Big Ideas in Education: the Datafication of Education

Code School Level Credits Semesters
EDUC3041 Education 3 20 Autumn UK
Code
EDUC3041
School
Education
Level
3
Credits
20
Semesters
Autumn UK

Summary

In an age of ‘big data’ and data analytics, this module examines the ways in which the collection and analysis of education (and related) data has framed education policy and practice and how this might develop in the future.  The module examines this trend within the broader sweep of the ‘datafication’ of capitalist, neoliberal societies.  Such data is generated at international, national and organisational levels and education professionals and stakeholders irrespective of their role - need to develop the necessary quantitative literacy to read and critique these applications and trends.  This module will investigate some of the core principles of sampling, measurement and statistical variation. Importantly, these issues will be explored in the context of some of the most common forms of quantitative/quantifiable data use in contemporary education settings.  The module will also consider emerging innovations in data analytics that some enthusiasts predict might transform learning in the coming years.  Key contexts will include:

 

Target Students

This is a module on the BA Education programme and is open to all Year 2 (Part I) or Year 3 (Part II) Undergraduate students or Exchange students.

Classes

This module is taught through a combination of seminars and lectures.

Assessment

Assessed by end of autumn semester

Educational Aims

This module aims to:Introduce participants to some of the most common and influential uses of large scale data collection and analysis in education. Examine key applications of statistical method, data visualisation and analytics in educationUnderstand the role of 'datafication' in education governance and policyDevelop critical statistical literacy in the context of education case studiesConsider possible future applications of data analyticsto support learning

Learning Outcomes

A. Knowledge and understanding 
Students should demonstrate a critical understanding of: 
 

the complexity of the interaction between learning and local and global contexts, and the ways in which statistics and data analytics inform us of, and influence, these relationships.

the societal and organisational structures and purposes of educational systems, and the possible implications for learners and the learning process. 

B. Intellectual Skills 
Students will be able to demonstrate the ability to: 
 

analyse educational concepts, theories and issues of policy in a systematic way, in particular those evidenced and influenced through statistics and data analytics 

C.  Professional practical skills  
Students will be able to demonstrate that they can: 
 

use critical statistical literacy and quantitative research skills appropriate to the discipline of education:  

D.  Transferable (key) skills 
Students should be able to: 
 

organise and articulate opinions and arguments in speech and writing using relevant specialist vocabulary

collect, process and synthesise statistical and other quantitative data, to create new syntheses and to present and justify a chosen position having drawn on relevant theoretical perspectives 

Conveners

View in Curriculum Catalogue
Last updated 07/01/2025.