Dr. Laura Pasquini offered a guest post about formal and informal online mentoring experiences in academic settings.

Walk through an example using Dr. Salmons’ eight-step process for teaching with research cases.

Academics face various pressures, from research teaching and administrative duties. The best way to create a positive culture in academia is to share. However, it may sometimes feel like there is no incentive to share teaching materials, if I have spent so many hours developing this work, why should I just hand it over to someone, “what’s in it for me?”

The beginning of term is nearing. You’re teaching a new module on Computational Social Science (CSS). The field is developing rapidly and so are best practices around teaching the theory, methods and techniques to students.

Where do you start when you’re putting together your teaching materials? Do you visit the websites and blogs of academics who are experienced in teaching CSS to look for resources? Do you search online for syllabi, reading lists and tutorials? Maybe you scour YouTube for videos to include in your slides?

Together with a group of UK academics, the SAGE Ocean team have been digging into where academics go to find teaching materials and what the barriers are for academics who want to share, reuse and give and get credit for the materials they produce for teaching. This post includes thoughts from the group on what’s needed to promote a stronger culture of sharing teaching materials in CSS. And we’ve curated a list of our favorite resources for you too!

As the participants gear up for the 2019 Summer Institute in Computational Social Science (SICSS), starting June 16th at Princeton and the 11 alumni-led partner locations situated right across the globe, we caught up with the founders of the SICSS, Chris Bail and Matt Salganik to find out how it all got going, the move to a data intensive society and the benefits of learning data science skills to make the most of this new data.

View the Get Creative! Research with Pictures & Stories webinar

I would argue that computational social science necessitates collaboration, and indeed is tamed by it. A collaborative approach provides the necessary structure, goals, and a critical approach to research methods. In response to the question of what computational social science has helped me achieve, it may seem obvious to mention the concrete projects, the outputs, the measurable outcomes. However, for me computational social science has achieved something more substantial and enduring—a new way of working, a new way of thinking, and a new kind of enthusiasm for research.

SAGE Research Methods has launched a new Data Science video collection, with hours of educational material for researchers of all levels and backgrounds.

Calling all social scientists. How were you trained? How are you keeping up (or not) with new developments in this rapidly changing digital world? How are you training your students?

This was the subject of an event sponsored by SAGE Ocean as part of the ESRC’s 2018 Festival of Social Science. In case you are not aware, Sage, who have been at the forefront of publishing qualitative work, have now launched SAGE Ocean – an initiative “to help social scientists to navigate vast datasets and work with new technologies”.

Last week, a mix of PhD students, early career and tenured researchers met in Cologne to discuss their latest projects around bias and discrimination on social media, and the algorithms underpinning many of the most pervasive services we use today.

Dr. Gina Gull discusses her research about unintentional discrimination, typically through implicit bias, in school settings.

Donald Dunn discusses his research about ethics and leadership.

Narelle Lemon offers suggestions for a mindful approach to social research.