Rosenshine suggests that a success rate of around 70% is too low. In the only issue he raises with Rosenshine’s principles, Sherrington suggests that we shouldn’t worry too much about the precision here; we might find that a lower success rate is in fact optimum.

Rosenshine uses the term ‘schema’ to denote a well-connected network of ideas (Rosenshine, p. 19). Schemata play an important role in his principles, relating to the cognitive science of learning, particularly theories about the ways information gets stored in long-term memory. Nevertheless, the pamphlet is highly accessible for teachers and the principles are no doubt relatable for most teachers (I’m not sure they are necessarily common sense, as Sherrington suggests). It provides a succinct list of evidence-based core skills, and is a really useful document for CPD. Review the experience of practising using the ideas that were discussed, exploring successes, refinements, next steps.The process of a student gradually gaining independence through modelling and scaffolding as their mastery over a skill or task increases is sometimes called ‘cognitive apprenticeship’. This is the process where a ‘master’ of a skill – i.e., someone who has achieved a level of mastery – teaches that skill to a student (‘apprentice’). The master also supports the apprentice as they become independent at proficiently completing the task or engaging in the skill in question (Rosenshine, p. 18). Thanks for framing your response – even though I’ve followed your blog for a while and have a fair idea of your views on certain topics it’s still useful to work out where you’re coming from! The cognitive load involved in a task is the cognitive effort (or amount of information processing) required by a person to perform this task. If the cognitive load needed for learning becomes excessive, little or no learning can occur’. [1]

Rosenshine writes that more effective teachers incorporate modelling and scaffolding into the process of offering explanations. By so doing, Rosenshine suggests that master teachers provide well-structured support for students as they build their schemata for new concepts (Sherrington, p. 15). ‘Schemata’ The more complex and interconnected our schemata are, the easier it is to make sense of and organise new information which relates to our existing schemata. Objective: to engage all students in teacher-student dialogue with time to think, preventing students from being overlooked, dominating, or hiding from involvement in dialogue. Re: ‘explicit to implicit’ and the connection between the two (if any)… while this may be equally refutable, I feel more aligned with Ullman’s research on this one – these are distinct memory systems that play different roles (I’m referring to declarative v procedural knowledge there). Yes, my views do tend to flit around, but the idea that declarative knowledge leads to procedural knowledge has always seemed a bit convenient/simplistic in all honesty. It has been a long while since I formally studied this area though so my current views are a tad bitty. We forget information that we don’t initially store successfully in a meaningful schema or we don’t retrieve frequently enough.

Mathematical problem solving is … improved when the basic skills (addition, multiplication, etc.) are overlearned and become automatic, thus freeing working-memory capacity. (p. 13) Rosenshine writes that less effective teachers asked fewer questions and almost no ‘process questions’ – questions about the process of learning, such as how students worked something out (contrast, for example, with factual questions) ( ibid.). Rosenshine’s ‘Principles’ provides a highly accessible bridge between educational research and classroom practice. The principles are research-based, extensively drawing upon research in education and cognitive science. Rosenshine expresses the principles succinctly and offers suggestions for the implementation of the principles in the classroom. He provides many examples of activities employed in the teaching practices of ‘master teachers’ – i.e., teachers whose students made the highest gains in achievement tests (p. 12).

Was at your Research Ed presentation on Saturday about this – compelling stuff and I was particularly intrigued by your description of teaching about magnets and magnetism – fascinating phenomenon. And if we take Brian Arthur’s view that technology can be seen as the exploitation of phenomenon that have been revealed, explored and explained by science this provides an interesting opportunity for science d&t collaboration. Students explore the phenomenon in science lessons; take the results of their exploration into their d&t lessons where they are challenged with, “Well, how can you exploit the phenomenon of magnetism?” Some of the explorations might be on paper only, some might develop small-scale models and some might develop working prototypes. I think it is likely that such exploitations would lead to a significantly enhanced understanding of magnetism as well as providing the opportunity for some open ended D&T.Rosenshine suggests that more effective teachers are ‘able to narrate the decisions and choices they make’ – for example, where to begin with a maths problem or how to start an essay. Sherrington writes that thinking aloud by the teacher is important for developing students’ ‘capacity for metacognition and self-regulation by modelling their own thought processes’ (Sherrington, p. 20). Here we see an example of Rosenshine’s use of research in cognitive science to support the importance of a principle: one of the reasons it’s important to learn something to the level where it becomes automatic is that the absence of effort required to recall what we’ve learned frees up space in our working memory, which we can then devote to other tasks – e.g., learning something new. In the classroom Get a response from all students in the class to a question, problem or task – e.g., multiple-choice questions, diagrams or calculations. This can be done verbally or through a written task.

Automaticity requires ‘overlearning’: learning beyond the point of ‘initial mastery’, such that recall is automatic and skills are fluent (p. 13). ‘When material is overlearned’, Rosenshine writes, ‘it can be recalled automatically and doesn’t take up any space in working memory’ (p. 18). Rosenshine gives the name ‘more effective teachers’ to those teachers whose classrooms made the highest gains in standardised achievement tests (Rosenshine, p. 12). He also refers to more effective teachers as ‘master teachers’. The teaching practices of more effective teachers constitute one of the sources of evidence Rosenshine uses to support his principles. Barak Rosenshine’s ‘Principles of Instruction’ has become increasingly influential in educational research and practice since its publication a decade ago. [1] Rosenshine (1930-2017) was formerly a professor of educational psychology in the College of Education at the University of Illinois. His research focused on learning instruction, teacher performance and student achievement. Much of his research focused on the distinctive features of effective teaching. His research has made a significant contribution to knowledge of the effectiveness of certain methods of ‘instruction’, which is typically defined as ‘the purposeful direction of the learning process’. [2] His principles of instruction are the culmination of his research into the effectiveness of methods of instruction. Model the techniques: get volunteers to show how the principles are enacted in lessons, bringing them alive, inviting questions and challenges, exploring potential obstacles.In the second stage, Rosenshine offers advice on how the principle can be employed in the classroom. Rosenshine’s guidance is supported by observations of the teaching practices of master teachers. He often provides several suggestions for classroom activities related to the principle under discussion.