Interest in leveraging data from various technologies to enhance education is on the rise. Artificial intelligence now plays a pivotal role in this ‘datafied’ educational landscape, offering promises of organisational efficiency, precise pedagogical interventions, and enriched student experiences. However, data can be double-edged—it can drive positive change or cause harm; improve schools and universities or transform them into surveillance entities; empower individuals or challenge their freedoms.
This course equips you with the knowledge to effectively understand and manage educational data. It provides essential holistic perspectives to comprehend how data and technologies influence decision-making, from educational policy to everyday classroom activities. Gain insights into data production, processing, visualisation, governance, and application. Explore the political economy of datafication in education, the actors involved, and the tools used, while addressing discrepancies between datafication goals and actual practices.
Engage with cutting-edge research from critical data studies and AI to examine the impact of data-driven technologies on education. Learn key concepts and theories, immerse yourself in data creation and analysis, and gain experience in critically evaluating data-driven practices relevant to your professional context.
Keywords: Data production, data visualisation, data use, data governance, data privacy.
The Data course is organised in thematic blocks. These change in time as the course is continuously updated to accommodate the latest trends in educational practice, EdTech industry, and research. However, the themes always comprehensively cover the key processes of datafication in education.
We start with exploring the definitions and nature of data in education, as well as discussing different approaches to the study datafication. Our strategy in this course is to take the ‘critical data studies’ approach, which means that we recognise and investigate datafication as the social and technological set of processes rather than only technological. Data are never neutral. We are interested in power relations between different actors involved in datafication as we study the effects of datafication on people and organisations.
We then engage in data production and analysis, including investigating the nuances of data visualisations. You’ll learn about how data are used and how they support (or not) ideas of the personalisation of learning, precise teaching interventions, and efficient organisational governance. You’ll learn about data governance, including arrangements of data privacy and informed consent.
“I view this course as absolutely fundamental to any educator. Digital data are now everywhere; and everyone involved in education in any capacity should understand the fundamentals of data practices. My approach in this course is to bring together practical activities of engaging with data, working with data governance materials, and reflecting with the help of research and theory. This way, students learn from doing, making and thinking.”
- Janja Komljenovic, Course Organiser
The course provides a fruitful and productive combination of investigating cases and materials from the real world; and the latest research and theoretical insights. The course sets out a rich set of diverse activities. You’ll collect data yourself and produce data visualisations. You’ll analyse examples of data practices and visualisations from other organisations, including from the EdTech industry, international organisations, or policymakers. You’ll study data flows and explore data systems. Data policies, such as privacy policies and terms of use of different platforms will be examined.
You’ll have a chance to join live video calls with peers and course tutors. Most other activities are asynchronous so that you can engage in them at the time that suits you. The course facilitates peer interaction and learning from each other. Together, we also follow current news and discuss how the course fits into the current dynamics of datafication in education.
You’ll build your learning activities throughout the course and will receive formative feedback from course tutors along the way.
There are two assessments in this course:
Individual data collection strategy (50%):
The design, implementation, analysis, and evaluation of an individual data collection strategy. You’ll begin collecting data after the introductory teaching block. In each block, you’ll produce a visualisation and a short reflection on this activity. Visualisations will vary and might include producing data visualisaton, as well as sketches of data flows and data systems. You will maintain a record of this activity throughout the taught weeks of the course. This data portfolio will be submitted for assessment, along with a 1000-word accompanying essay reflecting on the process, analysing the results, and evaluating the implications for educational practice.
Digital essay (50%):
A ‘digital artefact’ final assignment, critically reflecting on a chosen theme from the course. The theme should be personally or professionally of interest to you. This will be a chance to explore a theme you choose in more detail. The submitted work may be multimodal and presented in a digital online format, in a form equivalent to a 2000-word essay. The assignment will demonstrate critical engagement with key concepts from the course, use of relevant and appropriate literature, and exhibit the construction of fitting academic discourse.
These assessments are intended to evaluate your understanding of different data practices and technologies, and their underlying philosophies. It is an opportunity for you to demonstrate that you can transform theoretical knowledge into a practical, coherent, and sound material output.
You will expand your expertise with this essential module. By the end, you'll understand how data and AI influence education, from governance to teaching. You'll critically assess research, apply insights practically, and engage with data collection and analysis. You’ll gain skills to discuss and evaluate key data issues, enhancing your academic and professional growth.
On completion of the course, you will be able to:
- Demonstrate a critical understanding of how data is defined, produced, analysed, and understood in educational contexts
- Exhibit a critical awareness of key data-driven technologies and practices as they relate to educational governance, institutional administration, and the activities of teaching and learning
- Identify and critically analyse published research
- Engage critically and creatively with practical approaches to data collection and analysis
- Effectively discuss, analyse, and evaluate key issues related to the use of data in education, demonstrating the conventions of academic discourse
Check out some of the material chosen by Dr Janja Komljenovic, the Course Organiser.
Readings:
Komljenovic, J., Sellar, S. & Birch, K. Turning universities into data-driven organisations: seven dimensions of change. High Educ (2024). https://doi.org/10.1007/s10734-024-01277-z
Selwyn, N. (2021). The human labour of school data: exploring the production of digital data in schools. Oxford Review of Education, 47(3), 353–368. https://doi.org/10.1080/03054985.2020.1835628
Williamson, B. 2017. Big Data in Education: the digital future of learning, policy and practice. Sage.
Project outputs:
http://www.dear-data.com/theproject
Data concepts:
Rob Kitchin’s guide to concepts and methods in critical data studies: https://polity-books-backend.prod.politybooks.wiley.host/wp-content/uploads/2024/12/KITCHIN-9781509566525-EPDF.pdf
Data solidarity glossary: https://dthlab.org/data-solidarity-glossary/
Podcasts:
Luci Pangrazio: https://podme.com/se/avsnitt/3566431
Janja Komljenovic: https://freshedpodcast.com/368-komljenovic/