The SSH Training Discovery Toolkit provides an inventory of training materials relevant for the Social Sciences and Humanities.
Use the search bar to discover materials or browse through the collections. The filters will help you identify your area of interest.
|Teaching ideas: Guides for teaching data analysis||
This resource is a collection of short guides designed to make lesson planning more efficient for those teaching data analysis skills. Drawing on real classroom experiences, each guide includes suggested research questions, dataset and exercises:
|Building skills in quantitative methods and statistical software||
A collection of quantitative methods e-books and accompanying quizzes for direct use in teaching students or for self-study. They aim to build skills in quantitative methods and statistical software and use the Living Costs and Food Survey.
The e-books have been developed through a collaboration of the UK Data Service, National Centre for Research Methods (NCRM), and the Centre for Multi-Level Modelling at the University of Bristol and were created using the StatJR software based on original outputs from the project Using Statistical E-books to teach undergraduate students quantitative methods and statistical software funded by the British Academy.
|Teaching resource: Introducing quantitative analysis using SPSS||
The resource can serve both as an introduction to the Malaise Inventory - an established scale to measure signs of psychological distress - and as an introduction to quantitative analysis using SPSS. The data and resources are aimed for use with undergraduates and postgraduates and are designed to be used with SPSS (the data are also made available in Stata and tabdelimited formats).
This resource includes a guide on how to access data, an introduction to the established set of survey questions that measures psychological distress - the Malaise Inventory - and a number of data analysis exercises using SPSS.
|Teaching resource: Non-interview methods||
This teaching resource provides instructors and students with materials designed to assist in teaching qualitative methods of data collection.
This resource provides brief summaries of some of the different ways in which researchers can collect qualitative data, including focus groups, diaries, online data collection, and visual methods. Each summary is accompanied by an illustrative data sample from the extensive collections held by the UK Data Archive.
|OpenAIRE FAQ on Open Science, RDM||
FAQ by OpenAIRE answering various questions around Open Science and RDM.
|Use cases of OpenAIRE services for different stakeholders||
OpenAIRE is preparing use case narratives with scenarios of Open Science services offered by OpenAIRE targeting different users: researchers, research communities/research infrastructures, content providers, funders, managers of research.
The main goal is to showcase how OpenAIRE services are contributing to embed Open Science into researchers' daily workflow and to implement and align Open Science policies and infrastructures across European research institutions.
Benefits and assumptions of those who already use the OpenAIRE services and several best practices on Open Access publishing, sharing research data and enriching the repositories content will be made available on the website
|H2020 OpenAIRE Fact sheets||
In an effort to make open access for publications and data simple for everyone, OpenAIRE is creating factsheets with a brief overview of how to comply with H2020 OA mandates and how to use OpenAIRE services where available.
|A new generation of tools for meeting and networking online||
There is a new generation of tools that enriches the toolset of online facilitators. Comprising the tools Wonder me, Remo, Videofacilitator, Spatial Chat, Gather and Gemibo, this blog will compare them and evaluate their functions.
|UKDS: Teaching with Data|
|UK Data Service: Data Skills||
This source includes interactive modules designed for users who want to get to grips with key aspects of survey, longitudinal and aggregate data as well as tools that can be used to assess and improve data quality.
Modules can be conducted in your own time and you are able to dip in and out when needed. The modules give an introduction to key aspects of the data using short instructional videos, interactive quizzes and activities using open access software where possible. Tools include guides, documentation and exercises.