The U.S. Department of Justice introduced the Americans With Disabilities Act final rule for digital accessibility in 2024, requiring public colleges and universities to follow Web Content Accessibility Guidelines for ensuring that online programs, services and activities are accessible. These laws require institutions to update inaccessible documents and ensure new content follows accessibility requirements.
A recent survey by Anthology found that faculty members feel they lack sufficient support and access to resources to create an accessible online classroom environment, and they have a general lack of awareness of new ADA requirements.
Anthology’s survey—which included responses from 2,058 instructors at two- and four-year colleges and universities across the U.S.—highlights a need for professional development and institutional resources to help faculty meet students’ needs.
Supporting student success: Expanding accessibility isn’t just mandated by law; it has powerful implications for student retention and graduation outcomes.
Approximately one in five college students has a disability, up 10 percentage points from the previous decade, according to 2024 data from the U.S. Government Accountability Office. A majority of those students have a behavioral or emotional disability, such as attention deficit disorder, or a mental, emotional or psychiatric condition.
While a growing number of students with disabilities are enrolling in higher education, they are less likely than their peers without a disability to earn a degree or credential, due in part to the lack of accessibility or accommodations on campus.
Survey says: Only 10 percent of faculty believe their institution provides “absolutely adequate” tools to support students with disabilities, and 22 percent say they consider accessibility when designing course materials.
Instructors are largely unaware of the ADA’s Web Content Accessibility Guidelines; one-third of survey respondents said they are “not at all” aware of the requirements, and 45 percent said they were aware but “unclear on the details.”
When asked about the barriers to making course content accessible, faculty members pointed to a lack of training (29 percent), lack of time (28 percent) and limited knowledge of available tools (27 percent) as the primary obstacles.
A lack of awareness among faculty members can hinder student use of supports as well. A 2023 survey found that only about half of college students are aware of accessibility and disability services, though 96 percent of college staff members said the resources are available.
In Anthology’s survey, 17 percent of instructors said they were unaware of what tools their institution provides to help students access coursework in different formats, and 30 percent said they were aware but didn’t share information with students.
Less experienced faculty members were more likely to say they haven’t considered accessibility or were unaware of ADA requirements; one-third of respondents with fewer than two years of teaching experience indicated they rarely or never consider accessibility when creating materials.
One in four faculty members indicated more training on best practices would help them make their digital content more accessible, as would having the time to update and review course materials.
Improving accessibility: Some colleges and universities are taking action to empower faculty members to increase accessibility in the classroom and beyond.
The University of North Dakota in spring 2023 created an assistive technology lab, which trains faculty and staff members to make course resources accessible. The lab, led by the university’s Teaching Transformation and Development Academy, offers access to tech tools such as Adobe Acrobat Pro and the screen-reader software Job Access with Speech, for course content development. Lab staff also teach universal design principles and conduct course reviews, as needed.
The State University of New York system created the SUNY Accessibility Advocates and Allies Faculty Fellowship program in January, designating 11 fellows from across the system to expand digital accessibility and universal design for learning practices at system colleges. Fellows will explore strategies to build a culture of access, share expertise and experience, connect with communities of practice, and design a plan to engage their campus community, among other responsibilities.
The University of Iowa built a new digital hub for accessibility-related resources and information, providing a one-stop shop for campus members looking for support. The university is also soliciting questions from users to build out a regularly updated FAQ section of the website. Iowa has a designated Accessibility Task Force with 10 subcommittees that address various applications of accessibility needs, including within athletics, communication, health care, student life and teaching.
Colorado State University has taken several steps to improve community compliance for accessibility, including offering free access to Siteimprove, a web-accessibility assessment tool that helps website developers and content managers meet accessibility standards and improve digital user experience. Siteimprove offers training resources to keep users engaged in best practices, as well as templates for creating content, according to CSU’s website. The university also has an accessibility framework to help faculty members bring electronic materials into compliance.
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Your students are already running to AI for answers. The only question is — what’s it saying about your institution? More importantly, are you in the conversation or being left out? If you’re not actively shaping how your school shows up in AI-driven search and decision-making platforms, you’re not just invisible — you’re irrelevant.
Digital Darwinism in Higher Ed: Adapt Your Marketing for AI — or Get Left Behind Date: May 29, 2025 Time: 2:00 p.m. ET / 1:00 p.m. CT
In this webinar, Collegis Education’s Ashley Nicklay, Sr. Director of Marketing, and Jessica Summers, Director of Web Strategy, will unpack what “AI-ready” really means for higher ed marketing and enrollment leaders.We’ll explore how generative AI influences the student journey from search to selection, why most websites and content strategies are falling short, and what forward-thinking institutions are doing to lead the algorithm, rather than get buried by it.
This isn’t just about better SEO or smarter ads. It’s about understanding how AI evaluates your institution — and making sure you’re feeding it the right data, signals, and story to stay in the game.
What You’ll Learn
How AI impacts the early stages of the enrollment journey: Understand how tools like ChatGPT and Google’s AI Overviews influence what students see when exploring colleges.
Why AI prompt bias is real — and how to beat it: Learn how content, structured data and reputation shape AI responses.
What AI actually sees when it looks at your website (and what it may miss): Explore how site structure, clarity and technical markup shape what AI-based tools can find and summarize – and what they may overlook.
What it really means to have an AI-optimized website: We’ll show you our checklist of what your .edu needs to show up in AI-generated answers.
How to future-proof your marketing model in an AI-driven search landscape: Assess your current channels and content strategy for resilience as search becomes more conversational and less click-based.
Future-Ready Starts Here: Secure Your Spot
The institutions that will thrive tomorrow are learning how to market to machines today.Reserve your seat and find out what it takes to survive the AI era of higher ed marketing.
Complete the form on the right to reserve your spot.
Finding accurate information has long been a cornerstone skill of librarianship and classroom research instruction. When cleaning up some materials on a backup drive, I came across an article I wrote for the September/October 1997 issue of Book Report, a journal directed to secondary school librarians. A generation ago, “asking the librarian” was a typical and often necessary part of a student’s research process. The digital tide has swept in new tools, habits, and expectations. Today’s students rarely line up at the reference desk. Instead, they consult their phones, generative AI bots, and smart search engines that promise answers in seconds. However, educators still need to teach students the ability to be critical consumers of information, whether produced by humans or generated by AI tools.
Teachers haven’t stopped assigning projects on wolves, genetic engineering, drug abuse, or the Harlem Renaissance, but the way students approach those assignments has changed dramatically. They no longer just “surf the web.” Now, they engage with systems that summarize, synthesize, and even generate research responses in real time.
In 1997, a keyword search might yield a quirky mix of werewolves, punk bands, and obscure town names alongside academic content. Today, a student may receive a paragraph-long summary, complete with citations, created by a generative AI tool trained on billions of documents. To an eighth grader, if the answer looks polished and is labeled “AI-generated,” it must be true. Students must be taught how AI can hallucinate or simply be wrong at times.
This presents new challenges, and opportunities, for K-12 educators and librarians in helping students evaluate the validity, purpose, and ethics of the information they encounter. The stakes are higher. The tools are smarter. The educator’s role is more important than ever.
Teaching the new core four
To help students become critical consumers of information, educators must still emphasize four essential evaluative criteria, but these must now be framed in the context of AI-generated content and advanced search systems.
1. The purpose of the information (and the algorithm behind it)
Students must learn to question not just why a source was created, but why it was shown to them. Is the site, snippet, or AI summary trying to inform, sell, persuade, or entertain? Was it prioritized by an algorithm tuned for clicks or accuracy?
A modern extension of this conversation includes:
Was the response written or summarized by a generative AI tool?
Was the site boosted due to paid promotion or engagement metrics?
Does the tool used (e.g., ChatGPT, Claude, Perplexity, or Google’s Gemini) cite sources, and can those be verified?
Understanding both the purpose of the content and the function of the tool retrieving it is now a dual responsibility.
2. The credibility of the author (and the credibility of the model)
Students still need to ask: Who created this content? Are they an expert? Do they cite reliable sources? They must also ask:
Is this original content or AI-generated text?
If it’s from an AI, what sources was it trained on?
What biases may be embedded in the model itself?
Today’s research often begins with a chatbot that cannot cite its sources or verify the truth of its outputs. That makes teaching students to trace information to original sources even more essential.
3. The currency of the information (and its training data)
Students still need to check when something was written or last updated. However, in the AI era, students must understand the cutoff dates of training datasets and whether search tools are connected to real-time information. For example:
ChatGPT’s free version (as of early 2025) may only contain information up to mid-2023.
A deep search tool might include academic preprints from 2024, but not peer-reviewed journal articles published yesterday.
Most tools do not include digitized historical data that is still in manuscript form. It is available in a digital format, but potentially not yet fully useful data.
This time gap matters, especially for fast-changing topics like public health, technology, or current events.
4. The wording and framing of results
The title of a website or academic article still matters, but now we must attend to the framing of AI summaries and search result snippets. Are search terms being refined, biased, or manipulated by algorithms to match popular phrasing? Is an AI paraphrasing a source in a way that distorts its meaning? Students must be taught to:
Compare summaries to full texts
Use advanced search features to control for relevance
Recognize tone, bias, and framing in both AI-generated and human-authored materials
Beyond the internet: Print, databases, and librarians still matter
It is more tempting than ever to rely solely on the internet, or now, on an AI chatbot, for answers. Just as in 1997, the best sources are not always the fastest or easiest to use.
Finding the capital of India on ChatGPT may feel efficient, but cross-checking it in an almanac or reliable encyclopedia reinforces source triangulation. Similarly, viewing a photo of the first atomic bomb on a curated database like the National Archives provides more reliable context than pulling it from a random search result. With deepfake photographs proliferating the internet, using a reputable image data base is essential, and students must be taught how and where to find such resources.
Additionally, teachers can encourage students to seek balance by using:
Print sources
Subscription-based academic databases
Digital repositories curated by librarians
Expert-verified AI research assistants like Elicit or Consensus
One effective strategy is the continued use of research pathfinders that list sources across multiple formats: books, journals, curated websites, and trusted AI tools. Encouraging assignments that require diverse sources and source types helps to build research resilience.
Internet-only assignments: Still a trap
Then as now, it’s unwise to require students to use only specific sources, or only generative AI, for research. A well-rounded approach promotes information gathering from all potentially useful and reliable sources, as well as information fluency.
Students must be taught to move beyond the first AI response or web result, so they build the essential skills in:
Deep reading
Source evaluation
Contextual comparison
Critical synthesis
Teachers should avoid giving assignments that limit students to a single source type, especially AI. Instead, they should prompt students to explain why they selected a particular source, how they verified its claims, and what alternative viewpoints they encountered.
Ethical AI use and academic integrity
Generative AI tools introduce powerful possibilities including significant reductions, as well as a new frontier of plagiarism and uncritical thinking. If a student submits a summary produced by ChatGPT without review or citation, have they truly learned anything? Do they even understand the content?
To combat this, schools must:
Update academic integrity policies to address the use of generative AI including clear direction to students as to when and when not to use such tools.
Teach citation standards for AI-generated content
Encourage original analysis and synthesis, not just copying and pasting answers
A responsible prompt might be: “Use a generative AI tool to locate sources, but summarize their arguments in your own words, and cite them directly.”
In closing: The librarian’s role is more critical than ever
Today’s information landscape is more complex and powerful than ever, but more prone to automation errors, biases, and superficiality. Students need more than access; they need guidance. That is where the school librarian, media specialist, and digitally literate teacher must collaborate to ensure students are fully prepared for our data-rich world.
While the tools have evolved, from card catalogs to Google searches to AI copilots, the fundamental need remains to teach students to ask good questions, evaluate what they find, and think deeply about what they believe. Some things haven’t changed–just like in 1997, the best advice to conclude a lesson on research remains, “And if you need help, ask a librarian.”
Dr. Steve Baule is a faculty member at Winona State University (WSU), where he teaches in the Leadership Education Department. Prior to joining WSU, Baule spent 28 years in K-12 school systems in Illinois, Indiana, and Iowa, and two years teaching in the University of Wisconsin System. For the 13 years prior to moving to the university level, Baule served as a public -school superintendent. He has written 10 books on a variety of educational and historical topics and has served on the editorial boards for two journals. Baule earned an advanced diversity and equity certificate while in the UW system. He holds a doctorate in instructional technology from Northern Illinois University and a doctorate in educational leadership and policy studies from Loyola University Chicago.
Baule’s scholarly interests focus on online student engagement, educational technology– particularly the impact of 1:1 implementations, social-emotional learning, and the history of education. Baule led several efforts to improve student emotional health and reduce discipline issues prior to moving into higher education. He also writes on aspects of early American history.
Baule has held memberships in the American Association of School Administrators, the American Library Association, the American Association of School Librarians, the Association for Supervision and Curriculum Development, the Consortium for School Networking, the International Association of School Librarians, the National Association of Secondary School Principals, the National Staff Development Council, and many of their state affiliates. He has served as a consultant in the areas of educational technology, facilities design, library program development, team building, and communications.
Latest posts by Steven M. Baule, Ed.D., Ph.D. (see all)
The way higher institutions define and acknowledge student success in higher education today is changing rapidly. Today, diplomas and transcripts are no longer the benchmarks for measuring the success rate of students in their academics. To define success, you have to consider a complete and holistic journey and vision. Factors like the student’s academic excellence, mental and physical growth, and preparation for what comes next are increasingly becoming key to defining academic success. This is why universities are looking beyond enrolment figures, they are now more focused on helping their students thrive academically, socially, and professionally.
This brings us to the role of modern digital marketing tactics and advanced CRM tools. Colleges can create an environment that supports every student with the right resources they need to succeed, using the data-driven outreach and personalized support that these tools offer. In this blog post, we’ll explore the true meaning of student success and what key metrics are best placed to measure student success in higher education. We’ll also show you how marketing automation and CRM platforms (including HEM’s own Mautic for Education and Student Portal) can help drive real student achievement. Read on to find out what strategies and tools are best suited to define modern student success.
Looking for an all-in-one student information and CRM solution tailored to the education sector?
Try the HEM Student Portal!
Redefining Student Success Metrics in Higher Education: Beyond GPAs and Graduation Rates
Who you ask about the definition of academic success will also determine the type of answer you get. Administrators might lean towards metrics and retention rates. Students tend to have a more personal definition of success, like having supportive mentors, developing confidence, and building lasting connections.
This brings us to the question: What is the definition of student success? The definition of student success encompasses building communication skills and critical thinking activities, career or grad school readiness. In essence, a successful student grows through campus life, engages with the community, and adequately prepares themself for future opportunities.
Below are components of a comprehensive student success definition:
Academic Achievement: Mastering course material and maintaining strong GPAs
Persistence and Retention: Continuing enrolment term after term until graduation
Personal Development: Cultivating critical thinking, communication skills, and emotional intelligence
Engagement and Belonging: Finding community through meaningful campus involvement
Career Readiness: Building the confidence and skills needed for post-graduation success
As EDUCAUSE, a prominent education technology organization, points out, student success programs “promote student engagement, learning, and progress toward the student’s own goals through cross-functional leadership and the strategic application of technology.” This reaffirms the fact that true success calls for a harmonious relationship between human connection and technology.
Measuring What Matters: The Metrics of Achievement
How do we truly and correctly measure student success if we say that there are many sides to it? What is the definition of a successful student, and how to measure student success in higher education? While this question has intrigued higher educational professionals for decades, today’s schools are finding the right answers by combining traditional metrics and emerging indicators.
Traditional measurements include retention rates (are students returning each semester?), graduation rates (are they completing their degrees?), and academic performance (are they mastering the material?).
Now, these numbers matter. They help us tell to a reasonable degree if students are progressing toward their educational goals, or not. However, there’s a richer story to be told beyond these statistics, and you’ll learn about it shortly.
Student success metrics commonly include:
Retention Rates: The percentage of students who return for subsequent terms
Graduation Rates: How many students complete their degrees within expected timeframes
Academic Performance: Beyond grades—how students grow intellectually over time
Student Engagement: Participation in everything from research opportunities to campus events
Student Satisfaction: Feedback that reveals how students experience their education
Post-Graduation Outcomes: Career placement, graduate school acceptance, and alumni achievements
Away from these quantifiable measures, today’s schools value the essence of student-defined success. For them, it could be a first-generation student finding their voice, an international student building cross-cultural friendships, or a working parent balancing studies with family life. The schools that manage to combine statistical trends with individual stories will ultimately get the most complete picture of things.
Examples: ULM developed FlightPath, an open-source advising system for degree audits, early alerts, and “What If?” planning. It is designed to help you determine your progress toward a degree.
What do marketing strategies have to do with student success? What does digital marketing contribute to student success? Higher education marketing and student success are interconnected through a series of key touchpoints.
The path to college student success often begins with that first Instagram post that catches a high school junior’s eye or that personalized email that addresses their specific interests. It is all part of the coordinated digital marketing campaigns that today’s schools employ, to great success.
Attracting the right-fit students: When marketing materials paint an authentic picture of campus culture, incoming students arrive with realistic expectations and are more ready to engage.
Personalized communication: Tailored messages that speak to individual aspirations create early connections. When a prospective engineering student receives content about robotics competitions or research labs, they begin envisioning their place in your community.
Seamless onboarding: The summer before freshman year can be overwhelming. Automated campaigns that introduce new students to campus resources, share advice from current students, and foster peer connections help transform nervousness into excitement.
Feedback loops: Savvy marketing teams don’t just broadcast – they listen. Social media monitoring and regular surveys help identify pain points before they become barriers to success.
Examples: Gonzaga’s English Language Center moved from siloed data to a Student Success CRM on Salesforce, improving collaboration and early-alert capabilities for ESL learners.
Customer Relationship Management (CRM) systems are now important tools for tracking and supporting the student journey, especially in today’s data-driven world. These platforms present themselves as centralized hubs that help schools track student progress, identify potential challenges, and carry out timely interventions.
Colleges can transform how they engage with students at every stage using the right CRM. Take this scenario for example: A first-year student misses out on many classes and fails to log into the learning management system for two weeks. While this might have gone on without being detected in the past, probably until midterm grades showed a significant gap, not anymore. With a CRM, a trigger will set off based on this pattern and send automatic alerts to the students’ advisor, who can now contact support resources to arrest the decline before it further spirals.
Example: King’s College uses CRM Advise to flag risk factors, like missed classes, and automatically route alerts to advisors and support centers.
Here are six ways CRM tools elevate student success in higher education:
Centralizing the 360° Student View: Modern CRMs integrate data from admissions, advising, financial aid, and student life to create comprehensive student profiles. When an advisor can see that a struggling student is also working 30 hours weekly, they can provide more targeted support.
Enabling Early Alerts: By analyzing patterns like missed assignments or decreased LMS activity, CRMs can identify at-risk students before a crisis develops.
Automating Support Workflows: Smart CRMs ensure consistent communication throughout the student journey. From congratulatory messages when students ace exams to gentle nudges when they miss classes, automated workflows maintain continuous engagement without overwhelming staff.
Providing Data-driven Insights: Institutions can analyze which interventions are best-suited to promote student success, using comprehensive data collection.
Streamlining Administrative Processes: By simplifying registration, financial aid processes, and advising appointments, CRMs eliminate frustrating barriers that might otherwise derail student progress.
Promoting Community: Many platforms include features that connect students with mentors, study groups, and support communities. These all help to nurture the sense of belonging that anchors students during challenging times.
With solutions like Mautic by HEM, schools can enjoy robust CRM and marketing automation tailored specifically for them. The platform provides a central hub where you can manage all of your leads, applicants, agents, and parent contacts, enabling personalized support throughout the student lifecycle.
Example: Michael Vincent Academy, a Los Angeles-based beauty school, sought to enhance its student recruitment efficiency by streamlining lead management and follow-up processes. With HEM’s Mautic CRM, the academy automated key marketing tasks and introduced lead scoring, enabling staff to focus on high-value prospects. This allowed the team to dedicate more time to building meaningful connections with prospective students, ultimately improving recruitment outcomes.
Source: HEM
HEM’s Student Portal combines online application creation and management, SIS functionality, and lead-nurturing tools in one centralized system. As a student, this is designed to help you manage your journey – from initial application to enrolment to graduation and beyond.
As a school, using these specialized tools can help you address your institution’s unique needs and leverage the capacity of generic CRMs.
Source: HEM
Example: Students at Western Michigan University (WMU) use the Student Success Hub’s CRM to schedule and manage appointments, review advising notes, work on success plans, and tasks.
One of the key ingredients of college student success is the use of structured programming that helps students navigate important stages of their academic journey. Many schools have found value in offering a student success class or course, such as a freshman seminar or “College 101” course that equips students with essential skills and connections.
What is a student success class in college? It’s a course designed to help students be successful in college. It aims to help students properly navigate both academic requirements and college culture. Here is a list of subjects that these classes typically cover:
Effective study strategies tailored to college-level expectations
Time management techniques for balancing academic and personal demands
Campus resource navigation, introducing students to everything from tutoring to counselling
Financial literacy skills to manage college costs
Stress management and wellness practices
Career exploration and professional development
Research continues to show that the students who complete these courses earn more credits and have a higher graduation rate than those who don’t participate.
The Power of Storytelling in Student Success Marketing
By channelling authentic storytelling into their marketing narratives, schools can connect with prospective and current students. Stories have a way of transforming abstract content as “retention initiatives” into relatable human experiences that inspire action.
What if you created a series featuring diverse student voices? Think of the impact it can have. Think of first-generation students who initially had doubts about themselves but connected with mentors who had faith in them, the transfer student who found unexpected opportunities, or the international student who calls the school home.
Not only do these narratives attract prospective students, but they remind the current ones that challenges are not special and that success is very much achievable.
Tips to Boost Student Success with Marketing and CRM
Institutions looking to take advantage of digital marketing and CRM tools more effectively should consider these practical strategies.
Use Data to Personalize Outreach: Segment your communications based on student interests, challenges, and milestones to provide relevant support throughout their journey.
Implement Early Alert Systems: Configure your CRM to identify warning signs like decreased engagement or academic struggles, enabling timely, personalized interventions.
Integrate Your Systems: Ensure your marketing automation, CRM, and student information systems communicate seamlessly for a complete view of each student’s experience.
Maintain Consistent Communication: Develop messaging flows that accompany students from prospective inquiry through graduation while remaining authentic and supportive.
Leverage Student Feedback for Content: Gather testimonials and success stories that inspire current students and set realistic expectations for prospects.
Train Your Team on Tools: Invest in comprehensive training so everyone, from admissions counselors to faculty advisors, can effectively use your CRM to support student success.
Example:GSU’s Student Success 2.0 initiative includes implementing an enterprise CRM for a unified student record and early-alert triggers to boost retention by up to 1.2 % annually, with the National Institute for Student Success (NISS) also set up to that effect.
Creating a Culture of Success: A Holistic Approach
The most effective approach to student success blends marketing insights, CRM capabilities, and human connections in one big package. With these elements working in harmony, institutions can create environments where students from all backgrounds can thrive.
Remember that behind every data point is a student with dreams, challenges, and unlimited potential. When you align marketing, technology, and support programs around a student-centred vision of success, you can get positive outcomes in return. We don’t just improve statistics, we transform lives and fulfill higher education’s fundamental promise.
Looking for an all-in-one student information and CRM solution tailored to the education sector?
Try the HEM Student Portal!
Frequently Asked Questions
Question: What is the definition of student success?
Answer: The definition of student success encompasses building communication skills and critical thinking activities, career or grad school readiness.
Question: How to measure student success in higher education?
Answer: While this question has intrigued higher educational professionals for decades, today’s schools are finding the right answers by combining traditional metrics and emerging indicators.
Question: What is a student success class in college?
Answer: It’s a course designed to help students be successful in college. It aims to help students properly navigate both academic requirements and college culture.
AI tools enhance K-12 creativity and innovation through interactive projects
A new era for teachers as AI disrupts instruction
Report details uneven AI use among teachers, principals
For more news on AI and creativity, visit eSN’s Digital Learning hub
As AI becomes more commonplace in classrooms, it gives students access to creative tools that enhance learning, exploration, and innovation. K-12 students can use AI tools in various ways to boost creativity through art, storytelling, music, coding, and more.
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In my work with middle school students, I’ve seen how critical that period of development is to students’ future success. One area of focus in a middle schooler’s development is vocabulary acquisition.
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Art has a unique power in the ESL classroom–a magic that bridges cultures, ignites imagination, and breathes life into language. For English Language Learners (ELLs), it’s more than an expressive outlet.
In the year 2025, no one should have to be convinced that protecting data privacy matters. For education institutions, it’s really that simple of a priority–and that complicated.
Teachers are superheroes. Every day, they rise to the challenge, pouring their hearts into shaping the future. They stay late to grade papers and show up early to tutor struggling students.
This season of Voices of Student Success, “Preparing Gen Z for Unknown Futures,” addresses challenges in readying young people for the next chapter of their lives in the face of large-scale global changes. The latest episode addresses how digitization has made it easier for young people to engage in unhealthy habits, including substance abuse, pathological gambling or social media addiction, compared to past generations.
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Gathering and assessing the quality of information is one of the most effective ways to develop media literacy, critical thinking and effective communication skills. But without guidance, too many young people fail to question the reliability of visual images and overly rely on the first results they find on Google.
That’s why News Decoder has been working with the Swedish nonprofit, Voice4You, on a project called ProMS to create a self-guided digital tool that guides students in writing news stories.
The tool, called Mobile Stories, is now available across Europe. It takes students step-by-step through the journalistic process. Along the way, they gain critical thinking skills and a deeper understanding about the information they find, consume and share.
It empowers students to develop multimedia stories that incorporate original reporting for school, community or global audiences, with minimal input from educators. It comes with open-access learning resources developed by News Decoder.
After a decade of success in Sweden, Voice4You partnered with News Decoder to help make the tool available across Europe and the globe. Throughout the ProMS project, new English language content suitable for high schoolers was developed and piloted in 21 schools in Romania, Ireland and Finland. The Mobile Stories platform has demonstrated remarkable potential in building student confidence and media and information literacy by providing a platform and an opportunity to produce quality journalism.
From story pitch to publication
Using the new international version of Mobile Stories, students have already published 136 articles on mobilestories.com, with another 700 currently in production. Their topics range from book reviews and reporting from local cultural events to in-depth feature articles on the decline in young people’s mental health and child labor in the fast fashion industry.
“The tool looks like a blogging platform and on every step along the way of creating an article, students can access learning materials including video tutorials by professional journalists from around the world, articles and worksheets,” said News Decoder’s ProMS Project Manager Sabīne Bērziņa.
Some of these resources, such as videos and worksheets are open access, available to all.
Our recent study (Zhou et al, 2025) surveyed 595 undergraduate students across the UK to examine the evolving digital divide across all forms of digital technologies. Although higher education is expected to narrow this divide and build students’ digital confidence, our findings revealed the opposite. We found that the gap in digital confidence and skills between widening participation (WP) and non-WP students widened progressively throughout the undergraduate journey. While students reported peak confidence in Year 2, this was followed by a notable decline in Year 3, when the digital divide became most pronounced. This drop coincides with a critical period when students begin applying their digital skills in real-world contexts, such as job applications and final-year projects.
Based on our study (Zhou et al, 2025), while universities offer a wide range of support such as laptop loans, free access to remote systems, extracurricular digital skills training, and targeted funding to WP students, WP students often do not make use of these resources. The core issue lies not in the absence of support, but in its uptake. WP students are often excluded from the peer networks and digital communities where emerging technologies are introduced, shared, and discussed. From a Connectivist perspective (Siemens, 2005), this lack of connection to digital, social, and institutional networks limits their awareness, confidence, and ability to engage meaningfully with available digital tools.
Building on these findings, this blog asks a timely question: as Generative Artificial Intelligence (GenAI) becomes embedded in higher education, will it help bridge this divide or deepen it further?
GenAI may widen the digital divide — without proper strategies
While the digital divide in higher education is already well-documented in relation to general technologies, the emergence of GenAI introduces new risks that may further widen this gap (Cachat-Rosset & Klarsfeld, 2023). This matters because students who are GenAI-literate often experience better academic performance (Sun & Zhou, 2024), making the divide not just about access but also about academic outcomes.
Unlike traditional digital tools, GenAI often demands more advanced infrastructure — including powerful devices, high-speed internet, and in many cases, paid subscriptions to unlock full functionality. WP students, who already face barriers to accessing basic digital infrastructure, are likely to be disproportionately excluded. This divide is not only student-level but also institutional. A few well-funded universities are able to subscribe to GenAI platforms such as ChatGPT, invest in specialised GenAI tools, and secure campus-wide licenses. In contrast, many institutions, particularly those under financial pressure, cannot afford such investments. These disparities risk creating a new cross-sector digital divide, where students’ access to emerging technologies depends not only on their background, but also on the resources of the university they attend.
In addition, the adoption of GenAI currently occurs primarily through informal channels via peers, online communities, or individual experimentation rather than structured teaching (Shailendra et al, 2024). WP students, who may lack access to these digital and social learning networks (Krstić et al, 2021), are therefore less likely to become aware of new GenAI tools, let alone develop the confidence and skills to use them effectively. Even when they do engage with GenAI, students may experience uncertainty, confusion, or fear about using it appropriately especially in the absence of clear guidance around academic integrity, ethical use, or institutional policy. This ambiguity can lead to increased anxiety and stress, contributing to wider concerns around mental health in GenAI learning environments.
Another concern is the risk of impersonal learning environments (Berei & Pusztai, 2022). When GenAI are implemented without inclusive design, the experience can feel detached and isolating, particularly for WP students, who often already feel marginalised. While GenAI tools may streamline administrative and learning processes, they can also weaken the sense of connection and belonging that is essential for student engagement and success.
GenAI can narrow the divide — with the right strategies
Although WP students are often excluded from digital networks, which Connectivism highlights as essential for learning (Goldie, 2016), GenAI, if used thoughtfully, can help reconnect them by offering personalised support, reducing geographic barriers, and expanding access to educational resources.
To achieve this, we propose five key strategies:
Invest in infrastructure and access: Universities must ensure that all students have the tools to participate in the AI-enabled classroom including access to devices, core software, and free versions of widely used GenAI platforms. While there is a growing variety of GenAI tools on the market, institutions facing financial pressures must prioritise tools that are both widely used and demonstrably effective. The goal is not to adopt everything, but to ensure that all students have equitable access to the essentials.
Rethink training with inclusion in mind: GenAI literacy training must go beyond traditional models. It should reflect Equality, Diversity and Inclusion principles recognising the different starting points students bring and offering flexible, practical formats. Micro-credentials on platforms like LinkedIn Learning or university-branded short courses can provide just-in-time, accessible learning opportunities. These resources are available anytime and from anywhere, enabling students who were previously excluded such as those in rural or under-resourced areas to access learning on their own terms.
Build digital communities and peer networks: Social connection is a key enabler of learning (Siemens, 2005). Institutions should foster GenAI learning communities where students can exchange ideas, offer peer support, and normalise experimentation. Mental readiness is just as important as technical skill and being part of a supportive network can reduce anxiety and stigma around GenAI use.
Design inclusive GenAI policies and ensure ongoing evaluation: Institutions must establish clear, inclusive policies around GenAI use that balance innovation with ethics (Schofield & Zhang, 2024). These policies should be communicated transparently and reviewed regularly, informed by diverse student feedback and ongoing evaluation of impact.
Adopt a human-centred approach to GenAI integration: Following UNESCO’s human-centred approach to AI in education (UNESCO, 2024; 2025), GenAI should be used to enhance, not replace the human elements of teaching and learning. While GenAI can support personalisation and reduce administrative burdens, the presence of academic and pastoral staff remains essential. By freeing staff from routine tasks, GenAI can enable them to focus more fully on this high-impact, relational work, such as mentoring, guidance, and personalised support that WP students often benefit from most.
Conclusion
Generative AI alone will not determine the future of equity in higher education, our actions will. Without intentional, inclusive strategies, GenAI risks amplifying existing digital inequalities, further disadvantaging WP students. However, by proactively addressing access barriers, delivering inclusive and flexible training, building supportive digital communities, embedding ethical policies, and preserving meaningful human interaction, GenAI can become a powerful tool for inclusion. The digital divide doesn’t close itself; institutions must embed equity into every stage of GenAI adoption. The time to act is not once systems are already in place, it is now.
Dr Lei Fang is a Senior Lecturer in Digital Transformation at Queen Mary University of London. Her research interests include AI literacy, digital technology adoption, the application of AI in higher education, and risk management. lei.fang@qmul.ac.uk
Professor Xue Zhou is a Professor in AI in Business Education at the University of Leicester. Her research interests fall in the areas of digital literacy, digital technology adoption, cross-cultural adjustment and online professionalism. xue.zhou@le.ac.uk
Digital transformation is an ongoing journey for higher education institutions, but there is something quite distinctive about the current moment.
The combination of financial uncertainty, changing patterns of student engagement, and the seismic arrival of artificial intelligence is pointing to a future for higher education learning and teaching and a digital student experience that will certainly have some core elements in common with current practice but is likely in many respects to look rather different.
At the moment I see myself and my colleagues trying to cling to what we always did and what we always know. And I really do think the whole future of what we do and how we teach our students, and what we teach our students is going to accelerate and change very, very quickly now, in the next five years. Institutional leader
Our conversations with sector leaders and experts over the past six months indicate an ambition to build consistent, inclusive and engaging digital learning environments and to deploy data much more strategically. Getting it right opens up all kinds of possibilities to extend the reach of higher education and to innovate in models for engagement. But future change demands different kinds of technological capabilities, and working practices, and institutions are saying that they are hindered by legacy systems, organisational silos, and a lack of a unified vision.
Outdated systems do not “talk to each other,” and on a cultural level as departments and central teams also do not “talk to each other” – or may struggle to find a common language. And rather than making life easier, many feel that technology creates significant inefficiencies, forcing staff to spend more time on administrative tasks and less on what truly matters.
I think the problem always is when we hope something’s going to make it more efficient. But then it just adds a layer of complexity into what we’re doing…I think that’s what we struggle with – what can genuinely deliver some time savings and efficiencies as opposed to putting another layer in a process? Institutional leader
In the spirit of appreciative inquiry, our report Capability for change – preparing for digital learning futures draws on a series of in depth discussions with leaders of learning and teaching, and digital technology, digital experts and students’ union representatives. We explore the sorts of change that are already in train, and surface insight about how institutions are thinking in terms of building whole-organisation capabilities. “Digital dexterity” – the ability to deploy technology strategically, efficiently, and innovatively to achieve core objectives – may be yet another tech buzzword, but it captures a sense of where organisations are trying to get to.
While immediate financial pressures may require cutting costs and reprofiling investment, long term sustainability depends on moving forward with change, finding ways, not to do more with less but to do things differently. To realise the most value from technology investment institutional leaders need to find ways to ensure that across the institution staff teams have the knowledge, the motivation and the tools to deploy technology in the service of student success.
How institutions are building organisational capability
Running through all our conversations was a tension, albeit a potentially productive one: there needs to be much more consistency and clarity about the primary strategic objectives of the institution and the core technology platforms and applications that enable them. But the effect of, in essence, imposing a more streamlined “central” vision, expectations and processes should be to enable and empower the academic and professional teams to do the things that make for a great student experience. Our research indicates that institutions are focusing on three areas: leadership and strategy; digital capabilities of institutional staff; and breaking down the vertical silos that can hamper effective cross-organisational working.
A number of reflections point to strategy-level improvements – such as ensuring there is strategic alignment between institutional objectives for student success, and technology and digital strategies; listening to the feedback from students and staff about what they need from technology; setting priorities, and resourcing those priorities from end to end from technology procurement to deployment and evaluation of impact. One institutional leader described what happens when digital strategies get lost in principles and forget to align with the wider success of the organisation:
The old strategy is fairly similar, I imagine, to many digital strategies that you would have seen – it talks about being user focused, talks about lean delivery, talks about agile methodologies, product and change management and delivering value through showing, not telling. So it was a very top level strategy, but really not built with outcomes at its absolute core, like, what are the things that are genuinely going to change for people, for students? Institutional leader
Discussions of staff digital capabilities recognised that institutional staff are often hampered by organisational complexity and bureaucracy which too often is mirrored in the digital sphere. One e-learning professional suggested that there is a need for research to really understand why there is a tendency towards proliferation of processes and systems, and confront the impact on staff workloads.
There may also be limits to what can reasonably be expected from teaching staff in terms of digital learning design:
You need to establish minimum benchmarks and get everyone to that place, and then some people will be operating well beyond that. You can be clear about basic benchmark expectations around student experience – and then beyond that you need to put in actual support [such as learning design experts] to implement the curriculum framework. E-learning professional
But the broader insight on staff development was around shifting from provision of training on how to operate systems or tools to a more context-specific exploration of how the available technologies and data can help educators achieve their student success ambitions. Value is more systematically created across the organisation when those academic and professional teams who work directly with students are able to use the technology and data available creatively to enhance their practice and to problem solve.
Where data has been used before it’s very much sat with senior colleagues in the institution. And you know it’s helped in decision making. But the next step is to try and empower colleagues at the coal face to use data in their day to day interventions with their students… How can they use the data to inform how they support their students? Institutional leader
Decisive leadership may be successful in setting priorities and streamlining the processes and technologies that underpin them; strong focus on professional development may engage and enable institutional staff. But culture change will come when institutions find ways to systematically build “horizontals” across silos – mechanisms for collaborative and shared activity that bridge different perspectives, languages and disciplinary and professional cultures.
Some examples we saw included embedding digital professionals in faculties and academic business processes such as recruitment panels, convening of cross-organisation thinking on shared challenges, and appointment of “change agent” roles with a skillset and remit to roam across boundaries.
Technology providers must be part of the solution – acting as strategic partners rather than suppliers. One way to do that is to support institutions to pilot, test, and develop proof of concept before they decide to invest in large-scale change. Another is to work with institutions to understand how technology is deployed in practice, and the evolving needs of user communities. To be a great partner to the higher education sector means having a deep understanding not only of the technological capabilities that could help the sector but how these might weave into an organisation’s wider mission and values. In this way, technology providers can help to build capability for change.
English/language arts and science teachers were almost twice as likely to say they use AI tools compared to math teachers or elementary teachers of all subjects, according to a February 2025 survey from the RAND Corporation that delves into uneven AI adoption in schools.
“As AI tools and products for educational purposes become more prevalent, studies should track their use among educators. Researchers could identify the particular needs AI is addressing in schools and–potentially–guide the development of AI products that better meet those needs. In addition, data on educator use of AI could help policymakers and practitioners consider disparities in that use and implications for equitable, high-quality instruction across the United States,” note authors Julia H. Kaufman, Ashley Woo, Joshua Eagan, Sabrina Lee, and Emma B. Kassan.
One-quarter of ELA, math, and science teachers used AI tools for instructional planning or teaching in the 2023–2024 school year. Nearly 60 percent of surveyed principals also reported using AI tools for their work in 2023-2024.
Among the one-quarter of teachers nationally who reported using AI tools, 64 percent said that they used them for instructional planning only, whether for their ELA, math, or science instruction; only 11 percent said that they introduced them to students but did not do instructional planning with them; and 25 percent said that they did both.
Although one-quarter of teachers overall reported using AI tools, the report’s authors observed differences in AI use by subject taught and some school characteristics. For instance, close to 40 percent of ELA or science teachers said they use AI, compared to 20 percent of general elementary education or math teachers. Teachers and principals in higher-poverty schools were less likely to report using AI tools relative to those in lower-poverty schools.
Eighteen percent of principals reported that their schools or districts provided guidance on the use of AI by staff, teachers, or students. Yet, principals in the highest-poverty schools were about half as likely as principals in the lowest-poverty schools to report that guidance was provided (13 percent and 25 percent, respectively).
Principals cited a lack of professional development for using AI tools or products (72 percent), concerns about data privacy (70 percent) and uncertainty about how AI can be used for their jobs (70 percent) as factors having a major or minor influence on their AI use.
The report also offers recommendations for education stakeholders:
1. All districts and schools should craft intentional strategies to support teachers’ AI use in ways that will most improve the quality of instruction and student learning.
2. AI developers and decision-makers should consider what useful AI applications have the greatest potential to improve teaching and learning and how to make those applications available in high-poverty contexts.
3. Researchers should work hand-in-hand with AI developers to study use cases and develop a body of evidence on effective AI applications for school leadership, teaching, and learning.
Laura Ascione is the Editorial Director at eSchool Media. She is a graduate of the University of Maryland’s prestigious Philip Merrill College of Journalism.
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