META

This module has two components: Research Methods and Game Analytics and Responsible Innovation,

each of which is assessed separately.

The Research Methods component trains researchers in qualitative and quantitative games research

methods, including reproducibility, open science, and the use of York’s extensive facilities for

eye-tracking, brain imaging, and physiological data capture. Joint critique of papers outside the

researchers’ home disciplines develops a shared appreciation for differing epistemologies across

disciplines. researchers are assessed on a research paper reporting game data collected and analysed

by them.

In the Game Analytics and Responsible Innovation component, researchers work with large games

industry data sets, for example Dota 2, to learn principles of data wrangling, exploration, prediction,

machine learning, and data visualisation in week 1. Using innovative methods like design fiction,

researchers will then extrapolate potential ethical and societal ramifications of such games research

work (e.g. security, privacy), and apply responsible innovation frameworks like AREA to unpack how

they can anticipate, reflect, and engage with these ramifications in their work. researchers are assessed

on a data collection and responsible innovation plan for their PhD project.

The Methods and Data Module provides the interdisciplinary skills researchers need to be successful

and responsible researchers working with games.

Subject Content:

• Specify and justify a research question

• Collect qualitative and quantitative data, including game generated data, to address a research question

• Explore, analyse and visualise data appropriately

• Write up a study in the expected format for an academic publication

• Identify and consider ethical and societal ramifications of research, and apply responsible innovation frameworks to anticipate, reflect, engage with, and act on ramifications

Academic and Graduate Skills:

• Conduct a literature search and critique papers in terms of validity and rigour

• Prepare and deliver a substantial oral presentation on their work aimed at game designers or other industry stakeholders

• Identify and plan for future research training needs

• Understand principles and good practices of open science and reproducible research and apply them to your respective research

• Cairns, P. and Cox, A.(eds), Research Methods in HCI, CUP, 2008

• Cairns, P., Doing Better Statistics in Human Computer Interaction, CUP, 2019. • 

• Seif El-Nasr et al. (eds.): Game Analytics – Maximizing the Value of Player Data. Springer, 2013.

• Drachen, Mirza-Babaei, Nacke (eds), Games User Research, OUP, 2018