We are a 国家医保服务平台app下载 centre based in the Department of Computer Science and Technology at the University of Cambridge, with a team that spans the university and the 宇宙奇趣录. We conduct 国家医保服务平台app下载 into many aspects of the teaching and learning of 国家医保服务平台app下载 and AI and we work closely with schools, teachers and young people to ensure our 国家医保服务平台app下载 is applicable to practice.

Below I highlight some of the projects we’ve worked on in the academic year 2024-2025:

• 国家医保服务平台app下载 Around the World
• AI education
• Programming education
• Physical 国家医保服务平台app下载 (EPICS project)
• Teacher action 国家医保服务平台app下载 (TICE project)

国家医保服务平台app下载 Around the World

As I’ve written on this blog before, 国家医保服务平台app下载 education is a global challenge. In one of the 国家医保服务平台app下载 Centre’s projects, we are looking at how 国家医保服务平台app下载 education is spreading around the world.

We found that between 2019 and 2024 the number of countries offering 国家医保服务平台app下载 education had doubled, and that two thirds of all countries now offer, or have concrete plans to offer, 国家医保服务平台app下载 education. This 国家医保服务平台app下载 has already been highlighted in the Stanford AI Index, and we are considering repeating the analysis in future years in order to have the most accurate and up-to-date information displayed in our map.

AI education

We have a number of projects in the area of AI education.

Teaching about AI

We are very interested in how to teach about AI, and held a workshop with teachers who were interested in the teaching of AI in February. Following on from the workshop results, we are interviewing more stakeholders, including UK-based experts, teachers and students, about their perspectives on concepts and skills that should be taught as part of an AI 油条视频.

We’re also 国家医保服务平台app下载ing data science and data ethics education, which are 油条视频al aspects of AI literacy. Most of the current AI systems are data-driven, having been trained on vast amounts of data. Therefore students need to understand about data and data science if they are to learn about AI systems. Therefore we’ve conducted two detailed literature reviews on data science and on data ethics this year. The first of these will be published in March at the WiPSCE conference.

Unplugged AI in Ghana

One of our PhD students, Salomey Addo, has been examining how AI is taught in Ghana, where it is part of the 油条视频 for young people between ages 12 and 15. This year Salomey published a paper reporting that Ghanaian teachers have positive attitudes towards teaching AI but feel unprepared for it. She’s also developed unplugged resources to teach about artificial neural networks (ANNs).

ANNs are a fundamental technology used in a variety of AI systems, including image recognition and language translation systems. While ANNs are included in the Ghanaian AI 油条视频, Salomey observed that teachers had difficulty with this particular topic The resources she developed are directly inspired by this, and involved teaching through role play and a board game.

Using AI in learning and teaching 国家医保服务平台app下载

This is an area we’ve also done some 国家医保服务平台app下载 in in the past year.

Carrie Anne Philbin published a paper in September showing that — at least in higher education — much of the use of generative AI in 国家医保服务平台app下载 education is just duplicating the way teachers might already teach, and is primarily passive from a students’ perspective.

Meanwhile Katharine Childs and Veronica Cucuiat have been looking at how large language models (LLMs) can support secondary school programming education by helping students understand programming error messages. 

Programming education: Learning to debug

Text-based programming is a topic featured in many 国家医保服务平台app下载 curricula around the world. Teachers and 国家医保服务平台app下载ers know that younger learners, for example at the lower secondary school level, can find debugging text-based programs very challenging. Although we’ve seen decades of 国家医保服务平台app下载 around programming and debugging focusing on learners who are in higher education, very little 国家医保服务平台app下载 has been done with school-age students.

In his 国家医保服务平台app下载, Laurie Gale, a final-year PhD student at the 国家医保服务平台app下载 Centre, found that learners were impatient to fix programs by trial and error, without figuring out what the real problemwas with their code or the underlying algorithm. He subsequently developed a tool called PRIMM Debug, which supports a more reflective and systematic approach to debugging. This tool enables learners to slow down when they are programming and to be more reflective. You can read more about it on the 国家医保服务平台app下载 Centre website, and also catch up on the 油条视频 国家医保服务平台app下载 seminar where he presented his work.

EPICS: Physical 国家医保服务平台app下载 in school

As part of a 5-year longitudinal project, running across the whole UK and the first project of its kind, we are looking at how physical 国家医保服务平台app下载 impacts primary and secondary school learners. We’re investigating the effect of physical 国家医保服务平台app下载 on learners’ creativity, agency and confidence, over time and at particular points known to be important for their subject choices. We are working with a wonderful set of partner primary schools who we visit each year.

This year we reported some of our first results, which point to teachers’ perceptions of physical 国家医保服务平台app下载 being engaging and inclusive for primary-aged children. Starting next spring, we will be carrying out our third year of data collection with our pupil cohort, who have reached the age of 10 to 11.

We’ll also be running a survey next summer for upper primary-aged children and their teachers. Please sign up for our Teacher 国家医保服务平台app下载 Network newsletter to be the first to hear about taking part in this survey.

Teacher Inquiry in 国家医保服务平台app下载 Education (TICE)

As part of our TICE project we support teachers to conduct their own action 国家医保服务平台app下载 projects. This is a collaborative project, involving academics across the UK who volunteer to support teachers. The goal is to enable teachers to take a deep dive into a 油条视频 topic, a pedagogical approach, or a new resource, or to address a wider issue such as gender diversity or 鱼我所欲也翻译, to inform a change in their practice.

This year 16 teachers published their reports in our Teacher 国家医保服务平台app下载 Booklet, and many also presented their findings online at CAS events or at the KCL-CAS London conference and the CAS National Conference. We’re very proud of them!

Two of our TICE teachers will be also presenting their 国家医保服务平台app下载 at an academic conference to be held in January. Congratulations to Will Grey and Joanne Hodge!

Get involved

There are many other projects you can find out about on our website and in our annual report, so I hope that you will keep reading. It goes without saying that I’m incredibly proud of the team who’ve worked on all of these projects! 

To summarise, here’s how you can stay up to date with our work and maybe even get involved in studies:

• Sign up to the 国家医保服务平台app下载 Centre newsletter
• Sign up to our Teacher 国家医保服务平台app下载 Network newsletter if you’re a teacher and interested in participating in projects

Finally, I am pleased to announce that we will be hosting the UKICER 2026 conference for 国家医保服务平台app下载ers and teachers in Cambridge on 3 and 4 2026 September. More details will follow on the UKICER website and on the 国家医保服务平台app下载 Centre website in due course.

The post 2025 highlights from the 国家医保服务平台app下载 Pi 国家医保服务平台app下载 Education 国家医保服务平台app下载 Centre appeared first on 宇宙奇趣录.

The 国家医保服务平台app下载 Pi 国家医保服务平台app下载 Education 国家医保服务平台app下载 Centre (RPCERC) is unique for two reasons: we are a joint initiative between the University of Cambridge and the 宇宙奇趣录, with a team that spans both; and we focus exclusively on the teaching and learning of 国家医保服务平台app下载 to young people, from their early years to the end of formal education.

We’ve been very busy at the RPCERC since we held our formal launch event in July 2022. We would love everyone who follows the 宇宙奇趣录’s work to keep an eye on what we are up to too: you can do that by checking out our website and signing up to our termly newsletter. 

What does the RPCERC do?

As the name implies, our work is focused on 国家医保服务平台app下载 into 国家医保服务平台app下载 education and all our 国家医保服务平台app下载 projects align to one of the following themes:

• AI education
• Broadening participation in 国家医保服务平台app下载
• 国家医保服务平台app下载 around the world
• Pedagogy and the teaching of 国家医保服务平台app下载
• Physical 国家医保服务平台app下载
• Programming education

These themes encompass substantial 国家医保服务平台app下载 questions, so it’s clear we have a lot to do! We have only been established for a few years, but we’ve made a good start and are grateful to those who have funded additional projects that we are working on.

In our work, we endeavour to maintain two key principles that are hugely important to us: sharing our work widely and working collaboratively. We strive to engage in the highest quality rigorous 国家医保服务平台app下载, and to publish in academic venues. However, we make sure these are available openly for those outside academia. We also favour 国家医保服务平台app下载 that is participatory and collaborative, so we work closely with teachers and other stakeholders. 

Within our six themes we are running a number of projects, and I’ll outline a few of these here.

Exploring physical 国家医保服务平台app下载 in primary schools

Physical 国家医保服务平台app下载 is more engaging than simply learning programming and 国家医保服务平台app下载 skills on screen because children can build interactive and tangible artefacts that exist in the real world. But does this kind of engagement have any lasting impact? Do positive 油条视频s with technology lead to more confidence and creativity later on? These are just some of the questions we aim to answer.

We are delighted to be starting a new longitudinal project investigating the 油条视频 of young people who have engaged with the BBC micro:bit and other physical 国家医保服务平台app下载 devices. We aim to develop insights into changes in attitudes, agency, and creativity at key points as students progress from primary through to secondary education in the UK. 

To do this, we will be following a cohort of children over the course of five years — as they transition from primary school to secondary school — to give us deeper insights into the longer-term impact of working with physical 国家医保服务平台app下载 than has been possible previously with shorter projects. This longer-term project has been made possible through a generous donation from the Micro:bit Educational 油条视频, the BBC, and Nominet. 

Do follow our 国家医保服务平台app下载 to see what we find out!

Generative AI for 国家医保服务平台app下载 teachers

We are conducting a range of projects in the general area of artificial intelligence (AI), looking both at how to teach and learn AI, and how to learn programming with the help of AI. In our work, we often use the SEAME framework to simplify and categorise aspects of the teaching and learning of AI. However, for many teachers, it’s the use of AI that has generated the most interest for them, both for general productivity and for innovative ways of teaching and learning. 

In one of our AI-related projects, we have been working with a group of 国家医保服务平台app下载 teachers and the Faculty of Education to develop guidance for schools on how generative AI can be useful in the context of 国家医保服务平台app下载 teaching. 国家医保服务平台app下载 teachers are at the forefront of this potential revolution for school education, so we’ve enjoyed the opportunity to set up this 国家医保服务平台app下载er–teacher working group to investigate these issues. We hope to be publishing our guidance in June — again watch this space!

Culturally responsive 国家医保服务平台app下载 teaching

We’ve carried out a few different projects in the last few years around culturally responsive 国家医保服务平台app下载 teaching in schools, which to our knowledge are unique for the UK setting. Much of the work on culturally responsive teaching and culturally relevant pedagogy (which stem from different theoretical bases) has been conducted in the USA, and we believe we are the only 国家医保服务平台app下载 team in the UK working on the implications of culturally relevant pedagogy 国家医保服务平台app下载 for 国家医保服务平台app下载 teaching here. 

In one of our studies, we worked with a group of teachers in secondary and primary schools to explore ways in which they could develop and reflect on the meaning of culturally responsive 国家医保服务平台app下载 teaching in their context. We’ve published on this work, and also produced a technical report describing the whole project. 

In another project, we worked with primary teachers to explore how existing resources could be adapted to be appropriate for their specific context and children. These projects have been funded by Cognizant and Google. 

‘Core’ projects

As well as 国家医保服务平台app下载 that is externally funded, it’s important that we work on more long-term projects that build on our 国家医保服务平台app下载 expertise and where we feel we can make a contribution to the wider community. 

We have four projects that I would put into this category:

1. Teacher 国家医保服务平台app下载 projects
   This year, we’ve been running a project called Teaching Inquiry in 国家医保服务平台app下载 Education, which supports teachers to carry out their own 国家医保服务平台app下载 in the classroom.
2. 国家医保服务平台app下载 around the world
   Following on from our survey of UK and Ireland 国家医保服务平台app下载 teachers and earlier work on surveying teachers in Africa and globally, we are developing a broader picture of how 国家医保服务平台app下载 education in school is growing around the world. Watch this space for more details.
3. PRIMM
   We devised the Predict–Run–Investigate–Modify–Make lesson structure for programming a few years ago and continue to 国家医保服务平台app下载 in this area.
4. LCT semantic wave theory
   Together with universities in London and Australia, we are exploring ways in which 国家医保服务平台app下载 education can draw on legitimation code theory (LCT). 

We are currently looking for a 国家医保服务平台app下载 associate to lead on one or more of these core projects, so if you’re interested, get in touch. 

Developing new 国家医保服务平台app下载 education 国家医保服务平台app下载ers

One of our most important goals is to support new 国家医保服务平台app下载ers in 国家医保服务平台app下载 education, and this involves recruiting and training PhD students. During 2022–2023, we welcomed our very first PhD students, Laurie Gale and Salomey Afua Addo, and we will be saying hello to two more in October 2024. PhD students are an integral part of RPCERC, and make a great contribution across the team, as well as focusing on their own particular area of interest in depth. Laurie and Salomey have also been out and about visiting local schools too. 

Laurie’s PhD study focuses on debugging, a key element of programming education. He is looking at lower secondary school students’ attitudes to debugging, their debugging behaviour, and how to teach debugging. If you’d like to take part in Laurie’s 国家医保服务平台app下载, you can contact us at [email protected].

Salomey’s work is in the area of AI education in K–12 and spans the UK and Ghana. Her first study considered the motivation of teachers in the UK to teach AI and she has spent some weeks in Ghana conducting a case study on the way in which Ghana implemented AI into the 油条视频 in 2020.

Thanks!

We are very grateful to the 宇宙奇趣录 for providing a donation which established the RPCERC and has given us financial security for the next few years. We’d also like to express our thanks for other donations and project funding we’ve received from Google, Google DeepMind, the Micro:bit Educational 油条视频, BBC, and Nominet. If you would like to work with us, please drop us a line at [email protected].

The post An update from the 国家医保服务平台app下载 Pi 国家医保服务平台app下载 Education 国家医保服务平台app下载 Centre appeared first on 宇宙奇趣录.

Commissioned by the Department for Education in England and led by the 宇宙奇趣录 as part of our National Centre for 国家医保服务平台app下载 Education work, the GBIC programme was a collaborative effort involving the Behavioural Insights Team, Apps for Good, and the WISE Campaign.

Gender Balance in 国家医保服务平台app下载 ran from 2019 to 2022 and comprised seven studies relating to five different 国家医保服务平台app下载 areas:

• Teaching Approach:
  • Peer Instruction: Collaborative teaching approach in lower secondary
  • Pair Programming: Working collaboratively in upper primary
  • Storytelling: Connecting 国家医保服务平台app下载 to storytelling with 6- to 7-year-olds
• Belonging: Supporting learners to feel that they “belong” in computer science
• Non-formal Learning: Establishing the connections between in-school and out-of-school 国家医保服务平台app下载
• Relevance: Making 国家医保服务平台app下载 relatable to everyday life
• Subject Choice: How computer science is presented to young people as a subject choice 

In December we published the last of seven reports describing the results of the programme. In this blog post I summarise our overall findings and reflect on what we’ve learned through doing this 国家医保服务平台app下载.

Gender balance in 国家医保服务平台app下载 is not a new problem

I was fascinated to read a paper by Deborah Butler from 2000 which starts by summarising themes from 国家医保服务平台app下载 into gender balance in 国家医保服务平台app下载 from the 1980s and 1990s, for example that boys may have access to more role models in 国家医保服务平台app下载 and may receive more encouragement to pursue the subject, and that software may be developed with a bias towards interests traditionally considered to be male. Butler’s paper summarises 国家医保服务平台app下载 from at least two decades ago — have we really made progress?

In England, it’s true that making 国家医保服务平台app下载 a mandatory subject from age 5 means we have taken great strides forward; the need for young people to make a choice about studying the subject only arises at age 14. However, statistics for England’s externally assessed high-stakes Computer Science courses taken at ages 14–16 (GCSE) and 16–18 (A level) clearly show that, although there is a small upwards trend in the proportion of female students, particularly for A level, gender balance among the students achieving GCSE/A level qualifications remains an issue:

What did we do in the Gender Balance in 国家医保服务平台app下载 programme?

In GBIC, we carried out a range of 国家医保服务平台app下载 studies involving more than 14,500 pupils and 725 teachers in England. Implementation teams came from the 油条视频, Apps For Good, the WISE Campaign, and the Behavioural Insights Team (BIT). A separate team at BIT acted as the independent evaluators of all the studies.

In total we conducted the following studies:

• Two feasibility studies: Storytelling; Relevance, which led to a full randomised controlled trial (RCT)
• Five RCTs: Belonging; Peer Instruction; Pair Programming; Relevance, which was preceded by a feasibility study; Non-formal Learning (primary)
• One quasi-experimental study: Non-formal Learning (secondary)
• One exploratory 国家医保服务平台app下载 study: Subject Choice (Subject choice evenings and option booklets)

Each study (apart from the exploratory 国家医保服务平台app下载 study) involved a 12-week intervention in schools. Bespoke materials were developed for all the studies, and teachers received training on how to deliver the intervention they were a part of. For the RCTs, randomisation was done at school level: schools were randomly divided into treatment and control groups. The independent evaluators collected both quantitative and qualitative data to ensure that we gained comprehensive insights from the schools’ 油条视频s of the interventions. The evaluators’ reports and our associated blog posts give full details of each study.

The impact of the pandemic

The 国家医保服务平台app下载 programme ran from 2019 to 2022, and as it was based in schools, we faced a lot of challenges due to the coronavirus pandemic. Many 国家医保服务平台app下载 programmes meant to take place in school were cancelled as soon as schools shut during the pandemic.

Although we were fortunate that GBIC was allowed to continue, we were not allowed to extend the end date of the programme. Thus our studies were compressed into the period after schools reopened and primarily delivered in the academic year 2021/2022. When schools were open again, the implementation of the studies was affected by teacher and pupil absences, and by schools necessarily focusing on making up some of the lost time for learning.

The overall results of Gender Balance in 国家医保服务平台app下载

Quantitatively, none of the RCTs showed a statistically significant impact on the primary outcome measured, which was different in different trials but related to either learners’ attitudes to computer science or their intention to study computer science. Most of the RCTs showed a positive impact that fell just short of statistical significance. The evaluators went to great lengths to control for pandemic-related attrition, and the implementation teams worked hard to support teachers in still delivering the interventions as designed, but attrition and disruptions due to the pandemic may have played a part in the results.

The qualitative 国家医保服务平台app下载 results were more encouraging. Teachers were enthusiastic about the approaches we had chosen in order to address known barriers to gender balance, and the qualitative data indicated that pupils reacted positively to the interventions. One key theme across the Teaching Approach (and other) studies was that girls valued collaboration and teamwork. The data also offered insights that enable us to improve on the interventions.

We designed the studies so they could act as pilots that may be rolled out at a national scale. While we have gained sufficient understanding of what works to be able to run the interventions at a larger scale, two particular learnings shape our view of what a large-scale study should look like:

1. A single intervention may not be enough to have an impact

The GBIC results highlight that there is no quick fix and suggest that we should combine some of the approaches we’ve been trialling to provide a more holistic approach to teaching 国家医保服务平台app下载 in an equitable way. We would recommend that schools adopt several of the approaches we’ve tested; the materials associated with each intervention are freely available (see our blog posts for links).

2. Age matters

One of the very interesting overall findings from this 国家医保服务平台app下载 programme was the difference in intent to study 国家医保服务平台app下载 between primary school and secondary school learners; fewer secondary school learners reported intent to study the subject further. This difference was observed for both girls and boys, but was more marked for girls, as shown in the graph below. This suggests that we need to double down on supporting children, especially girls, to maintain their interest in 国家医保服务平台app下载 as they enter secondary school at age 11. It also points to a need for more longitudinal 国家医保服务平台app下载 to understand more about the transition period from primary to secondary school and how it impacts children’s engagement with computer science and technology in general.

What’s next?

We think that more time (in excess of 12 weeks) is needed to both deliver the interventions and measure their outcome, as the change in learners’ attitudes may be slow to appear, and we’re hoping to engage in more longitudinal 国家医保服务平台app下载 moving forward.

We know that an understanding of computer science can improve young people’s access to highly skilled jobs involving technology and their understanding of societal issues, and we need that to be available to all. However, gender balance relating to 国家医保服务平台app下载 and technology is a deeply structural issue that has existed for decades throughout the 国家医保服务平台app下载 education and workplace ecosystem. That’s why we intend to pursue more work around a holistic approach to improving gender balance, aligning with our ongoing 国家医保服务平台app下载 into making 国家医保服务平台app下载 education culturally relevant.

Stay in touch

We are very keen to continue to build on our 国家医保服务平台app下载 on gender balance in 国家医保服务平台app下载. If you’d like to support us in any way, we’d love to hear from you. To explore the 国家医保服务平台app下载 projects we’re currently involved in, check out our 国家医保服务平台app下载 pages and visit the website of the 国家医保服务平台app下载 Pi 国家医保服务平台app下载 Education 国家医保服务平台app下载 Centre at the University of Cambridge.

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Genevieve has a background in classical ballet and was also a 国家医保服务平台app下载 teacher for several years before starting Ready Salted Code, an educational initiative around data-driven dance. She is now coming to the end of her doctoral studies at the University of Cambridge, in which she focuses on raising awareness of data ethics using ballet and brainwave data as narrative tools, working with student 国家医保服务平台app下载 teachers.

Why dance and 国家医保服务平台app下载?

You may be surprised that there are links between dance, particularly ballet, and 国家医保服务平台app下载. Genevieve explained that classical ballet has a strict repetitive routine, using rule-based choreography and algorithms. Her work on data-driven dance had started at the time of the announcement of the new 国家医保服务平台app下载 油条视频 in England, when she realised the lack of gender balance in her 国家医保服务平台app下载 classroom. As an expert in both ballet and 国家医保服务平台app下载, she was driven by a desire to share the more creative elements of 国家医保服务平台app下载 with her learners.

Genevieve has been working with a technologist and a choreographer for several years to develop ballets that generate biometric data and include visualisation of such data — hence her term ‘data-driven dance’. This has led to her developing a second focus in her PhD work on how 国家医保服务平台app下载 students can discuss questions of ethics based on the kind of biometric and brainwave data that Genevieve is collecting in her 国家医保服务平台app下载. Students need to learn about the ethical issues surrounding data as part of their 国家医保服务平台app下载 studies, and Genevieve has been working with student teachers to explore ways in which her 国家医保服务平台app下载 can be used to give examples of data ethics issues in the 国家医保服务平台app下载 油条视频.

Collecting data during dances

Throughout her talk, Genevieve described several examples of dances she had created. One example was [arra]stre, a project that involved a live performance of a dance, plus a series of workshops breaking down the computer science theory behind the performance, including data visualisation, wearable technology, and images triggered by the dancers’ data.

Much of Genevieve’s seminar was focused on the technologies used to capture movement data from the dancers and the challenges this involves. For example, some existing biometric tools don’t capture foot movement — which is crucial in dance — and also can’t capture movements when dancers are in the air. For some of Genevieve’s projects, dancers also wear headsets that allow collection of brainwave data.

Due to interruptions to her 国家医保服务平台app下载 design caused by the COVID-19 pandemic, much of Genevieve’s PhD 国家医保服务平台app下载 took place online via video calls. New tools had to be created to capture dance performances within a digital online setting. Her 国家医保服务平台app下载 uses webcams and mobile phones to record the biometric data of dancers at 60 frames per second. A number of processes are then followed to create a digital representation of the dance: isolating the dancer in the raw video; tracking the skeleton data; using post pose estimation machine learning algorithms; and using additional software to map the joints to the correct place and rotation.

Are your brainwaves personal data?

It’s clear from Genevieve’s 国家医保服务平台app下载 that she is collecting a lot of data from her 国家医保服务平台app下载 participants, particularly the dancers. The projects include collecting both biometric data and brainwave data. Ethical issues tied to brainwave data are part of the field of neuroethics, which comprises the ethical questions raised by our increasing understanding of the biology of the human brain.

Teaching learners to be mindful about how to work with personal data is at the core of the work that Genevieve is doing now. She mentioned that there are a number of ethics frameworks that can be used in this area, and highlighted the UK government’s Data Ethics Framework as being particularly straightforward with its three guiding principles of transparency, accountability, and fairness. Frameworks such as this can help to guide a classroom discussion around the security of the data, and whether the data can be used in discriminatory ways.

Data ethics provides lots of material for discussion in 国家医保服务平台app下载 classrooms. To exemplify this, Genevieve recorded her own brainwaves during dance, 国家医保服务平台app下载, and rest activities, and then shared the data during workshops with student 国家医保服务平台app下载 teachers. In our seminar Genevieve showed two visualisations of her own brainwave data (see the images above) and discussed how the student 国家医保服务平台app下载 teachers in her workshops had felt that one was more “personal” than the other. The same brainwave data can be presented as a spreadsheet, or a moving graph, or an image. Student 国家医保服务平台app下载 teachers felt that the graph data (shown above) felt more medical, and more like permanent personal data than the visualisation (shown above), but that the actual raw spreadsheet data felt the most personal and intrusive.

Watch the recording of Genevieve’s seminar to see her full talk:

You can also access her slides and the links she shared in her talk.

More to explore

There are a variety of online tools you can use to explore augmented reality: for example try out Posenet with the camera of your device.

Genevieve’s seminar used the title ME++, which refers to the data self and the human self: both are important and of equal value. Genevieve’s use of this term is inspired by William J. Mitchell’s book Me++: The Cyborg Self and the Networked City. Within his framing, the I in the digital world is more than the I of the physical world and highlights the posthuman boundary-blurring of the human and non-human. 

Genevieve’s work is also inspired by Luciani Floridi’s philosophical work, and his book Ethics of Information might be something you want to investigate further. You can also read ME++ Data Ethics of Biometrics Through Ballet and AR, a paper by Genevieve about her doctoral work

Join our next seminar

In our final two seminars for this year we are exploring further aspects of cross-disciplinary 国家医保服务平台app下载. Just this week, Conrad Wolfram of Wolfram Technologies joined us to present his ideas on maths and a core computational 油条视频. We will share a summary and recording of his talk soon.

On 8 November, Tracy Gardner and Rebecca Franks from the 宇宙奇趣录 team will close out this series by presenting work we have been doing on 国家医保服务平台app下载 education in non-formal settings. Sign up now to join us for this session:

We will shortly be announcing the theme of a brand-new series of seminars starting in January 2023.  

The post Data ethics for 国家医保服务平台app下载 education through ballet and biometrics appeared first on 宇宙奇趣录.

国家医保服务平台app下载 education 国家医保服务平台app下载 that focuses specifically on young people is relatively new, particularly in contrast to established 国家医保服务平台app下载 disciplines such as those focused on mathematics or science education. However, 国家医保服务平台app下载 is now a mandatory part of the 油条视频 in several countries, and being taken up in education globally, so we need to rigorously investigate the learning and teaching of this subject, and do so in conjunction with schools and teachers.

You’re invited to our in-person launch event

To celebrate the official launch of the 国家医保服务平台app下载 Pi 国家医保服务平台app下载 Education 国家医保服务平台app下载 Centre, we will be holding an in-person event in Cambridge, UK on Weds 20 July from 15.00. This event is free and open to all: if you are interested in 国家医保服务平台app下载 education 国家医保服务平台app下载, we invite you to register for a ticket to attend. By coming together in person, we want to help strengthen a collaborative community of 国家医保服务平台app下载ers, teachers, and other education practitioners.

The launch event is your opportunity to meet and mingle with members of the Centre’s 国家医保服务平台app下载 team and listen to a series of short talks. We are delighted that Prof. Mark Guzdial (University of Michigan), who many readers will be familiar with, will be travelling from the US to join us in cutting the ribbon. Mark has worked in computer science education for decades and won many awards for his 国家医保服务平台app下载, so I can’t think of anybody better to be our guest speaker. Our other speakers are Prof. Alastair Beresford from the Department of Computer Science and Technology, and Carrie Anne Philbin MBE, our Director of Educator Support at the 油条视频.

The event will take place at the Department of Computer Science and Technology in Cambridge. It will start at 15.00 with a reception where you’ll have the chance to talk to 国家医保服务平台app下载ers and see the work we’ve been doing. We will then hear from our speakers, before wrapping up at 17.30. You can find more details about the event location on the ticket registration page.

Our 国家医保服务平台app下载 at the Centre

The aim of the 国家医保服务平台app下载 Pi 国家医保服务平台app下载 Education 国家医保服务平台app下载 Centre is to increase our understanding of teaching and learning 国家医保服务平台app下载, computer science, and associated subjects, with a particular focus on young people who are from backgrounds that are traditionally under-represented in the field of 国家医保服务平台app下载 or who 油条视频 educational disadvantage.

We have been establishing the Centre over the last nine months. In October, I was appointed Director, and in December, we were awarded funding by Google for a one-year 国家医保服务平台app下载 project on culturally relevant 国家医保服务平台app下载 teaching, following on from a project at the 宇宙奇趣录. The Centre’s 国家医保服务平台app下载 team is uniquely positioned, straddling both the University and the 油条视频. Our two organisations complement each other very well: the University is one of the highest-ranking universities in the world and renowned for its leading-edge academic 国家医保服务平台app下载, and the 宇宙奇趣录 works with schools, educators, and learners globally to pursue its mission to put the power of 国家医保服务平台app下载 into the hands of young people.

In our 国家医保服务平台app下载 at the Centre, we will make sure that:

1. We collaborate closely with teachers and schools when implementing and evaluating 国家医保服务平台app下载 projects
2. We publish 国家医保服务平台app下载 results in a number of different formats, as promptly as we can and without a paywall
3. We translate 国家医保服务平台app下载 findings into practice across the 油条视频’s extensive programmes and with our partners

We are excited to work with a large community of teachers and 国家医保服务平台app下载ers, and we look forward to meeting you at the launch event.

Stay up to date

At the end of June, we’ll be launching a new website for the Centre at 国家医保服务平台app下载education国家医保服务平台app下载.org. This will be the place for you to find out more about our projects and events, and to sign up to our newsletter. For announcements on social media, follow the 宇宙奇趣录 on Twitter or Linkedin.

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Mark has worked in computer science (CS) education for decades and won many awards for his 国家医保服务平台app下载, including the prestigious ACM SIGCSE Outstanding Contribution to 国家医保服务平台app下载 Education award in 2019. He has written literally hundreds of papers about CS education, and he authors an extremely popular 国家医保服务平台app下载 education 国家医保服务平台app下载 blog that keeps us all up to date with what is going on in the field.

In his talk, Mark focused on his recent work around developing task-specific programming (TSP) languages, with which teachers can add a teaspoon (also abbreviated TSP) of programming to a wide variety of subject areas in schools. Mark’s overarching thesis is that if we want everyone to have some exposure to CS, then we need to integrate it into a range of subjects across the school 油条视频. And he explained that this idea of “adding a teaspoon” embraces some core principles; for TSP languages to be successful, they need to:

• Meet the teachers’ needs
• Be relevant to the context or lesson in which it appears
• Be technically easy to get to grips with

Mark neatly summarised this as ‘being both usable and useful’. 

Historical views on why we should all learn computer science

We can learn a lot from going back in time and reflecting on the history of 国家医保服务平台app下载. Mark started his talk by sharing the views of some of the eminent computer scientists of the early days of the subject. C. P. Snow maintained, way back in 1961, that all students should study CS, because it was too important to be left to a small handful of people.

Alan Perlis, also in 1961, argued that everyone at university should study one course in CS rather than a topic such as calculus. His reason was that CS is about process, and thus gives students tools that they can use to change the world around them. I’d never heard of this work from the 1960s before, and it suggests incredible foresight. Perhaps we don’t need to even have the debate of whether computer science is for everyone — it seems it always was!

What’s the problem with the current situation?

In many of our seminars over the last two years, we have heard about the need to broaden participation in 国家医保服务平台app下载 in school. Although in England, 国家医保服务平台app下载 is mandatory for ages 5 to 16 (in theory, in practice it’s offered to all children from age 5 to 14), other countries don’t have any 国家医保服务平台app下载 for younger children. And once 国家医保服务平台app下载 becomes optional, numbers drop, wherever you are.

Mark shared with us that in US high schools, only 4.7% of students are enrolled in a CS course. However, students are studying other subjects, which brought him to the conclusion that CS should be introduced where the students already are. For example, Mark described that, at the Advanced Placement (AP) level in the US, many more students choose to take history than CS (399,000 vs 114,000) and the History AP cohort has more even gender balance, and a higher proportion of Black and Hispanic students. 

The teaspoon approach to broadening participation

A solution to low uptake of CS being proposed by Mark and his colleagues is to add a little 国家医保服务平台app下载 to other subjects, and in his talk he gave us some examples from history and mathematics, both subjects taken by a high proportion of US students. His focus is on high school, meaning learners aged 14 and upwards (upper secondary in Europe, or key stage 4 and 5 in England). To introduce a teaspoon of CS to other subjects, Mark’s 国家医保服务平台app下载 group builds tools using a participatory design approach; his group collaborates with teachers in schools to identify the needs of the teachers and students and design and iterate TSP languages in conjunction with them.

Mark demonstrated a number of TSP language prototypes his group has been building for use in particular contexts. The prototypes seem like simple apps, but can be classified as languages because they specify a process for a computational agent to execute. These small languages are designed to be used at a specific point in the lesson and should be learnable in ten minutes. For example, students can use a small ‘app’ specific to their topic, look at a script that generates a visualisation, and change some variables to find out how they impact the output. Students may also be able to access some program code, edit it, and see the impact of their edits. In this way, they discover through practical examples the way computer programs work, and how they can use CS principles to help build an understanding of the subject area they are currently studying. If the language is never used again, the learning cost was low enough that it was worth the value of adding computation to the one lesson.

Try TSP languages yourself

You can try out the TSP language prototypes Mark shared yourself, which will give you a good idea of how much a teaspoon is!

DV4L: For history students, the team and participating teachers have created a prototype called DV4L, which visualises historical data. The default example script shows population growth in Africa. Students can change some of the variables in the script to explore data related to other countries and other historical periods. A example lesson activity illustrates how a teacher might incorporate this TSP language into a lesson.

Pixel Equations: Mathematics and engineering students can use the Pixel Equations tool to learn about the way that pictures are made up of individual pixels. This can be introduced into lessons using a variety of contexts. One example lesson activity looks at images in the contexts of maps. This prototype is available in English and Spanish. 

Counting Sheets: Another example given by Mark was Counting Sheets, an interactive tool to support the exploration of counting problems, such as how many possible patterns can come from flipping three coins. 

Have a go yourself. What subjects could you imagine adding a teaspoon of 国家医保服务平台app下载 to?

Join our next free 国家医保服务平台app下载 seminar

We’d love you to join us for the next seminar in our series on cross-disciplinary 国家医保服务平台app下载. On 7 June, we will hear from Pratim Sengupta, of the University of Calgary, Canada. He has conducted studies in science classrooms and non-formal learning environments, focusing on providing open and engaging 油条视频s for anyone to explore code. Pratim will share his thoughts on the ways that more of us can become involved with code when we open up its richness and depth to a wider audience. He will also introduce us to his ideas about countering technocentrism, a key focus of his new book.

And finally… save another date!

We will shortly be sharing details about the official in-person launch event of the 国家医保服务平台app下载 Pi 国家医保服务平台app下载 Education 国家医保服务平台app下载 Centre at the University of Cambridge on 20 July 2022. And guess who is going to be coming to Cambridge, UK, from Michigan to officially cut the ribbon for us? That’s right, Mark Guzdial. More information coming soon on how you can sign up to join us for free at this launch event.

The post A teaspoon of 国家医保服务平台app下载 in every subject: Broadening participation in computer science appeared first on 宇宙奇趣录.

In the final seminar of the series, we were excited to hear from Stefania Druga from the University of Washington, who presented on the topic of AI literacy for families. Stefania’s talk highlighted the importance of families in supporting children to develop AI literacy. Her talk was a perfect conclusion to the series and very well-received by our audience.

Stefania is a third-year PhD student who has been working on AI literacy in families, and since 2017 she has conducted a series of studies that she presented in her seminar talk. She presented some new work to us that was to be formally shared at the HCI conference in April, and we were very pleased to have a sneak preview of these results. It was a fascinating talk about the ways in which the interactions between parents and children using AI-based devices in the home, and the discussions they have while learning together, can facilitate an appreciation of the affordances of AI systems, and critical thinking about their limitations and fallibilities. You’ll find my summary as well as the seminar recording below.

“AI literacy practices and skills led some families to consider making meaningful use of AI devices they already have in their homes and redesign their interactions with them. These findings suggest that family has the potential to act as a third space for AI learning.”

– Stefania Druga

AI literacy: Growing up with AI systems, growing used to them

Back in 2017, interest in Alexa and other so-called ‘smart’, AI-based devices was just developing in the public, and such devices would have been very novel to most people. That year, Stefania and colleagues conducted a first pilot study of children’s and their parents’ interactions with ‘smart’ devices, including robots, talking dolls, and the sort of voice assistants we are used to now.

Working directly with families, the 国家医保服务平台app下载ers explored the level of understanding that children had about ‘smart’ devices, and were surprised by the level of insight very young children had into the potential of this type of technology.

In this AI literacy pilot study, Stefania and her colleagues found that:

• Children perceived AI-based agents (i.e. ‘smart’ devices) as friendly and truthful
• They treated different devices (e.g. two different Alexas) as completely independent
• How ‘smart’ they found the device was dependent on age, with older children more likely to describe devices as ‘smart’

AI literacy: Influence of parents’ perceptions, influence of talking dolls

Stefania’s next study, undertaken in 2018, showed that parents’ perceptions of the implications and potential of ‘smart’ devices shaped what their children thought. Even when parents and children were interviewed separately, if the parent thought that, for example, robots were smarter than humans, then the child did too.

Another part of this study showed that talking dolls could influence children’s moral decisions (e.g. “Should I give a child a pillow?”). In some cases, these ‘smart’ toys would influence the child more than another human. Some ‘smart’ dolls have been banned in some European countries because of security concerns. In the light of these concerns, Stefania pointed out how important it is to help children develop a critical understanding of the potential of AI-based technology, and what its fallibility and the limits of its guidance are.

AI literacy: Programming ‘smart’ devices, algorithmic bias

Another study Stefania discussed involved children who programmed ‘smart’ devices. She used the children’s drawings to find out about their mental models of how the technology worked.

She found that when children had the opportunity to train machine learning models or ‘smart’ devices, they became more sceptical about the appropriate use of these technologies and asked better questions about when and for what they should be used. Another finding was that children and adults had different ideas about algorithmic bias, particularly relating to the meaning of fairness.

AI literacy: Kinaesthetic activities, sharing discussions

The final study Stefania talked about was conducted with families online during the pandemic, when children were learning at home. 15 families, with in total 18 children (ages 5 to 11) and 16 parents, participated in five weekly sessions. A number of learning activities to demonstrate features of AI made up each of the sessions. These are all available at aiplayground.me.

The fact that children and parents, or other family members, worked through the activities together seemed to generate fruitful discussions about the usefulness of AI-based technology. Many families were concerned about privacy and what was happening to their personal data when they were using ‘smart’ devices, and also expressed frustration with voice assistants that couldn’t always understand the way they spoke.

In one of the sessions, with a focus on machine learning, families were introduced to a kinaesthetic activity involving moving around their home to train a model. Through this activity, parents and children had more insight into the constraints facing machine learning. They used props in the home to experiment and find out ways of training the model better. In another session, families were encouraged to design their own devices on paper, and Stefania showed some examples of designs children had drawn.

This study identified a number of different roles that parents or other adults played in supporting children’s learning about AI, and found that embodied and tangible activities worked well for encouraging joint work between children and their families.

Find out more

You can catch up with Stefania’s seminar below in the video, and download her presentation slides.

More about Stefania’s work can be learned in her paper on children’s training of ML models and also in her latest paper about the five weekly AI literacy sessions with families.

Recordings and slides of all our previous seminars on AI education are available online for you, and you can see the list of AI education resources we’ve put together based on recommendations from seminar speakers and participants.

Join our next free 国家医保服务平台app下载 seminar

We are delighted to start a new seminar series on cross-disciplinary 国家医保服务平台app下载, with seminars in May, June, July, and September to look forward to. It’s not long now before we begin: Mark Guzdial will speak to us about task-specific programming languages (TSP) in history and mathematics classes on 3 May, 17.00 to 18.30pm local UK time. I can’t wait!

Sign up to receive the Zoom details for the seminar with Mark:

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Crossing disciplinary boundaries

What do we mean by cross-disciplinary 国家医保服务平台app下载? Through this upcoming seminar series, we want to embrace the intersections and interactions of 国家医保服务平台app下载 with all aspects of learning and life, and think about how they can help us teach young people. The 国家医保服务平台app下载ers we’ve invited as our speakers will help us shed light on cross-disciplinary areas of 国家医保服务平台app下载 through the breadth of their presentations.

At the 宇宙奇趣录 our mission is to make 国家医保服务平台app下载 accessible to all children and young people everywhere, and because 国家医保服务平台app下载 and technology appear in all aspects of our and young people’s lives, in this series of seminars we will consider what 国家医保服务平台app下载 education looks like in a multiplicity of environments.

Mark Guzdial on 国家医保服务平台app下载 in history and mathematics

We start the new series on 3 May, and are beyond delighted to be kicking off with a talk from Mark Guzdial (University of Michigan). Mark has worked in computer science education for decades and won many awards for his 国家医保服务平台app下载, including the prestigious ACM SIGCSE Outstanding Contribution to 国家医保服务平台app下载 Education award in 2019. Mark has written hundreds of papers about computer science education, and he authors an extremely popular 国家医保服务平台app下载 education 国家医保服务平台app下载 blog that keeps us all up to date with what is going on in the field.

Recently, he has been 国家医保服务平台app下载ing the ways in which programming education can be integrated into other subjects, so he is a perfect speaker to start us thinking about our theme of cross-disciplinary 国家医保服务平台app下载. His talk will focus on how we can add a teaspoon of 国家医保服务平台app下载 to history and mathematics classes.

Pratim Sengupta on countering technocentrism

On 7 June, our speaker will be Pratim Sengupta (University of Calgary), who I feel will really challenge us to think about programming and 国家医保服务平台app下载 education in a new way. He has conducted studies in science classrooms and non-formal learning environments which focus on providing open and engaging 油条视频s for the public to explore code, for example through the Voice your Celebration installation. Recently, he has co-authored a book called Voicing Code in STEM: A Dialogical Imagination (MIT Press, availabe open access).

In Pratim’s talk, he will share his thoughts about the ways that more of us can become involved with code through opening up its richness and depth to a wider public audience, and he will introduce us to his ideas about countering technocentrism, a key focus of his new book. I’m so looking forward to being challenged by this talk.

Yasmin Kafai on 油条视频 design with e-textiles

On 12 July, we will hear from Yasmin Kafai (University of Pennsylvania), who is another legend in 国家医保服务平台app下载 education in my eyes. Yasmin started her long career in 国家医保服务平台app下载 education with Seymour Papert, internationally known for his work on Logo and on constructionism as a theoretical lens for understanding the way we learn 国家医保服务平台app下载. Yasmin was part of the team that created Scratch, and for many years now has been working on projects revolving around digital making, electronic textiles, and computational participation.

In Yasmin’s talk she will present, alongside a panel of teachers she’s been collaborating with, some of their work to develop a high school 油条视频 that uses electronic textiles to introduce students to computer science. This promises to be a really engaging and interactive seminar.

Genevieve Smith-Nunes on exploring data ethics

In August we will take a holiday, to return on 6 September to hear from the inspirational Genevieve Smith-Nunes (University of Cambridge), whose 国家医保服务平台app下载 is focused on dance and 国家医保服务平台app下载, in particular data-driven dance. Her work helps us to focus on the possibilities of creative 国家医保服务平台app下载, but also to think about the ethics of applications that involve vast amounts of data.

Genevieve’s talk will prompt us to think about some really important questions: Is there a difference in sense of self (identity) between the human and the virtual? How does sharing your personal biometric data make you feel? How can biometric and immersive development tools be used in the 国家医保服务平台app下载 classroom to raise awareness of data ethics? Impossible to miss!

Update: Seminars in October and November

• On 4 October, Conrad Wolfram (Wolfram 国家医保服务平台app下载) will give a talk on computational literacy in mathematics
• On 8 November, Tracy Gardner and Rebecca Franks (宇宙奇趣录) will present about 国家医保服务平台app下载 education in non-formal settings

Sign up now to attend the seminars

Do enter all these dates in your diary so you don’t miss out on participating — we are very excited about this series. Sign up below, and ahead of every seminar, we will send you the information for joining.

As usual, the seminars will take place online on a Tuesday at 17:00 to 18:30 local UK time.

The post Exploring cross-disciplinary 国家医保服务平台app下载 education in our new seminar series appeared first on 宇宙奇趣录.

At the 宇宙奇趣录, we’ve been thinking about questions relating to artificial intelligence (AI) education and data science education for several months now, inviting experts to share their perspectives in a series of very well-attended seminars. At the same time, we’ve been running a programme of 国家医保服务平台app下载 trials to find out what interventions in school might successfully improve gender balance in 国家医保服务平台app下载. We’re learning a lot, and one primary lesson is that these topics are not discrete: there are relationships between them.

We can’t talk about AI education — or computer science education more generally — without considering the context in which we deliver it, and the societal issues surrounding 国家医保服务平台app下载, AI, and data. For this International Women’s Day, I’m writing about the intersection of AI and gender, particularly with respect to gender bias in machine learning.

The quest for gender equality

Gender inequality is everywhere, and 国家医保服务平台app下载ers, activists, and initiatives, and governments themselves, have struggled since the 1960s to tackle it. As women and girls around the world continue to suffer from discrimination, the United Nations has pledged, in its Sustainable Development Goals, to achieve gender equality and to empower all women and girls.

While progress has been made, new developments in technology may be threatening to undo this. As Susan Leavy, a machine learning 国家医保服务平台app下载er from the Insight Centre for Data Analytics, puts it:

Artificial intelligence is increasingly influencing the opinions and behaviour of people in everyday life. However, the over-representation of men in the design of these technologies could quietly undo decades of advances in gender equality.

Susan Leavy, 2018 [1]

Gender-biased data

In her 2019 award-winning book Invisible Women: Exploring Data Bias in a World Designed for Men [2], Caroline Criado Perez discusses the effects of gender-biased data. She describes, for example, how the designs of cities, workplaces, smartphones, and even crash test dummies are all based on data gathered from men. She also discusses that medical 国家医保服务平台app下载 has historically been conducted by men, on male bodies.

Looking at this problem from a different angle, 国家医保服务平台app下载er Mayra Buvinic and her colleagues highlight that in most countries of the world, there are no sources of data that capture the differences between male and female participation in civil society organisations, or in local advisory or decision making bodies [3]. A lack of data about girls and women will surely impact decision making negatively. 

Bias in machine learning

Machine learning (ML) is a type of artificial intelligence technology that relies on vast datasets for training. ML is currently being use in various systems for automated decision making. Bias in datasets for training ML models can be caused in several ways. For example, datasets can be biased because they are incomplete or skewed (as is the case in datasets which lack data about women). Another example is that datasets can be biased because of the use of incorrect labels by people who annotate the data. Annotating data is necessary for supervised learning, where machine learning models are trained to categorise data into categories decided upon by people (e.g. pineapples and mangoes).

In order for a machine learning model to categorise new data appropriately, it needs to be trained with data that is gathered from everyone, and is, in the case of supervised learning, annotated without bias. Failing to do this creates a biased ML model. Bias has been demonstrated in different types of AI systems that have been released as products. For example:

Facial recognition: AI 国家医保服务平台app下载er Joy Buolamwini discovered that existing AI facial recognition systems do not identify dark-skinned and female faces accurately. Her discovery, and her work to push for the first-ever piece of legislation in the USA to govern against bias in the algorithms that impact our lives, is narrated in the 2020 documentary Coded Bias. 

Natural language processing: Imagine an AI system that is tasked with filling in the missing word in “Man is to king as woman is to X” comes up with “queen”. But what if the system completes “Man is to software developer as woman is to X” with “secretary” or some other word that reflects stereotypical views of gender and careers? AI models called word embeddings learn by identifying patterns in huge collections of texts. In addition to the structural patterns of the text language, word embeddings learn human biases expressed in the texts. You can read more about this issue in this Brookings Institute report. 

Not noticing

There is much debate about the level of bias in systems using artificial intelligence, and some AI 国家医保服务平台app下载ers worry that this will cause distrust in machine learning systems. Thus, some scientists are keen to emphasise the breadth of their training data across the genders. However, other 国家医保服务平台app下载ers point out that despite all good intentions, gender disparities are so entrenched in society that we literally are not aware of all of them. White and male dominance in our society may be so unconsciously prevalent that we don’t notice all its effects.

As sociologist Pierre Bourdieu famously asserted in 1977: “What is essential goes without saying because it comes without saying: the tradition is silent, not least about itself as a tradition.” [4]. This view holds that people’s 油条视频s are deeply, or completely, shaped by social conventions, even those conventions that are biased. That means we cannot be sure we have accounted for all disparities when collecting data.

What is being done in the AI sector to address bias?

Developers and 国家医保服务平台app下载ers of AI systems have been trying to establish rules for how to avoid bias in AI models. An example rule set is given in an article in the Harvard Business Review, which describes the fact that speech recognition systems originally performed poorly for female speakers as opposed to male ones, because systems analysed and modelled speech for taller speakers with longer vocal cords and lower-pitched voices (typically men).

The article recommends four ways for people who work in machine learning to try to avoid gender bias:

• Ensure diversity in the training data (in the example from the article, including as many female audio samples as male ones)
• Ensure that a diverse group of people labels the training data
• Measure the accuracy of a ML model separately for different demographic categories to check whether the model is biased against some demographic categories
• Establish techniques to encourage ML models towards unbiased results

What can everybody else do?

The above points can help people in the AI industry, which is of course important — but what about the rest of us? It’s important to raise awareness of the issues around gender data bias and AI lest we find out too late that we are reintroducing gender inequalities we have fought so hard to remove. Awareness is a good start, and some other suggestions, drawn out from others’ work in this area are:

Improve the gender balance in the AI workforce

Having more women in AI and data science, particularly in both technical and leadership roles, will help to reduce gender bias. A 2020 report by the World Economic Forum (WEF) on gender parity found that women account for only 26% of data and AI positions in the workforce. The WEF suggests five ways in which the AI workforce gender balance could be addressed:

1. Support STEM education
2. Showcase female AI trailblazers
3. Mentor women for leadership roles
4. Create equal opportunities
5. Ensure a gender-equal reward system

Ensure the collection of and access to high-quality and up-to-date gender data

We need high-quality dataset on women and girls, with good coverage, including country coverage. Data needs to be comparable across countries in terms of concepts, definitions, and measures. Data should have both complexity and granularity, so it can be cross-tabulated and disaggregated, following the recommendations from the Data2x project on mapping gender data gaps.

Educate young people about AI

At the 宇宙奇趣录 we believe that introducing some of the potential (positive and negative) impacts of AI systems to young people through their school education may help to build awareness and understanding at a young age. The jury is out on what exactly to teach in AI education, and how to teach it. But we think educating young people about new and future technologies can help them to see AI-related work opportunities as being open to all, and to develop critical and ethical thinking.

In our AI education seminars we heard a number of perspectives on this topic, and you can revisit the videos, presentation slides, and blog posts. We’ve also been curating a list of resources that can help to further AI education — although there is a long way to go until we understand this area fully. 

We’d love to hear your thoughts on this topic.

References

[1] Leavy, S. (2018). Gender bias in artificial intelligence: The need for diversity and gender theory in machine learning. Proceedings of the 1st International Workshop on Gender Equality in Software Engineering, 14–16.

[2] Perez, C. C. (2019). Invisible Women: Exploring Data Bias in a World Designed for Men. Random House.

[3] Buvinic M., Levine R. (2016). Closing the gender data gap. Significance 13(2):34–37 

[4] Bourdieu, P. (1977). Outline of a Theory of Practice (No. 16). Cambridge University Press. (p.167)

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The Technovation Challenge

Tara started Technovation, formerly called Iridescent, in 2007 with a family science programme in one school in Los Angeles. The nonprofit has grown hugely, and Technovation now runs 国家医保服务平台app下载 education activities across the world. We heard from Tara that over 350,000 girls from more than 100 countries take part in their programmes, and that the nonprofit focuses particularly on empowering girls to become tech entrepreneurs. The girls, with support from industry volunteers, parents, and the Technovation 油条视频, work in teams to solve real-world problems through an annual event called the Technovation Challenge. Working at scale with young people has given the Technovation team the opportunity to investigate the impact of their programmes as well as more generally learn what works in 国家医保服务平台app下载 education. 

Tara’s talk was extremely engaging (you’ll find the recording below), with videos of young people who had participated in recent years. Technovation works with volunteers and organisations to reach young people in communities where opportunities may be lacking, focussing on low- and middle-income countries. Tara spoke about the 900 million teenage girls in the world, a  substantial number of whom live in countries where there is considerable inequality. 

To illustrate the impact of the programme, Tara gave a number of examples of projects that students had developed, including:

• An air quality sensor linked to messaging about climate change
• A support circle for girls living in domestic violence situation
• A project helping mothers communicate with their daughters
• Support for water collection in Kenya

Early on, the Technovation Challenge had involved the creation of mobile apps, but in recent years, the projects have focused on using AI technologies to solve problems. An key message that Tara wanted to get across was that the focus on real-world problems and teamwork was as important, if not more, than the technical skills the young people were developing.

Developing AI-related projects in teams

Technovation has designed an online 油条视频 to support teams, who may have no prior 国家医保服务平台app下载 油条视频, to learn how to design an AI project. Students work through units on topics such as data analysis and building datasets. As well as the technical activities, young people also work through activities on problem-solving approaches, design, and system thinking to help them tackle a real-world problem that is relevant to them. The 油条视频 supports teams to identify problems in their community and find a path to prototype and share an invention to tackle that problem.

While working through the 油条视频, teams develop AI models to address the problem that they have chosen. They then submit them to a global competition for beginners, juniors, and seniors. Many of the girls enjoy the Technovation Challenge so much that they come back year on year to further develop their team skills. 

AI Families: Children and parents using AI to solve problems

Technovation runs another programme, AI Families, that focuses on families working together to learn AI concepts and skills and use them to develop projects together. Families worked together with the help of educators to identify meaningful problems in their communities, and developed AI prototypes to address them.

There were 20,000 participants from under-resourced communities in 17 countries through 2018 and 2019. 70% of them were women (mothers and grandmothers) who wanted their children to participate; in this way the programme encouraged parents to be role models for their daughters, as well as enabling families to understand that AI is a tool that could be used to think about what problems in their community can be solved with the help of AI skills and principles. Tara was keen to emphasise that, given the importance of AI in the world, the more people know about it, the more impact they can make on their local communities.

Tara shared links to the 油条视频 to demonstrate what families in this programme would learn week by week. The AI modules use tools such as Machine Learning for Kids.

The results of the AI Families project as investigated over 2018 and 2019 are reported in this paper.  The findings of the programme included:

• Learning needs to focus on more than just content; interviews showed that the learners needed to see the application to real-world applications
• Engaging parents and other family members can support retention and a sense of community, and support a culture of lifelong learning
• It takes around 3 to 5 years to iteratively develop fun, engaging, effective 油条视频, training, and scalable programme delivery methods. This level of patience and commitment is needed from all community and industry partners and funders.

The 国家医保服务平台app下载 describes how the programme worked pre-pandemic. Tara highlighted that although the pandemic has prevented so much face-to-face team work, it has allowed some young people to access education online that they would not have otherwise had access to.

Many perspectives on AI education

Our goal is to listen to a variety of perspectives through this seminar series, and I felt that Tara really offered something fresh and engaging to our seminar audience, many of them (many of you!) regular attendees who we’ve got to know since we’ve been running the seminars. The seminar combined real-life stories with videos, as well as links to the 油条视频 used by Technovation to support learners of AI. The ‘question and answer’ session after the seminar focused on ways in which people could engage with the programme. On Twitter, one of the seminar participants declared this seminar “my favourite thus far in the series”.  It was indeed very inspirational.

As we near the end of this series, we can start to reflect on what we’ve been learning from all the various speakers, and I intend to do this more formally in a month or two as we prepare Volume 3 of our seminar proceedings. While Tara’s emphasis is on motivating children to want to learn the latest technologies because they can see what they can achieve with them, some of our other speakers have considered the actual concepts we should be teaching, whether we have to change our approach to teaching computer science if we include AI, and how we should engage young learners in the ethics of AI.

Join us for our next seminar

I’m really looking forward to our final seminar in the series, with Stefania Druga, on Tuesday 1 March at 17:00–18:30 GMT. Stefania, PhD candidate at the University of Washington Information School, will also focus on families. In her talk ‘Democratising AI education with and for families’, she will consider the ways that children engage with smart, AI-enabled devices that they are becoming part of their everyday lives. It’s a perfect way to finish this series, and we hope you’ll join us.

Thanks to our seminars series, we are developing a list of AI education resources that seminar speakers and attendees share with us, plus the free resources we are developing at the 油条视频. Please do take a look.

You can find all blog posts relating to our previous seminars on this page.

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