This resource is a quiz-style lesson presentation focussed on the impacts of machine learning social media algorithms on society and individuals. It is an interdisciplinary resource covering topics from health and wellbeing, technology, data and social studies and is also relevant to the NPA Data Science Qualification Suite. The contents are suitable for learners aged around 12 upwards and relevant to all ages. About the resource content: The presentation covers the definitions of algorithms and machine learning then provides examples of both beneficial uses and ethical problems with their use. The content then focusses on applications to social media user retention. The aims of social media companies, the contributions of automated decision making to societal biases, inequalities, the promotion of dangerous content, polarisation and echo-chamber creation are some of the main topics covered. This resource allows students to develop their awareness of the dangers posed to themselves and others when using social media and encourages responsible and informed use of platforms. The downloadable pack of resources includes a quiz-style informational presentation, and word document containing duplicate content in plain text format. Curriculum Relevance: This interdisciplinary resource is recommended for and relevant to all ages 12 and upwards, and covers themes from health and wellbeing, technology and social studies. This pack may particularly be a useful teaching resource for the National Progression Award Data Science SCQF Levels 4,5 and 6, particularly the Machine Learning Optional Unit. The resource relates to aims 4 and 11 of the qualification to “stimulate interest in data science” and to “Raise awareness of the societal issues relating to data science including data ethics” respectively. The resource contains content focussed on non-technical data skills such as consideration of the impact of data, and ethical use of data and AI. In particular it may be relevant to the level 6 qualification which “takes a more academic view of data science, situating it in the wider context of AI and big data” and aims to raise “awareness of data ethics”. The materials could also be used as part of English language activities in which students read and evaluate the linked articles, form and discuss their opinions and create factual or persuasive writing pieces on this topic. This resource was developed as part of an Open Content Curator Internship with The University of Edinburgh Open Educational Resources Service. Authors: Alyssa Heggison, with guidance and input from from Amy Yin, Megan Thomson and Dr Vicki Madden at The University of Edinburgh Information Services Group Unless otherwise stated, all content is released under a CC BY-SA 4.0 license. Cover Image:

This resource contains two items, a detailed lesson plan and an accompanying slideshow/deck. Created by The University of Edinburgh’s Wikimedian-in-Residence, Ewan McAndrew, the plan should assist any Wikipedia trainer in how to run a Wikipedia editing training sessions. If you’re located in the UK, please message Wikimedia UK (info@wikimedia.org.uk) to let them know you are planning to run a training session as there are signup sheets, feedback forms and Wikimedia swag materials they can provide you with along with guidance about best practice. They can also potentially link you with Wikipedians in your area to help out at the session. Cover image is Editing Wikipedia by Veronica Erb on Flickr, licensed under CC BY-SA 2.0.