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Automatic Marking and Grading

While teaching is wonderful, worthwhile and rewarding it is a highly demanding and stressful profession.  So it is little surprise that there is  high rate of staff turnover with nearly o ne in 10 teachers are leaving the teaching profession in English schools each year citing burnout, overwork and stress as the principal reasons (Department for Education). To improve teacher retention a better work life balance is needed. In fact, reducing high workload was one of the motivations for the industrial action of 2023 by the NEU.  One area where large improvements can be made in work-life balance is the marking of student work. Teachers spend 9 hours per week marking student work (EEF, 2016) and if any reductions can be achieved in this area then we can go a long way to improving working conditions for teachers.  Some efforts have been made to automate grading using for instance self-marking online multiple-choice tools like  www.diagnosticquestions.com  or Micorsoft Forms that allows keyw
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Mango Learning

We are a community of teachers that have developed extensive computing resources primarily aimed at the English secondary school curriculum that can be accessed here: www.mangolearning.academy .  Mango learning empowers teachers to deliver great lessons that explain complex ideas using clear and highly scaffolded teaching and learning resources. We are very excited to offer these resources for free to the community. These teaching and learning resources for computing are made by teachers for teachers and we understand the day-to-day challenges that teacher face.   The resources incorporate general and computing specific evidence-based pedagogy. We incorporated spaced retrieval practice though knowledge organisers, diagnostic questions and quizzes, for instance. We also incorporate ideas from cognitive load theory through lots of worked examples.   To help with coding we use PRIMM and block to text based pedagogical approaches.   To support literacy we address vocabulary head on, enco

Semantic Waves

In the previous post we looked at the transfer of learning from block based coding to text based languages.  Semantic waves offer a theory that help us to structure our lessons to support transfer of learning (Maton, Waite et al).  When we present concrete examples in single contexts transfer of learning is going to be weak.  We need to present multiple examples in a range of context.  This allows us to abstract out the underlaying features.  This idea of moving along a continuum between the abstract and concrete is given by the term semantic gravity.  For instance, if we talk about an algorithm in abstract terms we might say that it is a sequence of steps to solve a problem.  At this stage we have presented it as an abstract idea so has low semantic garvity.  In a lesson we might then go on and write algorithms for drawing squares.  This represents a concrete episode with high semantic gravity.  In a good lesson we might also want to give multiple examples of algorithm in different co

Block to Text Programming

When we move students on from block to text programming, we want to transfer the learning that they have made on block coding into text programming.   When we are transferring learning we want to transfer knowledge from one context into another. In moving from one context to another we need to think in an analogical manner such that when we know how to solve a problem in one domain we can use it to help us solve a problem in another domain. The use of analogous examples helps learners see the deeper structure. We do this by seeking out deep structures and remove the surface structure of a problem. This approach is called expansive framing and we have expectation of future use in a different context. In contrast, bounded framing does not have utility beyond the current learning. Current learning needs to make connections to earlier contexts from which learners are expected to transfer in knowledge to the new context. Transfer of learning does not happen by itself; the teacher needs to

Computational Thinking as Metacognition

Metacognition and computational thinking   Children do not easily see connections between the school subjects that they learn. Nearly everything can been viewed from an interdisciplinary perspective but in secondary schools knowledge is organised and delivered and partitioned into the subjects that we are familiar with: “Maths teachers teach maths, English teachers teach English, science teachers teach science and never the twain shall meet 1 . When complex knowledge and understanding is partitioned neatly into silos like this, it is little wonder that children cannot relate learning from one subject to another. Of course, knowledge and understanding are highly interrelated and getting children to see these complex connections will enrich their learning experience. Metacognitive strategies that can be applied across the curriculum can help to break some of these artificial barriers that children see between subjects. Metacognition is concerned with “learning about learning”. Equi

How to support your students to write code

For many children writing code can be a daunting prospect. To help children learn to write code more easily we can use a range of scaffolded pedagogies. Initially these approaches take ownership of the code away from the students thereby giving them confidence to explore and experiment with the code.   Gradually as the students learn more and more we can reduce the amount of support until they are able to write their own programs independently.   In a previous article we looked at approaches for supporting pupils to learn to read code that included activities such as explaining, predicting and tracing code, and live demonstrations with worked examples. This follow up article presents some approaches to support pupils with writing code. Fixing broken code Children can find and fix common syntax, runtime and logical errors in a piece of code. Errors might include missing brackets, missing speech marks, spelling mistakes and missing variables declarations, for instance. The pupils

Teaching Children to Read Code using Evidence-based Approaches

Before students can write code, they need to be able to read code. Computer science pedagogy is often based around the ideas of Piaget’s constructivism - where pupils develop their knowledge through exploration, and Papert’s constructionism - where pupils learn through creating artifacts. However, evidence has shown that learners need guidance to gain useful knowledge efficiently and to organise that knowledge in a clear and logical way. They need to be able to break a problem down, remove the unnecessary detail, find patterns and think algorithmically before they can start to write programs for solving problems. Just as we wouldn’t expect a young child to write prose before they can read, we need to provide guided approaches that use direct instruction and scaffolding to help our students read code before they can be expected to write code themselves. These guided approaches are needed just as much as, if not more than, creative discovery activities. Explain the code My first approach