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Science Education

Science Education

We live in a world which is ever more complex. SEFARI is committed to the use of research and knowledge to help us better understand the world around us, and to make better decisions. Science education underpins all our work – on the premise that learning is for everyone, and certainly not confined to the school classroom. SEFARI works with partners to utilise our research for shared learning and experience.

We have recently started to collate our, free to access, educational resources which can be accessed here.

Case Studies

2 Dec 2020

CALEDON: Gamers creating resilient forests

The public are being asked to report sightings of 22 tree pests and diseases and newly emerging threats.

10 Dec 2019

Protecting Potatoes - Scotland's Story

Since the emergence of late blight (Phytophthora infestans) in the 1840s this disease has presented a major challenge to the potato industry, with annual losses estimated to be £55 million in the UK.

27 Aug 2019

Infrared Spectroscopy – Helping to Protect Scotland’s Soils

Infrared (IR) Spectroscopy is a versatile analytical technique that can characterise a wide variety of different sample types e.g. from drugs and plastics to soil and minerals.

Blog

28 Jan 2021 - 16:26

SEFARI Gateway Update - January 2021

The past year has been, and 2021 will undoubtedly remain, challenging for us all.

10 Dec 2020 - 16:26

Extending reality: Helping farmers experience in-field events virtually

Currently, we are all experiencing unique working conditions, leading us to adapt to new ways of engaging and learning.  

20 Nov 2020 - 11:13

Beating the Winter Blues

Winter is here and this might conjure thoughts of cosy nights by a fire, mulled wine, and the holiday season. However, it also brings colder days and longer nights and for some Seasonal Affective Disorder (SAD).

Events

2021

23 Mar

High Performance Computing and Data Sharing - Virtual Workshop

Science is becoming ever more data driven, with many aspects of biology requiring increasing levels of computing power for data analysis, visualization, mathematical modelling, data simulations and computational biology.