#datafication

In a civilisation that has rendered time a unit of economic calculation and attention a monetisable extract, we must ask: what becomes of being when it is no longer allowed to dwell in duration, but instead is continuously summoned to perform, react, and produce data for unseen ends? Photo by KATRIN BOLOVTSOVA on Pexels.com The human subject, once grounded in temporal interiority, reflexive…

The year is 2025. For an average human living in the territories dressed with internet cables, the day starts by grabbing the smartphone and consuming whatever the algorithm has to offer. From grocery shopping to becoming a millionaire overnight through crypto trades, everything seems possible from behind the screen. Societies are increasingly shaped by the very algorithms that dictate behaviors, tastes, and desires. From the frenzy of aesthetic surgery trends to the instantaneous viral success of products, from the commodification of reality to the proliferation of memes, we have become subjects of a culture where everything is recontextualized, reshaped, and hyper-real. Our daily lives and social habits are shaped by the algorithm we constantly labor to. The lines between the real and the simulated blur further, as Baudrillard whispers from the early days of the internet, "We live in a world where there is more and more information, and less and less meaning." (Baudrillard 1994:79). Here, meaning becomes a construct of virtuality, a mere image or simulation of the real. As our perception of reality becomes distorted in an AI-mediated fashion, whose pace of progress is beyond our perception of the pace of living, the human condition and social order are caught in a tension between the expectations of a world driven by accelerating technological advancements and the limitations of societies struggling to keep up. The contemporary condition whispers to us to either try and stay relevant or stay out of the picture. But even then, salvation is not guaranteed. In fact, nothing is guaranteed except the increasing quest for the relentless advance of an unchecked, accelerationist future. 

Press Release – Tuesday, 09th December 2025: The Global South Alliance, a coalition of 26 digital rights organizations, launched today the second edition of the “Datafication and Democracy Fund” on December 9. The Fund will provide more US$ 72,000 to support research and advocacy projects focused on datafication and democracy to be implemented in 2026. The Datafication and Democracy Fund was…

In the evolving educational landscape, leveraging datafication for effective learning analytics is a game-changer. Educators and institutions now have the ability to turn vast streams of educational data into meaningful insights that enhance learner engagement, optimize outcomes, and refine instructional design.

Introduction to Datafication and Learning Analytics

Leveraging datafication for effective learning analytics involves transforming educational activities into quantifiable data. This empowers educators to track student progress, identify patterns, and intervene with precision. Rather than hoping for learning improvements, datafication enables strategic measurement and targeted support that align with core instructional objectives.

The Role of Datafication in Education

Datafication converts learning actions—such as resource usage and interaction timestamps—into measurable inputs. Through learning analytics, these inputs inform trends and identify obstacles. When educators ask how leveraging datafication for effective learning analytics works, they uncover ways to transform raw interactions into actionable intelligence, enhancing decision-making across pedagogical levels.

Driving Personalization with Learning Analytics

Incorporating datafication allows for highly individualized learning paths. Educators can analyze learners’ progress in real time to adjust pacing, recommend resources, and tailor feedback. This capability turns one-size-fits-all instruction into a flexible, learner-centered journey, where each student receives support tailored to their unique needs and pace.

Data-Driven Feedback Loops and Adaptive Learning

When datafication fuels learning analytics, feedback loops become dynamic. Analytics can highlight where a learner struggles and trigger adaptive content adjustments or timely intervention. Rather than static instruction, this approach nurtures continuous improvement and engagement through real-time responsiveness.

Improving Outcomes through Behavior Insights

Analyzing data patterns—like time spent on tasks, submission behaviors, or resource preferences—lets educators predict who may fall behind or succeed. Leveraging datafication for effective learning analytics enables early detection of disengagement and empowers educators to support learners with precision before challenges escalate.

Ethical Considerations in Learning Data

While datafication opens doors to deeper insight, ethics and privacy must remain central. Transparent data use policies, informed consent, and secure handling ensure that analytics support learners respectfully. Responsible practices safeguard trust while fully enabling the benefits of data-driven strategies.

Building Institutional Capacity for Analytics

To truly benefit from datafication in learning analytics, institutions need robust infrastructure. This includes training educators in data literacy, integrating analytics tools into workflows, and using data insights to drive policy and curricular improvements. Investments in capacity foster a sustainable, evidence-based learning ecosystem.

For More Info https://bi-journal.com/leveraging-datafication-for-effective-learning-analytics/

Conclusion

The persistence of political regimes founded upon the calculated disempowerment of critical intelligence is neither incidental nor anomalous; it constitutes, in fact, a necessity within the architecture of post-democratic populism. If the first part of this post has sought to expose how populist logic systematically restructures public discourse, institutional credibility, and the very grammar…

Data increasingly forms the backbone of systems and processes that shape how we do things and how we relate to each other. Datafication – the uptake of data to reorganize social processes – is reshaping everything from loyalty programs and digital identification systems to credit card payments and rental pricing platforms. Artificial intelligence accelerates these processes.

Making sense of what these changes mean for our everyday lives is no easy task. Datafied systems are highly technical and designed to be convenient and seamless; we tend to encounter them in brief moments of individualized transaction, which makes them difficult to see, let alone read, and their illegibility makes them very challenging to respond to. Communing Data Literacy offers a novel set of concepts and tools to help people make sense of how technology is altering their communities and their social interactions. Building on three years of design research by digital rights organizations in Chile, Colombia, Paraguay, Peru, and Uruguay, the volume analyzes people’s everyday experiences with datafication, rethinking data from the perspective of community and offering practical techniques for community engagement.

This week, our class benefitted from a guest lecture from Instagram sewing influencer, @pinkmimosabyjacinta, which really put the readings on the datafication of influencer work in context. Jacinta made clear how she balances her time online with her real day job due to the fact that she largely treats influencing as a hobby rather than as a way to make money. The readings opened up a vigorous class discussion later in the week, wherein we analyzed some examples of fashion influencers and bloggers. Students noted a number of ways beyond social media in which our lives are quantified and made into data. It is my hope this sets students up for some thoughtful engagement with our second documentary film of the semester next week.

The first book to draw a direct line between the datafication and prediction techniques of past eugenicists and today's often violent and extractive "big data" regimes. Predatory Data illuminates the throughline between the nineteenth century's anti-immigration and eugenics movements and our sprawling systems of techno-surveillance and algorithmic discrimination. With this book, Anita Say Chan offers a historical, globally multisited analysis of the relations of dispossession, misrecognition, and segregation expanded by dominant knowledge institutions in the Age of Big Data. While technological advancement has a tendency to feel inevitable, it always has a history, including efforts to chart a path for alternative futures and the important parallel story of defiant refusal and liberatory activism. Chan explores how more than a century ago, feminist, immigrant, and other minoritized actors refused dominant institutional research norms and worked to develop alternative data practices whose methods and traditions continue to reverberate through global justice-based data initiatives today. Looking to the past to shape our future, this book charts a path for an alternative historical consciousness grounded in the pursuit of global justice.