The following is a mock research proposal completed at the behest of ICT600-201 at the University of Kentucky over a two day period. It should not be construed as a ready proposal. All rights reserved.

Is political confirmation bias contributing to the digital divide?

Abstract

The convergence of social media and digital technology has amplified the voices of historically marginalized communities – including inner-city minorities, LGBTQ+ individuals, rural Appalachian residents, small-scale farmers, and ethnic minorities. These tools have, in theory, democratized access to civic participation and information-sharing once reserved for more privileged groups. However, as digital connectivity becomes more widespread, a persistent – and increasingly complex – digital divide endures. While physical access to technology is improving, political and cultural silos are deepening (Nadeem, 2022). This trend suggests that the digital divide is no longer solely about infrastructure or technical proficiency, but also includes attitudinal barriers rooted in cognitive bias. These biases, often shaped by polarized political identities, may inhibit individuals’ willingness or ability to engage with digital tools and information, reinforcing cycles of exclusion.

Redefining the Digital Divide

The digital divide is traditionally defined as a lack of broadband access to internet resources (Coleman & Atkinson, 2011). Yet recent trends in technology usage suggest that this definition is increasingly incomplete. Simply running a wire into a home or placing a smartphone in someone’s hand does not automatically confer the skills or awareness needed to engage meaningfully with digital content. This deeper layer of inequality — often referred to as the cognitive divide — encompasses gaps in digital literacy, critical thinking, and information processing. In fact, this cognitive component is frequently cited as a more stubborn and complex barrier than physical access alone (Fonseca, 2010).

Increasing Division

Political, moral, and cultural divisions have long been part of human society. Even within the relatively brief history of the United States, such divisions have often turned violent – most infamously during the Civil War, which left a lasting scar rooted in deep cultural and ideological bias. Closer to home, Kentucky offers its own history of internecine conflict. The Hatfield and McCoy feud, now more folklore than fact, stands as a symbol of how personal and political disputes can spiral into prolonged hostility. This author’s own hometown of Morehead saw the “Rowan County War” – a near open rebellion including government seizure, and multiple state militia deployments – all fueled by political strife and escalating personal animosity.

These historical episodes share a common thread: a breakdown in dialogue driven by cognitive bias – the mental shortcuts and judgments we form based on deeply held beliefs. While today’s divisions may not lead to literal shootouts, they are arguably more entrenched. According to a 2022 Pew Research Center study (Nadeem, 2022), political animosity in the U.S. has increased dramatically over the past two decades, with citizens not only disagreeing on policy, but actively disliking and distrusting those from opposing political parties. This growing polarization, mirrored in democracies worldwide, aligns closely with the rise of mobile internet and social media – technologies that can both connect and divide. The correlation raises an urgent question: is political cognitive bias now a barrier not just to civil discourse, but to digital inclusion itself?

Impact

The digital divide imposes a social and economic cost not only on those directly affected, but on society as a whole. For instance, as industries increasingly prioritize efficiency and automation, tasks as basic as applying for a job are often confined to online platforms. Individuals who attempt to apply in person are commonly redirected to kiosks or websites – effectively excluding those without the necessary digital skills or access. This not only marginalizes already vulnerable populations, but also reduces the available labor pool, hindering workforce development and deepening socioeconomic inequality (Steele, 2018).

These realities make it clear: the digital divide is not simply a matter of technology access. Cognitive and attitudinal barriers – such as lack of confidence, digital literacy, or trust in online systems – may play just as significant a role and are often far harder to address. A deeper understanding of these barriers is essential if we hope to develop targeted, effective strategies for bridging the gap and fostering true digital inclusion.

Objectives

The primary goal of this research is to determine whether a relationship exists between cognitive bias and attitudinal barriers that contribute to the digital divide. Specifically, it seeks to understand how political identity and associated biases may influence an individual’s willingness or ability to engage with digital tools and platforms.

By identifying this relationship, the study aims to inform the development of targeted educational programs that address these non-technical barriers. Such programs could help increase digital participation across underserved communities by improving confidence, trust, and digital literacy.

The findings may be valuable to educational coordinators, non-profit organizations, and community leaders working to bridge the digital divide. Additionally, industry stakeholders seeking to access untapped labor markets may benefit from insights into how attitudinal barriers affect workforce readiness. Finally, the research may lay a foundation for future studies focused on identifying and mitigating the granular causes of political or cultural resistance to technology adoption.

Literature Review

The digital divide is widely acknowledged as a persistent societal issue, documented across both anecdotal reports and peer-reviewed literature. However, despite broad agreement on its importance, scholars differ significantly on its root causes and even on how to define it. Three primary conceptualizations of the digital divide are commonly cited:

1. Access to Hardware and Connectivity:
   Frederick (2019) defines the digital divide as a basic gap in access to computer hardware and internet connectivity. This approach treats the issue as a logistical challenge – one that can be resolved through device distribution and network infrastructure. While straightforward, this definition fails to consider how effectively users engage with the technology once they have it. It also ignores the long-term sustainability of hardware deployment and ongoing support needs.
2. Broadband Quality and Availability:
   Coleman and Atkinson (2011) expand the definition to emphasize access to broadband internet. This framing introduces the idea of connection quality, highlighting that intermittent or slow connections can leave communities functionally unconnected despite appearing “online.” However, the lack of a universally accepted definition of “broadband” and the continued focus on infrastructure over engagement still limit this approach.
3. Cognitive and Functional Digital Literacy:
   Fonseca (2010) proposes a more nuanced view, suggesting that the digital divide also includes the inability to understand, learn, express, and create using technology. Rather than centering on devices or bandwidth, Fonseca frames the divide as a human development challenge – where educational access and digital fluency determine whether technology can be used meaningfully. This “cognitive divide” often emerges from socioeconomic inequalities that perpetuate themselves over time. For example, Fonseca highlights Costa Rica’s national initiative to blend digital and creative skills training, which has since positioned the country as a regional tech leader.

Building on this perspective, Partridge (2007) explores attitudinal barriers – psychological and emotional factors such as self-confidence and perceived relevance – which can deter individuals from engaging with digital tools. Importantly, Partridge finds that these barriers are often tied to age rather than socioeconomic status. Older adults may avoid technology not because of a lack of access, but due to internal doubts about their ability to learn or adapt.

Thrane et al. (2008) further complicate the picture by showing that technology resistance is not exclusive to older generations. They argue that even younger individuals can resist new digital tools if they fall outside the scope of their generational norms. This challenges the common assumption that digital fluency naturally increases over time and across younger cohorts.

Despite these insights, few studies have explored how cognitive bias, particularly political bias, may shape or reinforce attitudinal barriers to technology adoption. Cognitive bias – the tendency to process information through personal and ideological filters (Gillis & Bernstein, 2022) – could play a crucial role in digital exclusion. This research seeks to address that gap by examining whether politically-driven biases correlate with resistance to digital engagement, especially in communities already affected by limited access.

Methodology

This study will utilize a Likert-scale survey to examine potential relationships between political identity, cognitive bias, and digital engagement – supplemented by a series of semi-structured follow-up interviews to provide deeper qualitative insight.

Survey Design

The Likert survey will collect data in the following key areas:

• Political self-identification and degree of political alignment or passion
• Preferred sources of information (e.g., news outlets, social media)
• Attitudes toward opposing political perspectives and individuals
• Trust in alternative or unfamiliar informational sources
• Self-reported quality and reliability of online access
• Perceived importance of internet access in daily life
• Perceived importance of technology in educational contexts

A sample survey is provided in the Supplemental section below.

The survey will be administered in both digitally connected regions and regions affected by digital exclusion, enabling comparative analysis of cognitive and attitudinal profiles. Special attention will be paid to ensure geographic and demographic diversity in the respondent pool.

To overcome the anticipated challenges of access and engagement in digitally disconnected areas, manned kiosk stations will be deployed in high-traffic community spaces such as grocery stores, courthouse lobbies, and school drop-off zones to support in-person participation.

Survey Data Analysis

Collected survey data will be analyzed using the Proportional Odds Model – an ordinal regression technique suitable for interpreting ordered categorical responses. This model will test whether variables such as political alignment intensity or information source trust are predictive of attitudes toward digital tools, platforms, and usage patterns.

Measurable concentrations of politically aligned cognitive bias in areas with limited connectivity – compared to areas with stable access and lower bias – may indicate that attitudinal barriers are contributing to the digital divide.

Follow-Up Interviews

To complement survey findings, a series of semi-structured interviews will be conducted to capture the lived experiences, perspectives, and emotional narratives underlying participants’ digital behaviors and biases. These interviews will aim to reveal how political identity and cognitive bias influence digital inclusion, as expressed in participants’ own language.

Participant Selection

Interview participants will be randomly selected from the survey respondent pool using stratified sampling to ensure representation across the following demographic cohorts:

• Geographic location (urban, suburban, rural)
• Political self-identification (conservative, liberal, independent, apolitical)
• Age group (e.g., 18–29, 30–49, 50–64, 65+)
• Level of digital access (stable broadband, intermittent or mobile-only, no home access)
• Education level

This approach ensures a diverse, representative subset while allowing for the emergence of cohort-specific themes and cultural patterns.

Interview Format and Delivery

Each interview will last approximately 30 to 45 minutes and follow a semi-structured protocol – ensuring consistency in core questions while allowing flexibility to explore emergent topics.

Interviews will be conducted via:

• In-person sessions at libraries, community centers, or mobile kiosk stations
• Phone or video conferencing (where feasible)
• Partnerships with trusted local organizations to support outreach and moderation in low-trust or underserved areas

With participant consent, all interviews will be audio-recorded and transcribed for analysis. An interview script sample is included in the Supplemental section.

Interview Data Analysis

Interview transcripts will undergo thematic coding, blending:

• Deductive codes informed by survey constructs (e.g., trust, digital fluency, political bias)
• Inductive codes developed organically during transcript review

The resulting insights will help interpret and contextualize statistical patterns observed in the survey data. Moreover, they will highlight nuanced barriers – such as distrust in digital systems, identity-linked disengagement, or generational resistance – that may inform targeted educational strategies and culturally responsive digital inclusion efforts.

Limitations

Achieving an even and representative distribution of survey responses poses a significant challenge, particularly given the differing behaviors and access levels between digitally connected and disconnected populations. Simply collecting equal numbers of surveys from both groups may not be sufficient to account for structural and behavioral biases. A statistical weighting formula may be required to adjust for such disparities and reduce the risk of skewed results.

Moreover, the multifaceted nature of the digital divide introduces the potential for misattribution. It would be both methodologically flawed and ethically inappropriate to assume that individuals who exhibit strong political views and reside in disconnected areas necessarily suffer from cognitive or attitudinal barriers. The existence of cognitive bias alone does not imply resistance to digital engagement, nor does it confirm that political alignment is the root cause of digital exclusion.

Many contributing factors – such as infrastructure limitations, economic hardship, or geographic isolation – lie beyond the control of individuals and may exert a more direct influence on digital access. The identification of attitudinal barriers, if present, should therefore be seen not as definitive evidence of politically driven exclusion, but as an indicator warranting further investigation. This study aims to identify correlations that could inform deeper, more targeted research into the psychological and sociopolitical dimensions of the digital divide.

References

Coleman, P. D., & Atkinson, J. K. (2011). The digital divide in Kentucky: Is rural online learning sustainable? Retrieved December 7, 2022, from http://www.jsedimensions.org/wordpress/wp-content/uploads/2011/03/Atkinson2011.pdf

Fonseca, C. (2010). The Digital Divide and the Cognitive Divide: Reflections on the Challenge of Human Development in the Digital Age. Retrieved December 5, 2022, from https://itidjournal.org/index.php/itid/article/download/618/618-1657-2-PB.pdf

Frederick, D. E. (2019, September 3). The Fourth Industrial Revolution and the digital divide. Library Hi Tech News. Retrieved December 9, 2022, from https://www.emerald.com/insight/content/doi/10.1108/LHTN-07-2019-0048/full/html

Gillis, A. S., & Bernstein, C. (2022, June 22). What is cognitive bias? Enterprise AI. Retrieved December 5, 2022, from https://www.techtarget.com/searchenterpriseai/definition/cognitive-bias

Nadeem, R. (2022, November 17). As partisan hostility grows, signs of frustration with the two-Party system. Pew Research Center – U.S. Politics & Policy. Retrieved December 7, 2022, from https://www.pewresearch.org/politics/2022/08/09/as-partisan-hostility-grows-signs-of-frustration-with-the-two-party-system/

Partridge, H. (2007). Redefining the digital divide: Attitudes do matter! Retrieved December 5, 2022, from
https://asistdl.onlinelibrary.wiley.com/doi/10.1002/meet.1450440251 Steele, C. (2018, December 17). The impacts of digital divide. Digital Divide Council. Retrieved December 8, 2022, from http://www.digitaldividecouncil.com/the-impacts-of-digital-divide/

Thrane, L. E., Shelley, M. C., Shulman, S. W., Beisser, S. R., & Larson, T. B. (2008). E-political empowerment – taylor & francis. Taylor & Francis Online. Retrieved December 5, 2022, from https://www.tandfonline.com/doi/abs/10.1300/J399v01n04_03

Supplemental

Survey Sample

Political Identity and Passion

1. I consider myself strongly aligned with a particular political party or ideology.
2. My political beliefs are an important part of my personal identity.
3. I frequently discuss politics with friends, family, or coworkers.
4. I feel emotionally affected by political events or decisions.
5. People with opposing political views often seem misinformed or misguided.

Preferred Information Sources

6. I primarily get my news from sources that reflect my personal views.
7. I often cross-check information from sources with opposing viewpoints.
8. I trust information from major national news networks.
9. I rely heavily on social media to stay informed.
10. I avoid news sources that frequently feature views I disagree with.

Attitudes Toward Opposing Views

11. I find it difficult to have respectful conversations with people who have opposing political views.
12. I believe people with different political beliefs can still have valid perspectives.
13. I often feel frustrated or angry when reading political opinions that differ from mine.
14. I would feel uncomfortable attending a community event where the majority of attendees support a different political party than I do.

Trust in Unfamiliar or Unused Sources

15. I am skeptical of new or unfamiliar news sources, even if others recommend them.
16. I believe that some information online is intentionally misleading or manipulative.
17. I tend to trust content only if it aligns with what I already believe.
18. I avoid websites or apps I don’t recognize or haven’t used before.

Digital Access and Literacy (Self-Reported)

19. I have regular and reliable access to high-speed internet.
20. I feel confident using digital tools like email, online forms, or mobile apps.
21. I often struggle to keep up with new technology.
22. I am comfortable learning new digital tools when needed.
23. I feel left out when services or activities move entirely online.

Perceived Importance of Internet and Tech

24. Access to the internet is essential for full participation in modern society.
25. I believe internet access is a human right.
26. Technology is important for equal access to education.
27. I would attend training or workshops to improve my digital skills, if available.
28. I feel that technology can help bridge divides in society, not widen them.

Optional Demographics

• Age range
• Education level
• Annual household income (ranges)
• ZIP code or county of residence
• Primary language spoken at home
• Employment status

Interview Sample

Key Interview Topics

• “What kinds of support or resources would help you feel more confident using digital tools?”

Personal technology use

• “How do you use the internet in your daily life?”
• “Are there tools or platforms you avoid, and why?”

Political identity and trust

• “Do you think your political beliefs influence how you engage with digital platforms?”
• “Are there online spaces or news outlets you avoid because of how they represent political issues?”

Perceptions of digital inclusion

• “What would make it easier or more comfortable for you to use technology?”
• “Do you trust information you find online? What makes you decide whether to believe it?”

Barriers to engagement

• “Have you ever avoided a service, program, or opportunity because it was only available online?”