The COVID-19 pandemic has created the largest disruption of education systems in history [1]. Because of this worldwide crisis, 190 countries across the globe [1] were forced to institute closures of school services [1] [2] [3] [4] that affected at least 1.6 billion students [5].

To cushion the effect of the school closures [4], academic institutions saw a pressing need to implement alternative educational and assessment strategies [6] such as distance education as the sole means for learning and instruction [7] and blended learning to include both virtual and in-person instruction [2]. In ensuring academic continuity, educational institutions abruptly shifted to online learning [3] [8] [9] [10]. But the current situation is not without any challenges as “COVID-19 has shone a spotlight on the digital divide” [11].

Based on the data of UNESCO, some 826 million students do not have access to a household computer while 706 million learners have no internet at home. Learners in the most marginalized groups, who don’t have access to digital learning resources or lack the resilience and engagement to learn on their own, are at risk of falling behind [12]. In the advent of online education and the disparity of technological equipment available to the wealthy as compared to the poor students, instruction delivery will be inconsistent and unfair [11]. This crisis has exposed the many inadequacies and inequities in our education systems―from access to the broadband and computers needed for online education, and the supportive environments needed to focus on learning, up to the misalignment between resources and needs [12].

In Southeast Asia, a large segment of the population does not have access to the Internet and electronic devices [10]. Many people in Southeast Asia still cannot afford unlimited and stable Internet connection [13]. As a developing region, many students are from economically vulnerable families [10]. In as early as 2002, the Southeast Asian Ministers of Education Organization (SEAMEO) had been addressing the digital divide dilemma in the region by training and educating people through the SEAMEO Regional Centres [14]. The following interrelated factors contribute to the widening digital divide in Southeast Asia: economic development of the countries, availability of ICT infrastructure, level of education of the people and household income of family in the respected countries [14].

In the Philippines, the Commission on Higher Education (CHED) adopted and promulgated the guidelines on flexible learning delivery for implementation by all public and private higher education institutions to ensure safety of the Filipino learners during the coronavirus pandemic [15]. With in-person classes impossible, CHED put together distance learning options that include online platforms, offline modules, or a combination of the two, called blended or flexible learning [15]. But distance learning has made inequities, especially around the digital divide, more apparent than ever before and college students scramble to acquire digital devices and stable internet connection [16].

These scenarios give a glimpse of digital divide in an academic community in the Philippines. During this time of pandemic, digital divide is more than just “the gap between those who do and those who do not have access to new forms of information technology” [17] as it also encompasses a global issue that deals with the uneven distribution, access, and utilization of ICT [18] where certain parts of the population have substantially better opportunities than other parts of the population [19].

The study used descriptive method to determine the incidence of digital divide in times of pandemic among teacher education students. It is also relational in terms of analyzing the relationship between the respondents’ profile variables and use of ICT. For this reason, correlational and survey research models were used together.

The purpose of this quantitative study was to determine the existence of digital divide as regards access and use of ICT of a purposeful sample of 264 teacher education institution (TEI) students. Spearman Rho Correlation was used as statistical tool with 5% level of significance. As can be seen in Table 3, the findings from this study showed that residence, annual family income, and parents’ highest educational attainment significantly predicted digital divide in ICT usage. These findings suggest that in terms of residence, living in rural area put the students at a disadvantage in accessing the internet (p = 0.009). Having slow internet connection in their residence forces the students to have higher mobile data internet consumption (p < 0.01) so they tend to spend more time online (p < 0.01) doing school-related tasks.

**p < 0.01; *p < 0.05.

Annual family income is also found to be a predictor of digital divide. Access to internet (p = 0.035) is limited among students who belong to families with low income. Because of financial constraints, there is less budget allotted for internet expenditure (p < 0.01) that hampers students’ time (p < 0.01) to accomplish online activities. Thus, students with higher family income have superior access to internet.

Another predictor of digital divide is found in the parents’ highest educational attainment. The analysis indicates that internet access is influenced by the father’s educational attainment (p-value = 0.002) and mother’s educational attainment (p-value = 0.004). The strength of relationships was found to be positive weak correlation. Therefore, the respondents whose parents are highly educated have greater internet access.

The present paper contributes to the digital divide literature as it sheds light on the dim areas for policymakers to consider to close the gap among students, especially in times of natural phenomenon like a pandemic. The central finding of this study has confirmed the existence of digital divide along the demographic factors such as residence, annual family income and parents’ highest educational attainment. Significant differences were found to exist not only in access to the internet but also in mobile internet expenses and hours spent on the internet. The fact that more than 13% of students still don’t have internet connections poses critical implications and necessitates deliberate policy formulation. It is also good to note that while mobile learning is progressing, there are students whose gadgets remain to be low-tech making it hard for them to access instructional materials uploaded online.

During pandemic, digital divide is higher and the negative effects brought by the COVID-19 on students become more evident. Though closing the digital divide among the students is an enormous challenge, this study provides relevant information to design plans of action that will level the playing field among students. To ensure that no one is left behind, all sectors of society must exert their best efforts to fill in the gap of the widening digital divide.

The findings of the study may serve as a strong starting point for other researchers in conducting further studies on digital divide among higher education institution students to generate more conclusive and generalizable results.

Each author listed above has made substantial contributions to the conception, design of the study, manuscript or substantively revised it. The authors read and approved the final manuscript.

All data of this research project is available with the authors and can be made available on requests if required.

The authors declare that they have no competing interests.

Esteban Jr., A.M. and Cruz, M.J.P. (2021) Digital Divide in Times of Pandemic among Teacher Education Students. Open Access Library Journal, 8: e7323. https://doi.org/10.4236/oalib.1107323