United Kingdom

To support parents and carers with home learning, the subject experts of STEM Learning (UK-based STEM platform) have put together a selection of activities and materials. These include a wide range of free resources, guidance and professional development opportunities for teachers and educators, tips and resources for parents, daily activities as well as a 'homeschooling survival guide'. The lesson materials and resources are organised per topic (e.g. biology, chemistry, physics, computing, etc.), each with their own support pages and resources. STEM Learning's experts are available for support via webchat on weekdays between 08.30 - 16.30 (UK time). 

An additional 'home teaching' page will be launched later this week. This page will be focused on support for schools and teachers delivering lessons remotely.

STEM Learning's digital support platform proved extremely popular and recieved over 100.000 users in its first ten days. The portal is currently Google's top recommendation for home learning in the UK. The platform and all resources are free to access for everyone. For more information about the platform and individual resources and information about home teaching support, please visit the website via the link above. 

Teachers should obscure from students that they are doing Stem work because young people are put off if it is framed in this way, leading politicians have been told.

Stem is the commonly used acronym for science, technology, engineering and maths, but expert witnesses advised today against referring to Stem when dealing with students – instead, they should use terms such as “creativity”, “ideas” and “problem-solving”.

Clare Adamson, convener of the Scottish Parliament’s Education and Skills Committee, said today that some educators had told her a few weeks ago that they “only do Stem by stealth”, because “if they presented young people with a problem or a project, they got stuck in – until they labelled it [as Stem]”.

The Scottish government has been urged to tackle inequality following a parliamentary report into science, technology, engineering and maths (Stem) education. The publication, made available today from the Scottish Parliament’s Education and Skills Committee, which has been investigating Stem in early education, said more needed to be done to reduce the effects of gender and financial inequality on the standard of learning across the country. The committee's convener, SNP MSP Clare Adamson, has called on the Scottish government “to do more” to study how effective measures to promote Stem in schools have been.

Do employers in "non-STEM" occupations (e.g. Graphic Designers, Economists) seek to hire STEM (Science, Technology, Engineering, and Mathematics) graduates with a higher probability than non-STEM ones for knowledge and skills that they have acquired through their STEM education (e.g. "Microsoft C#", "Systems Engineering") and not simply for their problem solving and analytical abilities? This is an important question in the UK where less than half of STEM graduates work in STEM occupations and where this apparent leakage from the "STEM pipeline" is often considered as a wastage of resources. To address it, this paper goes beyond the discrete divide of occupations into STEM vs. non-STEM and measures STEM requirements at the level of jobs by examining the universe of UK online vacancy postings between 2012 and 2016. We design and evaluate machine learning algorithms that classify thousands of keywords collected from job adverts and millions of vacancies into STEM and nonSTEM. 35% of all STEM jobs belong to non-STEM occupations and 15% of all postings in non-STEM occupations are STEM. Moreover, STEM jobs are associated with higher wages within both STEM and non-STEM occupations, even after controlling for detailed occupations, education, experience requirements, employers, etc. Although our results indicate that the STEM pipeline breakdown may be less problematic than typically thought, we also find that many of the STEM requirements of "non-STEM" jobs could be acquired with STEM training that is less advanced than a full time STEM education. Hence, a more efficient way of satisfying the STEM demand in non-STEM occupations could be to teach more STEM in non-STEM disciplines. We develop a simple abstract framework to show how this education policy could help reduce STEM shortages in both STEM and non-STEM occupations.

EngineeringUK has published a research briefing on female underrepresentation in the industry. Despite efforts to address the imbalance, just 12% of those working in engineering are female. This disparity is largely due to girls dropping out of the educational pipeline at every decision point, despite generally performing better than boys in STEM subjects at school.

Evidence shows gender differences in understanding of and interest in engineering as well as perceptions of self-efficacy and identity are likely to be key factors when making subject and career choices. Girls are not only less knowledgeable about engineering and how to become an engineer, but also less likely to seek careers advice from others. 

To help more—and more diverse—students engage with science, the science capital teaching approach builds on good teaching practice. Its key distinction is an explicit focus on recognising and valuing students’ existing science capital, whilst also helping them to build new science capital.

The approach works within any science curriculum. It is not a new set of materials and it does not mean a dilution of science ideas and concepts. Instead, it is a reflective framework that involves making small tweaks to existing practice so as to re-orientate science lessons in ways that can better connect with the reality of students’ lives and experiences.

The concept of science capital is a way of encapsulating all the science-related knowledge, attitudes, experiences and social contacts that an individual may have.

The indicators in the report present a synthesis of research and innovation performance in the United Kingdom (UK). They relate knowledge investment and input to performance and economic output throughout the innovation cycle. They show thematic strengths in key technologies and also the high-tech and medium-tech contribution to the trade balance. The indicator on excellence in science and technology takes into consideration the quality of scientific production as well as technological development. The Innovation Output Indicator covers technological innovation, skills in knowledge-intensive activities, the competitiveness of knowledge-intensive goods and services, and the innovativeness of fast-growing enterprises, focusing on innovation output. The indicator on knowledge-intensity of the economy focuses on the economy’s sectoral composition and specialisation and shows the evolution of the weight of knowledge-intensive sectors and products.