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Showing posts from 2023

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 Mic...

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 ...

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 gi...

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 ...