![]() ![]() When sequencing learning we need to judiciously select the knowledge most likely to support and connect to new learning so that we do not unintentionally hinder students’ understanding. Whilst careful sequencing can support new learning by exposing its relationship to prior knowledge, we need to ensure its activation does not contribute to extraneous load. If, however, the teacher opened the lesson with a retrieval task that prompted students to recall the definitions of ‘empire,’ ‘monarchy’ and ‘reign’ and framed these within the context of the lesson – making explicit the connection between Queen Victoria and the British Empire’s role in widespread colonisation – then cognitive load is well-managed and the activation of prior knowledge is purposeful for the lesson, resulting in the delivery being far more cohesive and ensuring one idea connects to and informs the next. In this example, prior knowledge functions as extraneous load: students are left grappling with their working definitions of key terms and their recognition of Queen Victoria, alongside a plethora of completely new information, made more complicated by attempting to draw from their prior knowledge, as prompted by the teacher, with very little context. The teacher then provides an explanation of imperialism, with a brief allusion to their previous teaching of Russia the year before, polished off with the image of Queen Victoria’s statue that displays the words ‘The entitlement of Great Britain’ underneath. Students need to access a working definition of ‘empire’, relying on their understanding of vocabulary such as ‘monarchy’ and ‘reign’. Take, for example, a history teacher introducing the concept of colonialism through a study of the British Empire. ![]() Although activating prior knowledge is an effective method for reducing cognitive load, this needs always to serve new learning. This assists in reducing cognitive load as students can draw more effectively from their long-term memory, thereby reducing the load for their working memory. ![]() To create a sense of coherence for the discipline that we teach, we need to ask ourselves: Why this? Why now? Cognitive load theoryĬognitive load theory informs our curriculum sequencing by revealing the role of memory in helping students build the cognitive architecture required to access the curriculum effectively.Īs working memory is limited, we need to sequence our curriculum to reduce cognitive load by drawing on prior knowledge and logically sequencing episodes of learning so they accumulate in small stages, securing understanding at one stage before moving on to the next. The curriculum in many subjects is dependent on a deliberate approach to the sequencing of knowledge because one concept often relies on the understanding of what has come previously and what will come next.Įffective sequencing can also provide a way of embellishing and unifying what may otherwise seem like disconnected fragments of knowledge. We conclude with a new tentative model that takes into account these three dimensions and also point to several promising new lines of SL research.If a curriculum is to be coherent and follow a logical progression, attention needs to be paid to the order in which knowledge, in whatever form that might take, should be introduced and revisited. The review is articulated around three descriptive dimensions in relation to SL: the level of abstractness of the representations learned through SL, the effect of the level of attention and consciousness on SL, and the developmental trajectory of SL across the life-span. The purpose of this review is: (1) to provide a general overview of the primary models and theories of SL, (2) to describe the empirical research – with a focus on the event- related potential (ERP) literature – in support of these models while also highlighting the current limitations of this research, and (3) to present a set of new lines of ERP research to overcome these limitations. The underlying neurocognitive mechanisms of SL and the associated cognitive representations are still not well understood as reflected by the heterogeneity of the reviewed cognitive models. Statistical-sequential learning (SL) is the ability to process patterns of environmental stimuli, such as spoken language, music, or one’s motor actions, that unfold in time. ![]()
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