Module Code - Title:
SO4021
-
DATA LITERACY FOR THE 21ST CENTURY
Year Last Offered:
2025/6
Hours Per Week:
Grading Type:
N
Prerequisite Modules:
Rationale and Purpose of the Module:
This module provides a foundation for students to understand data in the modern world. Data is increasingly the capital of contemporary society and is foundational for both science and industry. The module focuses primarily on social data, how and why it is generated, how it is used, and how it can be used to explain important processes in economics, geography, history, political science, psychology and sociology. It does however also consider issues of data linking and how social and non-social data can be combined in powerful ways. Specific attention will focus on the different types of data that exist, how it is controlled and accessed, the different forms that it takes, and how this constrains and enables different types of analytic strategies.
Syllabus:
Topics covered in this module include:
What is data and why is it important?
Data in the Raw - How do we collect and disseminate data
Accessing data: Understanding locks and keys
Ensuring data integrity - What is 'dirty' data, what does it mean to 'clean' data and what are the implications of this
Data cleaning - How do we clean data and how does this depend upon research strategies and objectives
From data to data sets - how do we merge and combine data into logical and accessible systems and structures
Triaging data - How does one "vet" one's data, use simple statistics as diagnostic tools, and what exactly one should do when encountering issues
Summarizing data
Visualizing data - how to use graphics to show data properties
Data and popular media - how is data used or misused in popular media, particular new organizations
Learning Outcomes:
Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
On successful completion of this module, students will be able to:
Demonstrate an understanding of what data is in the social sciences
Demonstrate an understanding of the wide variety of data types and how this is connected to particular types of disciplines and the questions at their core
Demonstrate an understanding of how data is controlled and either accessible, partially accessible, or inaccessible
Demonstrate an understanding of the role of IT in the dissemination of data
Demonstrate an understanding of the translational activities that make data useful for social science
Affective (Attitudes and Values)
On successful completion of this module, students will be able to:
Demonstrate an appreciation of how social science data reflects real world processes and the lived experiences of people
Demonstrate an appreciation of how data is connected to power and can serve to enrich or undermine people's lives
Demonstrate an appreciation of the need for empathy and reflexivity when thinking about data and how it might be used
Psychomotor (Physical Skills)
On successful completion of this module, students will be able to:
Students will leave the course with enhanced analytic skills related to basic principles in data science
Students will have enhanced analytic capacities related to the translational activities that translate information into data
How the Module will be Taught and what will be the Learning Experiences of the Students:
The module will be a combination of lectures and tutorials. The lectures will provide an overview of the key concepts and skills related to each stage of the module. The tutorials will all involve hands on exercises in data collections, data management, data translation, and data analysis. Specific attention will focus on how different types of disciplines collect and analyse different types of data and the tutorial exercises will be tailored to their chosen major (and minor) field of study.
Research Findings Incorporated in to the Syllabus (If Relevant):
Prime Texts:
David Herzog (2015)
Data Literacy: A User's Guide
, Sage
Other Relevant Texts:
Andrew Bell and colleagues (2019)
Making sense of data in the media
, Sage
Donald Kettl (2017)
Little Bites of Big Data for Public Policy
, Sage
Ira Silver (2019)
Seeing Social Problems: The Hidden Stories Behind Contemporary Issues
, Sage
Programme(s) in which this Module is Offered:
BSSOSCUFA - SOCIAL SCIENCES
Semester(s) Module is Offered:
Autumn
Module Leader:
denis.maher@ul.ie