Course Details in 2026/27 Session

Module Title	LI Data Skills for the Digital World
School	Eng, Drama, & Creative Studies
Department	Eng Lang and Linguistics
Module Code	09 39274
Module Lead	Jason Grafmiller
Level	Intermediate Level
Credits	20
Semester	Semester 2
Pre-requisites
Co-requisites
Restrictions	None
Contact Hours	Seminar-10 hours Practical Classes and workshops-20 hours Guided independent study-170 hours Total: 200 hours
Exclusions
Description	This module introduces students to quantitative, data-oriented methods that are increasingly common in the study of language and the humanities, with an emphasis on the development of practical skills for students' future work at university and beyond. In the module, students examine why data analytic skills are important in fields such as linguistics, digital humanities, and other creative industries, and explore how these skills can be used in various applications. The module focuses on introducing data analysis and statistics in a way that is accessible to language and humanities students, and on getting students underway with analysis of their own data. The module also provides students with learning strategies for overcoming anxiety around programming and statistics. The module introduces students to the statistical programming environment \"R\", which is widely used in linguistics and other scientific fields. In both workshops and seminars, students will gain experience working with different kinds of data in R, and will be given the opportunity to collect their own data and create digital materials for effective \"data storytelling\" such as blogs or online dashboards. Students will learn how to create online content using reproducible workflows, documenting their work at each stage of data collection, analysis, and presentation.
Learning Outcomes	By the end of the module students should be able to: Demonstrate understanding of methods for collection and management of textual and quantitative data, including knowledge of methods in data annotation, open science principles, and data ethics Demonstrate working knowledge of common methods for exploratory analysis of various data types and the effective presentation and communication of both quantitative and qualitative information Demonstrate working knowledge of the statistical programming environment R Publish materials in a digital format, e.g. websites, dashboards, and online data/code repositories.
Assessment
Assessment Methods & Exceptions	Assessment: Summative assessment (100%): A project (equivalent to 3500 words) involving analysis of actual datasets collected by the student or provided by the module convenor. Students will publish the data, code and the results of their analysis in digital repository. The assessment will be split into several components: 25%: A written summary of the aims of the study (400 words max) 50%: Analysis of data using exploratory statistical methods, with a written description motivating the choice of methods (400 words max), as well as visual presentation of results using at least three tabular and/or graphical representations, with brief text descriptions (50 words max) 25%: Publication of the code that forms the basis of the analysis (equivalent of 400 words) Reassessment: Resubmission of research project
Other
Reading List