparison. Given that sets of Likert responses often appeared significant together in these comparisons, we ran a CrossCat analysis to look at the probability of dependence across Likert responses. Responses have a high probability of dependence on each other, limiting what we can claim about any discrete response ( Supplementary Figure 3 ).

Table 3. Comparison of combinations of synchronous methods on student perceptions. Effect size (f).

Mann-Whitney U pairwise comparisons were also used to check if improvement in student experience was associated with the number of methods used vs. the variety of types of methods. For every comparison, we found that more methods resulted in higher scores on all Likert measures except distraction ( Table 4 ). Even comparison between four or fewer methods and greater than four methods resulted in a 59% chance that the latter enjoyed the courses more ( p < 0.00001) and 60% chance that they felt more motivated to learn ( p < 0.00001). Students who selected more than four methods ( n = 417) were also 65.1% ( p < 0.00001), 62.9% ( p < 0.00001) and 64.3% ( p < 0.00001) more satisfied with instruction, engaged, and actively participating, respectfully. Therefore, there was an overlap between how the number and variety of methods influenced students’ experiences. Since the number of techniques per category is 2–3, we cannot fully disentangle the effect of number vs. variety. Pairwise comparisons to look at subsets of data with 2–3 methods from a single group vs. 2–3 methods across groups controlled for this but had low sample numbers in most groups and resulted in no significant findings (data not shown). Therefore, from the data we have in our survey, there seems to be an interdependence between number and variety of methods on students’ learning experiences.

Table 4. Comparison of the number of synchronous methods on student perceptions. Effect size (f).

Variation in Asynchronous Pedagogical Techniques Results in More Positive Perceptions of the Student Learning Experience

Along with synchronous pedagogical methods, students reported the asynchronous methods that were used for their classes. We divided these methods into three main categories and conducted pairwise comparisons. Learning methods include video lectures, video content, and posted study materials. Interacting methods include discussion/chat forums, live office hours, and email Q&A with professors. Testing methods include assignments and exams. Our results again show the importance of variety in students’ perceptions ( Table 5 ). For example, compared to providing learning materials only, providing learning materials, interaction, and testing improved enjoyment ( f = 0.546, p < 0.001), motivation ( f = 0.553, p < 0.0001), satisfaction with instruction ( f = 0.596, p < 0.00001), engagement ( f = 0.572, p < 0.00001) and active participation ( f = 0.563, p < 0.00001) (row 6). Similarly, compared to just being interactive with conversations, the combination of all three methods improved five out of six indicators, except for distraction in class (row 11).

Table 5. Comparison of combinations of asynchronous methods on student perceptions. Effect size (f).

Ordinal logistic regression was used to assess the likelihood that the platforms students used predicted student perceptions ( Supplementary Table 2 ). Platform choices were based on the answers to open-ended questions in the pre-test survey. The synchronous and asynchronous methods used were consistently more predictive of Likert responses than the specific platforms. Likewise, distraction continued to be our outlier with no differences across methods or platforms.

Students Prefer In-Person and Synchronous Online Learning Largely Due to Social-Emotional Reasoning

As expected, 86.1% (4,123) of survey participants report a preference for in-person courses, while 13.9% (666) prefer online courses. When asked to explain the reasons for their preference, students who prefer in-person courses most often mention the importance of social interaction (693 mentions), engagement (639 mentions), and motivation (440 mentions). These students are also more likely to mention a preference for a fixed schedule (185 mentions) vs. a flexible schedule (2 mentions).

In addition to identifying social reasons for their preference for in-person learning, students’ suggestions for improvements in online learning focus primarily on increasing interaction and engagement, with 845 mentions of live classes, 685 mentions of interaction, 126 calls for increased participation and calls for changes related to these topics such as, “Smaller teaching groups for live sessions so that everyone is encouraged to talk as some people don’t say anything and don’t participate in group work,” and “Make it less of the professor reading the pdf that was given to us and more interaction.”

Students who prefer online learning primarily identify independence and flexibility (214 mentions) and reasons related to anxiety and discomfort in in-person settings (41 mentions). Anxiety was only mentioned 12 times in the much larger group that prefers in-person learning.

The preference for synchronous vs. asynchronous modes of learning follows similar trends ( Table 6 ). Students who prefer live classes mention engagement and interaction most often while those who prefer recorded lectures mention flexibility.

Table 6. Most prevalent themes for students based on their preferred mode of remote learning.

Student Perceptions Align With Research on Active Learning

The first, and most robust, conclusion is that incorporation of active-learning methods correlates with more positive student perceptions of affect and engagement. We can see this clearly in the substantial differences on a number of measures, where students whose classes used only passive-learning techniques reported lower levels of engagement, satisfaction, participation, and motivation when compared with students whose classes incorporated at least some active-learning elements. This result is consistent with prior research on the value of active learning ( Freeman et al., 2014 ).

Though research shows that student learning improves in active learning classes, on campus, student perceptions of their learning, enjoyment, and satisfaction with instruction are often lower in active-learning courses ( Deslauriers et al., 2019 ). Our finding that students rate enjoyment and satisfaction with instruction higher for active learning online suggests that the preference for passive lectures on campus relies on elements outside of the lecture itself. That might include the lecture hall environment, the social physical presence of peers, or normalization of passive lectures as the expected mode for on-campus classes. This implies that there may be more buy-in for active learning online vs. in-person.

A second result from our survey is that student perceptions of affect and engagement are associated with students experiencing a greater diversity of learning modalities. We see this in two different results. First, in addition to the fact that classes that include active learning outperform classes that rely solely on passive methods, we find that on all measures besides distraction, the highest student ratings are associated with a combination of active and passive methods. Second, we find that these higher scores are associated with classes that make use of a larger number of different methods.

This second result suggests that students benefit from classes that make use of multiple different techniques, possibly invoking a combination of passive and active methods. However, it is unclear from our data whether this effect is associated specifically with combining active and passive methods, or if it is associated simply with the use of multiple different methods, irrespective of whether those methods are active, passive, or some combination. The problem is that the number of methods used is confounded with the diversity of methods (e.g., it is impossible for a classroom using only one method to use both active and passive methods). In an attempt to address this question, we looked separately at the effect of number and diversity of methods while holding the other constant. Across a large number of such comparisons, we found few statistically significant differences, which may be a consequence of the fact that each comparison focused on a small subset of the data.

Thus, our data suggests that using a greater diversity of learning methods in the classroom may lead to better student outcomes. This is supported by research on student attention span which suggests varying delivery after 10–15 min to retain student’s attention ( Bradbury, 2016 ). It is likely that this is more relevant for online learning where students report high levels of distraction across methods, modalities, and platforms. Given that number and variety are key, and there are few passive learning methods, we can assume that some combination of methods that includes active learning improves student experience. However, it is not clear whether we should predict that this benefit would come simply from increasing the number of different methods used, or if there are benefits specific to combining particular methods. Disentangling these effects would be an interesting avenue for future research.

Students Value Social Presence in Remote Learning

Student responses across our open-ended survey questions show a striking difference in reasons for their preferences compared with traditional online learners who prefer flexibility ( Harris and Martin, 2012 ; Levitz, 2016 ). Students reasons for preferring in-person classes and synchronous remote classes emphasize the desire for social interaction and echo the research on the importance of social presence for learning in online courses.

Short et al. (1976) outlined Social Presence Theory in depicting students’ perceptions of each other as real in different means of telecommunications. These ideas translate directly to questions surrounding online education and pedagogy in regards to educational design in networked learning where connection across learners and instructors improves learning outcomes especially with “Human-Human interaction” ( Goodyear, 2002 , 2005 ; Tu, 2002 ). These ideas play heavily into asynchronous vs. synchronous learning, where Tu reports students having positive responses to both synchronous “real-time discussion in pleasantness, responsiveness and comfort with familiar topics” and real-time discussions edging out asynchronous computer-mediated communications in immediate replies and responsiveness. Tu’s research indicates that students perceive more interaction with synchronous mediums such as discussions because of immediacy which enhances social presence and support the use of active learning techniques ( Gunawardena, 1995 ; Tu, 2002 ). Thus, verbal immediacy and communities with face-to-face interactions, such as those in synchronous learning classrooms, lessen the psychological distance of communicators online and can simultaneously improve instructional satisfaction and reported learning ( Gunawardena and Zittle, 1997 ; Richardson and Swan, 2019 ; Shea et al., 2019 ). While synchronous learning may not be ideal for traditional online students and a subset of our participants, this research suggests that non-traditional online learners are more likely to appreciate the value of social presence.

Social presence also connects to the importance of social connections in learning. Too often, current systems of education emphasize course content in narrow ways that fail to embrace the full humanity of students and instructors ( Gay, 2000 ). With the COVID-19 pandemic leading to further social isolation for many students, the importance of social presence in courses, including live interactions that build social connections with classmates and with instructors, may be increased.

Limitations of These Data

Our undergraduate data consisted of 4,789 responses from 95 different countries, an unprecedented global scale for research on online learning. However, since respondents were followers of @unjadedjade who focuses on learning and wellness, these respondents may not represent the average student. Biases in survey responses are often limited by their recruitment techniques and our bias likely resulted in more robust and thoughtful responses to free-response questions and may have influenced the preference for synchronous classes. It is unlikely that it changed students reporting on remote learning pedagogical methods since those are out of student control.

Though we surveyed a global population, our design was rooted in literature assessing pedagogy in North American institutions. Therefore, our survey may not represent a global array of teaching practices.

This survey was sent out during the initial phase of emergency remote learning for most countries. This has two important implications. First, perceptions of remote learning may be clouded by complications of the pandemic which has increased social, mental, and financial stresses globally. Future research could disaggregate the impact of the pandemic from students’ learning experiences with a more detailed and holistic analysis of the impact of the pandemic on students.

Second, instructors, students and institutions were not able to fully prepare for effective remote education in terms of infrastructure, mentality, curriculum building, and pedagogy. Therefore, student experiences reflect this emergency transition. Single-modality courses may correlate with instructors who lacked the resources or time to learn or integrate more than one modality. Regardless, the main insights of this research align well with the science of teaching and learning and can be used to inform both education during future emergencies and course development for online programs that wish to attract traditional college students.

Global Student Voices Improve Our Understanding of the Experience of Emergency Remote Learning

Our survey shows that global student perspectives on remote learning agree with pedagogical best practices, breaking with the often-found negative reactions of students to these practices in traditional classrooms ( Shekhar et al., 2020 ). Our analysis of open-ended questions and preferences show that a majority of students prefer pedagogical approaches that promote both active learning and social interaction. These results can serve as a guide to instructors as they design online classes, especially for students whose first choice may be in-person learning. Indeed, with the near ubiquitous adoption of remote learning during the COVID-19 pandemic, remote learning may be the default for colleges during temporary emergencies. This has already been used at the K-12 level as snow days become virtual learning days ( Aspergren, 2020 ).

In addition to informing pedagogical decisions, the results of this survey can be used to inform future research. Although we survey a global population, our recruitment method selected for students who are English speakers, likely majority female, and have an interest in self-improvement. Repeating this study with a more diverse and representative sample of university students could improve the generalizability of our findings. While the use of a variety of pedagogical methods is better than a single method, more research is needed to determine what the optimal combinations and implementations are for courses in different disciplines. Though we identified social presence as the major trend in student responses, the over 12,000 open-ended responses from students could be analyzed in greater detail to gain a more nuanced understanding of student preferences and suggestions for improvement. Likewise, outliers could shed light on the diversity of student perspectives that we may encounter in our own classrooms. Beyond this, our findings can inform research that collects demographic data and/or measures learning outcomes to understand the impact of remote learning on different populations.

Importantly, this paper focuses on a subset of responses from the full data set which includes 10,563 students from secondary school, undergraduate, graduate, or professional school and additional questions about in-person learning. Our full data set is available here for anyone to download for continued exploration: https://dataverse.harvard.edu/dataset.xhtml?persistentId= doi: 10.7910/DVN/2TGOPH .

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

GS: project lead, survey design, qualitative coding, writing, review, and editing. TN: data analysis, writing, review, and editing. CN and PB: qualitative coding. JW: data analysis, writing, and editing. CS: writing, review, and editing. EV and KL: original survey design and qualitative coding. PP: data analysis. JB: original survey design and survey distribution. HH: data analysis. MP: writing. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We want to thank Minerva Schools at KGI for providing funding for summer undergraduate research internships. We also want to thank Josh Fost and Christopher V. H.-H. Chen for discussion that helped shape this project.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2021.647986/full#supplementary-material

Aspergren, E. (2020). Snow Days Canceled Because of COVID-19 Online School? Not in These School Districts.sec. Education. USA Today. Available online at: https://www.usatoday.com/story/news/education/2020/12/15/covid-school-canceled-snow-day-online-learning/3905780001/ (accessed December 15, 2020).

Google Scholar

Bostock, S. J. (1998). Constructivism in mass higher education: a case study. Br. J. Educ. Technol. 29, 225–240. doi: 10.1111/1467-8535.00066

CrossRef Full Text | Google Scholar

Bradbury, N. A. (2016). Attention span during lectures: 8 seconds, 10 minutes, or more? Adv. Physiol. Educ. 40, 509–513. doi: 10.1152/advan.00109.2016

PubMed Abstract | CrossRef Full Text | Google Scholar

Chen, B., Bastedo, K., and Howard, W. (2018). Exploring best practices for online STEM courses: active learning, interaction & assessment design. Online Learn. 22, 59–75. doi: 10.24059/olj.v22i2.1369

Davis, D., Chen, G., Hauff, C., and Houben, G.-J. (2018). Activating learning at scale: a review of innovations in online learning strategies. Comput. Educ. 125, 327–344. doi: 10.1016/j.compedu.2018.05.019

Deslauriers, L., McCarty, L. S., Miller, K., Callaghan, K., and Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proc. Natl. Acad. Sci. 116, 19251–19257. doi: 10.1073/pnas.1821936116

Fink, L. D. (2013). Creating Significant Learning Experiences: An Integrated Approach to Designing College Courses. Somerset, NJ: John Wiley & Sons, Incorporated.

Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., et al. (2014). Active learning increases student performance in science, engineering, and mathematics. Proc. Natl. Acad. Sci. 111, 8410–8415. doi: 10.1073/pnas.1319030111

Gale, N. K., Heath, G., Cameron, E., Rashid, S., and Redwood, S. (2013). Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Med. Res. Methodol. 13:117. doi: 10.1186/1471-2288-13-117

Garrison, D. R., Anderson, T., and Archer, W. (1999). Critical inquiry in a text-based environment: computer conferencing in higher education. Internet High. Educ. 2, 87–105. doi: 10.1016/S1096-7516(00)00016-6

Gay, G. (2000). Culturally Responsive Teaching: Theory, Research, and Practice. Multicultural Education Series. New York, NY: Teachers College Press.

Gillingham, and Molinari, C. (2012). Online courses: student preferences survey. Internet Learn. 1, 36–45. doi: 10.18278/il.1.1.4

Gillis, A., and Krull, L. M. (2020). COVID-19 remote learning transition in spring 2020: class structures, student perceptions, and inequality in college courses. Teach. Sociol. 48, 283–299. doi: 10.1177/0092055X20954263

Goodyear, P. (2002). “Psychological foundations for networked learning,” in Networked Learning: Perspectives and Issues. Computer Supported Cooperative Work , eds C. Steeples and C. Jones (London: Springer), 49–75. doi: 10.1007/978-1-4471-0181-9_4

Goodyear, P. (2005). Educational design and networked learning: patterns, pattern languages and design practice. Australas. J. Educ. Technol. 21, 82–101. doi: 10.14742/ajet.1344

Gunawardena, C. N. (1995). Social presence theory and implications for interaction and collaborative learning in computer conferences. Int. J. Educ. Telecommun. 1, 147–166.

Gunawardena, C. N., and Zittle, F. J. (1997). Social presence as a predictor of satisfaction within a computer mediated conferencing environment. Am. J. Distance Educ. 11, 8–26. doi: 10.1080/08923649709526970

Harris, H. S., and Martin, E. (2012). Student motivations for choosing online classes. Int. J. Scholarsh. Teach. Learn. 6, 1–8. doi: 10.20429/ijsotl.2012.060211

Levitz, R. N. (2016). 2015-16 National Online Learners Satisfaction and Priorities Report. Cedar Rapids: Ruffalo Noel Levitz, 12.

Mansinghka, V., Shafto, P., Jonas, E., Petschulat, C., Gasner, M., and Tenenbaum, J. B. (2016). CrossCat: a fully Bayesian nonparametric method for analyzing heterogeneous, high dimensional data. J. Mach. Learn. Res. 17, 1–49. doi: 10.1007/978-0-387-69765-9_7

National Research Council (2000). How People Learn: Brain, Mind, Experience, and School: Expanded Edition. Washington, DC: National Academies Press, doi: 10.17226/9853

Richardson, J. C., and Swan, K. (2019). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Online Learn. 7, 68–88. doi: 10.24059/olj.v7i1.1864

Shea, P., Pickett, A. M., and Pelz, W. E. (2019). A Follow-up investigation of ‘teaching presence’ in the suny learning network. Online Learn. 7, 73–75. doi: 10.24059/olj.v7i2.1856

Shekhar, P., Borrego, M., DeMonbrun, M., Finelli, C., Crockett, C., and Nguyen, K. (2020). Negative student response to active learning in STEM classrooms: a systematic review of underlying reasons. J. Coll. Sci. Teach. 49, 45–54.

Short, J., Williams, E., and Christie, B. (1976). The Social Psychology of Telecommunications. London: John Wiley & Sons.

Tu, C.-H. (2002). The measurement of social presence in an online learning environment. Int. J. E Learn. 1, 34–45. doi: 10.17471/2499-4324/421

Zull, J. E. (2002). The Art of Changing the Brain: Enriching Teaching by Exploring the Biology of Learning , 1st Edn. Sterling, VA: Stylus Publishing.

Keywords : online learning, COVID-19, active learning, higher education, pedagogy, survey, international

Citation: Nguyen T, Netto CLM, Wilkins JF, Bröker P, Vargas EE, Sealfon CD, Puthipiroj P, Li KS, Bowler JE, Hinson HR, Pujar M and Stein GM (2021) Insights Into Students’ Experiences and Perceptions of Remote Learning Methods: From the COVID-19 Pandemic to Best Practice for the Future. Front. Educ. 6:647986. doi: 10.3389/feduc.2021.647986

Received: 30 December 2020; Accepted: 09 March 2021; Published: 09 April 2021.

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Copyright © 2021 Nguyen, Netto, Wilkins, Bröker, Vargas, Sealfon, Puthipiroj, Li, Bowler, Hinson, Pujar and Stein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Geneva M. Stein, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Is Online Learning Effective?

A new report found that the heavy dependence on technology during the pandemic caused “staggering” education inequality. What was your experience?

By Natalie Proulx

During the coronavirus pandemic, many schools moved classes online. Was your school one of them? If so, what was it like to attend school online? Did you enjoy it? Did it work for you?

In “ Dependence on Tech Caused ‘Staggering’ Education Inequality, U.N. Agency Says ,” Natasha Singer writes:

In early 2020, as the coronavirus spread, schools around the world abruptly halted in-person education. To many governments and parents, moving classes online seemed the obvious stopgap solution. In the United States, school districts scrambled to secure digital devices for students. Almost overnight, videoconferencing software like Zoom became the main platform teachers used to deliver real-time instruction to students at home. Now a report from UNESCO , the United Nations’ educational and cultural organization, says that overreliance on remote learning technology during the pandemic led to “staggering” education inequality around the world. It was, according to a 655-page report that UNESCO released on Wednesday, a worldwide “ed-tech tragedy.” The report, from UNESCO’s Future of Education division, is likely to add fuel to the debate over how governments and local school districts handled pandemic restrictions, and whether it would have been better for some countries to reopen schools for in-person instruction sooner. The UNESCO researchers argued in the report that “unprecedented” dependence on technology — intended to ensure that children could continue their schooling — worsened disparities and learning loss for hundreds of millions of students around the world, including in Kenya, Brazil, Britain and the United States. The promotion of remote online learning as the primary solution for pandemic schooling also hindered public discussion of more equitable, lower-tech alternatives, such as regularly providing schoolwork packets for every student, delivering school lessons by radio or television — and reopening schools sooner for in-person classes, the researchers said. “Available evidence strongly indicates that the bright spots of the ed-tech experiences during the pandemic, while important and deserving of attention, were vastly eclipsed by failure,” the UNESCO report said. The UNESCO researchers recommended that education officials prioritize in-person instruction with teachers, not online platforms, as the primary driver of student learning. And they encouraged schools to ensure that emerging technologies like A.I. chatbots concretely benefited students before introducing them for educational use. Education and industry experts welcomed the report, saying more research on the effects of pandemic learning was needed. “The report’s conclusion — that societies must be vigilant about the ways digital tools are reshaping education — is incredibly important,” said Paul Lekas, the head of global public policy for the Software & Information Industry Association, a group whose members include Amazon, Apple and Google. “There are lots of lessons that can be learned from how digital education occurred during the pandemic and ways in which to lessen the digital divide. ” Jean-Claude Brizard, the chief executive of Digital Promise, a nonprofit education group that has received funding from Google, HP and Verizon, acknowledged that “technology is not a cure-all.” But he also said that while school systems were largely unprepared for the pandemic, online education tools helped foster “more individualized, enhanced learning experiences as schools shifted to virtual classrooms.” ​Education International, an umbrella organization for about 380 teachers’ unions and 32 million teachers worldwide, said the UNESCO report underlined the importance of in-person, face-to-face teaching. “The report tells us definitively what we already know to be true, a place called school matters,” said Haldis Holst, the group’s deputy general secretary. “Education is not transactional nor is it simply content delivery. It is relational. It is social. It is human at its core.”

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Essay on Experience Of Online Classes

Students are often asked to write an essay on Experience Of Online Classes in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

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100 Words Essay on Experience Of Online Classes

Introduction to online classes.

Online classes are lessons taught over the internet. Instead of sitting in a classroom, students can learn from their own homes using a computer or a tablet. Teachers use videos, live chats, and online quizzes to teach students just like they would in a regular school.

Learning from Home

When you learn from home, you don’t have to travel to school. You can wake up, have breakfast, and go straight to your lessons in your pajamas if you want! It’s comfortable and saves time, but it can be hard to focus with distractions like TV and games.

Using Technology

Online classes often use fun tools like videos and interactive games to help you learn. You might chat with your teacher or classmates through typing or video calls. It’s a different way to learn, using tools that you might already enjoy.

Missing Friends

One thing many students miss in online classes is seeing their friends every day. It’s not the same as playing or talking in person. But you can still make friends by talking during online group work or in chat rooms.

250 Words Essay on Experience Of Online Classes

Online classes are a way for students to learn through the internet. They use computers or tablets to join virtual classrooms where teachers give lessons. This method became very popular when schools closed during the health crisis.

Students can take part in lessons from their own houses. They do not need to travel to school. This can save time and make it easier to attend class. They can also wear comfortable clothes and sometimes can snack while studying.

In online classes, students use tools like video calls and chat boxes. They watch lessons on screens and type questions to their teachers. Sometimes, they can watch recorded lessons again if they need to understand better.

Interacting with Others

Talking with classmates is different in online classes. Students can still work together on projects, but they do it through the computer. They might miss playing and talking with friends during breaks.

Some students might find it hard to focus at home. There can be noise or distractions. Also, if the internet is slow, it can be frustrating. Not all students have the same chance to use good computers or have fast internet.

500 Words Essay on Experience Of Online Classes

In recent times, many students around the world have started taking their classes online. This means instead of sitting in a classroom with other students and a teacher, they sit in front of a computer, tablet, or phone to learn new things. This switch to online classes has brought about many changes in how students study and interact with their teachers and classmates.

The Comfort of Home

One of the biggest perks of online classes is that you can learn from the comfort of your own home. You don’t need to wake up super early to catch the school bus or wear your school uniform. You can simply sit in your favorite spot, maybe with a pet by your side, and attend your classes. This comfort can make learning more enjoyable for some students.

Learning at Your Own Pace

Technical troubles.

But it’s not all easy. Sometimes, you might face technical problems like a bad internet connection or a computer that suddenly stops working. These issues can make it tough to follow along with the lesson and can be really frustrating, especially if you miss something important that your teacher said.

Missing Friends and Teachers

Another thing about online classes is that you might miss seeing your friends and teachers in person. It’s not quite the same to talk to them through a screen. You don’t get to play together during breaks or chat as you walk to the next class. For many students, this is one of the hardest parts of online learning.

Staying Focused

Being responsible.

With online classes, you need to be responsible for your own learning. Your parents and teachers won’t always be there to remind you to do your work. You have to make sure you log in on time, do your homework, and study for tests without someone constantly watching over you.

Online classes have become a big part of our lives. They allow us to learn new things from home and at our own speed, but they also come with challenges like technical issues and missing out on social interactions. It’s important to stay focused and be responsible for your own education when you’re learning online. Even though it’s different from traditional classroom learning, it’s still a valuable way to gain knowledge and skills that will help you in the future.

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Home / Essay Samples / Education / Online Classes / Lessons from the Screen: Reflections on Online Learning Experience

Lessons from the Screen: Reflections on Online Learning Experience

• Category: Literature , Education
• Topic: Literary Devices , Of Mice and Men , Online Classes

Pages: 3 (1305 words)

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“I remember the good old days” (Toy Story, 1995)

“different things can be sad” (lady bird, 2017), “just keep swimming” (finding nemo, 2003).

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