Tag Archives: research

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.

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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Embedding computational thinking skills in our learning resources

Post Syndicated from Oliver Quinlan original https://www.raspberrypi.org/blog/computational-thinking-skills-in-our-free-learning-resources/

Learning computing is fun, creative, and exploratory. It also involves understanding some powerful ideas about how computers work and gaining key skills for solving problems using computers. These ideas and skills are collected under the umbrella term ‘computational thinking’.

When we create our online learning projects for young people, we think as much about how to get across these powerful computational thinking concepts as we do about making the projects fun and engaging. To help us do this, we have put together a computational thinking framework, which you can read right now.

What is computational thinking? A brief summary

Computational thinking is a set of ideas and skills that people can use to design systems that can be run on a computer. In our view, computational thinking comprises:

  • Decomposition
  • Algorithms
  • Patterns and generalisations
  • Abstraction
  • Evaluation
  • Data

All of these aspects are underpinned by logical thinking, the foundation of computational thinking.

What does computational thinking look like in practice?

In principle, the processes a computer performs can also be carried out by people. (To demonstrate this, computing educators have created a lot of ‘unplugged’ activities in which learners enact processes like computers do.) However, when we implement processes so that they can be run on a computer, we benefit from the huge processing power that computers can marshall to do certain types of activities.

A group of young people and educators smiling while engaging with a computer

Computers need instructions that are designed in very particular ways. Computational thinking includes the set of skills we use to design instructions computers can carry out. This skill set represents the ways we can logically approach problem solving; as computers can only solve problems using logical processes, to write programs that run on a computer, we need to use logical thinking approaches. For example, writing a computer program often requires the task the program revolves around to be broken down into smaller tasks that a computer can work through sequentially or in parallel. This approach, called decomposition, can also help people to think more clearly about computing problems: breaking down a problem into its constituent parts helps us understand the problem better.

Male teacher and male students at a computer

Understanding computational thinking supports people to take advantage of the way computers work to solve problems. Computers can run processes repeatedly and at amazing speeds. They can perform repetitive tasks that take a long time, or they can monitor states until conditions are met before performing a task. While computers sometimes appear to make decisions, they can only select from a range of pre-defined options. Designing systems that involve repetition and selection is another way of using computational thinking in practice.

Our computational thinking framework

Our team has been thinking about our approach to computational thinking for some time, and we have just published the framework we have developed to help us with this. It sets out the key areas of computational thinking, and then breaks these down into themes and learning objectives, which we build into our online projects and learning resources.

To develop this computational thinking framework, we worked with a group of academics and educators to make sure it is robust and useful for teaching and learning. The framework was also influenced by work from organisations such as Computing At School (CAS) in the UK, and the Computer Science Teachers’ Association (CSTA) in the USA.

We’ve been using the computational thinking framework to help us make sure we are building opportunities to learn about computational thinking into our learning resources. This framework is a first iteration, which we will review and revise based on experience and feedback.

We’re always keen to hear feedback from you in the community about how we shape our learning resources, so do let us know what you think about them and the framework in the comments.

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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.

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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Gender balance in computing: current research

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/gender-balance-in-computing-current-research/

We’ve really enjoyed starting a series of seminars on computing education research over the summer, as part of our strategy to develop research at the Raspberry Pi Foundation. We want to deepen our understanding of how young people learn about computing and digital making, in order to increase the impact of our own work and to advance the field of computing education.

Part of deepening our understanding is to hear from and work with experts from around the world. The seminar series, and our online research symposium, are an opportunity to do that. In addition, these events support the global computing education research community by providing relevant content and a forum for discussion. You can see the talks recordings and slides of all our previous seminar speakers and symposium speakers on our website.

Gender balance in your computing classroom: what the research says

Our seventh seminar presentation was given by Katharine Childs from our own team. She works on our DfE-funded Gender Balance in Computing programme and gave a brilliant summary of some of the recent research around barriers to gender balance in school computing.

Screenshot of a presentation about gender balance in computing. Text says: "Key questions: What are the barriers which prevent girls' participation in computing? Which interventions can support girls to choose computing qualifications and careers?"

In her presentation, Katharine considered belongingness, role models, relevance to real-world contexts, and non-formal learning. She drew out the links between theory and practice and suggested a range of interventions. I recommend watching the video of her presentation and looking through her slides. 

Katharine has also been publishing a number of excellent blog posts summarising her research on gender balance:

You can read more about our Gender Balance in Computing project and sign up to receive regular newsletters about it.

Join our autumn seminar series

From September, our computing education research seminars will take place on the first Tuesday of each month, starting at 17:00 UK time.

We’re excited about the range of topics to be presented, and about our fantastic lineup of speakers: an international group from Australia, the US, Ireland, and Scotland will present on a survey of computing education curricular and teaching around the world; Shuchi Grover will talk to us about formative assessment; and David Weintrop will share his work on block-based programming. I’ll be talking about my research on PRIMM and the benefits of language and talk in the programming classroom. And we’re lining up more speakers after that.

Find out more and sign up today at rpf.io/research-seminars!

Thank you

We’d like to thank everyone who has participated in our seminar series, whether as speaker or attendee. We’ve welcomed attendees from 22 countries and speakers from the US, UK, and Spain. You’ve all really helped us to start this important work, and we look forward to working with you in the next academic year!

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Testing young children’s computational thinking

Post Syndicated from Oliver Quinlan original https://www.raspberrypi.org/blog/research-seminar-computational-thinking-test/

Computational thinking (CT) comprises a set of skills that are fundamental to computing and being taught in more and more schools across the world. There has been much debate about the details of what CT is and how it should be approached in education, particularly for younger students. 

A girl doing digital making on a tablet

In our research seminar this week, we were joined by María Zapata Cáceres from the Universidad Rey Juan Carlos in Madrid. María shared research she and her colleagues have done around CT. Specifically, she presented work on how we can understand what CT skills young children are developing. Building on existing work on assessing CT, she and her colleagues have developed a reliable test for CT skills that can be used with children as young as 5.

María Zapata Cáceres

Why do we need to test computational thinking?

Until we can assess something, María argues, we don’t know what children have or haven’t learned or what they are capable of. While testing is often associated with the final stages in learning, in order to teach something well, educators need to understand where their students’ skills are to know what they are aiming for them to learn. With CT being taught in increasing numbers of schools and in many different ways, María argues that it is imperative to be able to test learners on it.

Screenshot from an online research seminar about computational thinking with María Zapata Cáceres

How was the test developed?

One of the key challenges for assessing learning is knowing whether the activities or questions you present to learners are actually testing what you intend them to. To make sure this is the case, assessments go through a process of validation: they are tried out with large groups to ensure that the results they give are valid. María’s and her colleagues’ CT test for beginners is based on a CT test developed by researcher Marcos Román González. That test had been validated, but since it is aimed at 10- to 16-year-olds, María and her colleagues needed to adapt it for younger children and then validate the adapted rest.

Developing the first version

The new test for beginners consists of 25 questions, each of which has four possible responses, which are to be answered within 40 minutes. The questions are of two types: one that involves using instructions to draw on a canvas, and one that involves moving characters through mazes. Since the test is for younger children, María and her colleagues designed it so it involves as little text as possible to reduce the need for reading; instead the test includes self-explanatory symbols.

Screenshot from an online research seminar about computational thinking with María Zapata Cáceres

Developing a second version based on feedback

To refine the test, the researchers consulted with a group of 45 experts about the difficulty of the questions and the test’s length of the test. The general feedback was very positive.

Drawing on the experts’ feedback, María and her colleagues made some very specific improvements to the test to make it more appropriate for younger children:

  • The improve test mandates that an verbal explanation be given to children at the start, to make sure they clearly understand how to take the test and don’t have to rely on reading the instructions.
  • In some areas, the researchers added written explanations where experts had identified that questions contained ambiguity that could cause the children to misinterpret them.
  • A key improvement was to adapt the grids in the original test to include pathways between each box of the maze. It was found that children could misinterpret the maze, for example as allowing diagonal moves between squares; the added pathways are visual cues that it clear that this is not possible.
Screenshot from an online research seminar about computational thinking with María Zapata Cáceres

Validating the test

After these improvements, the test was validated with 299 primary school students aged 5-12. To assess the differences the improvements might make, the students were given different version of the test. María and her colleagues found that the younger students benefited from the improvements, and the improvements made the test more reliable for testing students’ computational thinking: students made fewer errors due to ambiguity and misinterpretation.

Statistical analysis of the test results showed that the improved version of the test is reliable and can be used with confidence to assess the skills of younger children.

What can you use this test for?

Firstly, the test is a tool for educators who want to assess the skills young people have and develop over time. Secondly, the test is also valuable for researchers. It can be used to perform projects that evaluate the outcomes of different approaches to teaching computational thinking, as well as projects investigating the effectiveness of specific learning resources, because the test can be given to children before and again after they engage with the resources.

Assessment is one of the many tools educators use to shape their teaching and promote the learning of their students, and tools like this CT test developed by María and her colleagues allow us to better understand what children are learning.

Find out more & join our next seminar

The video and slides of María’s presentation are available on our seminars page. To find out more about this test, and the process used to create and validate it, read the paper by María and her colleagues.

Our final seminar of this series takes place Tuesday 28 July before we take a break for the summer. In the session, we will explore gender balance in computing, led by Katharine Childs, who works on the Gender Balance in Computing research project at the Raspberry Pi Foundation. You can find out more and sign up to attend for free on our Computing Education Research Seminars page.

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Reducing the load: ways to support novice programmers

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/research-seminar-cognitive-load-subgoal-labels/

What’s your experience of learning to program? Have you given up and thought it just wasn’t for you? This has been the case for many people — and it’s the focus of a lot of research. Now that teaching programming is in the curriculum in many countries around the world, it’s even more important that we understand what we can do to make learning to program accessible and achievable for all students.

What is cognitive load for learners?

In education, one of the problems thought to cause students difficulty with learning anything — not just programming — is cognitive load. Cognitive load, a concept introduced in the 1980s by John Sweller, has received a lot of attention in the last few years. It is based on the idea that our working memory (the part of our memory that processes what we are currently doing) can only deal with a limited amount of information at any one time. For example, you can imagine that when you are just starting to learn to program, there is an awful lot going on in your working memory, and this can make the task of assimilating it all very challenging; selection, loops, arrays, and objects are all tricky concepts that you need to get to grips with. Cognitive load is a stress on a learner’s working memory, reducing their ability to process and learn new information.

Dr Briana Morrison (University of Nebraska-Omaha)

Finding ways of teaching programming that reduce cognitive load is really key for all of us engaged in computing education, so we were delighted to welcome Dr Briana Morrison (University of Nebraska-Omaha) as the speaker at our latest research seminar. Briana’s talk was titled ‘Using subgoal Labels to Reduce Cognitive Load in Introductory Programming’.

The thrust of Briana’s and her colleagues’ research is that, as educators, we can design instructional experiences around computer programming so that they minimise cognitive load. Using worked examples with subgoal labels is one approach that has been shown to help a lot with this. 

Subgoal labels help students memorise and generalise

Think back to the way you may have learned mathematics: in maths, worked examples are often used to demonstrate how to solve a problem step by step. The same can be done when teaching programming. For example, if we want to write a loop in Python, the teacher can show us a step-by-step approach using an example, and we can then apply this approach to our own task. Sounds reasonable, right?

What subgoal labels add is that, rather than just calling the steps of the worked example ‘Step 1’, ‘Step 2’, etc., the teacher uses memorable labels. For example, a subgoal label might be ‘define and initialise variables’. Such labels not only help us to remember, but more importantly, they help us to generalise the teacher’s example and grasp how to use it for many other applications.

Subgoal labels help students perform better

In her talk, Briana gave us examples of subgoal labels in use and explained how to write subgoal labels, as well as how to work with subject experts to find the best subgoal labels for a particular programming construct or area of teaching. She also shared with us some very impressive results from her team’s research examining the impact of this teaching approach. 

Screenshot of Dr Briana Morrison's research seminar talk

Briana and her colleagues have carried out robust studies comparing students who were taught using subgoals with students who weren’t. The study she discussed in the seminar involved 307 students; students in the group that learned with worked examples containing subgoal labels gave more complete answers to questions, and showed that they could understand the programming constructs at a higher level, than students who learned with worked examples that didn’t contain the subgoal labels. The study also found that the impact of subgoal labels was even more marked for students in at-risk groups (i.e. students at risk of performing badly or of dropping out).

It seems that this teaching approach works really well. The study’s participants were students in introductory computer science classes at university, so it would be interesting to see whether these results can be replicated at school level, where arguably cognitive load is even more of an issue.

Briana’s seminar was very well received, with attendees asking lots of questions about the details of the research and how it could be replicated. Her talk even included some audience participation, which got us all tapping our heads and rubbing our bellies!

Screenshot of Dr Briana Morrison's research seminar talk

Very helpfully, Briana shared a list of resources related to subgoal labels, which you can access via her talk slides on our seminars page.

You can also read more about the background and practical application of cognitive load theory and worked examples including subgoal labels in the Pedagogy Quick Read series we’re producing as part of our work in the National Centre of Computing Education.

Next up in our series

If you missed the seminar, you can find Briana’s presentation slides on our seminars page, where we’ll also soon upload a recording of her talk.

In our next seminar on Tuesday 14 July at 17:00–18:00 BST / 12:00–13:00 EDT / 9:00–10:00 PDT / 18:00–19:00 CEST, we’ll welcome Maria Zapata, Universidad Rey Juan Carlos, Madrid, who will be talking about computational thinking and how we can assess the computational thinking skills of very young children. To join the seminar, simply sign up with your name and email address and we’ll email you the link and instructions. If you attended Briana’s seminar, the link remains the same.

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Volunteer your Raspberry Pi to IBM’s World Community Grid

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/ibm-world-community-grid/

IBM’s World Community Grid is working with scientists at Scripps Research on computational experiments to help find potential COVID-19 treatments. Anyone with a Raspberry Pi and an internet connection can help.

Why is finding potential treatments for COVID-19 so important?

Scientists all over the globe are working hard to create a vaccine that could help prevent the spread of COVID-19. However, this process is likely to take many months — or possibly even years.

In the meantime, scientists are also searching for potential treatments for the symptoms of COVID-19. A project called OpenPandemics – COVID-19 is one such effort. The project is led by researchers in the Forli Lab at Scripps Research, who are enlisting the help of World Community Grid volunteers.

What is World Community Grid and how does it work? 

World Community Grid is an IBM social responsibility initiative that supports humanitarian scientific research. 

Image text reads: Accelerate research with no investment of time or money. When you become a World Community Grid volunteer, you donate your device's spare computing power to help scientists solve the world's biggest problems in health and sustainability.

As a World Community Grid volunteer, you download a secure software program to your Raspberry Pi, macOS or Windows computer, or Android device. This software program (called BOINC) is used to run World Community Grid projects, and is compatible with the Raspberry Pi OS and most other operating systems. Then, when your device is not using its full power, it automatically runs a simulated experiment in the background that will help predict the effectiveness of a particular chemical compound as a possible treatment for COVID-19. Finally, your device automatically returns the results of the completed simulation and requests the next simulation.

Over the course of the project, volunteers’ devices will run millions of simulations of small molecules interacting with portions of the virus that causes COVID-19. This is a process known as molecular docking, which is the study of how two or more molecules fit together. When a simulated chemical compound fits, or ‘docks’, with a simulation of part of the virus that causes COVID-19, that interaction may point to a potential treatment for the disease.

An image of a calendar with the text: Get results that matter. As a World Community Grid volunteer, your device does research calculations when it's idle, so just by using it as. you do every dat you can help scientists get results in months instead of decades. With your help, they can identify the most important areas to study in the lab, bringing them one step closer to discoveries that save lives and address global problems.

World Community Grid combines the results from your device along with millions of results from other volunteers all over the world and sends them to the Scripps Research team for analysis. While this process doesn’t happen overnight, it accelerates dramatically what would otherwise take many years, or might even be impossible.

OpenPandemics – COVID-19 is the first World Community Grid project to harness the power of Raspberry Pi devices, but the World Community Grid technical team is already working to make other projects available for Raspberry Pi very soon.

Getting ready for future pandemics

Scientists have learned from past outbreaks that pandemics caused by newly emerging pathogens may become more and more common. That’s why OpenPandemics – COVID-19 was designed to be rapidly deployed to fight future diseases, ideally before they reach a critical stage.

A image of a scientist using a microscope. Text reads: Your device could help search for potential treatments for COVID-19. Scientists are using World Community Grid to accelerate the search for treatments to COVIS-19. The tools and techniques the scientists develop to fight COVID-19 could be used in the future by all researchers to help more quickly find treatments for potential pandemics

To help address future pandemics, researchers need access to swift and effective tools that can be deployed very early, as soon as a threatening disease is identified. So, the researchers behind OpenPandemics – COVID-19 are creating a software infrastructure to streamline the process of finding potential treatments for other diseases. And in keeping with World Community Grid’s open data policy, they will make their findings and these tools freely available to the scientific community. 

Join a global community of science supporters

World Community Grid is thrilled to make OpenPandemics – COVID-19 available to everyone who wants to donate computing power from their Raspberry Pi. Every device can play a part in helping the search for COVID-19 treatments. Please join us!

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How we are helping you with computing teaching methods

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/how-we-are-helping-you-with-computing-teaching-methods/

One aspect of our work as part of the National Centre for Computing Education (NCCE) is producing free materials for teachers about teaching methods and pedagogy in computing. I am excited to introduce these materials to you here!

Teachers are asking us about teaching methods

Computing was included in the national curriculum in England in 2014, and after this, continued professional development (CPD) initiatives became available to support teachers to feel confident in topics they had not previously studied. Much of the CPD focussed on learning about programming, algorithms, networking, and how computers work.

Instructor explaining corporate software specific to trainees in computer class. Man and women sitting at table, using desktop, pointing at monitor and talking. Training concept

More recently however, I’ve found that increasing numbers of teachers are asking for support around teaching methods, particularly for how to support students who find programming and other aspects of computing difficult. Computing is a relatively new subject, but more and more research results are showing how to best teach it.

We offer CPD with our online courses

As part of the NCCE, we produce lots of free resources to support teachers with developing knowledge and skills in all aspects of computing. The NCCE’s Computing Hubs offer remotely delivered sessions, and we produce interactive, in-depth, free online courses for teachers to take over 3 or 4 weeks. Some of these online courses are about subject knowledge, while others focus on how to teach computing, the area referred to as pedagogical content knowledge*. For example, two of our courses are Programming Pedagogy in Primary Schools and Programming Pedagogy in Secondary Schools. Our pedagogy courses draw on the expertise and experience of many computing teachers working with students right now.

We share best practices in computing pedagogy

But that’s not all! We continually share tried and tested strategies for use in the computing classroom to help teachers, and those training to teach, support students more effectively. We believe that computing is for everyone and as such, we need a variety of possible approaches to teaching each topic up our collective sleeves, to ensure accessibility for all our students.

We develop all of this material in collaboration with in-the-classroom-now, experienced teachers and other experts, also drawing upon the latest computing education research. Our aim is to give you great, practical ideas for how to engage students who may be unmotivated or switched off, and new strategies to help you support students’ understanding of more complex computing concepts.

We support you to do classroom action research

One of the findings from decades of educational research is that teacher action research in the classroom is an extremely effective form of CPD! Teacher action research means reflecting on what the barriers to learning are in your classroom, planning an intervention (often in the form of a specific change to your teaching practice), and then evaluating whether it engenders improvement. Doing this has positive impacts both on your expertise as a teacher and on your students’ learning!

To support you with action research, we’re launching a special programme for classroom action research in computing. This takes the form of an online course, facilitated by experts in the field, lasting over a six-month period. Find out more about this opportunity.

Share your experiences with us

Right now we’re in unusual times, and surviving various combinations of home learning and remote delivery with your classes may be your greatest concern. However you’re getting on, we’d love to hear from you about your classroom practice in computing. Your experience with different ways of teaching computing in the classroom will add to our collective understanding about what works for teaching students. You can share your feedback with us, or get in touch with our pedagogy team at [email protected].

Other ways to learn and stay in touch:

 

*Back in 1987, Lee Shulman wrote: “Pedagogical content knowledge represents the blending of content and pedagogy into an understanding of how particular topics, problems or issues are organised, represented, and adapted to the diverse interests and abilities of learners, and presented for instruction.”

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Mathematics and programming: exploring the links

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/research-seminar-mathematics-programming-links/

“In my vision, the child programs the computer and, in doing so, both acquires a sense of mastery over a piece of the most modern and powerful technology and establishes an intimate contact with some of the deepest ideas from science, from mathematics, and from the art of intellectual model building.” – Seymour Papert, Mindstorms: Children, Computers, And Powerful Ideas, 1980

We owe much of what we have learned about children learning to program to Seymour Papert (1928–2016), who not only was a great mathematician and computer scientist, but also an inspirational educationalist. He developed the theoretical approach to learning we now know as constructionism, which purports that learning takes place through building artefacts that have meaning and can be shared with others. Papert, together with others, developed the Logo programming language in 1967 to help children develop concepts in both mathematics and in programming. He believed that programming could give children tangible and concrete experiences to support their acquisition of mathematical concepts. Educational programming languages such as Logo were widely used in both primary and secondary education settings during the 1980s and 90s. Thus for many years the links between mathematics and programming have been evident, and we were very fortunate to be able to explore this topic with our research seminar guest speaker, Professor Dame Celia Hoyles of University College London.

Dame Celia Hoyles

Professor Dame Celia Hoyles

Dame Celia Hoyles is a huge celebrity in the world of mathematical education and programming. As well as authoring literally hundreds of academic papers on mathematics education, including on Logo programming, she has received a number of prestigious awards and honours, and has served as the Chief Advisor to the UK government on mathematics in school. For all these reasons, we were delighted to hear her present at a Raspberry Pi Foundation computing education research seminar.

Mathematics is a subject we all need to understand the basics of — it underpins much of our other learning and empowers us in daily life. Yet some mathematical concepts can seem abstract and teachers have struggled over the years to help children to understand them. Since programming includes the design, building, and debugging of artefacts, it is a great approach for make such abstract concepts come to life. It also enables the development of both computational and mathematical thinking, as Celia described in her talk.

Learning mathematics through Scratch programming

Celia and a team* at University College London developed a curriculum initiative called ScratchMaths to teach carefully selected mathematical concepts through programming (funded by the Education Endowment Foundation in 2014–2018). ScratchMaths is for use in upper primary school (age 9–11) over a two-year period.

In the first year, pupils take three computational thinking modules, and in the second year, they move to three more mathematical thinking modules. All the ScratchMaths materials were designed around a pedagogical framework called the 5Es: explore, envisage, explain, exchange, and bridge. This enables teachers to understand the structure and sequencing of the materials as they use them in the classroom:

  • Explore: Investigate, try things out yourself, debug in reaction to feedback
  • Envisage: Have a goal in mind, predict outcome of program before trying
  • Explain: Explain what you have done, articulate reasons behind your approach to others
  • Exchange: Collaborate & share, try to see a problem from another’s perspective as well as defend your own approach and compare with others
  • bridgE: Make explicit links to the mathematics curriculum

Teachers in the ScratchMaths project participated in professional development (two days per module) to enable them to understand the materials and the pedagogical approach.

At the end of the project, external evaluators measured the childrens’ learning and found a statistically significant increase in computational thinking skills after the first year, but no difference between an intervention group and a control group in the mathematical thinking outcomes in the second year (as measured by the national mathematics tests at that age).

Celia discussed a number of reasons for these findings. She also drew out the positive perspective that children in the trial learned two subjects at the same time without any detriment to their learning of mathematics. Covering two subjects and drawing the links between them without detriment to the core learning is potentially a benefit to schools who need to fit many subjects into their teaching day.

Much more information about the programme and the materials, which are freely available for use, can be found on the ScratchMaths project’s website, and you can also read a research paper describing the project.

As at all our research seminars, participants had many questions for our speaker. Although the project was designed for primary education, where it’s more common to learn subjects together across the curriculum, several questions revolved around the project’s suitability for secondary school. It’s interesting to reflect on how a programme like ScratchMaths might work at secondary level.

Should computing be taught in conjunction or separately?

Teaching programming through mathematics, or vice versa, is established practice in some countries. One example comes from Sweden, where computing and programming is taught across different subject areas, including mathematics: “through teaching pupils should be given opportunities to develop knowledge in using digital tools and programming to explore problems and mathematical concepts, make calculations and to present and interpret data”. In England, conversely, we have a discrete computing curriculum, and an educational system that separates subjects out so that it is often difficult for children to see overlap and contiguity. However, having the focus on computing as a discrete subject gives enormous benefits too, as Celia outlined at the beginning of her talk, and it opens up the potential to give children an in-depth understanding of the whole subject area over their school careers. In an ideal world, perhaps we would teach programming in conjunction with a range of subjects, thus providing the concrete realisation of abstract concepts, while also having discrete computing and computer science in the curriculum.

Woman teacher and female students at a computer

In our current context of a global pandemic, we are continually seeing the importance of computing applications, for example computer modelling and simulation used in the analysis of data. This talk highlighted the importance of learning computing per se, as well as the mathematics one can learn through integrating these two subjects.

Celia is a member of the National Centre of Computing Education (NCCE) Academic Board, made up of academics and experts who support the teaching and learning elements of the NCCE, and we enjoy our continued work with her in this capacity. Through the NCCE, the Raspberry Pi Foundation is reaching thousands of children and educators with free computing resources, online courses, and advanced-level computer science materials. Our networks of Code Clubs and CoderDojos also give children the space and freedom to experiment and play with programming and digital making in a way that is concordant with a constructionist approach.

Next up in our seminar series

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

In our next seminar on Tuesday 16 June at 17:00–18:00 BST / 12:00–13:00 EDT / 9:00–10:00 PDT / 18:00–19:00 CEST, we’ll welcome Jane Waite, Teaching Fellow at Queen Mary University of London. Jane will be sharing insights about Semantic Waves and unplugged computing. To join the seminar, simply sign up with your name and email address and we’ll email you the link and instructions. If you attended Celia’s seminar, the link remains the same.

 

*The ScratchMaths team are :

  • Professor Dame Celia Hoyles (Mathematics) & Professor Richard Noss (Mathematics) UCL Knowledge Lab
  • Professor Ivan Kalas, (Computing) Comenius University, Bratislava, Slovakia
  • Dr Laura Benton (Computing) & Piers Saunders, (Mathematics) UCL Knowledge Lab
  • Professor Dave Pratt (Mathematics) UCL Institute of Education

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Learning AI at school — a peek into the black box

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/research-seminar-learning-ai-at-school/

“In the near future, perhaps sooner than we think, virtually everyone will need a basic understanding of the technologies that underpin machine learning and artificial intelligence.” — from the 2018 Informatics Europe & EUACM report about machine learning

As the quote above highlights, AI and machine learning (ML) are increasingly affecting society and will continue to change the landscape of work and leisure — with a huge impact on young people in the early stages of their education.

But how are we preparing our young people for this future? What skills do they need, and how do we teach them these skills? This was the topic of last week’s online research seminar at the Raspberry Pi Foundation, with our guest speaker Juan David Rodríguez Garcia. Juan’s doctoral studies around AI in school complement his work at the Ministry of Education and Vocational Training in Spain.

Juan David Rodríguez Garcia

Juan’s LearningML tool for young people

Juan started his presentation by sharing numerous current examples of AI and machine learning, which young people can easily relate to and be excited to engage with, and which will bring up ethical questions that we need to be discussing with them.

Of course, it’s not enough for learners to be aware of AI applications. While machine learning is a complex field of study, we need to consider what aspects of it we can make accessible to young people to enable them to learn about the concepts, practices, and skills underlying it. During his talk Juan demonstrated a tool called LearningML, which he has developed as a practical introduction to AI for young people.

Screenshot of a demo of Juan David Rodríguez Garcia's LearningML tool

Juan demonstrates image recognition with his LearningML tool

LearningML takes inspiration from some of the other in-development tools around machine learning for children, such as Machine Learning for Kids, and it is available in one integrated platform. Juan gave an enticing demo of the tool, showing how to use visual image data (lots of pictures of Juan with hats, glasses on, etc.) to train and test a model. He then demonstrated how to use Scratch programming to also test the model and apply it to new data. The seminar audience was very positive about the LearningML, and of course we’d like it translated into English!

Juan’s talk generated many questions from the audience, from technical questions to the key question of the way we use the tool to introduce children to bias in AI. Seminar participants also highlighted opportunities to bring machine learning to other school subjects such as science.

AI in schools — what and how to teach

Machine learning demonstrates that computers can learn from data. This is just one of the five big ideas in AI that the AI4K12 group has identified for teaching AI in school in order to frame this broad domain:

  1. Perception: Computers perceive the world using sensors
  2. Representation & reasoning: Agents maintain models/representations of the world and use them for reasoning
  3. Learning: Computers can learn from data
  4. Natural interaction: Making agents interact comfortably with humans is a substantial challenge for AI developers
  5. Societal impact: AI applications can impact society in both positive and negative ways

One general concern I have is that in our teaching of computing in school (if we touch on AI at all), we may only focus on the fifth of the ‘big AI ideas’: the implications of AI for society. Being able to understand the ethical, economic, and societal implications of AI as this technology advances is indeed crucial. However, the principles and skills underpinning AI are also important, and how we introduce these at an age-appropriate level remains a significant question.

Illustration of AI, Image by Seanbatty from Pixabay

There are some great resources for developing a general understanding of AI principles, including unplugged activities from Computer Science For Fun. Yet there’s a large gap between understanding what AI is and has the potential to do, and actually developing the highly mathematical skills to program models. It’s not an easy issue to solve, but Juan’s tool goes a little way towards this. At the Raspberry Pi Foundation, we’re also developing resources to bridge this educational gap, including new online projects building on our existing machine learning projects, and an online course. Watch this space!

AI in the school curriculum and workforce

All in all, we seem to be a long way off introducing AI into the school curriculum. Looking around the world, in the USA, Hong Kong, and Australia there have been moves to introduce AI into K-12 education through pilot initiatives, and hopefully more will follow. In England, with a computing curriculum that was written in 2013, there is no requirement to teach any AI or machine learning, or even to focus much on data.

Let’s hope England doesn’t get left too far behind, as there is a massive AI skills shortage, with millions of workers needing to be retrained in the next few years. Moreover, a recent House of Lords report outlines that introducing all young people to this area of computing also has the potential to improve diversity in the workforce — something we should all be striving towards.

We look forward to hearing more from Juan and his colleagues as this important work continues.

Next up in our seminar series

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

In our next seminar on Tuesday 2 June at 17:00–18:00 BST / 12:00–13:00 EDT / 9:00–10:00 PDT / 18:00–19:00 CEST, we’ll welcome Dame Celia Hoyles, Professor of Mathematics Education at University College London. Celia will be sharing insights from her research into programming and mathematics. To join the seminar, simply sign up with your name and email address and we’ll email the link and instructions. If you attended Juan’s seminar, the link remains the same.

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Making the best of it: online learning and remote teaching

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/research-seminar-online-learning-remote-teaching/

As many educators across the world are currently faced with implementing some form of remote teaching during school closures, we thought this topic was ideal for the very first of our seminar series about computing education research.

Image by Mudassar Iqbal from Pixabay

Research into online learning and remote teaching

At the Raspberry Pi Foundation, we are hosting a free online seminar every second Tuesday to explore a wide variety of topics in the area of digital and computing education. Last Tuesday we were delighted to welcome Dr Lauren Margulieux, Assistant Professor of Learning Sciences at Georgia State University, USA. She shared her findings about different remote teaching approaches and practical tips for educators in the current crisis.

Lauren’s research interests are in educational technology and online learning, particularly for computing education. She focuses on designing instructions in a way that supports online students who do not necessarily have immediate access to a teacher or instructor to ask questions or overcome problem-solving impasses.

A vocabulary for online and blended learning

In non-pandemic situations, online instruction comes in many forms to serve many purposes, both in higher education and in K-12 (primary and secondary school). Much research has been carried out in how online learning can be used for successful learning outcomes, and in particular, how it can be blended with face-to-face (hybrid learning) to maximise the impact of both contexts.

In her seminar talk, Lauren helped us to understand the different ways in which online learning can take place, by sharing with us vocabulary to better describe different ways of learning with and through technology.

Lauren presented a taxonomy for classifying types of online and blended teaching and learning in two dimensions (shown in the image below). These are delivery type (technology or instructor), and whether content is received by learners, or actually being applied in the learning experience.

Lauren Margulieux seminar slide showing her taxonomy for different types of mixed student instruction

In Lauren’s words: “The taxonomy represents the four things that we control as instructors. We can’t control whether our students talk to each other or email each other, or ask each other questions […], therefore this taxonomy gives us a tool for defining how we design our classes.”

This taxonomy illustrates that there are a number of different ways in which the four types of instruction — instructor-transmitted, instructor-mediated, technology-transmitted, and technology-mediated — can be combined in a learning experience that uses both online and face-to-face elements.

Using her taxonomy in an examination (meta-analysis) of 49 studies relating to computer science teaching in higher education, Lauren found a range of different ways of mixing instruction, which are shown in the graph below.

  • Lecture hybrid means that the teaching is all delivered by the teacher, partly face-to-face and partly online.
  • Practice hybrid means that the learning is done through application of content and receiving feedback, which happens partly face-to-face or synchronously and partly online or asynchronously.
  • Replacement blend refers to instruction where lecture and practice takes place in a classroom and part of both is replaced with an online element.
  • Flipped blend instruction is where the content is transmitted through the use of technology, and the application of the learning is supported through an instructor. Again, the latter element can also take place online, but it is synchronous rather than asynchronous — as is the case in our current context.
  • Supplemental blend learning refers to instruction where content is delivered face-to-face, and then practice and application of content, together with feedback, takes place online — basically the opposite of the flipped blend approach.

Lauren Margulieux seminar slide showing learning outcomes of different types of mixed student instruction

Lauren’s examination found that the flipped blend approach was most likely to demonstrate improved learning outcomes. This is a useful finding for the many schools (and universities) that are experimenting with a range of different approaches to remote teaching.

Another finding of Lauren’s study was that approaches that involve the giving of feedback promoted improved learning. This has also been found in studies of assessment for learning, most notably by Black and Wiliam. As Lauren pointed out, the implication is that the reason blended and flipped learning approaches are the most impactful is that they include face-to-face or synchronous time for the educator to discuss learning with the students, including giving feedback.

Lauren’s tips for remote teaching

Of course we currently find ourselves in the midst of school closures across the world, so our only option in these circumstances is to teach online. In her seminar talk, Lauren also included some tips from her own experience to help educators trying to support their students during the current crisis:

  • Align learning objectives, instruction, activities, assignments, and assessments.
  • Use good equipment: headphones to avoid echo and a good microphone to improve clarity and reduce background noise.
  • Be consistent in disseminating information, as there is a higher barrier to asking questions.
  • Highlight important points verbally and visually.
  • Create ways for students to talk with each other, through discussions, breakout rooms, opportunities to talk when you aren’t present, etc.
  • Use video when possible while talking with your students.
    Give feedback frequently, even if only very brief.

Although Lauren’s experience is primarily from higher education (post-18), this advice is also useful for K-12 educators.

What about digital equity and inclusion?

All our seminars include an opportunity to break out into small discussion groups, followed by an opportunity to ask questions of the speaker. We had an animated follow-up discussion with Lauren, with many questions focused on issues of representation and inclusion. Some questions related to the digital divide and how we could support learners who didn’t have access to the technology they need. There were also questions from breakout groups about the participation of groups that are typically under-represented in computing education in online learning experiences, and accessibility for those with special educational needs and disabilities (SEND). While there is more work needed in this area, there’s also no one-size-fits-all approach to working with students with special needs, whether that’s due to SEND or to material resources (e.g. access to technology). What works for one student based on their needs might be entirely ineffective for others. Overall, the group concluded that there was a need for much more research in these areas, particularly at K-12 level.

Much anxiety has been expressed in the media, and more formally through bodies such as the World Economic Forum and UNESCO, about the potential long-lasting educational impact of the current period of school closures on disadvantaged students and communities. Research into the most inclusive way of supporting students through remote teaching will help here, as will the efforts of governments, charities, and philanthropists to provide access to technology to learners in need.

At the Raspberry Pi Foundation, we offer lots of free resources for students, educators, and parents to help them engage with computing education during the current school closures and beyond.

How should the education community move forward?

Lauren’s seminar made it clear to me that she was able to draw on decades of research studies into online and hybrid learning, and that we should take lessons from these before jumping to conclusions about the future. In both higher education (tertiary, university) and K-12 (primary, secondary) education contexts, we do not yet know the educational impact of the teaching experiments we have found ourselves engaging in at short notice. As Charles Hodges and colleagues wrote recently in Educause, what we are currently engaging in can only really be described as emergency remote teaching, which stands in stark contrast to planned online learning that is designed much more carefully with pedagogy, assessment, and equity in mind. We should ensure we learn lessons from the online learning research community rather than making it up as we go along.

Today many writers are reflecting on the educational climate we find ourselves in and on how it will impact educational policy and decision-making in the future. For example, an article from the Brookings Institution suggests that the experiences of home teaching and learning that we’ve had in the last couple of months may lead to both an increased use of online tools at home, an increase in home schooling, and a move towards competency-based learning. An article by Jo Johnson (President’s Professorial Fellow at King’s College London) on the impact of the pandemic on higher education, suggests that traditional universities will suffer financially due to a loss of income from international students less likely to travel to universities in the UK, USA, and Australia, but that the crisis will accelerate take-up of online, distance-learning, and blended courses for far-sighted and well-organised institutions that are ready to embrace this opportunity, in sum broadening participation and reducing elitism. We all need to be ready and open to the ways in which online and hybrid learning may change the academic world as we know it.

Next up in our seminar series

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

Next Tuesday, 19 May at 17:00–18:00 BST, we will welcome Juan David Rodríguez from the Instituto Nacional de Tecnologías Educativas y de Formación del Profesorado (INTEF) in Spain. His seminar talk will be about learning AI at school, and about a new tool called LearningML. To join the seminar, simply sign up with your name and email address and we’ll email the link and instructions. If you attended Lauren’s seminar, the link remains the same.

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Cambridge Computing Education Research Symposium – recap of our online event

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/online-research-symposium-recap/

On Wednesday, we hosted the first-ever Cambridge Computing Education Research Symposium online. Research in computing education, particularly in school and for young people, is a young field compared to maths and science education, and we do not have much in terms of theoretical foundations. It is not a field that has received a lot of funding, so we cannot yet look to large-scale, longitudinal, empirical studies for evidence. Therefore, further research on how best to teach, learn, and assess computing is desperately needed. We also need to investigate ways of inspiring and motivating all young people in an area which is increasingly important for their future.

That’s why at the Raspberry Pi Foundationwe have made research a key part of our new strategy, and that’s why we worked with the University of Cambridge to hold this event.

Moving the symposium online

This was to be our first large-scale research event, held jointly with the University of Cambridge Department of Computer Science and Technology. Of course, current circumstances made it necessary for us to turn the symposium from a face-to-face into an online event at short notice.

Screengrab from the Cambridge Computing Education Research Symposium 2020 online event

An enthusiastic team took on the challenge, and we were delighted with how well the way the day went! You can see what participants shared throughout the day on Twitter.

Keynote presentation

Our keynote speaker was Dr Natalie Rusk of MIT and the Scratch Foundation, who shared her passion for digital creativity using Scratch.

Dr Natalie Rusk from the MIT Media Lab

We were excited to see images from early versions of Scratch and how it had developed over the years. Plus, Natalie revealed the cat blocks that were available on 1 April only — I had completely forgotten the day of the symposium was April Fools’ Day! The focus of Natalie’s presentation was on creativity, invention, tinkering, and the development of ideas over time, and she explored case studies of two ‘Scratchers’ who took a very different approach to working in the Scratch community on projects. The talk was well received by all.

Screengrab from the Cambridge Computing Education Research Symposium 2020 online event

Paper presentations

We heard from researchers from a range of institutions on topics under these themes:

  • Working with teachers on computing education research
  • Assessment tools and techniques
  • Perceptions and attitudes about computing
  • Theoretical frameworks used for computing education

Highlights for me were Ethel Tshukudu’s analysis of the way students transfer from one programming language to another, in which she draws on semantic transfer theory; and Paul Curzon’s application of Karl Maton’s semantic wave theory (taken from linguistics) to computing education.

The symposium’s focus was computing for young people, and much of the research presented was directly grounded in work with teachers and students in learning situations. Lynne Blair shared an interesting study highlighting female participation in A level computer science classes, which found the feeling of a lack of belonging among young women, a finding that echoes existing research around computing education and gender. Fenia Aivaloglou from the University of Leiden, Netherlands, considered the barriers faced by learners and teachers in extra-curricular code clubs, and Alison Twiner and Jo Shillingworth from the University of Cambridge shared a study on engaging young people in work-related computing projects.

We also heard how tools for supporting learners are developing, for example machine learning techniques to process natural language answers to questions on the free online learning platforms Isaac Computer Science and Isaac Physics.

Poster presentations

For the poster sessions, we divided into separate sessions so that the poster presenters could display and discuss their posters with a smaller group of people. This enabled more in-depth discussion about the topic being presented, which participants appreciated at this large online event. The 11 posters covered a wide range of topics from data visualisations in robotics to data-driven dance.

Screengrab from the Cambridge Computing Education Research Symposium 2020 online event

We showcased some of our own work on progression mapping with learning graphs for the NCCE Resource Repository; the Isaac Computer Science A level content platform; and our research into online learning with our free online courses for teachers.

Running an online symposium — what is it like?

From having successfully hosted this event online, we learned many lessons that we want to put into practice in future online events being offered by the Raspberry Pi Foundation.

There’s a plethora of tools available, and they all have their pros and cons (we used Google Meet). It’s my view that the tool is less important than the preparation needed for a large-scale online event, which is significant! The organising team hosted technical run-throughs with all presenters in the two days before the event, and instigated a ‘green room’ for all presenters to check their setups again five to ten minutes before their speaking slot. This helped to avoid a whole myriad of potential technical difficulties.

Screengrab from the Cambridge Computing Education Research Symposium 2020 online event

I’m so grateful to the great team at the Raspberry Pi Foundation, who worked behind the scenes all day to make sure that the participants and presenters got the most out of the event!

Stay in touch!

  • On the Research Symposium web page, you can now download the symposium’s abstract booklet. We will shortly be sharing recordings of the symposium’s presentations and files of slides and posters there as well.
  • When we moved the symposium online, we postponed two pre-symposium events: a workshop on gender balance, and a workshop on research-to-practice; we’re hoping to hold these as in-person events in the autumn.
  • Meanwhile, we are planning a series of online seminars, set to start on Tuesday 21 April at 17:00 BST and continue throughout the summer at two-week intervals.

If you’re interested in receiving a regular update about these and other research activities of ours, sign up to our newsletter.

We look forward to building a community of researchers and to sharing more of our work with you over the coming years.

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FluSense takes on COVID-19 with Raspberry Pi

Post Syndicated from Ashley Whittaker original https://www.raspberrypi.org/blog/flusense-takes-on-covid-19-with-raspberry-pi/

Raspberry Pi devices are often used by scientists, especially in biology to capture and analyse data, and a particularly striking – and sobering – project has made the news this week. Researchers at UMass Amherst have created FluSense, a dictionary-sized piece of equipment comprising a cheap microphone array, a thermal sensor, an Intel Movidius 2 neural computing engine, and a Raspberry Pi. FluSense monitors crowd sounds to forecast outbreaks of viral respiratory disease like seasonal flu; naturally, the headlines about their work have focused on its potential relevance to the COVID-19 pandemic.

A photo of Forsad Al Hossain and Tauhidur Rahman with the FluSense device alongside a logo from the Amherst University of Massachusetts

Forsad Al Hossain and Tauhidur Rahman with the FluSense device. Image courtesy of the University of Massachusetts Amherst

The device can distinguish coughing from other sounds. When cough data is combined with information about the size of the crowd in a location, it can provide an index predicting how many people are likely to be experiencing flu symptoms.

It was successfully tested in in four health clinic waiting rooms, and now, PhD student Forsad Al Hossain and his adviser, assistant professor Tauhidur Rahman, plan to roll FluSense out in other large spaces to capture data on a larger scale and strengthen the device’s capabilities. Privacy concerns are mitigated by heavy encryption, and Al Hossain and Rahman explain that the emphasis is on aggregating data, not identifying sickness in any single patient.

The researchers believe the secret to FluSense’s success lies in how much of the processing work is done locally, via the neural computing engine and Raspberry Pi: “Symptom information is sent wirelessly to the lab for collation, of course, but the heavy lifting is accomplished at the edge.”

A bird's-eye view of the components inside the Flu Sense device

Image courtesy of the University of Massachusetts Amherst

FluSense offers a different set of advantages to other tools, such as the extremely popular self-reporting app developed by researchers at Kings College Hospital in London, UK, together with startup Zoe. Approaches like this rely on the public to sign up, and that’s likely to skew the data they gather, because people in some demographic groups are more likely than others to be motivated and able to participate. FluSense can be installed to capture data passively from groups across the entire population. This could be particularly helpful to underprivileged groups who are less likely to have access to healthcare.

Makers, engineers, and scientists across the world are rising to the challenge of tackling COVID-19. One notable initiative is the Montreal General Hospital Foundation’s challenge to quickly design a low-cost, easy to use ventilator which can be built locally to serve patients, with a prize of CAD $200,000 on offer. The winning designs will be made available to download for free.

There is, of course, loads of chatter on the Raspberry Pi forum about the role computing has in beating the virus. We particularly liked this PSA letting you know how to free up some of your unused processing power for those researching treatments.

screenshot of the hand washer being built from a video on instagram

Screenshot via @deeplocal on Instagram

And to end on a cheering note, we *heart* this project from @deeplocal on Instagram. They’ve created a Raspberry Pi-powered soap dispenser which will play 20 seconds of your favourite song to keep you at the sink and make sure you’re washing your hands for long enough to properly protect yourself.

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Attend our Cambridge Computing Education Research Symposium

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/cambridge-computing-education-research-symposium-2020/

Are you an academic, researcher, student, or educator who is interested in computing education research? Then come and join us in Cambridge, UK on 1 April 2020 for discussion and networking at our first-ever research symposium.

Dr Natalie Rusk from the MIT Media Lab is our keynote speaker

Dr Natalie Rusk from the MIT Media Lab is our keynote speaker

Join our symposium

At the Raspberry Pi Foundation, we carry out research that deepens our understanding of how young people learn about computing and digital making and helps to increase the impact of our work and advance the field of computing education.

As part of our research work, we are launching the Cambridge Computing Education Research Symposium, a new one-day symposium hosted jointly by us and the University of Cambridge.

The theme of the symposium is school-level computing education, both formal and non-formal. The symposium will offer an opportunity for researchers and educators to share their work, meet others with similar interests, and build collaborative projects and networks.

University of Cambridge Computer Laboratory

The William Gates Building in Cambridge houses the Department of Computer Science and Technology (Computer Laboratory) and will be the symposium venue

The symposium will take place on 1 April 2020 at the Department of Computer Science and Technology. The day will include a range of talks and a poster session, as well as a keynote speech from Dr Natalie Rusk, Research Scientist at the MIT Media Laboratory and one of the creators of the Scratch programming language.

Registration for the symposium is now open: book your place today!

Pre-symposium workshops and networking

When you register to attend, you’ll also have the chance to sign up for one of two parallel workshops taking place on 31 March 2020 at the Raspberry Pi Foundation office in Cambridge.

Workshop 1 concerns the topic of gender balance in computing, while in workshop 2, we’ll consider what research-in-practice looks like in the computing classroom.

The workshops will draw on the experiences of everyone who is participating, and they’ll provide a forum for innovative ideas and new opportunities for collaboration to emerge.

You’re also invited to join us on the evening of 31 March for an informal networking event over food and drink at the Raspberry Pi Foundation office — a great chance to meet, mingle, and make connections ahead of the symposium day.

Register for the symposium to secure your place at these events! We look forward to meeting you there.

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‘Gender Balance in Computing’ research project launch

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/gender-balance-in-computing-research-project-launch/

I am excited to reveal that a consortium of partners has been awarded £2.4 million for a new research project to investigate how to engage more girls in computing, as part of our work with the National Centre for Computing Education. The award comes at a crucial time in computing education, after research by the University of Roehampton and the Royal Society recently found that only 20% of computing candidates for GCSE and 10% for A level Computer Science were girls.

The project will investigate ways to make computing more inclusive.

The project

‘Gender Balance in Computing’ is a collaboration between the consortium of the Raspberry Pi Foundation, STEM Learning, BCS, The Chartered Institute for IT, and the Behavioural Insights Team. Our partners, Apps for Good and WISE, will also be working on the project. Trials will run from 2019–2022 in Key Stages 1–4, and more than 15,000 students and 550 schools will be involved. It will be the largest national research effort to tackle this issue to date!

Our research around gender balance has many synergies with the work of the wider National Centre for Computing Education (NCCE) programme, which also focuses on pedagogy and widening participation. We will also be working with NCCE Computing Hubs when planning and implementing the trials.

How it will work

‘Gender Balance in Computing’ will develop and roll out several projects that aim to increase the number of girls choosing to study a computing subject at GCSE and A level. The consortium has already identified some of the possible reasons why a large percentage of girls don’t consider computing as the right choice for further study and potential careers. These include: feeling that they don’t belong in the subject; not being sufficiently encouraged; and feeling that computing is not relevant to them. We will go on to research and pilot a series of new interventions, with each focusing on addressing a different barrier to girls’ participation.

We will also trial initiatives such as more inclusive pedagogical approaches to teaching computing to facilitate self-efficacy, and relating informal learning opportunities, which are often popular with girls, to computing as an academic subject or career choice.

Signposting the links between informal and formal learning is one of the interventions that will be trialled.

Introducing our partners

WISE works to increase the participation, contribution, and success of women in the UK’s scientific, technology, and engineering (STEM) workforce. Since 1984, they have supported young women into careers in STEM, and are committed to raising aspirations and awareness for girls in school to help them achieve their full potential. In the past three years, their programmes have inspired more than 13,500 girls.

The Behavioural Insights Team have worked with governments, local authorities, businesses and charities to tackle major policy problems. They generate and apply behavioural insights to inform policy and improve public services.

Apps for Good has impacted more than 130,000 young people in 1500 schools and colleges across the UK since their foundation in 2010. They are committed to improving diversity within the tech sector, engaging schools within deprived and challenging contexts, and enthusing girls to pursue a pathway in computing; in 2018, 56% of students participating in an Apps for Good programme were female.

“A young person’s location, background, or gender should never be a barrier to their future success. Apps for Good empowers young people to change their world through technology, and we have a strong track record of engaging girls in computing. We are excited to be a part of this important work to create, test, and scale solutions to inspire more girls to pursue technology in education. We look forward to helping to build a more diverse talent pool of future tech creators.” Sophie Ball & Natalie Moore, Co-Managing Directors, Apps for Good

The Raspberry Pi Foundation has a strong track record for inclusion through our informal learning programmes: out of the 375,000 children who attended a Code Club or a CoderDojo in 2018, 140,000 (37%) were girls. This disparity between the gender balance in informal learning and the imbalance in formal learning is one of the things our new research project will be investigating.

The challenge of encouraging more girls to take up computing has long been a concern, and overcoming it will be critical to ensuring that the nation’s workforce is suitably skilled to work in an increasingly digital world. I’m therefore very proud to be working with this group of excellent organisations on this important research project (and on such a scale!). Together, we have the opportunity to rigorously trial a range of evidence-informed initiatives to improve the gender balance in computing in primary and secondary schools.

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What we are learning about learning

Post Syndicated from Oliver Quinlan original https://www.raspberrypi.org/blog/what-we-are-learning-about-learning/

Across Code Clubs, CoderDojos, Raspberry Jams, and all our other education programmes, we’re working with hundreds of thousands of young people. They are all making different projects and learning different things while they are making. The research team at the Raspberry Pi Foundation does lots of work to help us understand what exactly these young people learn, and how the adults and peers who mentor them share their skills with them.

Coolest Projects International 2018

Senior Research Manager Oliver Quinlan chats to participants at Coolest Projects 2018

We do our research work by:

  • Visiting clubs, Dojos, and events, seeing how they run, and talking to the adults and young people involved
  • Running surveys to get feedback on how people are helping young people learn
  • Testing new approaches and resources with groups of clubs and Dojos to try different ways which might help to engage more young people or help them learn more effectively

Over the last few months, we’ve been running lots of research projects and gained some fascinating insights into how young people are engaging with digital making. As well as using these findings to shape our education work, we also publish what we find, for free, over on our research page.

How do children tackle digital making projects?

We found that making ambitious digital projects is a careful balance between ideas, technology, and skills. Using this new understanding, we will help children and the adults that support them plan a process for exploring open-ended projects.

Coolest Projects USA 2018

Coolest Projects USA 2018

For this piece of research, we interviewed children and young people at last year’s Coolest Projects International and Coolest Projects UK , asking questions about the kinds of projects they made and how they created them. We found that the challenge they face is finding a balance between three things: the ideas and problems they want to address, the technologies they have access to, and their skills. Different children approached their projects in different ways, some starting with the technology they had access to, others starting with an idea or with a problem they wanted to solve.

Achieving big ambitions with the technology you have to hand while also learning the skills you need can be tricky. We’re planning to develop more resources to help young people with this.

Coolest Projects International 2018

Research Assistant Lucia Florianova learns about Rebel Girls at Coolest Projects International 2018

We also found out a lot about the power of seeing other children’s projects, what children learn, and the confidence they develop in presenting their projects at these events. Alongside our analysis, we’ve put together some case studies of the teams we interviewed, so people can read in-depth about their projects and the stories of how they created them.

Who comes to Code Club?

In another research project, we found that Code Clubs in schools are often diverse and cater well for the communities the schools serve; Code Club is not an exclusive club, but something for everyone.

Code Club Athens

Code Clubs are run by volunteers in all sorts of schools, libraries, and other venues across the world; we know a lot about the spaces the clubs take place in and the volunteers who run them, but less about the children who choose to take part. We’ve started to explore this through structured visits to clubs in a sample of schools across the West Midlands in England, interviewing teachers about the groups of children in their club. We knew Code Clubs were reaching schools that cater for a whole range of communities, and the evidence of this project suggests that the children who attend the Code Club in those schools come from a range of backgrounds themselves.

Scouts Raspberry Pi

Photo c/o Dave Bird — thanks, Dave!

We found that in these primary schools, children were motivated to join Code Club more because the club is fun rather than because the children see themselves as people who are programmers. This is partly because adults set up Code Clubs with an emphasis on fun: although children are learning, they are not perceiving Code Club as an academic activity linked with school work. Our project also showed us how Code Clubs fit in with the other after-school clubs in schools, and that children often choose Code Club as part of a menu of after-school clubs.

Raspberry Jam

Visitors to Pi Towers Raspberry Jam get hands-on with coding

In the last few months we’ve also published insights into how Raspberry Pi Certified Educators are using their training in schools, and into how schools are using Raspberry Pi computers. You can find our reports on all of these topics over at our research page.

Thanks to all the volunteers, educators, and young people who are finding time to help us with their research. If you’re involved in any of our education programmes and want to take part in a research project, or if you are doing your own research into computing education and want to start a conversation, then reach out to us via [email protected].

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Security and Human Behavior (SHB 2018)

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/05/security_and_hu_7.html

I’m at Carnegie Mellon University, at the eleventh Workshop on Security and Human Behavior.

SHB is a small invitational gathering of people studying various aspects of the human side of security, organized each year by Alessandro Acquisti, Ross Anderson, and myself. The 50 or so people in the room include psychologists, economists, computer security researchers, sociologists, political scientists, neuroscientists, designers, lawyers, philosophers, anthropologists, business school professors, and a smattering of others. It’s not just an interdisciplinary event; most of the people here are individually interdisciplinary.

The goal is to maximize discussion and interaction. We do that by putting everyone on panels, and limiting talks to 7-10 minutes. The rest of the time is left to open discussion. Four hour-and-a-half panels per day over two days equals eight panels; six people per panel means that 48 people get to speak. We also have lunches, dinners, and receptions — all designed so people from different disciplines talk to each other.

I invariably find this to be the most intellectually stimulating conference of my year. It influences my thinking in many different, and sometimes surprising, ways.

This year’s program is here. This page lists the participants and includes links to some of their work. As he does every year, Ross Anderson is liveblogging the talks. (Ross also maintains a good webpage of psychology and security resources.)

Here are my posts on the first, second, third, fourth, fifth, sixth, seventh, eighth, ninth, and tenth SHB workshops. Follow those links to find summaries, papers, and occasionally audio recordings of the various workshops.

Next year, I’ll be hosting the event at Harvard.

Detecting Lies through Mouse Movements

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/05/detecting_lies_.html

Interesting research: “The detection of faked identity using unexpected questions and mouse dynamics,” by Merulin Monaro, Luciano Gamberini, and Guiseppe Sartori.

Abstract: The detection of faked identities is a major problem in security. Current memory-detection techniques cannot be used as they require prior knowledge of the respondent’s true identity. Here, we report a novel technique for detecting faked identities based on the use of unexpected questions that may be used to check the respondent identity without any prior autobiographical information. While truth-tellers respond automatically to unexpected questions, liars have to “build” and verify their responses. This lack of automaticity is reflected in the mouse movements used to record the responses as well as in the number of errors. Responses to unexpected questions are compared to responses to expected and control questions (i.e., questions to which a liar also must respond truthfully). Parameters that encode mouse movement were analyzed using machine learning classifiers and the results indicate that the mouse trajectories and errors on unexpected questions efficiently distinguish liars from truth-tellers. Furthermore, we showed that liars may be identified also when they are responding truthfully. Unexpected questions combined with the analysis of mouse movement may efficiently spot participants with faked identities without the need for any prior information on the examinee.

Boing Boing post.

Another Spectre-Like CPU Vulnerability

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/05/another_spectre.html

Google and Microsoft researchers have disclosed another Spectre-like CPU side-channel vulnerability, called “Speculative Store Bypass.” Like the others, the fix will slow the CPU down.

The German tech site Heise reports that more are coming.

I’m not surprised. Writing about Spectre and Meltdown in January, I predicted that we’ll be seeing a lot more of these sorts of vulnerabilities.

Spectre and Meltdown are pretty catastrophic vulnerabilities, but they only affect the confidentiality of data. Now that they — and the research into the Intel ME vulnerability — have shown researchers where to look, more is coming — and what they’ll find will be worse than either Spectre or Meltdown.

I still predict that we’ll be seeing lots more of these in the coming months and years, as we learn more about this class of vulnerabilities.