Algorithmic Gatekeeping in Digital Education

Welcome to this Open Educational Resource (OER) on Algorithmic Gatekeeping and the Future of Knowledge. 

In an era where artificial intelligence systems increasingly mediate access to information, understanding the dynamics of visibility and epistemic authority becomes crucial. Jen Ross (2023) emphasises that speculative methods can challenge the invisibility and inevitability of data in education, encouraging educators and learners to critically engage with the systems that shape knowledge dissemination. ​

Drawing on the core themes of the digital futures for learning, visibility, interface, and sustainability, this OER critically examines how digital infrastructures, especially algorithmic curation, challenge traditional forms of epistemic authority. Ross's work on speculative methods provides a framework for questioning and reimagining the role of data-driven technologies in educational contexts. ​

Throughout the modules, you’ll reflect on how knowledge was curated in the past, analyse how AI shapes visibility in the present, and envision more equitable futures for digital education. This OER is not about resisting technology; it’s about reclaiming the values that underlie meaningful education and asserting our collective role in shaping what comes next.

Let’s begin this journey by understanding where we’ve come from, so we can better decide where we’re going.

By the end of this Open Educational Resource (OER), you will have developed a critical understanding of how AI-driven algorithms are reshaping the way knowledge is curated, made visible, and legitimised within digital education. You will examine who holds authority over knowledge in the digital era, how information is filtered and ranked, and the broader implications of algorithmic gatekeeping for education and society.

This OER will help you to:

• Trace the historical evolution of knowledge gatekeeping, from traditional institutions such as universities, publishers, and media organisations, to today's algorithmically curated digital platforms.
  
  

• Analyse how algorithms curate information, prioritising, filtering, or suppressing content based on metrics such as engagement, virality, and commercial value.
  
  

• Understand the role of epistemic control, and how power structures determine what is seen as credible, trustworthy, and worth preserving in educational contexts.
  
  

• Examine the impact of algorithmic visibility, particularly how platforms like search engines, social media, and recommendation systems shape what learners see, learn, and engage with.
  
  

• Critique digital literacy in the age of AI, and develop strategies to engage critically with algorithmic content, including recognising bias, misinformation, and content removal.
  
  

• Engage with futuring methods in education, imagining possible futures where algorithmic curation either supports or undermines knowledge accessibility, diversity, and scholarly integrity.

This OER is designed to take approximately three hours to complete. The time is spread across a variety of activities to support a balanced experience of reading, exploration, listening, writing, and reflection.

• 📖 Reading & Exploration (60 minutes)
  Engage with key open-access readings and explore both historical and digital archives related to knowledge gatekeeping.
  
  

• 🎧 Listening & Watching (30 minutes)
  Watch short videos that introduce key concepts and case studies on visibility and algorithmic filtering.
  
  

• 📝 Writing & Discussion (45 minutes)
  Respond to guided questions, write short reflections, and view or contribute to peer responses using collaborative tools.
  
  

• 🔎 Critical Thinking & Analysis (45 minutes)
  Compare historical and algorithmic models of gatekeeping, reflect on real-world examples, and draw informed conclusions.

 Before you begin, take a moment to consider your own learning habits in the digital age. These questions are designed to prompt initial reflection and prepare you to engage critically with the ideas in this OER:

• In what ways do you think AI influences what you learn online?
  Consider how recommendation algorithms and search results shape your exposure to ideas, content, and perspectives.
  
  

• How much do you rely on online resources for your own learning?
  Reflect on the platforms, tools, or websites you use to gather knowledge—and how much you trust them.
  
  

• To what extent do you trust what you read and see on the internet?
  Think especially about social media platforms that push short-form content—how do they affect your sense of credibility, accuracy, or bias