Tag Archives: research seminar

The digital divide: interactions between socioeconomic disadvantage and computing education

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/digital-divide-socioeconomic-disadvantage-computing-education/

Digital technology is developing at pace, impacting us all. Most of us use screens and all kinds of computers much more than we did five years ago. The total number of apps downloaded globally each quarter has doubled since 2015, reflecting both increased smartphone penetration and the increasingly prominent role of apps in our lives. However, access to digital technology and the internet is not yet equal: there is still a ‘digital divide’, i.e. some people do not have as much access to digital technologies as others, if any at all.

This month we welcomed Dr Hayley Leonard and Thom Kunkeler at our research seminar series, to present findings on ‘Why the digital divide does not stop at access: understanding the complex interactions between socioeconomic disadvantage and computing education’. Both Hayley and Thom work as researchers at the Raspberry Pi Foundation, where we have a focus on increasing our understanding of computing education for all. They shared some results of a research project they’d carried out with a group of young people who benefitted from our Learn at Home campaign.

Digital inequality: beyond the dichotomy of access

Hayley introduced some of the existing research and thinking around digital inequality, and Thom presented the results of their research project. Setting the scene, Hayley explained that the term ‘digital divide’ can create a dichotomous have/have-not view of the world, as can the concept of a ‘gap’. However, the research presents a more nuanced picture. Rather than describing digital inequality as purely centred on access to technology, some researchers characterise three levels of the digital divide:

  • Level 1: Access
  • Level 2: Skills (digital skills, internet skills) and uses (what you do once you have access)
  • Level 3: Outcomes (what you achieve)

This characterisation is useful because it enables us to look beyond access and also towards what happens once people have access to technology. This is where our Learn At Home campaign came in.

The presenters gave a brief overview of the impact of the campaign, in which the Raspberry Pi Foundation has partnered with 80 youth and community organisations and to date, thanks to generous donors, has given 5100 Raspberry Pi desktop computer kits (including monitors, headphones, etc.) to young people in the UK who didn’t have the resources to buy their own computers.

Hayley Leonard presents an online slide describing the interview responses of recipients of Raspberry Pi desktop computer kits, which revolved around five themes: ease of homework completion; connecting with others; having their own device; new opportunities for learning; improved understanding of schoolwork.
Click on the image to enlarge it. Learn more in the first Learn at Home campaign impact report.

Computing, identity, and self-efficacy

As part of the Learn At Home campaign, Hayley and Thom conducted a pilot study of how young people from underserved communities feel about computing and their own digital skills. They interviewed and analysed responses of fifteen young people, who had received hardware through Learn At Home, about computing as a subject, their confidence with computing, stereotypes, and their future aspirations.

Thom Kunkeler presents an online slide describing the background and research question of the 'Learn at Home campaign' pilot study: underrepresentation, belonging, identity, archetypes, and the question "How do young people from underserved communities feel about computing and their own digital skills?".
Click on the image to enlarge it.

The notion of a ‘computer person’ was used in the interview questions, following work conducted by Billy Wong at the University of Reading, which found that young people experienced a difference between being a ‘computer person’ and ‘doing computing’. The study carried out by Hayley and Thom largely supports this finding. Thom described two major themes that emerged from their analysis: a mismatch between computing and interviewees’ own identities, and low self-indicated self-efficacy.

Showing that stereotypes still persist of what a ‘computer person’ is like, a 13-year-old female interviewee described them as “a bit smart. Very, very logical, because computers are very logical. Things like smart, clever, intelligent because computers are quite hard.” Four of the interviewees were also more likely to associate a ‘computer person’ with being male.

Thom Kunkeler presents an online slide of findings of the 'Learn at Home campaign' pilot study. The young people interviewed associated the term 'computing person' with the attributes smart, clever, intelligent, nerdy/geeky, problem-solving ability.
The young people interviewed associated a ‘computing person’ with the following characteristics: smart, clever, intelligent, nerdy/geeky, problem-solving ability. Click on the image to enlarge it.

The majority of the young people in the study said that they could be this ’computer person’. Even for those who did not see themselves working with computers in the future, being a ’computer person’ was still a possibility: One interviewee said, “I feel like maybe I’m quite good at using a computer. I know my way around. Yes, you never know. I could be, eventually.”

Five of the young people indicated relatively low self-efficacy in computing, and thought there were more barriers to becoming a computer person, for example needing to be better at mathematics. 

In terms of future career goals, only two (White male) participants in the study considered computing as a career, with one (White female) interviewee understanding that choosing computing as a qualification might be important for her future career. This aligns with research into computer science (CS) qualification choice at age 14 in England, explored in a previous seminar, which highlighted the interaction between income, gender, and ethnicity: White girls from lower-income families were more likely to choose a CS qualification than White girls more from more affluent families, while very few Asian, Black, and Chinese girls from low-income backgrounds chose a CS qualification.

Evaluating computing education opportunities using the CAPE framework

An interesting aspect of this seminar was how Hayley and Thom situated their work in the relatively new CAPE framework, which describes different levels at which to evaluate computer science education opportunities. The CAPE framework highlights that capacity and access to computing (C and A in the framework) are only part of the challenge of making computer science education equitable; students’ participation (P) in and experience (E) of computing are key factors in keeping them engaged longer-term.

A diagram illustrating the CAPE framework for assessing computing education opportunities according to four aspects. 1, capacity, which relates to availability of resources. 2, access, which relates to whether learners have the opportunity to engage in the subject. 3, participation, which relates to whether learners choose to engage with the subject. 4, experience, which relates to what the outcome of learners' participation is.
Socioeconomic status (SES) can affect learner engagement with computing education at four levels set out in the CAPE framework.

As we develop computing education in the curriculum, we can use the CAPE framework to evaluate our provision. For example, where I’m writing from in England, we have the capacity to teach computing through the availability of professional development training for teachers, fully developed curriculum materials such as the Teach Computing Curriculum, and community support for teachers through organisations such as Computing at School and the National Centre for Computing Education. In terms of access we have an established national curriculum in the subject, but access to it has been interrupted for many due to the coronavirus pandemic. In terms of participation we know that gender and economic status can impact whether young people choose computer science as an elective subject post-14, and taking an intersectional view reveals that the issue of participation is more complex than that. Finally, according to our seminar speakers, young people’s experience of computing education can be impacted by their digital or technological capital, by their self-efficacy, and by the relevance of the subject to their career aspirations and goals. This analysis really enhances our understanding of digital inequality, as it moves us away from the have/have-not language of the digital divide and starts to unpack the complexity of the impacting factors. 

Although this was not covered in this month’s seminar, I also want to draw out that the CAPE framework also supports our understanding of global computing education: we may need to focus on capacity building in order to create a foundation for the other levels. Lots to think about! 

If you’d like to find out more about this project, you can read the paper that relates to the research and the impact report of the early phases of the Learn At Home initiative. 

If you missed the seminar, you can find the presentation slides on our seminars page and watch the recording of the researchers’ talk:

Join our next seminar

The next seminar will be the final one in the current series focused diversity and inclusion, which we’re co-hosting with the Royal Academy of Engineering. It will take place on Tuesday 13 July at 17:00–18:30 BST / 12:00–13:30 EDT / 9:00–10:30 PDT / 18:00–19:30 CEST, and we’ll welcome Prof Ron Eglash, a prominent researcher in the area of ethnocomputing. The title of Ron’s seminar is Computing for generative justice: decolonizing the circular economy.

To join this free event, click below and sign up with your name and email address:

I want to sign up to attend

We’ll email you the link and instructions. See you there!

This was our 17th research seminar — you can find all the related blog posts here, and download the first volume of our seminar proceedings with contributions from previous guest speakers.

The post The digital divide: interactions between socioeconomic disadvantage and computing education appeared first on Raspberry Pi.

What does equity-focused teaching mean in computer science education?

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/equity-focused-teaching-in-computer-science-education/

Today, I discuss the second research seminar in our series of six free online research seminars focused on diversity and inclusion in computing education, where we host researchers from the UK and USA together with the Royal Academy of Engineering. By diversity, we mean any dimension that can be used to differentiate groups and people from one another. This might be, for example, age, gender, socio-economic status, disability, ethnicity, religion, nationality, or sexuality. The aim of inclusion is to embrace all people irrespective of difference. 

In this seminar, we were delighted to hear from Prof Tia Madkins (University of Texas at Austin), Dr Nicol R. Howard (University of Redlands), and Shomari Jones (Bellevue School District) (find their bios here), who talked to us about culturally responsive pedagogy and equity-focused teaching in K-12 Computer Science.

  • Tia Madkins
    Prof Tia Madkins
  • Nicol Howard
    Dr Nicol R. Howard
  • Shomari Jones
    Shomari Jones

Equity-focused computer science teaching

Tia began the seminar with an audience-engaging task: she asked all participants to share their own definition of equity in the seminar chat. Amongst their many suggestions were “giving everybody the same opportunity”, “equal opportunity to access high-quality education”, and “everyone has access to the same resources”. I found Shomari’s own definition of equity very powerful: 

“Equity is the fair treatment, access, opportunity, and advancement of all people, while at the same time striving to identify and eliminate barriers that have prevented the full participation of some groups. Improving equity involves increasing justice and fairness within the procedures and processes of institutions or systems, as well as the distribution of resources. Tackling equity requires an understanding of the root cause of outcome disparity within our society.”

Shomari Jones

This definition is drawn directly from the young people Shomari works with, and it goes beyond access and opportunity to the notion of increasing justice and fairness and addressing the causes of outcome disparity. Justice was a theme throughout the seminar, with all speakers referring to the way that their work looks at equity in computer science education through a justice-oriented lens.

Removing deficit thinking

Using a justice-oriented approach means that learners should be encouraged to use their computer science knowledge to make a difference in areas that are important to them. It means that just having access to a computer science education is not sufficient for equity.

Tia Madkins presents a slide: "A justice-oriented approach to computer science teaching empowers students to use CS knowledge for transformation, moves beyond access and achievement frames, and is an asset- or strengths-based approach centering students and families"

Tia spoke about the need to reject “deficit thinking” (i.e. focusing on what learners lack) and instead focus on learners’ strengths or assets and how they bring these to the school classroom. For researchers and teachers to do this, we need to be aware of our own mindset and perspective, to think about what we value about ethnic and racial identities, and to be willing to reflect and take feedback.

Activities to support computer science teaching

Nicol talked about some of the ways of designing computing lessons to be equity-focused. She highlighted the benefits of pair programming and other peer pedagogies, where students teach and learn from each other through feedback and sharing ideas/completed work. She suggested using a variety of different programs and environments, to ensure a range of different pathways to understanding. Teachers and schools can aim to base teaching around tools that are open and accessible and, where possible, available in many languages. If the software environment and tasks are accessible, they open the doors of opportunity to enable students to move on to more advanced materials. To demonstrate to learners that computer science is applicable across domains, the topic can also be introduced in the context of mathematics and other subjects.

Nicol Howard presents a slide: "Considerations for equity-focused computer science teaching include your beliefs (and your students' beliefs) and how they impact CS classrooms; tiered activities and pair programming; self-expressions versus CS preparation; equity-focused lens"

Learners can benefit from learning computer science regardless of whether they want to become a computer scientist. Computing offers them skills that they can use for self-expression or to be creative in other areas of their life. They can use their knowledge for a specific purpose and to become more autonomous, particularly if their teacher does not have any deficit thinking. In addition, culturally relevant teaching in the classroom demonstrates a teacher’s deliberate and explicit acknowledgment that they value all students in their classroom and expect students to excel.

Engaging family and community

Shomari talked about the importance of working with parents and families of ethnically diverse students in order to hear their voices and learn from their experiences.

Shomari Jones presents a slide: “Parents without backgrounds and insights into the changing landscape of technology struggle to negotiate what roles they can play, such as how to work together in computing activities or how to find learning opportunities for their children.”

He described how the absence of a background in technology of parents and carers can drastically impact the experiences of young people.

“Parents without backgrounds and insights into the changing landscape of technology struggle to negotiate what roles they can play, such as how to work together in computing activities or how to find learning opportunities for their children.”

Betsy DiSalvo, Cecili Reid, and Parisa Khanipour Roshan. 2014

Shomari drew on an example from the Pacific Northwest in the US, a region with many successful technology companies. In this location, young people from wealthy white and Asian communities can engage fully in informal learning of computer science and can have aspirations to enter technology-related fields, whereas amongst the Black and Latino communities, there are significant barriers to any form of engagement with technology. This already existent inequity has been enhanced by the coronavirus pandemic: once so much of education moved online, it became widely apparent that many families had never owned, or even used, a computer. Shomari highlighted the importance of working with pre-service teachers to support them in understanding the necessity of family and community engagement.

Building classroom communities

Building a classroom community starts by fostering and maintaining relationships with students, families, and their communities. Our speakers emphasised how important it is to understand the lives of learners and their situations. Through this understanding, learning experiences can be designed that connect with the learners’ lived experiences and cultural practices. In addition, by tapping into what matters most to learners, teachers can inspire them to be change agents in their communities. Tia gave the example of learning to code or learning to build an app, which provides learners with practical tools they can use for projects they care about, and with skills to create artefacts that challenge and document injustices they see happening in their communities.

Find out more

If you want to learn more about this topic, a great place to start is the recent paper Tia and Nicol have co-authored that lays out more detail on the work described in the seminar: Engaging Equity Pedagogies in Computer Science Learning Environments, by Tia C. Madkins, Nicol R. Howard and Natalie Freed, 2020.

You can access the presentation slides via our seminars page.

Join our next free seminar

In our next seminar on Tuesday 2 March at 17:00–18:30 BST / 12:00–13:30 EDT / 9:00–10:30 PDT / 18:00–19:30 CEST, we’ll welcome Jakita O. Thomas (Auburn University), who is going to talk to us about Designing STEM Learning Environments to Support Computational Algorithmic Thinking and Black Girls: A Possibility Model for Changing Hegemonic Narratives and Disrupting STEM Neoliberal Projects. To join this free online seminar, simply sign up with your name and email address.

I want to sign up for the next seminar

Once you’ve signed up, we’ll email you the seminar meeting link and instructions for joining. If you attended Peter’s and Billy’s seminar, the link remains the same.

The post What does equity-focused teaching mean in computer science education? appeared first on Raspberry Pi.

Computing education and underrepresentation: the data from England

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/computing-education-underrepresentation-data-england-schools/

In this blog post, I’ll discuss the first research seminar in our six-part series about diversity and inclusion. Let’s start by defining our terms. Diversity is any dimension that can be used to differentiate groups and people from one another. This might be, for example, age, gender, socio-economic status, disability, ethnicity, religion, nationality, or sexuality. The aim of inclusion is to embrace all people irrespective of difference.

It’s vital that we are inclusive in computing education, because we need to ensure that everyone can access and learn the empowering and enabling technical skills they need to support all aspects of their lives.

One male and two female teenagers at a computer

Between January and June of this year, we’re partnering with the Royal Academy of Engineering to host speakers from the UK and USA for a series of six research seminars focused on diversity and inclusion in computing education.

We kicked off the series with a seminar from Dr Peter Kemp and Dr Billy Wong focused on computing education in England’s schools post-14. Peter is a Lecturer in Computing Education at King’s College London, where he leads on initial teacher education in computing. His research areas are digital creativity and digital equity. Billy is an Associate Professor at the Institute of Education, University of Reading. His areas of research are educational identities and inequalities, especially in the context of higher education and STEM education.

  • Peter Kemp
    Dr Peter Kemp
  • Dr Billy Wong

Computing in England’s schools

Peter began the seminar with a comprehensive look at the history of curriculum change in Computing in England. This was very useful given our very international audience for these seminars, and I will summarise it below. (If you’d like more detail, you can look over the slides from the seminar. Note that these changes refer to England only, as education in the UK is devolved, and England, Northern Ireland, Scotland, and Wales each has a different education system.)

In 2014, England switched from mandatory ICT (Information and Communication Technology) to mandatory Computing (encompassing information technology, computer science, and digital literacy). This shift was complemented by a change in the qualifications for students aged 14–16 and 16–18, where the primary qualifications are GCSEs and A levels respectively:

  • At GCSE, there has been a transition from GCSE ICT to GCSE Computer Science over the last five years, with GCSE ICT being discontinued in 2017
  • At A level before 2014, ICT and Computing were on offer as two separate A levels; now there is only one, A level Computer Science

One of the issues is that in the English education system, there is a narrowing of the curriculum at age 14: students have to choose between Computer Science and other subjects such as Geography, History, Religious Studies, Drama, Music, etc. This means that those students that choose not to take a GCSE Computer Science (CS) may find that their digital education is thereby curtailed from then onwards. Peter’s and Billy’s view is that having a more specialist subject offer for age 14+ (Computer Science as opposed to ICT) means that fewer students take it, and they showed evidence of this from qualifications data. The number of students taking CS at GCSE has risen considerably since its introduction, but it’s not yet at the level of GCSE ICT uptake.

GCSE computer science and equity

Only 64% of schools in England offer GCSE Computer Science, meaning that just 81% of students have the opportunity to take the subject (some schools also add selection criteria). A higher percentage (90%) of selective grammar schools offer GCSE CS than do comprehensive schools (80%) or independent schools (39%). Peter suggested that this was making Computer Science a “little more elitist” as a subject.

Peter analysed data from England’s National Pupil Database (NPD) to thoroughly investigate the uptake of Computer Science post-14 with respect to the diversity of entrants.

He found that the gender gap for GCSE CS uptake is greater than it was for GCSE ICT. Now girls make up 22% of the cohort for GCSE CS (2020 data), whereas for the ICT qualification (2017 data), 43% of students were female.

Peter’s analysis showed that there is also a lower representation of black students and of students from socio-economically disadvantaged backgrounds in the cohort for GCSE CS. In contrast, students with Chinese ancestry are proportionally more highly represented in the cohort. 

Another part of Peter’s analysis related gender data to the Income Deprivation Affecting Children Index (IDACI), which is used as an indicator of the level of poverty in England’s local authority districts. In the graphs below, a higher IDACI decile means more deprivation in an area. Relating gender data of GCSE CS uptake against the IDACI shows that:

  • Girls from more deprived areas are more likely to take up GCSE CS than girls from less deprived areas are
  • The opposite is true for boys
Two bar charts relating gender data of GCSE uptake against the Income Deprivation Affecting Children Index. The graph plotting GCSE ICT data shows that students from areas with higher deprivation are slightly more likely to choose the GCSE, irrespective of gender. The graph plotting GCSE Computer Science data shows that girls from more deprived areas are more likely to take up GCSE CS than girls from less deprived areas, and the opposite is true for boys.

Peter covered much more data in the seminar, so do watch the video recording (below) if you want to learn more.

Peter’s analysis shows a lack of equity (i.e. equality of outcome in the form of proportional representation) in uptake of GCSE CS after age 14. It is also important to recognise, however, that England does mandate — not simply provide or offer — Computing for all pupils at both primary and secondary levels; making a subject mandatory is the only way to ensure that we do give access to all pupils.

What can we do about the lack of equity?

Billy presented some of the potential reasons for why some groups of young people are not fully represented in GCSE Computer Science:

  • There are many stereotypes surrounding the image of ‘the computer scientist’, and young people may not be able to identify with the perception they hold of ‘the computer scientist’
  • There is inequality in access to resources, as indicated by the research on science and STEM capital being carried out within the ASPIRES project

More research is needed to understand the subject choices young people make and their reasons for choosing as they do.

We also need to look at how the way we teach Computing to students aged 11 to 14 (and younger) affects whether they choose CS as a post-14 subject. Our next seminar revolves around equity-focused teaching practices, such as culturally relevant pedagogy or culturally responsive teaching, and how educators can use them in their CS learning environments. 

Meanwhile, our own research project at the Raspberry Pi Foundation, Gender Balance in Computing, investigates particular approaches in school and non-formal learning and how they can impact on gender balance in Computer Science. For an overview of recent research around barriers to gender balance in school computing, look back on the research seminar by Katharine Childs from our team.

Peter and Billy themselves have recently been successful in obtaining funding for a research project to explore female computing performance and subject choice in English schools, a project they will be starting soon!

If you missed the seminar, watch recording here. You can also find Peter and Billy’s presentation slides on our seminars page.

Next up in our seminar series

In our next research seminar on Tuesday 2 February at 17:00–18:30 BST / 12:00–13:30 EDT / 9:00–10:30 PDT / 18:00–19:30 CEST, we’ll welcome Prof Tia Madkins (University of Texas at Austin), Dr Nicol R. Howard (University of Redlands), and Shomari Jones (Bellevue School District), who are going to talk to us about culturally responsive pedagogy and equity-focused teaching in K-12 Computer Science. To join this free online seminar, simply sign up with your name and email address.

I want to sign up for the next seminar

Once you’ve signed up, we’ll email you the seminar meeting link and instructions for joining. If you attended Peter’s and Billy’s seminar, the link remains the same.

The post Computing education and underrepresentation: the data from England appeared first on Raspberry Pi.

Block-based programming: does it help students learn?

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/block-based-programming-does-it-help-students-learn-research-seminar/

At the Raspberry Pi Foundation, we are continually inspired by young learners in our community: they embrace digital making and computing to build creative projects, supported by our resources, clubs, and volunteers. While creating their projects, they are learning the core programming skills that underlie digital making.

Over the years, many tools and environments have been developed to make programming more accessible to young people. Scratch is one example of a block-based programming environment for young learners, and it’s been shown to make programming more accessible to them; on our projects site we offer many step-by-step Scratch project resources.

Mark Scratch
A Scratch code-along, led by one of our educators on our weekly Digital Making at Home live stream

But does block-based programming actually help learning? Does it increase motivation and support students? Where is the hard evidence? In our latest research seminar, we were delighted to hear from Dr David Weintrop, an Assistant Professor at the University of Maryland who has done research in this area for several years and published widely on the differences between block-based and text-based programming environments.

David Weintrop

A variety of block-based programming environments

The first useful insight David shared was that we should avoid thinking about block-based programming as synonymous with the well-known Scratch environment. There are several other environments, with different affordances, that David referred to in his talk, such as Snap, Pencil Code, Blockly, and more.

Logos of block-based programming environments

Some of these, for example Pencil Code, offer a dual-modality (or hybrid) environment, where learners can write the same program in a text-based and a block-based programming environment side by side. Dual-modality environments provide this side-by-side approach based on the assumption that being able to match a text-based program to its block-based equivalent supports the development of understanding of program syntax in a text-based language.

Screenshot of the Pencil Code dual-modality programming environment

As a tool for transitioning to text-based programming

Another aspect of the research around block-based programming focuses on its usefulness as a transition to a text-based language. David described a 15-week study he conducted in high schools in the USA to investigate differences in student learning caused by use of block-based, text-based, and hybrid (a mixture of both using a dual-modality platform) programming tools.

Details of the study design: classroom-based, 3 conditions, 2 phases, quasi-experimental mixed method study

The 90 students in the study (14 to 16 years old) were divided into three groups, each with a different intervention but taught by the same teacher. In the first phase of the study (5 weeks), the groups were set the same tasks with the same learning objectives, but they used either block-based programming, text-based programming, or the hybrid environment.

After 5 weeks, students were given a test to assess learning outcomes, and they were asked questions about their attitudes to programming (specifically their perception of computing and their confidence). In the second phase (10 weeks), all the students were taught Java (a common language taught in the USA for end-of-school assessment), and then the test and attitudinal questions were repeated.

The results showed that at the 5-week point, the students who had used block-based programming scored higher in their learning outcome assessment, but at the final assessment after 15 weeks, all groups’ scores were roughly equivalent.  

A graph of assessment scores of the three groups in the study. The final scores are not significantly different.

In terms of students’ perception of computing and confidence, the responses of the Blocks group were very positive at the 5-week point, while at the 15-week point, the responses were less positive. The responses from the Text group showed a gradual increase in positivity between the 5- and 15-week points. The Hybrid group’s responses weren’t as negative as those of the Text group at the 5-week point, and their positivity didn’t decrease like the Blocks group’s did.

Taking both methods of assessment into account, the Hybrid group showed the best results in the study. The gains associated with the block-based introduction to programming did not translate to those students being further ahead when learning Java, but starting with block-based programming also did not hamper students’ transition to text-based programming.

David completed his talk by recommending dual-modality environments (such as Pencil Code) for teaching programming, as used by the Hybrid group in his study. 

More research is needed

The seminar audience raised many questions about David’s study, for example whether the actual teaching (pedagogy) may have differed for the three groups, and whether the results are not just due to the specific tools or environments that were used. This is definitely an area for further research. 

It seems that students may benefit from different tools at different times, which is why a dual-modality environment can be very useful. Of course, competence in programming takes a long time to develop, so there is room on the research agenda for longitudinal studies that monitor students’ progress over many months and even years. Such studies could take into account both the teaching approach and the programming environment in order to determine what factors impact a deep understanding of programming concepts, and students’ desire to carry on with their programming journey. 

Next up in our series

If you missed the seminar, you can find David’s presentation slides and a recording of his talk on our seminars page.

Our next free online seminar takes place on Tuesday 5 January at 17:00–18:00 BST / 12:00–13:00 EDT / 9:00–10:00 PDT / 18:00–19:00 CEST. We’ll welcome Peter Kemp and Billy Wong, who are going to share insights from their research on computing education for underrepresented groups. To join this free online seminar, simply sign up with your name and email address.

I want to sign up for the next seminar

Once you’ve signed up, we’ll email you the seminar meeting link and instructions for joining. If you attended David’s seminar, the link remains the same.

The January seminar will be the first one in our series focusing on diversity and inclusion in computing education, which we’re co-hosting with the Royal Academy for Engineering. We hope to see you there!

The post Block-based programming: does it help students learn? appeared first on Raspberry Pi.

Diversity and inclusion in computing education — new research seminars

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/diversity-inclusion-computing-education-research-seminars/

At the Raspberry Pi Foundation, we host a free online research seminar once a month to explore a wide variety of topics in the area of digital and computing education. This year, we’ve hosted eleven seminars — you can (re)discover slides and recordings on our website.

A classroom of young learners and a teacher at laptops

Now we’re getting ready for new seminars in 2021! In the coming months, our seminars are going to focus on diversity and inclusion in computing education. This topic is extremely important, as we want to make sure that computing is accessible to all, that we understand how to actively remove barriers to participation for learners, and that we understand how to teach computing in an inclusive way. 

We are delighted to announce that these seminars focusing on diversity and inclusion will be co-hosted by the Royal Academy of Engineering. The Royal Academy of Engineering is harnessing the power of engineering to build a sustainable society and an inclusive economy that works for everyone.

Royal Academy of Engineering logo

We’re very excited to be partnering with the Academy because of our shared interest in ensuring that computing and engineering are inclusive and accessible to all.

Our upcoming seminars

The seminars take place on the first Tuesday of the month at 17:00–18:30 GMT / 12:00–13:30 EST / 9:00–10:30 PST / 18:00–19:30 CET.

  • 5 January 2021: Peter Kemp (King’s College London) and Billy Wong (University of Reading) will be looking at computing education in England, particularly GCSE computer science, and how it is accessed by groups typically underrepresented in computing.
  • 2 February 2021: Professor Tia Madkins (University of Texas at Austin), Nicol R. Howard (University of Redlands), and Shomari Jones (Bellevue School District) will be talking about equity-focused teaching in K–12 computer science. Find out more.
  • 2 March 2021: Dr Jakita O. Thomas (Auburn University, Alabama) will be talking about her research on supporting computational algorithmic thinking in the context of intersectional computing.
  • April 2021: event to be confirmed
  • 4 May 2021: Dr Cecily Morrison (Microsoft Research) will be speaking about her work on physical programming for people with visual impairments.

Join the seminars

We’d love to welcome you to these seminars so we can learn and discuss together. To get access, simply sign up with your name and email address.

I want to sign up for the seminar series

Once you’ve signed up, we’ll email you the seminar meeting link and instructions for joining. If you attended our seminars in the past, the link remains the same.

The post Diversity and inclusion in computing education — new research seminars appeared first on Raspberry Pi.

PRIMM: encouraging talk in programming lessons

Post Syndicated from Oliver Quinlan original https://www.raspberrypi.org/blog/primm-talk-in-programming-lessons-research-seminar/

Whenever you learn a new subject or skill, at some point you need to pick up the particular language that goes with that domain. And the only way to really feel comfortable with this language is to practice using it. It’s exactly the same when learning programming.

A girl doing Scratch coding in a Code Club classroom

In our latest research seminar, we focused on how we educators and our students can talk about programming. The seminar presentation was given by our Chief Learning Officer, Dr Sue Sentance. She shared the work she and her collaborators have done to develop a research-based approach to teaching programming called PRIMM, and to work with teachers to investigate the effects of PRIMM on students.

Sue Sentance

As well as providing a structure for programming lessons, Sue’s research on PRIMM helps us think about ways in which learners can investigate programs, start to understand how they work, and then gradually develop the language to talk about them themselves.

Productive talk for education

Sue began by taking us through the rich history of educational research into language and dialogue. This work has been heavily developed in science and mathematics education, as well as language and literacy.

In particular the work of Neil Mercer and colleagues has shown that students need guidance to develop and practice using language to reason, and that developing high-quality language improves understanding. The role of the teacher in this language development is vital.

Sue’s work draws on these insights to consider how language can be used to develop understanding in programming.

Why is programming challenging for beginners?

Sue identified shortcomings of some teaching approaches that are common in the computing classroom but may not be suitable for all beginners.

  • ‘Copy code’ activities for learners take a long time, lead to dreaded syntax errors, and don’t necessarily build more understanding.
  • When teachers model the process of writing a program, this can be very helpful, but for beginners there may still be a huge jump from being able to follow the modeling to being able to write a program from scratch themselves.

PRIMM was designed by Sue and her collaborators as a language-first approach where students begin not by writing code, but by reading it.

What is PRIMM?

PRIMM stands for ‘Predict, Run, Investigate, Modify, Make’. In this approach, rather than copying code or writing programs from scratch, beginners instead start by focussing on reading working code.

In the Predict stage, the teacher provides learners with example code to read, discuss, and make output predictions about. Next, they run the code to see how the output compares to what they predicted. In the Investigate stage, the teacher sets activities for the learners to trace, annotate, explain, and talk about the code line by line, in order to help them understand what it does in detail.

In the seminar, Sue took us through a mini example of the stages of PRIMM where we predicted the output of Python Turtle code. You can follow along on the recording of the seminar to get the experience of what it feels like to work through this approach.

The impact of PRIMM on learning

The PRIMM approach is informed by research, and it is also the subject of research by Sue and her collaborators. They’ve conducted two studies to measure the effectiveness of PRIMM: an initial pilot, and a larger mixed-methods study with 13 teachers and 493 students with a control group.

The larger study used a pre and post test, and found that the group who experienced a PRIMM approach performed better on the tests than the control group. The researchers also collected a wealth of qualitative feedback from teachers. The feedback suggested that the approach can help students to develop a language to express their understanding of programming, and that there was much more productive peer conversation in the PRIMM lessons (sometimes this meant less talk, but at a more advanced level).

The PRIMM structure also gave some teachers a greater capacity to talk about the process of teaching programming. It facilitated the discussion of teaching ideas and learning approaches for the teachers, as well as developing language approaches that students used to learn programming concepts.

The research results suggest that learners taught using PRIMM appear to be developing the language skills to talk coherently about their programming. The effectiveness of PRIMM is also evidenced by the number of teachers who have taken up the approach, building in their own activities and in some cases remixing the PRIMM terminology to develop their own take on a language-first approach to teaching programming.

Future research will investigate in detail how PRIMM encourages productive talk in the classroom, and will link the approach to other work on semantic waves. (For more on semantic waves in computing education, see this seminar by Jane Waite and this symposium talk by Paul Curzon.)

Resources for educators who want to try PRIMM

If you would like to try out PRIMM with your learners, use our free support materials:

Join our next seminar

If you missed the seminar, you can find the presentation slides alongside the recording of Sue’s talk on our seminars page.

In our next seminar on Tuesday 1 December at 17:00–18:30 GMT / 12:00–13:30 EsT / 9:00–10:30 PT / 18:00–19:30 CEST. Dr David Weintrop from the University of Maryland will be presenting on the role of block-based programming in computer science education. To join, simply sign up with your name and email address.

I want to sign up to the next seminar

Once you’ve signed up, we’ll email you the seminar meeting link and instructions for joining. If you attended this past seminar, the link remains the same.

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Formative assessment in the computer science classroom

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/research-seminar-formative-assessment-computer-science-classroom/

In computing education research, considerable focus has been put on the design of teaching materials and learning resources, and investigating how young people learn computing concepts. But there has been less focus on assessment, particularly assessment for learning, which is called formative assessment. As classroom teachers are engaged in assessment activities all the time, it’s pretty strange that researchers in the area of computing and computer science in school have not put a lot of focus on this.

Shuchi Grover

That’s why in our most recent seminar, we were delighted to hear about formative assessment — assessment for learning — from Dr Shuchi Grover, of Looking Glass Ventures and Stanford University in the USA. Shuchi has a long track record of work in the learning sciences (called education research in the UK), and her contribution in the area of computational thinking has been hugely influential and widely drawn on in subsequent research.

Two types of assessment

Assessment is typically divided into two types:

  1. Summative assessment (i.e. assessing what has been learned), which typically takes place through examinations, final coursework, projects, etcetera.
  2. Formative assessment (i.e. assessment for learning), which is not aimed at giving grades and typically takes place through questioning, observation, plenary classroom activities, and dialogue with students.

Through formative assessment, teachers seek to find out where students are at, in order to use that information both to direct their preparation for the next teaching activities and to give students useful feedback to help them progress. Formative assessment can be used to surface misconceptions (or alternate conceptions) and for diagnosis of student difficulties.

Venn diagram of how formative assessment practices intersect with teacher knowledge and skills
Click to enlarge

As Shuchi outlined in her talk, a variety of activities can be used for formative assessment, for example:

  • Self- and peer-assessment activities (commonly used in schools).
  • Different forms of questioning and quizzes to support learning (not graded tests).
  • Rubrics and self-explanations (for assessing projects).

A framework for formative assessment

Shuchi described her own research in this topic, including a framework she has developed for formative assessment. This comprises three pillars:

  1. Assessment design.
  2. Teacher or classroom practice.
  3. The role of the community in furthering assessment practice.
Shuchi Grover's framework for formative assessment
Click to enlarge

Shuchi’s presentation then focused on part of the first pillar in the framework: types of assessments, and particularly types of multiple-choice questions that can be automatically marked or graded using software tools. Tools obviously don’t replace teachers, but they can be really useful for providing timely and short-turnaround feedback for students.

As part of formative assessment, carefully chosen questions can also be used to reveal students’ misconceptions about the subject matter — these are called diagnostic questions. Shuchi discussed how in a classroom setting, teachers can employ this kind of question to help them decide what to focus on in future lessons, and to understand their students’ alternate or different conceptions of a topic. 

Formative assessment of programming skills

The remainder of the seminar focused on the formative assessment of programming skills. There are many ways of assessing developing programming skills (see Shuchi’s slides), including Parsons problems, microworlds, hotspot items, rubrics (for artifacts), and multiple-choice questions. As an MCQ example, in the figure below you can see some snippets of block-based code, which students need to read and work out what the outcome of running the snippets will be. 

Click to enlarge

Questions such as this highlight that it’s important for learners to engage in code comprehension and code reading activities when learning to program. This really underlines the fact that such assessment exercises can be used to support learning just as much as to monitor progress.

Formative assessment: our support for teachers

Interestingly, Shuchi commented that in her experience, teachers in the UK are more used to using code reading activities than US teachers. This may be because code comprehension activities are embedded into the curriculum materials and support for pedagogy, both of which the Raspberry Pi Foundation developed as part of the National Centre for Computing Education in England. We explicitly share approaches to teaching programming that incorporate code reading, for example the PRIMM approach. Moreover, our work in the Raspberry Pi Foundation includes the Isaac Computer Science online learning platform for A level computer science students and teachers, which is centered around different types of questions designed as tools for learning.

All these materials are freely available to teachers wherever they are based.

Further work on formative assessment

Based on her work in US classrooms researching this topic, Shuchi’s call to action for teachers was to pay attention to formative assessment in computer science classrooms and to investigate what useful tools can support them to give feedback to students about their learning. 

Advice from Shuchi Grover on how to embed formative assessment in classroom practice
Click to enlarge

Shuchi is currently involved in an NSF-funded research project called CS Assess to further develop formative assessment in computer science via a community of educators. For further reading, there are two chapters related to formative assessment in computer science classrooms in the recently published book Computer Science in K-12 edited by Shuchi.

There was much to take away from this seminar, and we are really grateful to Shuchi for her input and look forward to hearing more about her developing project.

Join our next seminar

If you missed the seminar, you can find the presentation slides and a recording of the Shuchi’s talk on our seminars page.

In our next seminar on Tuesday 3 November at 17:00–18:30 BST / 12:00–13:30 EDT / 9:00–10:30 PT / 18:00–19:30 CEST, I will be presenting my work on PRIMM, particularly focusing on language and talk in programming lessons. To join, simply sign up with your name and email address.

I want to sign up to the next seminar

Once you’ve signed up, we’ll email you the seminar meeting link and instructions for joining. If you attended this past seminar, the link remains the same.

The post Formative assessment in the computer science classroom appeared first on Raspberry Pi.

How is computing taught in schools around the world?

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/international-computing-curriculum-metrecc-research-seminar/

Around the world, formal education systems are bringing computing knowledge to learners. But what exactly is set down in different countries’ computing curricula, and what are classroom educators teaching? This was the topic of the first in the autumn series of our Raspberry Pi research seminars on Tuesday 8 September.

A glowing globe floating above an open hand in the dark

We heard from an international team (Monica McGill , USA; Rebecca Vivian, Australia; Elizabeth Cole, Scotland) who represented a group of researchers also based in England, Malta, Ireland, and Italy. As a researcher working at the Raspberry Pi Foundation, I myself was part of this research group. The group developed METRECC, a comprehensive and validated survey tool that can be used to benchmark and measure developments of the teaching and learning of computing in formal education systems around the world. Monica, Rebecca, and Elizabeth presented how the research group developed and validated the METRECC tool, and shared some findings from their pilot study.

What’s in a curriculum? Developing a survey tool

Those of us who work or have worked in school education use the word ‘curriculum’ frequently, although it’s an example of education terminology that means different things in different contexts, and to different people. Following Porter and Smithson (2001)1, we can distinguish between the intended curriculum and the enacted curriculum:

  • Intended curriculum: Policy tools as curriculum standards, frameworks, or guidelines that outline the curriculum teachers are expected to deliver.
  • Enacted curriculum: Actual curricular content in which students engage in the classroom, and adopted pedagogical approaches; for computer science (CS) curricula, this also includes students’ use of technology, physical computing devices, and tools in CS lessons.

To compare the intended and enacted computing curriculum in as many countries as possible, at particular points in time, the research group Monica, Rebecca, Elizabeth, and I were part of developed the METRECC survey tool.

A classroom of students in North America

METRECC stands for MEasuring TeacheREnacted Computing Curriculum. The METRECC survey has 11 categories of questions and is designed to be completed by computing teachers within 35–40 minutes. Following best practice in research, which calls for standardised research instruments, the research group ensured that the survey produces valid, reliable results (meaning that it works as intended) before using it to gather data.

Using METRECC in a pilot study

In their pilot study, the research group gathered data from 7 countries. The intended curriculum for each country was determined by examining standards and policies in place for each country/state under consideration. Teachers’ answers in the METRECC survey provided the countries’ enacted curricula. (The complete dataset from the pilot study is publicly available at csedresearch.org, a very useful site for CS education researchers where many surveys are shared.)

Two girls coding at a computer under supervision of a female teacher

The researchers then mapped the intended to the enacted curricula to find out whether teachers were actually teaching the topics that were prescribed for them. Overall, the results of the mapping showed that there was a good match between intended and enacted curricula. Examples of mismatches include lower numbers of primary school teachers reporting that they taught visual or symbolic programming, even though the topic did appear on their curriculum.

A table listing computer science topics
This table shows computer science topic the METRECC tool asks teachers about, and what percentage of respondents in the pilot study stated that they teach these to their students.

Another aspect of the METRECC survey allows to measure teachers’ confidence, self-efficacy, and self-esteem. The results of the pilot study showed a relationship between years of experience and CS self-esteem; in particular, after four years of teaching, teachers started to report high self-esteem in relation to computer science. Moreover, primary teachers reported significantly lower self-esteem than secondary teachers did, and female teachers reported lower self-esteem than male teachers did.

Adapting the survey’s language

The METRECC survey has also been used in South Asia, namely Bangladesh, Nepal, Pakistan, and Sri Lanka (where computing is taught under ICT). Amongst other things, what the researchers learned from that study was that some of the survey questions needed to be adapted to be relevant to these countries. For example, while in the UK we use the word ‘gifted’ to mean ‘high-attaining’, in the South Asian countries involved in the study, to be ‘gifted’ means having special needs.

Two girls coding at a computer under supervision of a female teacher

The study highlighted how important it is to ensure that surveys intended for an international audience use terminology and references that are pertinent to many countries, or that the survey language is adapted in order to make sense in each context it is delivered. 

Let’s keep this monitoring of computing education moving forward!

The seminar presentation was well received, and because we now hold our seminars for 90 minutes instead of an hour, we had more time for questions and answers.

My three main take-aways from the seminar were:

1. International collaboration is key

It is very valuable to be able to form international working groups of researchers collaborating on a common project; we have so much to learn from each other. Our Raspberry Pi research seminars attract educators and researchers from many different parts of the world, and we can truly push the field’s understanding forward when we listen to experiences and lessons of people from diverse contexts and cultures.

2. Making research data publicly available

Increasingly, it is expected that research datasets are made available in publicly accessible repositories. While this is becoming the norm in healthcare and scientific, it’s not yet as prevalent in computing education research. It was great to be able to publicly share the dataset from the METRECC pilot study, and we encourage other researchers in this field to do the same. 

3. Extending the global scope of this research

Finally, this work is only just beginning. Over the last decade, there has been an increasing move towards teaching aspects of computer science in school in many countries around the world, and being able to measure change and progress is important. Only a handful of countries were involved in the pilot study, and it would be great to see this research extend to more countries, with larger numbers of teachers involved, so that we can really understand the global picture of formal computing education. Budding research students, take heed!

Next up in our seminar series

If you missed the seminar, you can find the presentation slides and a recording of the researchers’ talk on our seminars page.

In our next seminar on Tuesday 6 October at 17:00–18:30 BST / 12:00–13:30 EDT / 9:00–10:30 PT / 18:00–19:30 CEST, we’ll welcome Shuchi Grover, a prominent researcher in the area of computational thinking and formative assessment. The title of Shuchi’s seminar is Assessments to improve student learning in introductory CS classrooms. To join, simply sign up with your name and email address.

I want to sign up to the next seminar

Once you’ve signed up, we’ll email you the seminar meeting link and instructions for joining. If you attended this past seminar, the link remains the same.

1. Andrew C. Porter and John L. Smithson. 2001. Defining, Developing and Using Curriculum Indicators. CPRE Research Reports, 12-2001. (2001)

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