Digital Literacy in the Age of AI: Analysis and Voices from the Field

In November 2022, generative artificial intelligence (AI) burst into everyday life in homes, classrooms, workplaces, and communities. For education, the rapid acceleration of this technology provided new opportunities that could transform assessments, personalize learning, and support instruction, but it also raised uncertainty and concerns about policies that would impact professional development (PD), access and equity, data privacy, and student safety.

Questions have also emerged about what counts as digital literacy, AI literacy, and even how both relate to computer science (CS). This brief explores these questions through a literature review, stakeholder interviews, a focus group of educators and students, and a 50-state scan of the digital literacy skills landscape.

The work affirms that digital literacy is as fundamental as reading, writing, and math. Stakeholders in education describe digital literacy as a foundation that everyone needs, AI literacy as a major core component of digital literacy, and CS as a discipline that contributes computational concepts and practices to strengthen AI literacy. Taken together, the United States needs a comprehensive national digital literacy skills framework with measurable outcomes, and aligned systems and policies that integrate digital literacy, AI literacy, and CS.

The National Literacy Trust defines “literacy as the ability to read, write, speak and listen in a way that lets us communicate effectively and make sense of the world.” For decades, literacy has been a key indicator of a community’s well-being. Research shows that higher literacy rates correlate with better economic opportunity, improved health, greater access to education, and expanded life choices. Improving literacy has been the underpinning of United Nations Educational, Scientific and Cultural Organization's (UNESCO) Sustainability Goals, which acknowledge the fact that eradicating poverty and hunger cannot occur without literate populations.

Digital literacy builds on this core understanding of literacy. This term was introduced in 1997 by Paul Gilster, who described it as “the ability to understand and use information in multiple formats from a wide range of sources when it is presented via computers.” As technologies have evolved, so has the definition of digital literacy. UNESCO defines it as “a means of identification, understanding, interpretation, creation, and communication in an increasingly digital, text-mediated, information-rich and fast-changing world.” Common Sense Media, Technology in Education (ISTE) and the Association for Supervision and Curriculum Development (ASCD), and K–12 education systems expanded the definition to include privacy and security, social competencies such as respectful communication, civic engagement, and digital citizenship.

National Digital Inclusion Alliance (NDIA) recommends the American Library Association’s (ALA) definition of digital literacy: “the ability to use information and communication technologies to find, evaluate, create, and communicate information, requiring both cognitive and technical skills.” Other thought leaders like the European Commission’s DigCom, DQ Institute, and Mozilla describe digital literacy as interconnected literacies that include media, visual, computer, information, and communication literacies, encompassing collaboration, problem-solving, and creativity.

In short, these definitions of digital literacy vary depending on the audience, but they consistently center five areas: technical skills, information skills, citizenship and safety, everyday functional skills, and cognitive and social competencies. Despite the recognition that these skills are essential, the United States lacks a national framework and system for measuring digital literacy, making it challenging to set clear expectations, improve progress, and advocate for sustained investments in comprehensive digital literacy education for all.

GenAI, a type of AI that can create new content, has sparked both excitement and trepidation in education. In late 2022, the initial public release of ChatGPT triggered a massive surge in public awareness that rapidly accelerated research, practice, policy activity, and industry interest in AI in education. Since then, reports and research from organizations such as Bellwether, RAND, Digital Promise, Kapor Foundation, Common Sense Media, UNESCO, Organisation for Economic Co-operation and Development (OECD), EdSafe AI Alliance, Stanford Accelerator for Learning, State Educational Technology Directors Association (SETDA), National Institute of Standards and Technology, Alliance for Learning Innovation Coalition, and UC Irvine have examined genAI’s opportunities, challenges, and perils across K–12 practice, policy, equity, PD, governance, infrastructure, data, frameworks, research gaps, and learner outcomes.

In April 2025, the Trump administration released the “Advancing Artificial Intelligence Education for American Youth” executive order and issued guidance for use in schools in July 2025—formal federal commitments to expanding AI’s role in classrooms, and supporting accelerating AI adoption across the education system. These are coupled with repeated federal government attempts to block states from regulating AI.

With all the activity, confusion is mounting over how AI literacy, digital literacy, and even CS [1] relate, and where each one begins and ends. Practitioners in particular are left unsure how to connect existing efforts with new opportunities, how to prepare, what to prioritize, or how to scaffold to best meet the needs of their students.

Although all three terms address how humans engage with technology, they entered through different pathways. Digital literacy is mostly rooted in digital equity, media literacy and information literacy, and edtech communities. CS gained traction through state standards and coding for all efforts.

AI literacy has mostly arrived via the tech industry, workforce narratives, and AI policy debates. Industries recognize that AI is changing how America works, learns, and competes. Findings from the Jobs to the Future survey indicate that AI use in the workforce has risen significantly, yet more than half of workers say they don’t feel prepared to use AI in their jobs similar to gaps in teacher training. Additionally, narratives from the tech industry focus on preparing people for an AI-powered economy and competitiveness, and market AI literacy as future-ready skills for workforce readiness. Proponents of CS education have embedded AI within CS frameworks. The AI policy debates have ranged from data privacy and student protections, equity and access, and bias in datasets to environmental impact.

While important for industry to emphasize AI as necessary for workforce development and for the CS field to incorporate AI into CS standards, these narratives can unintentionally overshadow the critical need for digital literacy. Without a strong digital literacy foundation, the broader skills required for lifelong learning, civic engagement, and workplace success are weakened. The draft Empowering Learners for the Age of AI: An AI Literacy Framework for Primary and Secondary Education by OECD and European Commission (funded by Code.org) offers helpful guidance on how educators can engage, create, manage, and design with AI in the classroom. However, despite its clarity on AI-specific competencies, digital literacy is rarely mentioned. This can leave practitioners asking how the AI framework connects with existing standards, curricula, and PD tied to digital literacy, digital citizenship, media literacy, or CS, and the foundational skills assumed. For example, are students expected to already know how to search, evaluate resources, protect privacy, or use digital tools?

To gain a better understanding of these issues in the context of public education, we interviewed 12 stakeholders including community practitioners, researchers, and experts from national and international nonprofits. While we recognize that perspectives may differ from those not interviewed, there is agreement among those interviewed that AI literacy must be integrated, equitable, and grounded in human-centered learning, and not solely driven by industry agendas.

Interviewees emphasized that AI literacy is an extension of digital literacy and not a separate or competing domain. June Ahn from UC Irvine, Pati Ruiz from Digital Promise, and Ji Soo Song from SETDA describe digital literacy as a broad foundation that everyone needs, AI literacy as a core component of digital literacy, and CS as a discipline that contributes computational concepts and practices to strengthen AI literacy. They, and others, stress the importance of strengthening foundational digital literacy skills before layering advanced AI concepts. Amy Huffman from NDIA agreed, saying “AI literacy is a natural extension of digital literacy. Digital literacy is incomplete if it doesn’t include AI.”

Even with broad agreement that AI literacy is core and falls within the digital literacy umbrella, its purpose varies depending on how AI tools are being used. Some describe it as knowing how to use AI applications to complete tasks, while others emphasize a deeper conceptual and cognitive shift AI introduces. Ahn said, “We still need all the foundation skills, but because AI makes it easier to create products, how we assess or understand if someone has certain literacy skills needs to change.” For example, Ahn no longer assigns final papers to his graduate students. Instead students submit a draft paper, and the final exam in class is critiquing other students’ work. This shows how learning is being reassessed in an age of AI. It is no longer the product that is being assessed, but the meta-skills such as critical thinking, reasoning, and analysis.

The need to reimagine assessments was also raised by others. Interviewees emphasized the absence of clear outcomes and measurement systems for AI literacy. There is no widely accepted definition of proficiency or guidance on how to assess AI-related skills. To understand what works and for whom, research needs to be at the forefront, stressed Isabelle Hau from Stanford Accelerator for Learning, who underscored the need to invest in understanding the impact of AI on learning while frameworks and teacher training are being implemented.

Many also raised deep concerns about AI’s impact on student well-being and human connection. Andy Rotherham from Bellwether emphasized the need for healthy relationships with technology, warning that risks in AI may be more troubling than cell phone usage. Amina Fazlullah from Common Sense Media said, “Kids spending more time with artificial companions has huge implications. We’re unleashing tools we don’t understand.”

Despite the growing use of AI in schools, there is a lag between responding to AI’s rapid development by industry and community readiness, whether this is hesitation or gaps in training and policy. Commercialization is also heightening concerns about trustworthiness in AI products. In some cases, frameworks and models are being introduced without addressing underlying learning goals, and emerging faster than the capacity to adopt or see a use for. “It’s the Wild West. There are currently no safety nets,” said Fazlullah.

Across the board, interviewees voiced equity concerns. They warned that AI will deepen inequity unless implementation is intentional and grounded in community realities. “AI will be used more heavily in lower-income schools. It may be more efficient but less human-centered, and affluent kids will get better and richer learning,” said Rotherham. A recent RAND report indicates that teachers in the lowest-poverty schools were more likely than their counterparts in higher-poverty schools to report using AI tools for planning or teaching. Fazlullah noted, “Parents of color are more hopeful about AI’s benefits—but their kids are most harmed by weak guardrails and discipline disparities.”

Furthermore, Victor Villegas of Oregon State University who teaches digital literacy in Indigenous and Native American communities finds that current genAI products are not culturally reflective. However, he notes that AI offers meaningful opportunities if designed responsibly: “AI can help level the playing field—translation, accessibility, tutoring—if it is guided, safe, and culturally grounded.” Without reliable access to devices and broadband at home and school, rural, Tribal, and low-income communities in particular are cut off from these opportunities.

Interviewees also noted that this is an opportunity and responsibility for states and districts to set standards for safety, efficacy, and transparency. Stakeholders underscored the need for locally adaptable, inclusive approaches rather than one-size-fits-all frameworks. Flexible models are needed that can be tailored to community contexts, learner needs, and policy environments. Yuhyun Park from DQ Institute, who works globally, emphasized the importance of “meeting countries [communities] where they are.” Ruiz pointed to Digital Promise’s multiple modes of engagement to accommodate various entry points for learners, and Song acknowledged that states operate at different paces and under different mandates, and the importance of meeting students and families where they are.

Locally, teachers and librarians are already meaningfully advancing AI and digital literacy. For example, the public library in Pottsboro, Texas, a town of 7,000 people, illustrates grassroots ingenuity. The library, run by volunteers and donations, was about to close because of lack of funding. Instead, volunteer development director Dianne Connery realized that focusing on digital literacy as an essential service the town could not live without was the answer. They received funding for an e-sport team and digital navigators for telehealth and hired teens to collect data on water and sewage to improve their town. They embed AI literacy as a tool to create resumes and alt text, and support civic engagement. Today, the library has a paid director and resources for a new library building through taxpayer funding.

Finally, interviewees described the current AI and digital literacy landscape as complex and fragmented. There are multiple overlapping and emerging frameworks ranging from international, national, state, and district that when combined with competing priorities make it challenging to develop coherent policies and practices. However, there is broad recognition the field needs shared definitions, principles, and guidance that connect a continuum from identifying problems and strengthening foundational digital literacy, to recognizing AI literacy as core, designing responsible solutions, and supporting implementation, evaluation, and continuous improvement.

Overview

New America’s Teaching, Learning, and Tech program hosted a roundtable of students and educators in spring 2025 in order to (1) to understand the level of digital literacy among students and educators, and (2) explore the curricula and resources needed for more meaningful digital learning.

The roundtable brought together five students and five educators from diverse districts to discuss their experiences with technology, the status of digital literacy instruction, and the skills they believe students and educators need to succeed in school, work, and life.

Participants were asked guiding questions about how technology supports or complicates their lives, which digital literacy skills they view as essential, where they currently gain these skills, and how well prepared they feel for academic and professional settings. They also reflected on how existing instruction aligns with recognized frameworks such as the Global Standards for Digital Intelligence. Across the board, participants emphasized the importance of core digital literacy skills and expressed ongoing concerns about access, training, and the rapid rise of AI tools.

Key Findings

Digital Literacy as a Core Competency

Students and educators agreed that digital literacy is inseparable from skills such as problem solving, critical thinking abilities, and adaptability. Skills like learning new software, evaluating online information, and navigating unfamiliar systems translate directly to real-world flexibility and independent problem solving. As one teacher noted, “The skills that really matter aren’t just technical—they’re durable skills like critical thinking and problem-solving. It’s less about whether students know how to use a specific tool and more about whether [students] have the thinking skills to apply to any tool.”

One recurring barrier noted by participants is the assumption by educators that today’s K–12 students who were born into a digital world already possess digital competence. As one educator said, “Sometimes educators fall into this trap of just assuming that they [students] will just pick these things up…but just because you’ve grown up around the technology doesn’t mean you know how to use it appropriately and professionally.”

Gaps in Educator Preparation and PD

Participants said that many educators themselves lack robust digital literacy skills, limiting their ability to integrate digital tools into instruction, teach digital skills effectively, and engage safely and confidently with technology. Students echoed this and shared that their “teachers have varying levels of technology knowledge.” Educators added that much of what they know about digital tools comes from informal learning—self-teaching through YouTube, experimenting on their own, or turning to colleagues for help. While educators reported that PD has begun to increase, largely in response to AI’s rapid entry into classrooms, they agreed that far more training is needed before teachers feel equipped to use AI responsibly and meaningfully.

Several noted a structural challenge, echoing a recent SETDA report: PD tends to prioritize curriculum-focused training over innovation-focused training. As a result, educators who receive PD on emerging technologies, including AI, are often those outside the core four subjects of math, reading/English/language arts, science, and social studies, leaving many classroom teachers without the preparation needed to integrate AI into their core instruction.

Ongoing Barriers to Accessing Broadband and Devices

Participants emphasized that students cannot meaningfully develop digital literacy skills without reliable access to broadband internet and devices. COVID-era programs—such as the Emergency Connectivity Fund and Affordable Connectivity Program—temporarily expanded connectivity, but many have since expired. Districts now face challenges in maintaining equitable access.

The digital divide remains one of the biggest barriers to digital literacy development, especially for students in rural and Tribal communities where internet access is limited or nonexistent. One educator described a student from a rural reservation who had never been taught how to use a software program due to lack of connectivity: “She was just trying to figure out the basics—things many take for granted with a stable internet. It made me wonder how many students are simply expected to know how to access their classes and keep up.” This educator also underscored a core tension: State and national standards increasingly assume digital literacy, yet many students still lack the basic connectivity needed to meet those expectations.

Digital Literacy Gaps Undermining AI Literacy

Participants stressed that fundamental digital literacy, especially the ability to evaluate and responsibly engage with digital content, is essential for responsible AI use. While students increasingly reported using platforms like Canva AI, NotebookLM, and MagicSchool, many lack the skills to assess AI-generated content for bias, accuracy, or responsible use. One educator noted that students are given access to AI tools without instruction on safety, verification, or responsible use. Another educator working with Indigenous communities emphasized that many AI systems embed colonial assumptions, raising concerns about cultural appropriation and misinformation.

Educators said that current AI literacy efforts are often superficial, focusing on tool usage rather than the underlying competencies required for responsible engagement. Both students and teachers suggested that training tends to prioritize applications over critical understanding, which educators note can result in students engaging passively with material, accepting AI outputs without question, and misusing tools to complete work without comprehension. While students may know how to use AI as a tool, they may not possess the digital literacy skills to evaluate its outputs, question its biases, or understand the responsible implications of its use.

To deepen our understanding of how states are supporting digital literacy instruction, New America conducted a 50-state scan [2] and organized findings into four domains: digital literacy frameworks, AI literacy frameworks, instructional support, and broadband access. These domains were combined into a single Digital Literacy Skills Score for each state. The descriptions below summarize the criteria used for each domain. A full list of resources—including standards, initiatives, programs, and frameworks considered—can be found here. Broadband data was drawn from the FCC National Broadband Map in August 2025.

Note: This 50-state scan was conducted in June and July 2025, a period of significant transition following the federal cancellation of the U.S. Department of Commerce’s Digital Equity Grants. These grants were intended to support a wide range of digital equity initiatives, including major planned improvements to digital literacy instruction.

Digital Literacy Frameworks

For the purposes of this 50-state scan, digital literacy frameworks are broadly defined, encompassing initiatives that directly target digital literacy, skills, and citizenship [3], and are related to competencies in media, technology, and information literacy. While many states have some form of framework, the landscape remains uneven. In many cases, digital literacy is embedded within broader technology or digital learning plans and not a standalone statewide priority.

We analyzed the extent to which states met the criteria by examining the following:

Direct digital literacy framework: States with dedicated frameworks, policies, or curricula for digital literacy, skills, and citizenship qualified. States also qualified if digital literacy competencies were integrated into English language arts (ELA), CS, or artificial intelligence frameworks.

Indirect digital literacy framework: States without explicit digital literacy frameworks including related competencies—media, information or technology literacy—as either standalone guidance or woven into existing curricula qualified.

Frameworks updated since 2020: Federal COVID-19 relief prompted many states to revise their digital literacy frameworks to support remote learning. Updates after 2020 signal a commitment to maintaining current and emerging digital learning needs. Both direct and indirect standards were considered.

Frameworks updated since 2023: The rise of genAI prompted additional updates in some states. States met this criterion if they updated frameworks—direct or indirect—to reflect new technologies and classroom realities.

Alignment with best practices: States met this criterion if their frameworks referenced or were informed by research-based models from organizations such as ISTE + ASCD, Common Sense Media, the DQ Institute, CSForAll, Code.org, Cyber.org, National Council of Teachers of English, ALA, or Common Core State Standards.

AI Literacy Frameworks

AI literacy framework: States qualified if they had dedicated AI literacy frameworks or policies, incorporated AI literacy into AI guidance documents, or embedded AI literacy concepts in ELA, CS, or social studies standards. AI literacy includes understanding how AI functions, recognizing benefits and risks, and using AI tools safely and effectively.

Educator-specific AI guidance: While many states publish general AI guidance for government agencies, fewer provide guidance tailored specifically to educators. States met this criterion if their departments of education offered educator-focused resources, such as written guidance, webinars, or PD training on AI.

Instructional Support

Tailored online PD platforms: States met this criterion if they offered online PD platforms created, commissioned, or tailored by the state department of education. Third-party vendor platforms qualified if they were state-commissioned; simple collections of external link lists did not.

PD offerings in digital literacy: States qualified if their PD platforms included courses, webinars, or in-person training on digital literacy, skills, or citizenship.

Dedicated edtech leadership roles: States met this criterion if they had at least one state-level staff member responsible for advancing edtech initiatives and serving as a point of contact for districts, educators, and partners.

Dedicated edtech teams: States qualified if the state department of education maintained an edtech team, signaling systemic commitment and capacity to keep pace with emerging technologies.

Broadband Access

Broadband service to 90 percent of residential buildings: States met this criterion if more than 90 percent of residential buildings had access to wired or licensed fixed wireless broadband at speeds equal to or faster than 100 mbps for uploading and 20 mbps for downloading, the FCC benchmark for reliable online learning, browsing, video conferencing, and streaming.

The 50-state scan below (Figure 1) assessed each state’s fulfillment of the four domains (digital literacy framework, AI literacy framework, instructional support, and broadband access) and converted findings into a combined Digital Literacy Skills Score ranging from 1 to 12.

Approximately one-third of the states (Arizona, Kentucky, Massachusetts, Maryland, North Carolina, North Dakota, New Hampshire, Nevada, Oklahoma, Oregon, South Carolina, Utah, and Virginia) have Digital Literacy Skills Scores of 11 or 12, demonstrating strong activity across most or all domains. States with the lowest Digital Literacy Skills Scores (Arkansas, West Virginia), of 5 or below, indicate limited AI or digital literacy frameworks and low levels of broadband access and instructional support.

Most states indicated some level of support for digital literacy frameworks and instructional support. Interestingly, California, Idaho, and Kansas score relatively high on digital literacy frameworks, but low to none for instructional support.

Comparisons across domains revealed differences in priorities. Hawaii, Michigan, and West Virginia appear to prioritize AI literacy over digital literacy, while Texas, Iowa, Tennessee, and Vermont showed strong digital literacy activity, but limited engagement in AI literacy.

We also examined per-pupil spending related to Digital Literacy Skills Scores. Maryland, Massachusetts, North Dakota, New Hampshire, Oregon, and South Carolina had relatively high scores (11 or 12), and high per-pupil spending. Mississippi, North Carolina, and Utah achieved high scores despite low per-pupil spending, suggesting that strategic prioritization may contribute significantly to progress in digital literacy and AI readiness.

Digital literacy skills in education are as fundamental as reading, writing, and math. Yet despite decades of evolving definitions and widespread agreement on its importance, and state and district efforts, the United States lacks a comprehensive national framework, measurable outcomes, and systems and policies to ensure all young people develop digital literacy skills needed in school, work, and life. The rapid emergence of genAI intensified the gaps in digital literacy, uneven access to technology, and lack of culturally relevant content and tools, and the need for community-driven ecosystems. While AI offers transformative opportunities in education for teaching, assessment, accessibility, and personalized learning, its rapid acceleration has policymakers, educators, learners, researchers, technologists, and others scrambling to respond to immediate risks such as data privacy and student safety while also building the sustainable infrastructure needed for responsible edtech innovation and resilience. Without reinforcing the importance of foundational digital literacy skills, AI risks can deepen inequities rather than alleviating them.

Confusion is also growing over how digital literacy, AI literacy, and CS relate. Practitioners in particular are left unsure how to connect existing efforts with new opportunities, how to prepare, what to prioritize or how to scaffold to best meet the needs of their students. Educator and student focus group participants alike stressed that fundamental digital literacy, especially the ability to evaluate and responsibly engage with digital content, is essential for responsible AI use. Similar to a SETDA report, participants noted that many current AI literacy efforts focus on how to use the tool rather than the underlying competencies required for responsible engagement. As a result, students may learn to use AI but lack the digital literacy skills to evaluate outputs, question biases, or understand responsible implications of their use.

While important to emphasize AI as necessary for workforce development and to incorporate AI into CS standards, these narratives on their own can (1) make it challenging for teachers to build on their current efforts and realities, and (2) de-emphasize the foundational digital literacy skills such as information literacy, digital citizenship, online safety, accessibility, and evaluation of digital content that are essential for lifelong learning, civic engagement, and workplace success.

These findings point to the need in education for coherent, community-led approaches that integrate digital literacy, AI literacy, and CS rather than treating them as siloed priorities. The five recommendations below are aimed at strengthening digital literacy teaching and learning in ways that are equity-centered and grounded in the experiences of educators, students, and communities.

• Establish a comprehensive, national framework for digital literacy with AI literacy as a core component, and CS as a discipline that contributes computational concepts and practices to strengthen AI literacy.
  • Districts, states, and communities should develop coherent frameworks that articulate digital literacy, AI literacy, and CS as interconnected and mutually reinforcing, and in context of existing standards, curricula, and practices tied to digital literacy and CS. Frameworks should be updated regularly, grounded in research-based models, and adaptable to local contexts.
• Invest in sustained, high-quality educator PD.
  • Educators need ongoing PD that builds confidence and competence in teaching digital literacy and AI-related skills across all subjects. States and districts should invest in PD platforms, AI-specific guidance, instructional coaching, and dedicated edtech leadership to ensure that educators can safely and effectively integrate age-appropriate digital literacy in the classroom. These efforts need to acknowledge or update existing PD tied to digital literacy and CS.
• Close access gaps in broadband and devices.
  • Universal connectivity and device access remain a prerequisite for any kind of online engagement. Ensure that underserved areas such as rural, Tribal, and low-income communities receive sustained investment in broadband expansion, device programs, and technical support. Without equitable access, advances in AI-enabled tools risk exacerbating rather than reducing opportunity gaps.
• Center equity, safety, and human well-being in adoption and governance of digital literacy, particularly AI literacy components.
  • Prioritize transparency, culturally informed design, privacy protections, and safeguards against bias and harm, especially for communities disproportionately impacted by digital surveillance and algorithmic bias.
• Invest in research and evaluation, and coherent measurement systems.
  • Invest in rigorous research to understand what works, for whom, and under what conditions. Establish indicators that are aligned with broader learning goals to track progress, guide resource allocation, and support continuous improvement. States and districts should build/update systems for monitoring implementation, measuring student outcomes, and sharing promising practices across communities.

[1] For the purposes of this brief, "digital skills” are the technical abilities required to use devices, software, and digital tools. “Digital literacy” builds on these skills by adding the critical, reflective, and contextual competencies needed to navigate, evaluate, and create in digital environments. Together, “digital literacy skills” integrate both technical proficiency and critical engagement. “AI literacy”—the ability to understand, use, and critically engage with AI systems in informed and responsible ways—is a core component of digital literacy. “Computer science” focuses on the study of computers and computational systems used to solve problems.

[2] For the purposes of the scan, digital literacy skills = digital literacy + AI literacy + instructional support + broadband access.

[3] Although terms are sometimes used interchangeably, digital skills describe technical use; digital literacy adds critical understanding and context; and digital citizenship further emphasizes ethical, safe, and community-oriented behavior in digital spaces.