We are committed to make computing and creating with digital technologies accessible to all young people, including through our work with educators and researchers. In our current online research seminar series, we focus on computing education for primary-aged children (K–5, ages 5 to 11). In the series’ second seminar, we were delighted to welcome Dr Jean Salac, researcher in the Code & Cognition Lab at the University of Washington.

Jean’s work sits across computing education and human-computer interaction, with an emphasis on justice-focused computing for youth. She talked to the seminar attendees about her work on developing strategies to support primary school students learning to program in Scratch. Specifically, Jean described an approach called TIPP&SEE and how teachers can use it to guide their learners through programming activities.

What is TIPP&SEE?

TIPP&SEE is a metacognitive approach for programming in Scratch. The purpose of metacognitive strategies is to help students become more aware of their own learning processes.

TIPP&SEE scaffolds students as they learn from example Scratch projects: TIPP (Title, Instructions, Purpose, Play) is a scaffold to read and run a Scratch project, while SEE (Sprites, Events, Explore) is a scaffold to examine projects more deeply and begin to adapt them. 

Using, modifying and creating

TIPP&SEE is inspired by the work of Irene Lee and colleagues who proposed a progressive three-stage approach called Use-Modify-Create. Following that approach, learners move from reading pre-existing programs (“not mine”) to adapting and creating their own programs (“mine”) and gradually increase ownership of their learning.

Proponents of scaffolded approaches like Use-Modify-Create argue that engaging learners in cycles of using existing programs (e.g. worked examples) before they move to adapting and creating new programs encourages ownership and agency in learning. TIPP&SEE builds on this model by providing additional scaffolding measures to support learners.

Impact of TIPP&SEE

Jean presented some promising results from her research on the use of TIPP&SEE in classrooms. In one study, fourth-grade learners (age 9 to 10) were randomly assigned to one of two groups: (i) Use-Modify-Create only (the control group) or (ii) Use-Modify-Create with TIPP&SEE. Jean found that, compared to learners in the control group, learners in the TIPP&SEE group:

• Were more thorough, and completed more tasks
• Wrote longer scripts during open-ended tasks
• Used more learned blocks during open-ended tasks

In another study, Jean compared how learners in the TIPP&SEE and control groups performed on several cognitive tests. She found that, in the TIPP&SEE group, students with learning difficulties performed as well as students without learning difficulties. In other words, in the TIPP&SEE group the performance gap was much narrower than in the control group. In our seminar, Jean argued that this indicates the TIPP&SEE scaffolding provides much-needed support to diverse groups of students.

Using TIPP&SEE in the classroom

TIPP&SEE is a multi-step strategy where learners start by looking at the surface elements of a program, and then move on to examining the underlying code. In the TIPP phase, learners first read the title and instructions of a Scratch project, identify its purpose, and then play the project to see what it does.

In the second phase, SEE, learners look inside the Scratch project to click on sprites and predict what each script is doing. They then make changes to the Scratch code and see how the project’s output changes. By changing parameters, learners can observe which part of the output changes as a result and then reason how each block functions. This practice is called deliberate tinkering because it encourages learners to observe changes while executing programs multiple times with different parameters.

You can read more of Jean’s research on TIPP&SEE on her website. There’s also a video on how TIPP&SEE can be used, and free lesson resources based on TIPP&SEE are available in Elementary Computing for ALL and Scratch Encore.

Learning about learning in computing education

Jean’s talk highlighted the need for computing to be inclusive and to give equitable access to all learners. The field of computing education is still in its infancy, though our understanding of how young people learn about computing is growing. We ourselves work to deepen our understanding of how young people learn through computing and digital making experiences.

In our own research, we have been investigating similar teaching approaches for programming, including the use of the PRIMM approach in the UK, so we were very interested to learn about different approaches and country contexts. We are grateful to Dr Jean Salac for sharing her work with researchers and teachers alike. Watch the recording of Jean’s seminar to hear more:

Free support for teaching programming and more to primary school learners

If you are looking for more free resources to help you structure your computing lessons:

• Download our comprehensive classroom resources in The Computing Curriculum, which includes units of programming lessons for age 5 and upwards.
• Take one of our online courses about teaching computing. The course Teaching programming to 5- to 11-year-olds is especially relevant to this seminar.
• Read The Big Book of Computing Pedagogy, a special edition of our Hello World magazine.

Join our next seminar

In the next seminar of our online series on primary computing, I will be presenting my research on integrated computing and literacy activities. Sign up now to join us for this session on Tues 7 March:

As always, the seminars will take place online on the first Tuesday of the month at 17:00–18:30 UK time. Hope to see you there!

The post Supporting beginner programmers in primary school using TIPP-SEE appeared first on Raspberry Pi Foundation.

Conrad has been an influential figure in the areas of AI, data science, and computation for over 30 years. The company he co-founded, Wolfram Research, develops computational technologies including the Wolfram programming language, which is used by the Mathematica and WolframAlpha programs. In the seminar, Conrad spoke about his work on developing a mathematics curriculum “for the AI age”.

Computation is everywhere

In his talk, Conrad began by talking about the ubiquity of computation. He explained how computation (i.e. an operation that follows conditions to give a defined output) has transformed our everyday lives and led to the development of entire new sub-disciplines, such as computational medicine, computational marketing, and even computational agriculture. He then used the WolframAlpha tool to give several practical examples of applying high-level computation to problem-solving in different areas.

The power of computation for mathematics

Conrad then turned his attention to the main question of his talk: if computation has also changed real-world mathematics, how should school-based mathematics teaching respond? He suggested that, as computation has impacted all aspects of our daily lives, school subjects should be reformed to better prepare students for the careers of the future.

His biggest criticism was the use of hand calculation methods in mathematics teaching. He proposed that a mathematics curriculum that “assumes computers exist” and uses computers (rather than humans) to compute answers would better support students to develop a deep understanding of mathematical concepts and principles. In other words, if students spent less time doing hand-calculation methods, they could devote more time to more complex problems.

What does computational problem-solving look like?

One interesting aspect of Conrad’s talk was how he modelled the process of solving problems using computation. In all of the example problems, he outlined that computational problem-solving follows the same four-step process:

1. Define the question: Students think about the scope and details of the problem and define answerable questions to tackle.
2. Abstract to computable form: Using the information provided, students translate the question into a precise abstract form, such as a diagram or algorithm, so that it can be solved by a computer-based agent.
3. Computer answers: Using the power of computation, students solve the abstract question and resolve any issues during the computation process.
4. Interpret results: Students reinterpret and recontextualise the abstract answer to derive useful results. If problems emerge, students refine or fix their work.

Depending on the problem, the process can be repeated multiple times until the desired solution is reached. Rather than being proposed as a static list of outcomes, the process was presented by Conrad as an iterative cycle than resembles an “ascending helix”:

A curriculum for a world with AI

In the later stages of his talk, Conrad talked about the development of a new computational curriculum to better define what a modern mathematics curriculum might look like. The platform that hosts the curriculum, named Computer-Based Math (or CBM), outlines the need to integrate computational thinking into mathematics in schools. For instance, one of the modules, How Fast Could I Cycle Stage 7 Of The An Post Rás?, asks students to develop a computational solution to a real-world problem. Following the four-step problem-solving process, students apply mathematical models, computational tools, and real-world data to generate a valid solution:

Some future challenges he remarked on included how a computer-based mathematics curriculum could be integrated with existing curricula or qualifications, at what ages computational mathematics should be taught, and what assessment, training, and hardware would be needed to support teachers to deliver such a curriculum. 

Conrad concluded the talk by arguing that the current need for computational literacy is similar to the need for mass literacy and pondering whether the UK could lead the push towards a new computational curriculum suitable for learners who grow up with AI technologies. This point provided food for thought during our discussion section, especially for teachers interested in embedding computation into their lessons, and for researchers thinking about the impact of AI in different fields. We’re grateful to Conrad for speaking about his work and mission — long may it continue!

You can catch up on Conrad’s talk with his slides and the talk’s recording:

More to explore

Conrad’s book, The Math(s) Fix: An Education Blueprint for the AI Age, gives more details on how he thinks data science, AI, and computation could be embedded into the modern maths curriculum.

You can also explore Wolfram Research’s Computer-Based Maths curriculum, which offers learning materials to help teachers embed computation in their maths lessons. 

Finally, try out Wolfram’s tools to solve everyday problems using computation. For example, you might ask WolframAlpha data-rich questions, which the tool converts from text input into a computable problem using natural language processing. (Two of my favourite example questions are: “How old was Leonardo when the Mona Lisa was painted?” and “What was the weather like when I was born?”)

Join our next seminar

In the final seminar of our series on cross-curricular computing, we welcome Dr Tracy Gardner and Rebecca Franks (Raspberry Pi Foundation) to present their ongoing work on computing education in non-formal settings. Sign up now to join us for this session on Tues 8 November:

We will shortly be announcing the theme of a brand-new series of research seminars starting in January 2023. The seminars will take place online on the first Tuesday of the month at 17:00–18:30 UK time.

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