Learning during COVID-19: Behavioural deterrents

Investigating the difficulties or obstructions that such remote learners have in meeting their learning objectives.

Learning during COVID-19: Behavioural deterrents
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The COVID-19 pandemic has had a significant impact on education, resulting in the closure of schools, colleges, and universities(Pokhrel & Chhetri, 2021; Zhu & Liu, 2020). Traditional classrooms were replaced with online classrooms, which had a profound impact on instructors' and students' engagement, resulting in a paradigm change in the teaching and learning process(Pokhrel & Chhetri, 2021). Post-pandemic, the hybrid approach to learning is here to stay, with many governments adopting online means to train both instructors and young learners. Therefore, it's important to understand the difficulties associated with learning in a distant or online setting. This piece investigates the difficulties or obstructions that such remote learners have in meeting their learning objectives.

Previous studies have emphasised a number of crucial factors that influence online learning from the perspective of the student, such as having a computer at home, gender, consistent instructions and feedback from teachers, a sense of community within the learning environment, family support, time management abilities, feedback from teachers, resource-intensive course content and design components, and overall perception(Gaytan, 2015; Hone & El Said, 2016; Volery & Lord, 2000). Studies have shown that online learning may not be suitable for all learners. Negative perceptions about online learning are one of the leading factors contributing to the loss of student motivation and persistence(Kauffman 2015). However, in countries like India, recent research found that metropolitan areas were more accepting of online education than rural areas due to resource availability(Muthuprasad et al., 2021).

Identifying the factors that can lead to success or failure in an e-learning environment might help course designers predict future learning outcomes and prevent them from choosing courses in the format they prefer if it isn't the right one. Furthermore, identifying the learner barriers can help design a better approach to online learning that match the requirements of learners. Appropriate teaching methods, support, course structure, and design may all contribute to better learning outcomes.

I. Cognitive overload and Mental Fatigue:

Students who are subjected to a huge amount of complicated knowledge that takes a long time to absorb may suffer from cognitive overload (Sweller et al., 1998). Often referred to as "mental fatigue," perceived cognitive overload is associated with learning-related emotional states, as it has been shown to dramatically alter engagement and performance. However, modest levels of cognitive load have also been proven to lead to boredom (Atiomo, 2020).

Cognitive overload in online learning activities has been proved several times in the past (Chen et al., 2011) to influence students’ acceptance, achievement, and participation in online learning. The relationship between a student's emotional health and cognitive load is also supported by research, which contends that anxiety can impede cognitive function, including working memory and the allocation of attentional resources, by causing mental tiredness (Atiomo, 2020), (Sweller et al., 2019).

The cognitive load theory is regarded as one of the most essential educational theories for instructors (Atiomo 2020) because it provides educators with an explanatory framework for how the material might be presented to learners in order to enhance their mental performance (Kirschner, 2002).

II. Engagement and Negative Emotions:

Few researchers studied the student’s emotions in various e-learning situations in order to determine how they may relate to students' engagement. They found that learners feel good emotions during synchronous learning activities (chats with teachers and among student groups), and their engagement dimensions of emotional relevance and involvement improve dramatically. The study therefore emphasises how crucial it is for an online instructor to regulate students' negative emotions since they might have a detrimental impact on both the emotional and behavioural aspects of participation(D’Errico et al., 2016).

Boredom, cognitive overload, and anxiety are negative learning-related emotions (LREs) that have direct consequences on acceptance and indirect implications on learning outcomes(Xie, 2021). However, perceived anxiety was found to have a direct effect on knowledge improvement. Cognitive load has been shown to greatly increase boredom in distant learning, Surprisingly, students' anxiety was shown to have a positive association with perceived knowledge growth and a negative association with cognitive load(Xie, 2021).

III. Sustained Attention, and Concentration:

Many studies have been conducted to measure student attention in a classroom context. Attention is the ability to actively process information in the environment while shutting out other information. Because attention is limited in terms of both capacity and duration, it is critical to have methods for successfully managing the attentional resources.

A recent experiment on the use of the attention monitoring alert mechanism(AMAM), used human electroencephalogram (EEG) detection technology, to support students’ online English learning, verifying that AMAM support improves learning performance and sustained attention. Analytical results show that the AMAM provides greater benefits for female learners than for male learners. The AMAM simultaneously improved the sustained attention of both genders(Chen & Wang, 2018). Another novel approach, such as brain gyms and kinesthetic learning through movement, have resulted in improved student concentration(Anggraini & Dewi, n.d.).

Hunger induced by the pandemic impacted nutrition, productivity, and education in developing nations(Mishra & Rampal, 2020; Workie et al., 2020). Researchers have observed a positive correlation between hydration, nutrient consumption, and better attention in online learning(Adolphus et al., 2013; Krisnana et al., 2021). In turn, learning is impacted more severely as a result.

IV. Climate Conditions effecting learner performance:

Although no study has been conducted on the environmental implications of remote learning during the COVID epidemic, there is strong evidence that classroom temperatures affect learning outcomes. A new study integrated standardised achievement data from 58 countries and 12,000 US school districts with accurate weather and academic calendar information to show that the pace of learning slows as the frequency of hot school days increases(Park et al., 2021). Another study provides substantial evidence for the detrimental impacts of severe temperatures on human capital; 10 more days in a year with an average daily temperature over 29C relative to 15-17C lowers math and reading exam performance by 0.03 and 0.02 standard deviations, respectively, comparable to negating one-fourth of the gains from smaller class sizes(Garg et al., 2017)

These findings imply that climatic changes may lead to inequalities in learning outcomes both between countries and then within countries based on socioeconomic status, which might have serious implications for the magnitude and functional form of climate damage to education systems.


The research demonstrated that the following aspects influence online learner involvement and engagement patterns: technology, content, environment, emotions, and information overload. The United Nations 2030 Agenda will place an emphasis on democratisation of education via the use of technology. It is critical, then, to design pedagogically user-friendly online course administration systems. More study on interface design, learner engagement patterns, and cognitive load in online learning can help instructional designers and educators create effective online learning.


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