Online Learning Impact on Students From Low-Income Backgrounds

Introduction

Online learning has gained prominence in contemporary times, especially during the ongoing Covid-19 pandemic, which has led to the closure of traditional face-to-face learning in a classroom setup. Educators and policymakers have shifted focus to distance learning as a way of content and instruction delivery to ensure that students continue with their education for the 2020/2021 academic year. However, while switching from institutionalized learning to online learning is the only alternative during these challenging times, it is important to understand how this shift affects various student cohorts, specifically based on their socio-economic backgrounds. The available literature shows that students from low-income backgrounds are affected negatively by distance learning. This form of education presents various challenges to this group of learners, including the lack of Internet connectivity and other socio-economic factors. Overall, online learning has adverse impacts on students from low-income backgrounds, and the underlying question is why such a noble innovation would have negative outcomes among this group of learners.

Effects of Online Learning on Poor Students

Distance learning requires students to have the right infrastructure to support such a form of content delivery. For instance, learners are needed to have access to a computer or other related devices and Internet connectivity to create an enabling learning environment interacting with tutors and other students meaningfully. However, the lack of the needed resources to access the Internet and computers is a major challenge that students from poor backgrounds have to face as they endeavor to participate in online learning. Internet connectivity is a multifaceted issue that should be addressed within the larger context of the socio-economic status of learners. For instance, to the majority of people, the term “Internet connectivity” implies whether students have access to computers or not, in what is commonly referred to as the digital divide. According to Añover et al., “Contrary to what many believe, not all students have home computers with an Internet connection. Some students who have Internet access only have a dial-up connection” (5). Therefore, without access to home computers and the necessary Internet connectivity, students from poor backgrounds are unlikely to benefit from the many benefits associated with online learning.

However, critics would argue against this position by claiming that the cost of owning a computer and access to reliable Internet connectivity has dropped significantly in modern times, and thus most students should be readily equipped for distance learning irrespective of their socio-economic background. Additionally, public schools offering online programs have the responsibility of ensuring that students have the right tools, in terms of access to computers and the necessary bandwidth to engage meaningfully in this form of learning. However, these premises are wrong because, as Añover et al. posit, “the assumption that all students have a high-speed home Internet connection is a commonly held myth about students” (6). Therefore, students from poor backgrounds are negatively impacted by distance learning, owing to the lack of the necessary tools for such a form of learning. As such, the failure to participate in online learning, especially during the current closure of schools due to the Covid-19 pandemic, implies that these students would lag behind their peers who are currently continuing with their learning uninterrupted, thus entrenching inequality across the entire education system, as discussed next.

Learning has been a challenge for students from low-income backgrounds, even in traditional institutionalized education. A study by the National Center for Education Statistics (NCES) showed that a smaller percentage of low-SES (socioeconomic status) than middle-SES students “attained a bachelor’s or higher degree by 2012 (14 vs. 29 percent), and the percentages for both groups were smaller than the percentage of high-SES students whose highest level of education was a bachelor’s or higher degree (60 percent)” (2). As such, one would expect online education to bridge the gap of inequality in access to education among students from poor backgrounds. However, this situation of inequality in terms of academic achievement is exacerbated by the understanding that students from poor backgrounds are not engaged in online learning owing to their socio-economic status. Therefore, it suffices to argue that online learning entrenches the culture of inequality in education, whereby students from low-income backgrounds are affected disproportionately. The main underlying problem highlighted in this argument is that these students are in dire need of education as a way of getting themselves out of the cycle of poverty that has affected their families for generations. As such, instead of online education facilitating access to learning, it becomes a barrier.

However, critics would argue that distance learning is bridging the gaps created by institutionalized learning by presenting equal opportunities to all students, regardless of their socio-economic backgrounds. This statement is superficially true because such an argument overlooks the many externalizing factors that affect students from poor backgrounds even when they have access to computers and reliable Internet connectivity. For instance, due to poverty, such students could be forced to work multiple jobs, which affects their academic performance and increases the probability of quitting learning. A study conducted by Hovdhaugen found that “students who work full time alongside studying full time are less likely to complete their program than students working short part-time or not working at all” (631). While this study was conducted using participants drawn from institutionalized learning, the results could be generalized to apply in online learning. The underlying issue here is that of the availability of time to engage meaningfully in learning activities, regardless of the platform being used. As such, students from poor backgrounds are likely to perform poorly or drop out of college due to the lack of enough time to study.

Additionally, online education fails students from low-income because they are not fully prepared for such a form of learning. A 2017 report by Dynarski showed that online students “did substantially worse than students in the same face-to-face course – they earned lower grades, were less likely to succeed in subsequent courses, and more likely to drop out.” Therefore, when students from poor socio-economic backgrounds enroll in online learning, they are likely to fail, as they are unprepared for such a form of learning. According to Berkowitz et al., students from poor backgrounds are poorly prepared for school as compared to their peers from high socio-economic families (426). As such, low-income students need the presence of highly qualified school teachers to improve their preparedness and proficiency. However, online learning deprives such students of the opportunity to interact with their teachers through face-to-face meetings in traditional classroom settings, which is a major barrier to effective distance learning (Safford and Stinton 136). Therefore, these students are likely to fail or remain behind their peers, and this situation ultimately affects their upward social mobility because they do not have the academic credentials needed to compete fairly in the job market.

Nevertheless, proponents of online education would argue that virtual classes are designed to mimic the traditional classroom settings. Therefore, there are no major differences between these two set-ups, and students would learn equally well, whether online or in a face-to-face environment. However, the available evidence suggests that students in online learning perform poorly as compared to their peers in the traditional classroom set-ups. A study by Heppen et al. sought to find out how students in online learning performed in algebra as compared to those in institutionalized learning (272). The results showed that compared to “students in face-to-face credit recovery, students in online credit recovery reported that the course was more difficult, were less likely to recover credit, and scored lower on an algebra posttest” (Heppen et al. 272). These findings indicate that students from poor backgrounds, whereby the majority are unprepared for learning characterized by the lack of proficiency, would be negatively impacted by online learning. Such an environment compounds the problem because these learners need close supervision and motivation from their teachers, which could only be effective in face-to-face learning settings.

Conclusion

This paper has demonstrated the negative effects of online learning on students from low-income backgrounds. While this form of learning presents new opportunities for learners to advance their studies regardless of location, it has several adverse barriers to effective education, especially within the context of students with poor socio-economic statuses. Therefore, it is important for educators and policymakers to look into this issue and address the underlying problems in online education and its impacts on students from poor backgrounds. This form of learning is bound to be the most preferred choice in the future; hence, the need to design it in a way that promotes access the education and resolves the inequalities that affect students from poor backgrounds.

Works Cited

Añover, Verónica, et al. “A Study of the Effects of Students’ Socioeconomic Status on the Online Learning Environment.” New York University, Web. 

Berkowitz, Ruth, et al. “A Research Synthesis of the Associations Between Socioeconomic Background, Inequality, School Climate, and Academic Achievement.” Review of Educational Research, vol. 87, no. 2, 2017, pp. 425-469.

Dynarski, Susan. “Online Schooling: Who is Harmed and Who is Helped.” Brookings, 2020. Web.

Heppen, Jessica, et al. “The Struggle to Pass Algebra: Online vs. Face-to-Face Credit Recovery for At-Risk Urban Students.” Journal of Research on Educational Effectiveness, vol. 10, no. 2, 2017, pp. 272-296.

Hovdhaugen, Elisabeth. “Working While Studying: The Impact of Term-time Employment on Dropout Rates.” Journal of Education and Work, vol. 28, no.6, 2015, pp. 631-651.

NCES. “Postsecondary Attainment: Differences by Socioeconomic Status.” NCES, 2020. Web.

Safford, Kimberly, and Julia Stinton. “Barriers to Blended Digital Distance Vocational Learning for Non‐traditional Students.” British Journal of Educational Technology, vol. 47, no. 1, 2016, pp. 135-150.