The digital divide has been a topic of concern for many years, and the events surrounding the Covid-19 pandemic have shined a light on how big that divide really is. Mashable (2021) defined the digital divide as “a gap in internet and technology access that prohibits people from participating in vital parts of society.” This divide could be due to lacking infrastructure and cell phone service in rural or poor areas as well as barriers to adoption such as cost, lack of devices, and personal preferences among the population (Brake, 2020).
The digital divide should be a concern for everyone. In the world today, if a person does not have access to technology or the internet, they are at a distinct disadvantage in several ways. It is harder for them to:
look at and apply for jobs,
access educational opportunities (school for children and retraining for adults),
access social or government services,
participate in civic and community life, and
get information needed during a crisis (Mashable, 2021; Brake, 2020).
It is also more difficult for the community to reach and serve vulnerable populations if that population does not have adequate access (Mashable, 2021).
When schools went remote, studies have shown that 16 million students were caught in the digital divide, and those more often affected were students of color and those living in rural areas (Mashable, 2021). Twenty percent of adolescents say lack of connection and devices has been a problem when it comes to completing assignments for online school, and forty percent of teachers say students either do no not have access or a device to complete their work (Brake, 2020).
There have been several ideas to help improve accessibility. Providing hotspots can be a good short-term solution. Longer term solutions include increasing internet speeds (especially upload), improving and updating broadband infrastructure in currently underserved areas, and ensuring that all households have the physical hardware needed to access the internet (Mashable, 2021).
Solutions
A good question to ask with all the technology that has been at our disposal in the last twenty years is why does the digital divide still exist? There are many answers to that question. One answer is that there has not been sufficient investment in building the infrastructure for steady internet connections in rural and lower income areas. The minimum standards set by the government for broadband (25 MB/s download and 3 MB/s upload) may not be sufficient for uploading to today’s cloud-based applications, especially when there are multiple users on the same network or multiple WiFi signals in a small area creating interference (Mashable, 2021). There is a push to have the FCC upgrade the upstream minimum standards to prevent saturation. Over twenty-five percent of rural Americans do not have access a broadband connection that meets the minimum standards because providers have not invested in rural areas (Brake, 2020). Hopefully, this will be addressed by policy-makers in the wake of the pandemic.
The encouraging news is that during the shutdowns of schools and businesses during the early days of Covid-19 the current broadband networks in the United States were able to meet the increased demand with very minimal degradation in speed. However, this was not true for everyone as rural and poorer areas lacked needed infrastructure (Brake, 2020). This was especially true in Texas where roughly 440,000 rural households did not have access to broadband. About one third of Texas households do not have an internet connection (Ramsey, 2020). The pandemic shined the light on areas that need attention in regard to internet access such as ensuring that all students have devices and the ability to connect to the internet at home and affordability. In the United States, broadband is fairly affordable, but many Americans cannot pay for it. This is also something that does not affect all demographic groups equally. Creating a better broadband subsidy for all low-income users is a needed step (Brake, 2020). Steps toward this have been taken through the Affordable Connectivity Program (Emergency Broadband Benefit, 2021).
A Less Obvious Effect of the Digital Divide
Another issue that goes along with the digital divide is the use of big data for predictive analysis in schools. I believe there is a big digital divide here as well. Not all schools have the capability, for various reasons, to fully utilize the information available to them. This divide can lead to inequitable outcomes for students from one school district to the next.
Predictive modeling can be used to estimate potential future outcomes by using data about similar individuals with known outcomes, and it can identify at-risk students and interventions that would benefit them. Predictive modeling allows for hundreds of measures to be used to create the model and calculate risks along with a ranking of risk to determine the most effective interventions (Porter & Balu, 2016). In addition to determine whether a student is at-risk, the capability to use data for predictive modeling can help teachers guide instruction in ways to personalize education for students to help fill in existing gaps in their knowledge. If schools and teachers do not have the proper technology or training to use the tools, then time, money and opportunities are wasted (SREB, 2018). SREB (2018) indicated that studies show the United States has the highest graduation rates despite students being outperformed by students in other countries. I would say that this type of digital divide is, indeed, occurring since we are not effectively using the data we have available.
If this area of the digital divide was addressed by ensuring access to adequate bandwidth, technology and training, then society as a whole would benefit. More students would successfully finish school with the digital literacy skills needed to gain higher education or find jobs. This would also improve the economy (SREB, 2018).
Here is a video describing some of the ways predictive analytics can be used.
Resources
Brake, D. (2020, July 13). Lessons from the pandemic: Broadband policy after covid-19. Lessons From the Pandemic: Broadband Policy After COVID-19. Retrieved February 1, 2022, from https://itif.org/publications/2020/07/13/lessons-pandemic-broadband-policy-after-covid-19
Educause. (2019, July 31). Predictive analytics in pursuit of student success. YouTube. Retrieved February 4, 2022, from https://www.youtube.com/watch?v=bD3gRnuivj4
Emergency broadband benefit. Federal Communications Commission. (2021, December 31). Retrieved January 27, 2022, from https://www.fcc.gov/broadbandbenefit
Mashable. (2021, April 26). The 'digital divide' and covid-19's impact on internet access: Mashable. YouTube. Retrieved January 27, 2022, from https://youtu.be/xkbZPAJF88k
Porter, K.E. & Balu, R., (2016). PREDICTIVE MODELING OF K-12 ACADEMIC OUTCOMES: A Primer for Researchers Working with Education Data. Retrieved April 3, 2018 from https://www.mdrc.org/sites/default/files/Predictive_Modeling_of_K-12_Academic_Outcomes.pdf
Ramsey, R. (2020, April 1). Analysis: A digital divide with dire consequences for Texas. The Texas Tribune. Retrieved January 28, 2022, from https://www.texastribune.org/2020/04/01/digital-divide-dire-consequences-texas/
SREB, (2018). 10 Issues in Educational Technology, 2108. Retrieved December 7, 2019 from https://www.sreb.org/sites/main/files/file-attachments/10issues_v8-web_version_accessible.pdf?1521568731
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