From 27 to 29 September 2023, we and the University of Cambridge are hosting the WiPSCE International Workshop on Primary and Secondary Computing Education Research for educators and researchers. This year, this annual conference will take place at Robinson College in Cambridge. We’re inviting all UK-based teachers of computing subjects to apply for one of five ‘all expenses paid’ places at this well-regarded annual event.
You could attend WiPSCE with all expenses paid
WiPSCE is where teachers and researchers discuss research that’s relevant to teaching and learning in primary and secondary computing education, to teacher training, and to related topics. You can find more information about the conference, including the preliminary programme, at wipsce.org.
As a teacher at the conference, you will:
Engage with high-quality international research in the field where you teach
Learn ways to use that research to develop your own classroom practice
Find out how to become an advocate in your professional community for research-informed approaches to the teaching of computing.
We are delighted that, thanks to generous funding from a funder, we can offer five free places to UK computing teachers, covering:
The registration fee
Two nights’ accommodation at Robinson College
Up to £500 supply costs paid to your school to cover your teaching
You need to be a currently practising, UK-based teacher of Computing (England), Computing Science (Scotland), ICT or Digital Technologies (N. Ireland), or Computer Science (Wales)
Your headteacher needs to be able to provide written confirmation that they are happy for you to attend WiPSCE
You need to be available to attend the whole conference from Wednesday lunchtime to Friday afternoon
You need to be willing to share what you learn from the conference with your colleagues at school and with your broader teaching community, including through writing an article about your experience and its relevance to your teaching for this blog or Hello World magazine
The application form will ask your for:
Your name and contact details
Demographic and school information
Your teaching experience
A statement of up to 500 words on why you’re applying and how you think your teaching practice, your school and your colleagues will benefit from your attendance at WiPSCE (500 words is the maximum, feel free to be concise)
After the 19 July deadline, we’re aiming to inform you of the outcome of your application on Friday 21 July.
Use the information you share in your form, particularly in your statement
Select applicants from a mix of primary and secondary schools, with a mix of years of computing teaching experience, and from a mix of geographic areas
Join us in strengthening research-informed computing classroom practice
We’d be delighted to receive your application. Being able to facilitate teachers’ attendance at the conference is very much aligned with our approach to research. Both at the Foundation and the Raspberry Pi Computing Education Research Centre, we’re committed to conducting research that’s directly relevant to schools and teachers, and to working in close collaboration with teachers.
We hope you are interested in attending WiPSCE and becoming an advocate for research-informed computing education practice. If your application is unsuccessful, we hope you consider coming along anyway. We’re looking forward to meeting you there. In the meantime, you can keep up with WiPSCE news on Twitter.
Learning materials, teaching approaches, and the curriculum as a whole are three areas where culturally relevance is important.
In our latest research study, funded by Cognizant, we worked with 13 primary school teachers in England on adapting computing lessons to incorporate culturally relevant and responsive principles and practices. Here’s an insight into the workshop we ran with them, and what the teachers and we have taken away from it.
Adapting lesson materials based on culturally relevant pedagogy
In the group of 13 England-based primary school Computing teachers we worked with for this study:
One third were specialist primary Computing teachers, and the other two thirds were class teachers who taught a range of subjects
Some acted as Computing subject lead or coordinator at their school
Most had taught Computing for between three and five years
The majority worked in urban areas of England, at schools with culturally diverse catchment areas
In November 2022, we held a one-day workshop with the teachers to introduce culturally relevant pedagogy and explore how to adapt two six-week units of computing resources.
An example of a collaborative activity from the workshop
The first part of the workshop was a collaborative, discussion-based professional development session exploring what culturally relevant pedagogy is. This type of pedagogy uses equitable teaching practices to:
Draw on the breadth of learners’ experiences and cultural knowledge
Facilitate projects that have personal meaning for learners
Develop learners’ critical consciousness
The rest of the workshop day was spent putting this learning into practice while planning how to adapt two units of computing lessons to make them culturally relevant for the teachers’ particular settings. We used a design-based approach for this part of the workshop, meaning researchers and teachers worked collaboratively as equal stakeholders to decide on plans for how to alter the units.
We worked in four groups, each with three or four teachers and one or two researchers, focusing on one of two units of work from The Computing Curriculum for teaching digital skills: a unit on photo editing for Year 4 (ages 8–9), and a unit about vector graphics for Year 5 (ages 9–10).
We based the workshop around two Computing Curriculum units that cover digital literacy skills.
In order to plan how the resources in these units of work could be made culturally relevant for the participating teachers’ contexts, the groups used a checklist of ten areas of opportunity. This checklist is a result of one of our previous research projects on culturally relevant pedagogy. Each group used the list to identify a variety of ways in which the units’ learning objectives, activities, learning materials, and slides could be adapted. Teachers noted down their ideas and then discussed them with their group to jointly agree a plan for adapting the unit.
By the end of the day, the groups had designed four really creative plans for:
A Year 4 unit on photo editing that included creating an animal to represent cultural identity
A Year 4 unit on photo editing that included creating a collage all about yourself
A Year 5 unit on vector graphics that guided learners to create their own metaverse and then add it to the class multiverse
A Year 5 unit on vector graphics that contextualised the digital skills by using them in online activities and in video games
Outcomes from the workshop
Before and after the workshop, we asked the teachers to fill in a survey about themselves, their experiences of creating computing resources, and their views about culturally relevant resources. We then compared the two sets of data to see whether anything had changed over the course of the workshop.
The workshop was a positive experience for the teachers.
After teachers had attended the workshop, they reported a statistically significant increase in their confidence levels to adapt resources to be culturally relevant for both themselves and others.
Teachers explained that the workshop had increased their understanding of culturally relevant pedagogy and of how it could impact on learners. For example, one teacher said:
“The workshop has developed my understanding of how culturally adapted resources can support pupil progress and engagement. It has also highlighted how contextual appropriateness of resources can help children to access resources.” – Participating teacher
Some teachers also highlighted how important it had been to talk to teachers from other schools during the workshop, and how they could put their new knowledge into practice in the classroom:
“The dedicated time and value added from peer discourse helped make this authentic and not just token activities to check a box.” – Participating teacher
“I can’t wait to take some of the work back and apply it to other areas and subjects I teach.” – Participating teacher
What you can expect to see next from this project
After our research team made the adaptations to the units set out in the four plans made during the workshop, the adapted units were delivered by the teachers to more than 500 Year 4 and 5 pupils. We visited some of the teachers’ schools to see the units being taught, and we have interviewed all the teachers about their experience of delivering the adapted materials. This observational and interview data, together with additional survey responses, will be analysed by us, and we’ll share the results over the coming months.
As part of the project, we observed teachers delivering the adapted units to their learners.
In our next blog post about this work, we will delve into the fascinating realm of parental attitudes to culturally relevant computing, and we’ll explore how embracing diversity in the digital landscape is shaping the future for both children and their families.
We’ve also written about this professional development activity in more detail in a paper to be published at the UKICER conference in September, and we’ll share the paper once it’s available.
Finally, we are grateful to Cognizant for funding this academic research, and to our cohort of primary computing teachers for their enthusiasm, energy, and creativity, and their commitment to this project.
Every day, most of us both consume and create data. For example, we interpret data from weather forecasts to predict our chances of a good weather for a special occasion, and we create data as our carbon footprint leaves a trail of energy consumption information behind us. Data is important in our lives, and countries around the world are expanding their school curricula to teach the knowledge and skills required to work with data, including at primary (K–5) level.
Kate FarrellProf. Judy Robertson
In our most recent research seminar, attendees heard about a research-based initiative called Data Education in Schools. The speakers, Kate Farrell and Professor Judy Robertson from the University of Edinburgh, Scotland, shared how this project aims to empower learners to develop data literacy skills and succeed in a data-driven world.
“Data literacy is the ability to ask questions, collect, analyse, interpret and communicate stories about data.”
– Kate Farrell & Prof. Judy Robertson
Being a data citizen
Scotland’s national curriculum does not explicitly mention data literacy, but the topic is embedded in many subjects such as Maths, English, Technologies, and Social Studies. Teachers in Scotland, particularly in primary schools, have the flexibility to deliver learning in an interdisciplinary way through project-based learning. Therefore, the team behind Data Education in Schools developed a set of cross-curricular data literacy projects. Educators and education policy makers in other countries who are looking to integrate computing topics with other subjects may also be interested in this approach.
Data citizens have skills they need to thrive in a world shaped by digital technology.
The Data Education in Schools projects are aimed not just at giving learners skills they may need for future jobs, but also at equipping them as data citizens in today’s world. A data citizen can think critically, interpret data, and share insights with others to effect change.
Kate and Judy shared an example of data citizenship from a project they had worked on with a primary school. The learners gathered data about how much plastic waste was being generated in their canteen. They created a data visualisation in the form of a giant graph of types of rubbish on the canteen floor and presented this to their local council.
Sorting food waste from lunch by type of material
As a result, the council made changes that reduced the amount of plastic used in the canteen. This shows how data citizens are able to communicate insights from data to influence decisions.
A cycle for data literacy projects
Across its projects, the Data Education in Schools initiative uses a problem-solving cycle called the PPDAC cycle. This cycle is a useful tool for creating educational resources and for teaching, as you can use it to structure resources, and to concentrate on areas to develop learner skills.
The PPDAC data problem-solving cycle
The five stages of the cycle are:
Problem: Identifying the problem or question to be answered
Plan: Deciding what data to collect or use to answer the question
Analysis: Preparing, modelling, and visualising the data, e.g. in a graph or pictogram
Conclusion: Reviewing what has been learned about the problem and communicating this with others
Smaller data literacy projects may focus on one or two stages within the cycle so learners can develop specific skills or build on previous learning. A large project usually includes all five stages, and sometimes involves moving backwards — for example, to refine the problem — as well as forwards.
Data literacy for primary school learners
At primary school, the aim of data literacy projects is to give learners an intuitive grasp of what data looks like and how to make sense of graphs and tables. Our speakers gave some great examples of playful approaches to data. This can be helpful because younger learners may benefit from working with tangible objects, e.g. LEGO bricks, which can be sorted by their characteristics. Kate and Judy told us about one learner who collected data about their clothes and drew the results in the form of clothes on a washing line — a great example of how tangible objects also inspire young people’s creativity.
As learners get older, they can begin to work with digital data, including data they collect themselves using physical computing devices such as BBC micro:bit microcontrollers or Raspberry Pi computers.
Free resources for primary (and secondary) schools
For many attendees, one of the highlights of the seminar was seeing the range of high-quality teaching resources for learners aged 3–18 that are part of the Data Education in Schools project. These include:
Data 101 videos: A set of 11 videos to help primary and secondary teachers understand data literacy better.
Lesson resources: Lots of projects to develop learners’ data literacy skills. These are mapped to the Scottish primary and secondary curriculum, but can be adapted for use in other countries too.
More resources are due to be published later in 2023, including a set of prompt cards to guide learners through the PPDAC cycle, a handbook for teachers to support the teaching of data literacy, and a set of virtual data-themed escape rooms.
You may also be interested in the units of work on data literacy skills that are part of The Computing Curriculum, our complete set of classroom resources to teach computing to 5- to 16-year-olds.
Join our next seminar on primary computing education
At our next seminar we welcome Aim Unahalekhaka from Tufts University, USA,who will share research about a rubric to evaluate young learners’ ScratchJr projects. If you have a tablet with ScratchJr installed, make sure to have it available to try out some activities. The seminar will take place online on Tuesday 6 June at 17.00 UK time, sign up now to not miss out.
To find out more about connecting research to practice for primary computing education, you can see a list of our upcoming monthly seminars on primary (K–5) teaching and learning and watch the recordings of previous seminars in this series.
Broadening participation and finding new entry points for young people to engage with computing is part of how we pursue our mission here at the Raspberry Pi Foundation. It was also the focus of our March online seminar, led by our own Dr Bobby Whyte. In this third seminar of our series on computing education for primary-aged children, Bobby presented his work on ‘designing multimodal composition activities for integrated K-5 programming and storytelling’. In this research he explored the integration of computing and literacy education, and the implications and limitations for classroom practice.
Motivated by challenges Bobby experienced first-hand as a primary school teacher, his two studies on the topic contribute to the body of research aiming to make computing less narrow and difficult. In this work, Bobby integrated programming and storytelling as a way of making the computing curriculum more applicable, relevant, and contextualised.
Critically for computing educators and researchers in the area, Bobby explored how theories related to ‘programming as writing’ translate into practice, and what the implications of designing and delivering integrated lessons in classrooms are. While the two studies described here took place in the context of UK schooling, we can learn universal lessons from this work.
What is multimodal composition?
In the seminar Bobby made a distinction between applying computing to literacy (or vice versa) and true integration of programming and storytelling. To achieve true integration in the two studies he conducted, Bobby used the idea of ‘multimodal composition’ (MMC). A multimodal composition is defined as “a composition that employs a variety of modes, including sound, writing, image, and gesture/movement [… with] a communicative function”.
Storytelling comes together with programming in a multimodal composition as learners create a program to tell a story where they:
Decide on content and representation (the characters, the setting, the backdrop)
Structure text they’ve written
Use technical aspects (i.e. motion blocks, tension) to achieve effects for narrative purposes
Defining multimodal composition (MMC) for a visual programming context
Multimodality for programming and storytelling in the classroom
To investigate the use of MMC in the classroom, Bobby started by designing a curriculum unit of lessons. He mapped the unit’s MMC activities to specific storytelling and programming learning objectives. The MMC activities were designed using design-based research, an approach in which something is designed and tested iteratively in real-world contexts. In practice that means Bobby collaborated with teachers and students to analyse, evaluate, and adapt the unit’s activities.
Mapping of the MMC activities to storytelling and programming learning objectives
The first of two studies to explore the design and implementation of MMC activities was conducted with 10 K-5 students (age 9 to 11) and showed promising results. All students approached the composition task multimodally, using multiple representations for specific purposes. In other words, they conveyed different parts of their stories using either text, sound, or images.
Bobby found that broadcast messages and loops were the least used blocks among the group. As a consequence, he modified the curriculum unit to include additional scaffolding and instructional support on how and why the students might embed these elements.
Bobby modified the classroom unit based on findings from his first study
In the second study, the MMC activities were evaluated in a classroom of 28 K-5 students led by one teacher over two weeks. Findings indicated that students appreciated the longer multi-session project. The teacher reported being satisfied with the project work the learners completed and the skills they practised. The teacher also further integrated and adapted the unit into their classroom practice after the research project had been completed.
How might you use these research findings?
Factors that impacted the integration of storytelling and programming included the teacher’s confidence to teach programming as well as the teacher’s ability to differentiate between students and what kind of support they needed depending on their previous programming experience.
In addition, there are considerations regarding the curriculum. The school where the second study took place considered the activities in the unit to be literacy-light, as the English literacy curriculum is ‘text-heavy’ and the addition of multimodal elements ‘wastes’ opportunities to produce stories that are more text-based.
Bobby’s research indicates that MMC provides useful opportunities for learners to simultaneously pursue storytelling and programming goals, and the curriculum unit designed in the research proved adaptable for the teacher to integrate into their classroom practice. However, Bobby cautioned that there’s a need to carefully consider both the benefits and trade-offs when designing cross-curricular integration projects in order to ensure a fair representation of both subjects.
Can you see an opportunity for integrating programming and storytelling in your classroom? Let us know your thoughts or questions in the comments below.
Join our next seminar on primary computing education
At our next seminar, we welcome Kate Farrell and Professor Judy Robertson (University of Edinburgh). This session will introduce you to how data literacy can be taught in primary and early-years education across different curricular areas. It will take place online on Tuesday 9 May at 17.00 UK time, don’t miss out and sign up now.
Yo find out more about connecting research to practice for primary computing education, you can find other our upcoming monthly seminars on primary (K–5) teaching and learning and watch the recordings of previous seminars in this series.
In our first seminar of 2023, we were delighted to welcome Dr Katie Rich and Carla Strickland. They spoke to us about teaching the programming construct of variables in Grade 3 and 4 (age 8 to 10).
Dr Katie RichCarla Strickland
We are hearing from a diverse range of speakers in our current series of monthly online research seminars focused on primary (K-5) computing education. Many of them work closely with educators to translate research findings into classroom practice to make sure that all our younger learners have positive first experiences of learning computing. An important goal of their research is to impact the development of pedagogy, resources, and professional development to support educators to deliver computing concepts with confidence.
Variables in computing and mathematics
Dr Katie Rich (American Institutes of Research) and Carla Strickland (UChicago STEM Education) are both part of a team that worked on a research project called Everyday Computing, which aims to integrate computational thinking into primary mathematics lessons. A key part of the Everyday Computing project was to develop coherent learning resources across a number of school years. During the seminar, Katie and Carla presented on a study in the project that revolved around teaching variables in Grade 3 and 4 (age 8 to 10) by linking this computing concept to mathematical concepts such as area, perimeter, and fractions.
Variables are used in both mathematics and computing, but in significantly different ways. In mathematics, a variable, often represented by a single letter such as x or y, corresponds to a quantity that stays the same for a given problem. However, in computing, a variable is an identifier used to label data that may change as a computer program is executed. A variable is one of the programming constructs that can be used to generalise programs to make them work for a range of inputs. Katie highlighted that the research team was keen to explore the synergies and tensions that arise when curriculum subjects share terms, as is the case for ‘variable’.
Defining a learning trajectory
At the start of the project, in order to be able to develop coherent learning resources across school years, the team reviewed research papers related to teaching the programming construct of variables. In the papers, they found a variety of learning goals that related to facts (what learners need to know) and skills (what learners need to be able to do). They grouped these learning goals and arranged the groups into ‘levels of thinking’, which were then mapped onto a learning trajectory to show progression pathways for learning.
Four of the five levels of thinking identified in the study: Data Storer, Data User, Variable User, Variable Creator. Click to enlarge.
Learning materials about variables
Carla then shared three practical examples of learning resources their research team created that integrated the programming construct of variables into a maths curriculum. The three activities, described below, form part of a series of lessons called Action Fractions. You can read more about the series of lessons in this research paper.
Robot Boxesis an unpluggedactivity that is positioned at the Data User level of thinking. It relates to creating instructions for a fictional robot. Learners have to pay attention to different data the robot needs in order to draw a box, such as the length and width, and also to the value that the robot calculates as area of the box. The lesson uses boxes on paper as concrete representations of variables to which learners can physically add values.
Ambling Animals is set at the ‘Data Storer’ and ‘Variable Interpreter’ levels of thinking. It includes a Scratch project to help students to locate and compare fractions on number lines. During this lesson, find a variable that holds the value of the animal that represents the larger of two fractions.
Adding Fractions draws on facts and skills from the ‘Variable Interpreter’ and ‘Variable Implementer’ levels of thinking and also includes a Scratch project. The Scratch project visualises adding fractions with the same denominator on a number line. The lesson starts to explain why variables are so important in computer programs by demonstrating how using a variable can make code more efficient.
Takeaways: Cross-curricular teaching, collaborative research
Teaching about the programming construct of variables can be challenging, as it requires young learners to understand abstract ideas. The research Katie and Carla presented shows how integrating these concepts into a mathematics curriculum is one way to highlight tangible uses of variables in everyday problems. The levels of thinking in the learning trajectory provide a structure helping teachers to support learners to develop their understanding and skills; the same levels of thinking could be used to introduce variables in other contexts and curricula.
Many primary teachers use cross-curricular learning to increase children’s engagement and highlight real-world examples. The seminar showed how important it is for teachers to pay attention to terms used across subjects, such as the word ‘variable’, and to explicitly explain a term’s different meanings. Katie and Carla shared a practical example of this when they suggested that computing teachers need to do more to stress the difference between equations such as xy = 45 in maths and assignment statements such as length = 45 in computing.
The Everyday Computing project resources were created by a team of researchers and educators who worked together to translate research findings into curriculum materials. This type of collaboration can be really valuable in driving a research agenda to directly improve learning outcomes for young people in classrooms.
How can this research influence your classroom practice or other activities as an educator? Let us know your thoughts in the comments. We’ll be continuing to reflect on this question throughout the seminar series.
You can watch Katie’s and Carla’s full presentation here:
Join our seminar series on primary computing education
We continue on Tuesday 7 February at 17.00 UK time, when we will hear from Dr Jean Salac, University of Washington. Jean will present her work in identifying inequities in elementary computing instruction and in developing a learning strategy, TIPP&SEE, to address these inequities. Sign up now, and we will send you a joining link for the session.
Improving gender balance in computing is part of our work to ensure equitable learning opportunities for all young people. Our Gender Balance in Computing (GBIC) research programme has been the largest effort to date to explore ways to encourage more girls and young women to engage with Computing.
Storytelling: Connecting computing 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 computing
Relevance: Making computing 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 research.
Gender balance in computing is not a new problem
I was fascinated to read a paper by Deborah Butler from 2000 which starts by summarising themes from research into gender balance in computing from the 1980s and 1990s, for example that boys may have access to more role models in computing 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 research from at least two decades ago — have we really made progress?
In England, it’s true that making Computing 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:
Computer Science qualification (England):
In 2018:
In 2021:
In 2022:
GCSE (age 16)
20.41%
20.77%
21.37%
A level (age 18)
11.74%
14.71%
15.17%
Percentage of girls among the students achieving Computer Science qualifications in England’s secondary schools
What did we do in the Gender Balance in Computing programme?
In GBIC, we carried out a range of research studies involving more than 14,500 pupils and 725 teachers in England. Implementation teams came from the Foundation, 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 research study: Subject Choice (Subject choice evenings and option booklets)
Each study (apart from the exploratory research 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’ experiences of the interventions. The evaluators’ reports and our associated blog posts give full details of each study.
The impact of the pandemic
The research 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 research 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 Computing
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 research 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 Computing 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 research programme was the difference in intent to study Computing 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 Computing as they enter secondary school at age 11. It also points to a need for more longitudinal research 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.
Compared to primary school age girls, girls aged 12 to 13 show dramatically reduced intent to continue studying computing.
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 research moving forward.
In the final seminar in our series on cross-disciplinary computing, Dr Tracy Gardner and Rebecca Franks, who work here at the Foundation, described the framework underpinning the Foundation’s non-formal learning pathways. They also shared insights from our recently published literature review about the impact that non-formal computing education has on learners.
Dr Tracy GardnerRebecca Franks
Tracy and Rebecca both have extensive experience in teaching computing, and they are passionate about inspiring young learners and broadening access to computing education. In their work here, they create resources and content for learners in coding clubs and young people at home.
How non-formal learning creates opportunities for computing education
UNESCO defines non-formal learning as “institutionalised, intentional, and planned… an addition, alternative, and/or complement to formal education within the process of life-long learning of individuals”. In terms of computing education, this kind of learning happens in after-school programmes or children’s homes as they engage with materials that have been carefully designed by education providers.
At the Raspberry Pi Foundation, we support two global networks of free, volunteer-led coding clubs where regular non-formal learning takes place: Code Club, teacher- and volunteer-led coding clubs for 9- to 13-year-olds taking place in schools in more than160 countries; and CoderDojo, volunteer-led programming clubs for young people aged 7–17 taking place in community venues and offices in 100 countries. Through free learning resources and other support, we enable volunteers to run their club sessions, offering versatile opportunities and creative, inclusive spaces for young people to learn about computing outside of the school curriculum. Volunteers who run Code Clubs or CoderDojos report that participating in the club sessions positively impacts participants’ programming skills and confidence.
Rebecca and Tracy are part of the team here that writes the learning resources young people in Code Clubs and CoderDojos (and beyond) use to learn to code and create technology.
Helping learners make things that matter to them
Rebecca started the seminar by describing how the team reviewed existing computing pedagogy research into non-formal learning, as well as large amounts of website visitor data and feedback from volunteers, to establish a new framework for designing and creating coding resources in the form of learning paths.
What the Raspberry Pi Foundation takes into account when creating non-formal learning resources. Click to enlarge.
As Rebecca explained, non-formal learning paths should be designed to bridge the so-called ‘Turing tar-pit’: the gap between what learners want to do, and what they have the knowledge and resources to achieve.
To prevent learners from getting frustrated and ultimately losing interest in computing, learning paths need to:
Be beginner-friendly
Include scaffolding
Support learner’s design skills
Relate to things that matter to learners
When Rebecca and Tracy’s team create new learning paths, they first focus on the things that learners want to make. Then they work backwards to bridge the gap between learners’ big ideas and the knowledge and skills needed to create them. To do this, they use the 3…2…1…Make! framework they’ve developed.
An illustration of the 3…2…1…Make! structure of the new Raspberry Pi Foundation non-formal learning paths.
Learning paths designed according to the framework are made up of three different types of project in a 3-2-1 structure:
Three Explore projects to introduce creators to a set of skills and provide step-by-step instructions to help them develop initial confidence
Two Design projects to allow creators to practise the skills they learned in the previous Explore projects, and to express themselves creatively while they grow in independence
One Invent project where creators use their skills to meet a project brief for a particular audience
Rebecca and Tracy’s team have created several new learning pathways based on the 3…2…1…Make! framework and received much positive feedback on them. They are now looking to develop more tools and libraries to support learners, to increase the accessibility of the paths, and also to conduct research into the impact of the framework.
New literature review of non-formal computing education showcases its positive impact
In the second half of the seminar, Tracy shared what the research literature says about the impact of non-formal learning. She and researchers at the Foundation particularly wanted to find out what the research says about computing education for K–12 in non-formal settings. They systematically reviewed 421 papers, identifying 88 papers from the last seven years that related to empirical research on non-formal computing education for young learners. Based on these 88 papers, they summarised the state of the field in a literature review.
So far, most studies of non-formal computing education have looked at knowledge and skill development in computing, as well as affective factors such as interest and perception. The cognitive impact of non-formal education has been generally positive. The papers Tracy and the research reviewed suggested that regular learning opportunities, such as weekly Code Clubs, were beneficial for learners’ knowledge development, and that active teaching of problem solving skills can lead to learners’ independence.
Non-formal computing education also seems to be beneficial in terms of affective factors (although it is unclear yet whether the benefits remain long-term, since most existing research studies conducted have been short-term ones). For example, out-of-school programmes can lead to more positive perception and increased awareness of computing for learners, and also boost learners’ confidence and self-efficacy if they have had little prior experience of computing. The social aspects of participating in coding clubs should not be underestimated, as learners can develop a sense of belonging and support as they work with their peers and mentors.
The literature review showed that non-formal computing complements formal in-school education in many ways. Not only can Code Clubs and CoderDojos be accessible and equitable spaces for all young people, because the people who run them can tailor learning to the individuals. Coding clubs such as these succeed in making computing fun and engaging by enabling a community to form and allowing learners to make things that are meaningful to them.
What existing studies in non-formal computing aren’t telling us
Another thing the literature review made obvious is that there are big gaps in the existing understanding of non-formal computing education that need to be researched in more detail. For example, most of the studies the papers in the literature review described took place with female students in middle schools in the US.
That means the existing research tells us little about non-formal learning:
In other geographic locations
In other educational settings, such as primary schools or after-school programmes
For a wider spectrum of learners
We would also love to see studies that hone in on:
The long-term impact of non-formal learning
Which specific factors contribute to positive outcomes
Non-formal learning about aspects of computing beyond programming
3…2…1…research!
We’re excited to continue collaborating within the Foundation so that our researchers and our team creating non-formal learning content can investigate the impact of the 3…2…1…Make! framework.
The aim of the 3…2…1…Make! framework is to enable young people to create things and solve problems that matter to them using technology.
This collaboration connects two of our long-term strategic goals: to engage millions of young people in learning about computing and how to create with digital technologies outside of school, and to deepen our understanding of how young people learn about computing and how to create with digital technologies, and to use that knowledge to increase the impact of our work and advance the field of computing education. Based on our research, we will iterate and improve the framework, in order to enable even more young people to realise their full potential through the power of computing and digital technologies.
Join our seminar series on primary computing education
From January, you can join our new monthly seminar series on primary (K–5) teaching and learning. In this series, we’ll hear insights into how our youngest learners develop their computing knowledge, so whether you’re a volunteer in a coding club, a teacher, a researcher, or simply interested in the topic, we’d love to see you at one of these monthly online sessions.
The first seminar, on Tuesday 10 January at 5pm UK time, will feature researchers and educators Dr Katie Rich and Carla Strickland. They will share findings on how to teach children about variables, one of the most difficult aspects of computing for young learners. Sign up now, and we will send you notifications and joining links for each seminar session.
We are excited to announce our next free online seminars, running monthly from January 2023 and focusing on primary school (K–5) teaching and learning of computing.
Our seminars, having covered various topics in computing education over the last three years, will now offer you a close look at current questions and research in primary computing education. Through this series we want to connect research and teaching practice, and further primary computing education across the globe.
Are these seminars for me?
Our upcoming seminars are for everyone interested in computing education, not just for primary school teachers — you are all cordially invited to join us. Previous seminars have been attended by a valuable mix of teachers, volunteers, tech industry professionals, and researchers, all keen to explore how computing education research can be put into practice.
Whether you teach in a classroom, or support learners in a coding club, you will find out how our youngest learners develop their computing knowledge. You’ll also explore with us what this means for your learning context in practical terms.
What you can expect from the online seminars
Each seminar starts with a presenter explaining, in easy-to-understand terms, some recent research they have done. The presentation is followed by a discussion in smaller groups. We then regroup for a Q&A session with the presenter.
Attendees of our previous seminars have said:
“The seminar will be useful in my practice when our coding club starts.”
“I love this initiative, your choice of speakers has been fantastic. You are creating a very valuable CPD resource for Computer Science teachers and educators all over the world. Thank you. 🙏”
“Just wanted to say a huge thank you for organising this. It was brilliant to hear the presentation but also the input from other educators in the breakout room. I currently teach in a department of one, which can be quite lonely, so to join other educators was brilliant and a real encouragement.”
Learn from specialists to benefit your own learners
Computer science has been taught in universities for many years, and only more recently has the subject been introduced in schools. That means there isn’t a lot of research about computing education for school-aged learners yet, and even less research about how young children of primary school age learn about computing.
That’s why we are excited to invite you to learn with us as we hear from international primary computing research teams who share their knowledge in our online seminars:
Tuesday 10 January 2023: Kicking off our series are Dr Katie Rich and Carla Strickland from Chicago with a seminar on how they developed new instructional materials for teaching variables in primary school. They will specifically focus on how they combined research with classroom realities, and share experiences of using their new materials in class.
Tuesday 7 February 2023: Dr Jean Salac from the University of Washington is particularly interested in identifying and addressing inequities in the computing classroom, and will speak about a new learning strategy that has been found to improve students’ understanding of computing concepts and to increase equal access to computing.
Tuesday 7 March 2023: Our own Dr Bobby Whyte from the Raspberry Pi Foundation will share practical examples of how primary computing can be integrated into literacy education. He will specifically look at storytelling elements within computing education and discuss the benefits of combining competency areas.
May 2023: Information coming soon
Tuesday 6 June 2023: In a collaborative seminar, Aim Unahalekhaka from Tufts University in Massachusetts will first present her research into how children learn coding through ScratchJr. Participants are encouraged to bring a tablet or device with ScratchJr to then look at practical project evaluations and teaching strategies that can help young learners create purposefully.
Tuesday 12 September 2023: Joining us from the University of Passau in Germany, Luisa Greifenstein will speak about how to give children appropriate feedback that encourages positive attitudes towards computing education. In particular, she will be looking at the effects of different feedback strategies and present a new Scratch tool that offers automated feedback.
October 2023: Information coming soon
Tuesday 7 November 2023: We are delighted to be joined by Dr Aman Yadav from Michigan State University who will focus on computational thinking and its value for primary schooling. In his seminar, he will not only discuss the unique opportunities for computational thinking in primary school but also discuss findings from a recent project that focused on teachers’ perspectives.
Sign up now to attend the seminars
All our seminars start at 17:00 UK time (18:00 CET / 12:00 noon ET / 9:00 PT) and take place in an online format. Sign up now to receive a calendar invitation and the link to join on the day of each seminar.
Conrad has been an influential figure in the areas of AI, data science, and computation for over 30 years. The company he co-founded, Wolfram Research, develops computational technologies including the Wolfram programming language, which is used by the Mathematica and WolframAlpha programs. In the seminar, Conrad spoke about his work on developing a mathematics curriculum “for the AI age”.
Computation is everywhere
In his talk, Conrad began by talking about the ubiquity of computation. He explained how computation (i.e. an operation that follows conditions to give a defined output) has transformed our everyday lives and led to the development of entire new sub-disciplines, such as computational medicine, computational marketing, and even computational agriculture. He then used the WolframAlpha tool to give several practical examples of applying high-level computation to problem-solving in different areas.
Yes, there are more people in the UK than sheep in New Zealand.
The power of computation for mathematics
Conrad then turned his attention to the main question of his talk: if computation has also changed real-world mathematics, how should school-based mathematics teaching respond? He suggested that, as computation has impacted all aspects of our daily lives, school subjects should be reformed to better prepare students for the careers of the future.
Hand calculation methods are time-consuming.
His biggest criticism was the use of hand calculation methods in mathematics teaching. He proposed that a mathematics curriculum that “assumes computers exist” and uses computers (rather than humans) to compute answers would better support students to develop a deep understanding of mathematical concepts and principles. In other words, if students spent less time doing hand-calculation methods, they could devote more time to more complex problems.
What does computational problem-solving look like?
One interesting aspect of Conrad’s talk was how he modelled the process of solving problems using computation. In all of the example problems, he outlined that computational problem-solving follows the same four-step process:
Define the question: Students think about the scope and details of the problem and define answerable questions to tackle.
Abstract to computable form: Using the information provided, students translate the question into a precise abstract form, such as a diagram or algorithm, so that it can be solved by a computer-based agent.
Computer answers: Using the power of computation, students solve the abstract question and resolve any issues during the computation process.
Interpret results: Students reinterpret and recontextualise the abstract answer to derive useful results. If problems emerge, students refine or fix their work.
Depending on the problem, the process can be repeated multiple times until the desired solution is reached. Rather than being proposed as a static list of outcomes, the process was presented by Conrad as an iterative cycle than resembles an “ascending helix”:
The problem-solving ‘helix’ model.
A curriculum for a world with AI
In the later stages of his talk, Conrad talked about the development of a new computational curriculum to better define what a modern mathematics curriculum might look like. The platform that hosts the curriculum, named Computer-Based Math (or CBM), outlines the need to integrate computational thinking into mathematics in schools. For instance, one of the modules, How Fast Could I Cycle Stage 7 Of The An Post Rás?, asks students to develop a computational solution to a real-world problem. Following the four-step problem-solving process, students apply mathematical models, computational tools, and real-world data to generate a valid solution:
Sample module from Computer-Based Math. Click to enlarge.
Some future challenges he remarked on included how a computer-based mathematics curriculum could be integrated with existing curricula or qualifications, at what ages computational mathematics should be taught, and what assessment, training, and hardware would be needed to support teachers to deliver such a curriculum.
Conrad concluded the talk by arguing that the current need for computational literacy is similar to the need for mass literacy and pondering whether the UK could lead the push towards a new computational curriculum suitable for learners who grow up with AI technologies. This point provided food for thought during our discussion section, especially for teachers interested in embedding computation into their lessons, and for researchers thinking about the impact of AI in different fields. We’re grateful to Conrad for speaking about his work and mission — long may it continue!
You can catch up on Conrad’s talk with his slides and the talk’s recording:
You can also explore Wolfram Research’s Computer-Based Maths curriculum, which offers learning materials to help teachers embed computation in their maths lessons.
Finally, try out Wolfram’s tools to solve everyday problems using computation. For example, you might ask WolframAlpha data-rich questions, which the tool converts from text input into a computable problem using natural language processing. (Two of my favourite example questions are: “How old was Leonardo when the Mona Lisa was painted?” and “What was the weather like when I was born?”)
Join our next seminar
In the final seminar of our series on cross-curricular computing, we welcome Dr Tracy Gardner and Rebecca Franks (Raspberry Pi Foundation) to present their ongoing work on computing education in non-formal settings. Sign up now to join us for this session on Tues 8 November:
We will shortly be announcing the theme of a brand-new series of research seminars starting in January 2023. The seminars will take place online on the first Tuesday of the month at 17:00–18:30 UK time.
For our seminar series on cross-disciplinary computing, it was a delight to host Genevieve Smith-Nunes this September. Her research work involving ballet and augmented reality was a perfect fit for our theme.
Genevieve Smith-Nunes
Genevieve has a background in classical ballet and was also a computing 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 Computing teachers.
Why dance and computing?
You may be surprised that there are links between dance, particularly ballet, and computing. 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 Computing curriculum in England, when she realised the lack of gender balance in her computing classroom. As an expert in both ballet and computing, she was driven by a desire to share the more creative elements of computing with her learners.
Two of Genevieve’s data-driven ballet dances: [arra]stre and [PAIN]byte
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 Computing students can discuss questions of ethics based on the kind of biometric and brainwave data that Genevieve is collecting in her research. Students need to learn about the ethical issues surrounding data as part of their Computing studies, and Genevieve has been working with student teachers to explore ways in which her research can be used to give examples of data ethics issues in the Computing curriculum.
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 research design caused by the COVID-19 pandemic, much of Genevieve’s PhD research took place online via video calls. New tools had to be created to capture dance performances within a digital online setting. Her research 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 research that she is collecting a lot of data from her research 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.
Brainwave data visualisation using the Emotiv software.
Data ethics provides lots of material for discussion in Computing classrooms. To exemplify this, Genevieve recorded her own brainwaves during dance, research, and rest activities, and then shared the data during workshops with student computing teachers. In our seminar Genevieve showed two visualisations of her own brainwave data (see the images above) and discussed how the student computing 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 computing 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:
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.
In our final two seminars for this year we are exploring further aspects of cross-disciplinary computing. Just this week, Conrad Wolfram of Wolfram Technologies joined us to present his ideas on maths and a core computational curriculum. We will share a summary and recording of his talk soon.
On 2 November, Tracy Gardner and Rebecca Franks from our team will close out this series by presenting work we have been doing on computing education in non-formal settings. Sign up now to join us for this session:
In our current series of research seminars, we are exploring how computing can be connected to other subjects using cross-disciplinary approaches. In July 2022, our speakers were Professor Yasmin Kafai from the University of Pennsylvania and Elaine Griggs, an award-winning teacher from Pembroke High School, Massachusetts, and we heard about their use of e-textiles to engage learners and broaden participation in computing.
Professor Yasmin Kafai illustrated her research with a wonderful background made up of young people’s e-textile projects
Building new clubhouses
The spaces where young people learn about computing have sometimes been referred to as clubhouses to relate them to the places where sports or social clubs meet. A computing clubhouse can be a place where learners come together to take part in computing activities and gain a sense of community. However, as Yasmin pointed out, research has found that computing clubhouses have also often been dominated by electronics and robotics activities. This has led to clubhouses being perceived as exclusive spaces for only the young people who share those interests.
Yasmin’s work is motivated by the idea of building new clubhouses that include a wide range of computing interests, with a specific focus on spaces for e-textile activities, to show that diverse uses of computing are valued.
A group of young people share their projects at Coolest Projects
Yasmin’s research into learning through e-textiles has taken place in formal computing lessons in high schools in America, by developing and using a unit from the Exploring Computer Science curriculum called “Stitching the Loop”. In the seminar, we were fortunate to be joined by Elaine, a computer science and robotics teacher who has used the scheme of work in her classroom. Elaine’s learners have designed wearable electronic textile projects with microcontrollers, sensors, LEDs, and conductive thread. With these materials, learners have made items such as paper circuits, wristbands, and collaborative banners, as shown in the examples below.
Items created by learners in the e-textile units of work
Teaching approaches for equity-oriented learning
The hands-on, project-based approach in the e-textile unit has many similarities with the principles underpinning the work we do at the Raspberry Pi Foundation. However, there were also two specific teaching approaches that were embedded in Elaine’s teaching in order to promote equitable learning in the computing classroom:
Prioritising time for learners to design their artefacts at the start of the activity.
Reflecting on learning through the use of a digital portfolio.
Making time for design
As teachers with a set of learning outcomes to deliver, we can often feel a certain pressure to structure lessons so that our learners spend the most time on activities that we feel will deliver those outcomes. I was very interested to hear how in these e-textile projects, there was a deliberate choice to foreground the aesthetics. When learners spent time designing their artefacts and could link it to their own interests, they had a sense of personal ownership over what they were making, which encouraged them to persevere and overcome any difficulties with sewing, code, or electronics.
Spending time on design helped this learner to persevere with problem-solving
My personal reflection was that creating a digital textiles project based on a set template could be considered the equivalent of teaching programming by copying code. Both approaches would increase the chances of a successful output, but wouldn’t necessarily increase learners’ understanding of computing concepts, nor encourage learners to perceive computing as a subject where everyone belongs. I was inspired by the insights shared at the seminar about how prioritising design time can lead to more diverse representations of making.
Reflecting on learning using a digital portfolio
Elaine told us that learners were encouraged to create a digital portfolio which included photographs of the different stages of their project, examples of their code, and reflections on the problems that they had solved during the project. In the picture below, the learner has shared both the ‘wrong’ and ‘right’ versions of their code, along with an explanation of how they debugged the error.
A learner’s example of debugging code from their portfolio
Yasmin explained the equity-oriented theories underpinning the digital portfolio teaching approach. The learners’ reflections allowed deeper understanding of the computing and electronics concepts involved and helped to balance the personalised nature of their artefacts with the need to meet learning goals.
Yasmin also emphasised how important it was for learners to take part in a series of projects so that they encountered computing and electronics concepts more than once. In this way, reflective journalling can be seen as an equitable teaching approach because it helps to move learners on from their initial engagement into more complex projects. Thinking back to the clubhouse model, it is equally important for learners to be valued for their complex e-textile projects as it is for their complex robotics projects, and so portfolios of a series of e-textile projects show that a diverse range of learners can be successful in computing at the highest levels.
Try e-textiles with your learners
Science and nature models made with an RPF project
If you’re thinking about ways of introducing e-textile activities to your learners, there are some useful resources here:
The Exploring Computer Science page contains all the information and resources relating to the “Stitching the Loop” electronic textiles unit. You can also find the video that Yasmin and Elaine shared during the seminar.
For e-textiles in a non-formal learning space, the StitchFest webpage has lots of information about an e-textile hackathon that took place in 2014, designed to broaden participation and perceptions in computing.
We’re having a short break in the seminar series but will be back in September when we’ll be continuing to find out more about cross-disciplinary approaches to computing.
In our next seminar on Tuesday 6 September 2022 at 17:00–18:30 BST / 12:00–13:30 EST / 9:00–10:30 PST / 18:00–19:30 CEST, we’ll be hearing all about the links between computing and dance, with our speaker Genevieve Smith-Nunes (University of Cambridge). Genevieve will be speaking about data ethics for the computing classroom through biometrics, ballet, and augmented reality (AR) which promises to be a fascinating perspective on bringing computing to new audiences.
When we teach children and young people about computing, do we consider how the subject has developed over time, how it relates to our students’ lives, and importantly, what our values are? Professor Pratim Sengupta shared some of the research he and his colleagues have been working on related to these questions in our June 2022 research seminar.
Prof. Pratim Sengupta
Pratim revealed a complex landscape where we as educators can be easily trapped by what may seem like good intentions, thereby limiting learning and excluding some students. His presentation, entitled Computational heterogeneity in STEM education, introduced me to the concept of technocentrism and profoundly impacted my thinking about the essence of programming and how I research it. In this blog post, particularly for those unable to attend this stimulating seminar, I give my simplified view of the rich philosophy shared by Pratim, and my fledgling steps to admit to my technocentrism and overcome it.
Our seminars on teaching cross-disciplinary computing
Between May 2022 and November 2022, we are hosting a new series of free research seminars about teaching computing in different ways and in different contexts. This second seminar of the series was well attended with participants from the USA, Asia, Africa, and Europe, including teachers, researchers, and industry professionals, who contributed to a lively and thought-provoking discussion.
Pratim is a learning scientist based in Canada with a long and distinguished career. He has studied how to teach computational modelling in K-12 STEM classrooms and investigates the complexity of learning. Grounded in working with teachers and students, he brings together computing, science, education, and social justice. Based on his work at Northwestern University, Vanderbilt University, and now with the Mind, Matter and Media lab at the University of Calgary, Pratim has published hundreds of academic papers over some 20 years. Pratim and his team challenge how we focus on making technological artefacts — code for code’s sake — in computing education, and refocuses us on the human experience of coding and learning to code.
What is technocentrism?
Pratim started the seminar by giving us an overview of some of the key ideas that underpin the way that computing is usually taught in schools, including technocentrism (Figure 1).
Figure 1: The features of technocentrism, a way of thinking about how we teach computing, particularly programming (Sengupta, 2022). Click to enlarge.
I have come to a simplified understanding of technocentrism. To me, it appears to be a way of looking at how we learn about computer science, where one might:
Focus on the finished product (e.g. a computer program), rather than thinking about the people who create, learn about, or use a program
Ignore the context and the environment, rather than paying attention to the history, the political situation, and the social context of the task at hand
View computing tasks as being implemented (enacted) by writing code, rather than seeing computing activities as rich and complex jumbles of meaning-making and communication that involve people using chatter, images, and lots of gestures
Anchor learning in concepts and skills, rather than placing the values and viewpoints of learners at the heart of teaching
Examples of technocentrism and how to overcome it
Pratim recounted several research activities that he and his team have engaged with. These examples highlight instances of potential technocentrism and investigate how we might overcome it.
In the first example research activity, Pratim explained how in maths and physics lessons, middle school students were asked to develop models to solve time and distance problems. Rather than immediately coding a potential solution, the researcher and teacher supported the learners to spend much time developing a shared perspective to understand and express the problems first. Students grappled with different ways of representing the context, including graphs and diagrams (see Figure 2). Gradually and carefully, teachers shifted students to recognise what was important and what was not, to move them toward a meaningful language to describe and solve the problems.
Figure 2: Two graphs from students showing different representations of a context, and a researcher’s bar chart representing how students’ shared understanding emerged over time (Sengupta, 2022). Click to enlarge.
In a second example research activity, students were asked to build a machine that draws shapes using sensors, motors, and code. Rather than jumping straight to a solution, the students spent time with authentic users of their machines. Throughout the process, students worked with others, expressing the context through physical movement, clarifying their thoughts by drawing diagrams, and finding the sweet spot between coding, engineering design, and maths (see Figure 3).
Figure 3: Students used physical movements and user guides to be with others and publicly share and experience the task with authentic users (Sengupta, 2022). Click to enlarge.
In a third example research activity, racial segregation of US communities was discussed with pre-service teachers. The predominately white teachers found talking about the topic very difficult at the beginning of the activity. To overcome this hesitancy, teachers were first asked to work with a simulation that modelled the process of segregation through abstracted dots (or computational agents), a transitional other. Following this hypothetical representation, the context was then recontextualised through a map of real data points of the ethnicity of residents in an area of the US. This kind of map is called a Racial Dot Map based on US census data. When the teachers were able to interpret the link between the abstracted dot simulation and the real-world data they were able to talk about racism and segregation in a way they could not do before. The initial simulation and the recontextualisation were a pedagogical tool to reveal racism and provide a space where students felt comfortable discussing their values and beliefs that would otherwise have remained implicit.
Figure 4: To facilitate discussion of racial segregation, a simulation was used that bridges abstracted dots and real people, giving pre-service teachers a space to reflect on discrimination (Sengupta, 2022). Click to enlarge.
My takeaways
Pratim shared four implications of this research for computing pedagogy (see Figure 5).
Figure 5: Pratim’s four implications for pedagogy. Click to enlarge
As a researcher of pedagogy, these points provide takeaways that I can relate to my own research practice:
Code is a voice within an experience rather than symbols at a point in time. For example, when I listen to students predicting what a snippet of code will do, I think of the active nature of each carefully chosen command and how for each student, the code corresponds with them differently.
Code lives as a translation bridging many dimensions, such as data representation, algorithms, syntax, and user views. This statement resonates deeply with my liking of Carsten Schultes’s block model [1] but extends to include the people involved.
We should listen carefully and attentively to teachers, rather than making assumptions about what happens in classrooms. Teachers create new ideas. This takeaway is very important and reminds me about the trust and relationships built between teachers and researchers and how important it is to listen.
Uncertainty and ambiguity exist in learning, and this can take time to recognise. This final point makes me smile. As a developer, teacher, and researcher, I have found dealing with ambiguity hard at various points in my career. Still, over time, I think I am getting better at seeing it and celebrating it.
Listening to Pratim share his research on the teaching and learning of computing and the pitfalls of technocentrism has made me think deeply about how I view computer science as a subject and do research about it. I have shared some of my reflections in this blog, and I plan to incorporate the underlying theory and ideas in my ongoing research projects.
If you would like to find out more about Pratim’s work, please look over his slides, watch his presentation, read the upcoming chapter in our seminar proceedings, or respond to this blog by leaving a comment so we can discuss!
Today we share the second report in our series of findings from the Gender Balance in Computing research programme, which we’ve been running as part of the National Centre for Computing Education and with various partners. In this £2.4 million research programme, funded by the Department for Education in England, we aim to identify ways to encourage more female learners to engage with Computing and choose to study it further.
Previously, we shared the evaluation report about our pilot study of using a storytelling approach with very young computing learners. This new report, again coming from the Behavioural Insights Team (BIT) which acts as the programme’s independent evaluator, describes our study of another teaching approach.
Existing research suggests that computing is not always taught in a way that is engaging for girls in particular [1], and that we can improve this. With the intervention at hand, we wanted to explore the effects of using a pair programming teaching approach with primary school learners aged 8 to 11. We have critically and carefully examined the findings, which show mixed outcomes regarding the effectiveness of the approach, and we believe that the research provides insights that increase our shared understanding of how to teach computing effectively to young learners.
Computing education through a collaborative lens
Many people think that writing computer programs is a task carried out by people working individually. A 2017 study of 8- and 9-year-olds [2] confirms this: when asked to draw a picture of a computer scientist doing work, 90% of the children drew a picture of one person working alone. This stereotype is present in teaching and learning about computing and computer science; many computer programming lessons take place in a way that promotes solitary working, with individual students sitting in front of separate computers, working on their own code and debugging their own errors.
Professional software development rarely happens like this. For example, at the Raspberry Pi Foundation, our software engineers work collaboratively on design and often pair up to solve problems. Computing education research also has identified the importance of looking at computer programming through a collaborative lens. This viewpoint allows us to see computing as a subject with scope for collaborative group work in which students create useful applications together and are part of a community where programming has a shared social context [3].
Researching collaborative learning in the primary computing classroom
One teaching approach in computing that promotes collaborative learning is pair programming (a practice also used in industry). This is a structured way of working on programming tasks where learners are paired up and take turns acting as the driver or the navigator. The driver controls the keyboard and mouse and types the code. The navigator reads the instructions, supports the driver by watching out for errors in the code, and thinks strategically about next steps and solutions to problems. Learners swap roles every 5 to 10 minutes, to ensure that both partners can contribute equally and actively to the collaborative learning.
As one part of the Gender Balance in Computing programme, we designed a project to explore the effect of pair programming on girls’ attitudes towards computing. This project builds on research from the USA which suggests that solving problems collaboratively increases girls’ persistence when they encounter difficulties in programming tasks [4].
In the Pair Programming project, we worked with teachers of Year 4 (ages 8–9) and Year 6 (ages 10–11) in schools in England. From January to March 2020, we ran a pilot study with 10 schools and used the resulting teacher feedback to finalise the training and teaching materials for a full randomised controlled trial. Due to the coronavirus pandemic, we trained teachers in the pair programming approach using an online course instead of face-to-face training.
A tweet from a school about taking part in the pair programming study.
The randomised controlled trial ran from September to December 2021 with 97 schools. Schools were randomly allocated to either the intervention group and used the pair programming training and the scheme of work we designed, or to the control group and taught Computing in their usual way, not aware that we were investigating the effects of pair programming. Due to the coronavirus pandemic, our training of teachers in the pair programming approach had to take place via an online course instead of face to face.
Teachers in both groups delivered 12 weeks of Computing lessons, in which learners used Scratch programming to draw shapes and create animations. The lessons covered computing concepts from Key Stage 2 (ages 7–11), such as using sequences, selection, and repetition in programs, as well as digital literacy skills such as using technology respectfully.
What can we learn about pair programming from the study?
The findings about this particular intervention were limited by the amount of data the independent evaluators at BIT were able to collect amongst learners and teachers given the ongoing pandemic. BIT’s evaluation was primarily based on quantitative data collected from learners at the start and the end of the intervention. To collect the data, they used a validated instrument called the Student Computer Science Attitude Survey (SCSAS), which asks learners about their attitudes towards Computing. The evaluators compared the datasets gathered from the intervention group (who took part in pair programming lessons) and the control group (who took part in Computing lessons taught with a ‘business as usual’ model).
The evaluators’ data analysis found no statistically significant evidence that the pair programming approach positively affected girls’ attitudes towards computing or their intention to study computing in the future. The lack of statistically significant results, called a null result in research projects, can appear disappointing at first. But our work involves careful reflection and critical thinking about all outcomes of our research, and the result of this project is no exception. These are factors that may have contributed towards the result:
The independent evaluators suggested that the intervention may lead to different findings if it were implemented again without the disruptions caused by the pandemic. One of their recommendations was to revert to our original planned model of providing face-to-face training to teachers delivering the pair programming approach, and we believe this would embed a deeper understanding of the approach.
Our research built upon a prior study [4] that suggested a connection between pair programming and increased confidence about problem-solving in girls of a similar age. That study took place in a non-formal setting in an all-girls group, whereas our research was situated in formal education in mixed gender groups. It may be that these differences are significant.
It may be that there is no causal link between using the pair programming approach and an increase in girls’ attitudes towards computing, or that the link may only become apparent over a longer time-scale, or that the pair programming approach needs to be combined with other strategies to achieve a positive effect.
The evaluators also gathered qualitative data by running teacher and learner interviews, and we were pleased that this data provided some rich insights into the benefits of using a pair programming approach in the primary classroom, and gave some promising indications of possible benefits for female learners in particular.
Teachers spoke positively about the use of paired activities, and felt that having the defined roles of driver and navigator helped both partners to contribute equally to the programming tasks. Learners said that they enjoyed working in pairs, even though there could be some moments of frustration. Some of the teachers were even planning to integrate pair programming into future lessons. This suggests that the approach was effective both in engaging and motivating learners, as well as in facilitating the planned learning outcomes of the lessons, and that it can be used more widely in primary computing teaching.
“I don’t know why I’ve never thought to do computing like that, actually, because it’s a really good vehicle for the fact that there are two roles, clearly defined. There’s all your conversation, and knowledge comes through that, and then they’re both equally having a turn.” — Primary school teacher (report, p. 38)
“I like working with both [both as a partner and by yourself] because when you do pair programming, you’re collaborating with your partner, making links, and you have to tell them what to do. But if you have a really good idea and then they put the wrong thing in the wrong place, it’s quite annoying.” — Female learner (report, p. 40)
Both teachers and learners felt that having the support of a partner boosted learners’ confidence, which echoes previous research in the field [5, 6]. In computing, boys more accurately assess their capabilities, whereas girls tend to underestimate their performance [7]. When learners feel a positive emotion such as confidence towards a subject, combined with a belief that they can succeed in tasks related to that subject, this shows self-efficacy [8]. Our findings suggest that, through the use of the pair programming approach, both boys and girls improved their sense of self-efficacy towards Computing, which is corroborated by quotes from learners themselves. This is interesting because a sense of self-efficacy in Computing is linked to the decisions to pursue further study in the subject [9]. More research could build on this observation.
“I do think that having that equal time to have a go at both, thinking of the girls I’ve got, will have helped my girls, because they lack a bit of confidence. They were learning very quickly that, ‘Actually, yes, we are sure. We can do this.’” — Primary teacher (report, p. 44)
“It might be easier to do pair programming [compared to ‘normal’ lessons] because if you’re stuck, your partner can be helpful.” — Female learner (report, p. 43)
Watch this short video that shows pair programming being used in a primary classroom.
Read the evaluation report of the pair programming intervention, where you’ll also find more quotes from teachers and learners.
Try the free training course on pair programming we designed and used for this project. It also includes links to the lesson plans that teachers worked with.
Collaboration in our research
We will continue to publish evaluation reports and our reflections on the other projects in the Gender Balance in Computing programme. If you would like to stay up-to-date with the programme, you can sign up to the newsletter.
The insights gained from this trial will feed forwards into our future work. Through the process of working with schools on this project, we have increased our understanding of the process of research in educational settings in many ways. We are very grateful for the input from teachers who took part in the first stage of the trial, with whom we developed an effective co-production model for developing resources, a model we will use in future research projects. Teachers who took part in the second stage of the project told us that the resources we provided were of good quality, which demonstrates the success of this co-production approach to developing resources.
In our new Raspberry Pi Computing Education Research Centre, created with the University of Cambridge Department of Computer Science and Technology, we will collaborate closely with teachers and schools when implementing and evaluating research projects. You are invited to the free in-person launch event of the Centre on 20 July in Cambridge, UK, where we hope to meet many teachers, researchers, and other education practitioners to strengthen a collaborative community around computing education research.
References
[1] Goode, J., Estrella, R., & Margolis, J. (2018). Lost in Translation: Gender and High School Computer Science. In Women and Information Technology. https://doi.org/10.7551/mitpress/7272.003.0005
[2] Alexandria K. Hansen, Hilary A. Dwyer, Ashley Iveland, Mia Talesfore, Lacy Wright, Danielle B. Harlow, and Diana Franklin. 2017. Assessing Children’s Understanding of the Work of Computer Scientists: The Draw-a-Computer-Scientist Test. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE ’17). Association for Computing Machinery, New York, NY, USA, 279–284. https://doi.org/10.1145/3017680.3017769
[3] Yasmin B. Kafai and Quinn Burke. 2013. The social turn in K-12 programming: moving from computational thinking to computational participation. In Proceeding of the 44th ACM technical symposium on Computer science education (SIGCSE ’13). Association for Computing Machinery, New York, NY, USA, 603–608. https://doi.org/10.1145/2445196.2445373
[5] Charlie McDowell, Linda Werner, Heather E. Bullock, and Julian Fernald. 2006. Pair programming improves student retention, confidence, and program quality. Commun. ACM 49, 8 (August 2006), 90–95. https://doi.org/10.1145/1145287.1145293
[6] Denner, J., Werner, L., Campe, S., & Ortiz, E. (2014). Pair programming: Under what conditions is it advantageous for middle school students? Journal of Research on Technology in Education, 46(3), 277–296. https://doi.org/10.1080/15391523.2014.888272
[7] Maria Kallia and Sue Sentance. 2018. Are boys more confident than girls? the role of calibration and students’ self-efficacy in programming tasks and computer science. In Proceedings of the 13th Workshop in Primary and Secondary Computing Education (WiPSCE ’18). Association for Computing Machinery, New York, NY, USA, Article 16, 1–4. https://doi.org/10.1145/3265757.3265773
[9] Allison Mishkin. 2019. Applying Self-Determination Theory towards Motivating Young Women in Computer Science. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE ’19). Association for Computing Machinery, New York, NY, USA, 1025–1031. https://doi.org/10.1145/3287324.3287389
Last summer, the Raspberry Pi Foundation and the University of Cambridge Department of Computer Science and Technology created a new research centre focusing on computing education research for young people in both formal and non-formal education. The Raspberry Pi Computing Education Research Centre is an exciting venture through which we aim to deliver a step-change for the field.
Computing education research that focuses specifically on young people is relatively new, particularly in contrast to established research disciplines such as those focused on mathematics or science education. However, computing is now a mandatory part of the curriculum 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 Raspberry Pi Computing Education Research 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 computing education research, we invite you to register for a ticket to attend. By coming together in person, we want to help strengthen a collaborative community of researchers, teachers, and other education practitioners.
The launch event is your opportunity to meet and mingle with members of the Centre’s research 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 research, 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 Foundation.
Prof. Mark GuzdialProf. Alastair BeresfordCarrie Anne Philbin MBE
The event will take place at the Department of Computer Science and Technologyin Cambridge. It will start at 15.00 with a reception where you’ll have the chance to talk to researchers 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 research at the Centre
The aim of the Raspberry Pi Computing Education Research Centre is to increase our understanding of teaching and learning computing, 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 computing or who experience 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 research project on culturally relevant computing teaching, following on from a project at the Raspberry Pi Foundation. The Centre’s research team is uniquely positioned, straddling both the University and the Foundation. 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 research, and the Raspberry Pi Foundation works with schools, educators, and learners globally to pursue its mission to put the power of computing into the hands of young people.
In our research at the Centre, we will make sure that:
We collaborate closely with teachers and schools when implementing and evaluating research projects
We publish research results in a number of different formats, as promptly as we can and without a paywall
We translate research findings into practice across the Foundation’s extensive programmes and with our partners
We are excited to work with a large community of teachers and researchers, 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 computingeducationresearch.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 Raspberry Pi Foundation on Twitter or Linkedin.
From May to November 2022, our seminars focus on the theme of cross-disciplinary computing. Through this seminar series, we want to explore the intersections and interactions of computing with all aspects of learning and life, and think about how they can help us teach young people. We were delighted to welcome Prof. Mark Guzdial (University of Michigan) as our first speaker.
Professor Mark Guzdial, University of Michigan
Mark has worked in computer science (CS) education for decades and won many awards for his research, including the prestigious ACM SIGCSE Outstanding Contribution to Computing Education award in 2019. He has written literally hundreds of papers about CS education, and he authors an extremely popular computing education research 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 curriculum. 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 computing. 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 computing in school. Although in England, computing 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 computing for younger children. And once computing becomes optional, numbers drop, wherever you are.
Not enough students are experiencing computer science in school.
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 computing 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 research 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.
We have recorded the seminar and will be sharing the video very soon, so bookmark this page.
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.
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 computing to?
Join our next free research seminar
We’d love you to join us for the next seminar in our series on cross-disciplinary computing. 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 experiences 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.
We will shortly be sharing details about the official in-person launch event of the Raspberry Pi Computing Education Research 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.
We’ve been running the Gender Balance in Computing programme of research since 2019, as part of the National Centre for Computing Education (NCCE) and with various partners. It’s a £2.4 million research programme funded by the Department for Education in England that aims to identify ways to encourage more girls and young women to engage with Computing and choose to study it further. The programme is made up of four separate areas of research, in which we are running a number of interventions.
The first independent evaluation report from the Behavioural Insights Team (BIT) on our series of interventions has now been published. It relates to an intervention within the research area ‘Teaching Approach’, evaluating our pilot study of teaching computing to Key Stage 1 children using a storytelling approach. The evaluators from BIT found that this pilot study produced evidence of promise for the storytelling approach. They recommend conducting a full-size trial to test how effective this approach is for engaging female pupils with Computing.
Teaching computing through storytelling
Like many Computing curricula around the world, the English National Curriculum emphasises the importance of teaching Computing through a range of content so that pupils can express themselves and develop their ideas using digital tools. Our ‘Teaching Approach’ project builds on research grounded in sociocultural learning theories that suggest teaching approaches that encourage collaboration and use a variety of contexts can make Computing a more inclusive subject for all learners. Within this project, we are running three different interventions, each with learners of different ages.
Evidence indicates that gender stereotypes around Computing develop early (1). Therefore we designed a trial — the first of its kind in England — to explore a storytelling approach for teaching Computing with younger children (6- to 7-year-olds). A small body of research suggests that using storytelling as a learning context for Computing can be engaging for both boys and girls. Research results indicate that:
Teaching computing through storytelling and story-writing is effective for motivating 11- to 14-year-old girls to learn programming (2)
Children who write computer programs to tell stories see Computing as a subject that is equally as easy or difficult for both boys and girls (3)
In a non-formal learning space, primary-aged girls are more likely to choose a storybook beginner electronics activity rather than open-ended beginner electronics free play (4)
The pilot study and the evaluation methods
As combining evidence from research with older students and in non-formal education is experimental, we designed this storytelling trial as a small pilot study. Our aim was to generate early evidence as to how feasible a teaching approach that uses storytelling might be in the primary Computing classroom.
We recruited 53 schools to take part in the pilot study, which ran from April to July 2021. Many schools were still facing challenges due to the ongoing coronavirus pandemic, and we are very grateful to the teachers and learners who have taken part for their contribution to this important research.
To conduct the study, we created a free online training course, and a scheme of work, for schools to teach Computing concepts to 6- and 7-year olds using a storytelling approach. Over a sequence of the 12 lessons in the scheme of work, pupils used the ScratchJr programming environment to animate their own digital stories and learn about Computing concepts, such as sequence and repetition, linked to elements of stories, such as structure, rhyme, and speech.
To enable the independent evaluation of the effectiveness of the storytelling approach by BIT, schools were allocated either to an intervention group, which used the training course and the storytelling scheme of work, or to a control group, which taught Computing in their usual way and was not made aware that the approach being trialled involved storytelling. For their evaluation, BIT gathered data from both groups to compare them:
They conducted surveys measuring learners’ attitudes toward computing and their intentions to study it in the future
They carried out observations of lessons, interviews with teachers, and discussions with learners
They ran a survey to gather feedback about the trial from teachers
The gathered data was assessed against five categories: evidence of promise, fidelity, acceptability, feasibility, and readiness for trial.
Main findings of the evaluation team
After analysing the data collected from observations, interviews, learner discussions, pupil surveys, and teacher surveys, the key finding of the independent evaluators was that the storytelling teaching approach had evidence of promise, and that it is worthwhile scaling up our intervention for a larger trial with more schools.
The evaluators’ teacher interviews confirmed the early development of gender stereotypes in the classroom. This highlights the importance of introducing Computing to young learners in a way that engages both boys and girls.
“I’ve really noticed how there’s already differences in views of what’s a boy, what’s a girl, the boys are getting in front of me, like, ‘I want a boy car, I don’t want a girl car’. Then we’ve got the other side where we’ve got fairy tales and princesses and, ‘Oh, I’m a bunny. Do you want to play with me?’”
Teacher (evaluation report, p. 22)
Teachers told the evaluators that pupils enjoyed personalising their stories in ScratchJr, and that they themselves felt positive about the use of storytelling to teach computing.
“I think [the storytelling aspect] gives them something real to work through, so it’s not… abstract… I think through the storytelling, they’re able to make it as funny or whatever they want, and it’s also their own interest. [Female student], she dotes on animals, so she’s always having giraffes and all of that, so it’s something that they can make their own connections too… Yes, I did really like the storytelling.”
Teacher (evaluation report, p. 26)
Teacher feedback provided some evidence that the storytelling lessons had equally increased both male and female pupils’ interest, confidence, and skills.
The independent evaluation team advised caution when interpreting the quantitative data from the pupil surveys, due to the small sample size in this pilot study and the high attrition rates caused by coronavirus-related disruptions. We ourselves would like to add that the study raises questions about the reliability of quantitative survey data collected from very young children using Likert scales, BIT’s chosen survey format for this evaluation. Although the evaluators have made some positive steps in creating a new survey suitable for young children, this research instrument may need further testing; the survey results would need to be interpreted in this light, and more research in this area would be recommended.
This intervention was based on one of the teaching approaches for which there was only early evidence of effectiveness, so it is a good outcome to have a larger trial recommended based on our pilot study. It’s often said that research ends up recommending more research, but in this case our small pilot project really does give robust evidence that we should trial the storytelling approach with more schools.
The independent evaluators collected feedback from both teachers and pupils that confirms the storytelling intervention we designed is feasible in the classroom. The feedback also indicates where we can make small adjustments that will refine and develop the training and scheme of work for a larger-scale study (evaluation report, p. 35), and we will consider this feedback carefully. While some teachers suggested that the training be shortened, less experienced teachers highlighted the need to ensure the training introduces teachers to all of the content covered in the lessons. This feedback helps us to better understand how Computing is taught in primary schools, and how this is influenced by the wide variety of experience and subject knowledge that teachers have. Interestingly, in the control group, some of the teachers reported that they also introduced coding to their learners by having them create stories. We would like to conduct further research into how schools introduce young learners to programming, and we’ll be continuing to reflect on how best to offer flexible content for teacher training related to our research studies.
We’re now looking at how to continue to investigate the effectiveness of the storytelling approach through a larger trial, alongside other projects in which we’re exploring female engagement in computing education through our recently established Raspberry Pi Computing Education Research Centre.
More evaluations are on the way for our other studies in the Gender Balance in Computing programme, including:
Two other trials of teaching approaches
Interventions in non-formal education contexts
Trials of approaches to building a sense of belonging in Computing
Research into the impact of timetabling and options evenings
If you would like to stay up-to-date with the research programme, you can sign up to the Gender Balance in Computing newsletter. We will also post our reflections on the projects on this blog when the evaluations are completed.
1 Mulvey, K. L. and Irvin, M. J. (2018). Judgments and reasoning about exclusion from counter-stereotypic STEM career choices in early childhood. Early Child. Res. Q. 44, 220–230. https://doi.org/10.1016/j.ecresq.2018.03.016
2 Kelleher, C., Pausch, R. and Kiesler, S. (2007). Storytelling alice motivates middle school girls to learn computer programming. In CHI ’07: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1455–1464. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/1240624.1240844
3 Zaidi, R., Freihofer, I. and Childress Townsend, G. (2017). Using Scratch and Female Role Models while Storytelling Improves Fifth-Grade Students’ Attitudes toward Computing. In SIGCSE ’17: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 791–792. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3017680.3022451
4 McLean, M., & Harlow, D. (2017). Designing inclusive STEM activities: A comparison of playful interactive experiences across gender. In IDC ’17: Proceedings of the 2017 Conference on Interaction Design and Children, 567–574. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3078072.3084326
Between September 2021 and March 2022, we’ve been partnering with The Alan Turing Institute to host a series of free research seminars about how to young people about AI and data science.
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 Druga, University of Washington
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. 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.
A slide from Stefania’s AI literacy seminar. Click to enlarge.
Working directly with families, the researchers 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.
A slide from Stefania’s AI literacy seminar. Click to enlarge.
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.
A slide from Stefania’s AI literacy seminar. Click to enlarge.
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.
A slide from Stefania’s AI literacy seminar. Click to enlarge.
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.
A slide from Stefania’s AI literacy seminar. Click to enlarge.
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.
A slide from Stefania’s AI literacy seminar. Click to enlarge.
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.
We are delighted to launch our next series of free online seminars, this time on the topic of cross-disciplinary computing, running monthly from May to November 2022. As always, our seminars are for all researchers, educators, and anyone else interested in research related to computing education.
Crossing disciplinary boundaries
What do we mean by cross-disciplinary computing? Through this upcoming seminar series, we want to embrace the intersections and interactions of computing with all aspects of learning and life, and think about how they can help us teach young people. The researchers we’ve invited as our speakers will help us shed light on cross-disciplinary areas of computing through the breadth of their presentations.
At the Raspberry Pi Foundation our mission is to make computing accessible to all children and young people everywhere, and because computing and technology appear in all aspects of our and young people’s lives, in this series of seminars we will consider what computing education looks like in a multiplicity of environments.
Mark Guzdial on computing 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 research, including the prestigious ACM SIGCSE Outstanding Contribution to Computing Education award in 2019. Mark has written hundreds of papers about computer science education, and he authors an extremely popular computing education research blog that keeps us all up to date with what is going on in the field.
Recently, he has been researching 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 computing. His talk will focus on how we can add a teaspoon of computing 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 computing education in a new way. He has conducted studies in science classrooms and non-formal learning environments which focus on providing open and engaging experiences 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 curriculum design with e-textiles
On 12 July, we will hear from Yasmin Kafai (University of Pennsylvania), who is another legend in computing education in my eyes. Yasmin started her long career in computing education with Seymour Papert, internationally known for his work on Logo and on constructionism as a theoretical lens for understanding the way we learn computing. 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 curriculum 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 research is focused on dance and computing, in particular data-driven dance. Her work helps us to focus on the possibilities of creative computing, 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 computing classroom to raise awareness of data ethics? Impossible to miss!
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. Later on in the series, we will also host a talk by our own researchers and developers at the Raspberry Pi Foundation about our non-formal learning research. Watch this space for details about the October and November seminars, which we are still finalising.
Computer programming is now part of the school curriculum in England and many other countries. Although not necessarily the primary focus of the computing curriculum, programming can be the area teachers find most challenging to teach. There is much evidence emerging from research on how to teach programming, particularly from projects with undergraduate learners. That’s why I recently wrote a report summarising over 170 programming pedagogy papers: Teaching programming in schools: A review of approaches and strategies.
I hope this blog post about how I approached writing the report whets your appetite to read it, and encourages you to read more research summaries in general.
My approach to summarising research papers
Summarising findings from more than 170 research papers into 34 pages was not a task for the faint-hearted. I could not have embarked on this task without previous experience of writing similar, smaller reviews; working on a host of research projects; and writing reports about research for many different audiences.
I love reading about computer science education. It evokes very strong emotions, making me by turns happy, curious, impressed, alarmed, and even cross. When I summarise the papers of other researchers, I am very careful when deciding what to include and what to leave out, in order to do the researchers’ work justice while not overselling it or misleading readers. Sometimes research papers can be hard to fathom, with lots of jargon and statistics. In other papers, the conclusions drawn have many limitations: the project the paper describes hasn’t produced robust enough evidence to give a clear, generalisable message. Academic integrity and not misrepresenting the work of others is paramount. And naturally, there are many more than 170 papers about teaching programming, but I had to stop somewhere. All this makes summarising research a tricky task that one has to undertake with great care.
Another important aspect of summarising research is how to group papers. A long list saying “this paper said this”, “this paper said that” would not be easy to access and would not draw out overall themes. Often research studies span many topics. What might be a helpful grouping for one reader might not be interesting for another.
For this report, I grouped papers into three sections:
Classroom strategies: Here I included well-researched classroom strategies that teachers can use to teach programming in schools
Contexts and environments for learning programming: Here I outlined research related to opportunities for teaching programming, including different programming languages and the classroom context
Supporting learners: Here I summarised research that helps teachers support learners, particularly learners who have difficulties with programming
Why you as a teacher should read research summaries
Teachers, as very busy professionals, have little time to replan lessons, and programming lessons are challenging to start with. However, the potential long-term benefit may outweigh the short-term cost when it comes to reading research summaries: new insights from firmly grounded research can improve your teaching and enable more of your learners to be successful.
The process of translating research into practice is an area that I and the research team here are particularly interested in investigating. We are looking forward to working with teachers to explore this.
The Raspberry Pi Foundation regularly shares research summaries in the form of:
Our seminars in this series on AI and data science education, co-hosted with The Alan Turing Institute, have been covering a range of different topics and perspectives. This month was no exception. We were delighted to be able to host Tara Chklovski, CEO of Technovation, whose presentation was called ‘Teaching youth to use AI to tackle the Sustainable Development Goals’.
Tara Chklovski
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 computing 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 curriculum, 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 computing education.
Click to enlarge
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 curriculum to support teams, who may have no prior computing experience, 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 curriculum supports teams to identify problems in their community and find a path to prototype and share an invention to tackle that problem.
Click to enlarge
While working through the curriculum, 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.
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 curriculum, training, and scalable programme delivery methods. This level of patience and commitment is needed from all community and industry partners and funders.
The research 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 curriculum 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 Foundation. Please do take a look.
You can find all blog posts relating to our previous seminars on this page.
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