Course Details in 2024/25 Session

Module Title	LM Applied Data Science for Learning Environments
School	Educational Enterprise
Department	Wiley
Module Code	03 37057
Module Lead	Richard Mason/Jon Watkins
Level	Masters Level
Credits	10
Semester	Semester 1 or 2
Pre-requisites
Co-requisites
Restrictions	None
Exclusions
Description	Data science offers the ability to assimilate and disseminate complex data structures, making sense of a wide range of effects. Education is a data rich field in the web age, providing learners with vast numbers of interactions with apps, online tests, and online materials. Directly studying the effects of these artefacts is often very difficult, and data science offers methods of finding out “what actually happened” from the data, allowing developers and designers the opportunity to improve the use of technology, and aid students in their learning goals. This module offers students the ability to appreciate the utility of data science within education.
Learning Outcomes	By the end of the module students should be able to: Critically understand and apply summary statistics. Critically understand and apply summary machine learning to breakdown data. Use appropriate data science technologies to summarise and visualise data stories. Understand and apply ethics of data. Appreciate data science techniques for learning and education.
Assessment	37057-01 : Report : Coursework (70%) 37057-02 : Presentation : Coursework (30%)
Assessment Methods & Exceptions	Assessment 1 x Report-based analysis of a dataset providing insight into an education based phenomenon (1500 words) (70%) 1 x Communicate and present a data story to an alternative audience (30%) Reassessment Re-submission of failed elements
Other
Reading List