Reading week
There will be no lecture in reading week. Instead you will work individually on preparing for the second half of the unit.
Choose one article from the list below which feels interesting. Take notes on what you read so you can use it to support your later work in the unit.
Reflect on our three practical experience: GenAI, data visualisation and AR/VR. Which did you enjoy most? Which is most valuable for education?
Review what we have studied so far on the unit. Discuss with other students (if possible) in order to identify your technology to focus on for the assignment. This can be one of our case studies or something else entirely.
- Big Data Comes to School: Implications for Learning, Assessment, and Research
- Learning Analytics: the Emergence of a Discipline
- Multimodal Learning Analytics and Education Data Mining: Using Computational Technologies to Measure Complex Learning Tasks
- Learning Analytics: at the Nexus of Big Data, Digital Innovation, and Social Justice in Education
- The data-doppelganger and the cyborg-self: theorising the datafication of education
- Critical Data Studies: A Dialog on Data and Space
- Is it Paranoia? A Critical Approach to Platform Literacy
- Let’s not forget: Learning analytics are about learning
- New research problems and agendas in learning, media and technology: the editors’ wishlist
- Logo in Mainstream Schools: The struggle over the soul of an educational innovation
- Who owns educational theory? Big data, algorithms and the expert power of education data science
- Machine behaviourism: future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies
- The challenges of platform capitalism: understanding the logic of a new business model
- 'Hypernudge': Big Data as a mode of regulation by design
- Digital education governance: data visualization, predictive analytics, and ‘real-time’ policy instruments
- Achieving big data privacy in education
- Algorithmic paranoia and the convivial alternative
- The production of prediction: What does machine learning want?
- Thinking critically about and researching algorithms
- 'Hypernudge': Big Data as a mode of regulation by design
- Decoding ClassDojo: psycho-policy, social-emotional learning and persuasive educational technologies
- Learning analytics and AI: Politics, pedagogy and practices
- Amazon and the New Global Connective Architectures of Education Governance
