## Key Ideas > [!abstract] Core concepts > > - **Elements must interact for comprehension**: Learning difficulty depends on how many elements must be considered simultaneously and their interdependence > - **Expertise determines complexity**: Same task has different element interactivity for novices vs experts due to chunking differences > - **Careful progression essential**: Gradually increase interacting elements to prevent cognitive overload whilst building understanding ## Definition Cognitive Load Theory suggests that for learning to occur, elements of new information must be considered and related in working memory, then incorporated into long-term memory (Sweller, van Merriënboer, & Paas, 2019). An **element** is anything that needs to be processed, and **interactivity** refers to how reliant one element is on other elements for comprehension (Sweller, 2010). Element interactivity describes the degree to which elements of information must be processed simultaneously in working memory. ## Connected to [[Problem-Solving]] | [[Cognitive Load Theory]] | [[Prior Knowledge]] | [[Chunking]] | [[Part-whole approach]] | [[Fluency]] | [[Worked Examples]] --- ## Types of element interactivity Element interactivity exists on a continuum (Sweller, 2010). Tasks with low element interactivity involve elements that are independent of each other (learning one does not require understanding another). Memorising chemical element symbols exemplifies low interactivity; knowing helium's symbol does not depend on knowing hydrogen's symbol. Each element can be learnt in isolation without cognitive penalty. Elements can be processed sequentially without confusion, working memory load remains manageable, and learning can proceed element by element at any pace. Tasks with high element interactivity involve elements that are interrelated and rely on one another for comprehension (understanding requires simultaneous processing). [[Prior Knowledge|Solving linear equations]] requires simultaneous consideration of equality symbol meaning, inverse operations, algebraic notation, order of operations, and arithmetic fluency. Elements must be processed simultaneously in working memory, creating high working memory demand even for simple-appearing tasks. Cognitive overload is likely for novices without chunked knowledge. High element interactivity explains why some topics remain consistently difficult regardless of teaching quality (Sweller, 2010; Pollock, Chandler, & Sweller, 2002). ## Expertise impact The degree of element interactivity depends on the learner's expertise (Sweller, 2010). Numerous elements for a novice may be only one or a few elements for an expert who has [[Chunking|chunked]] these disparate elements (Miller, 1956; Cowan, 2001; Chase & Simon, 1973). When solving 4x + 3 = 15, a novice must consider equality, algebra, inverse operations, and arithmetic separately, creating high intrinsic load. An expert sees "linear equation" as a single procedural unit, creating low intrinsic load. The same task has different element interactivity depending on the learner's prior knowledge and chunking ability. ## Teaching implications When element interactivity is high, teachers should limit how many elements change between problems (Paas & van Merriënboer, 1994). After showing a worked example of calculating trapezium area, teachers should provide a near-identical question. Teachers should avoid immediate progression to similar problems with different units, as this overloads students (Sweller, 2010). Breaking down concepts reduces element interactivity initially before gradually increasing it (Pollock, Chandler, & Sweller, 2002; Catrambone, 1998). For equations, teachers should teach one-step equations with addition and subtraction first, then practise until [[Fluency|fluent]] (Ericsson & Kintsch, 1995). Next, teach one-step equations with multiplication and division, again practising until fluent. Finally, mix both types to increase interactivity. Teachers should monitor cognitive load and watch for signs of overload when element interactivity increases (Sweller, 2010). Students need more time when element interactivity is high. [[Worked Examples]] (Sweller & Cooper, 1985) and the [[Part-whole approach]] (Pollock, Chandler, & Sweller, 2002) provide scaffolding to manage complexity. ## Key warnings and pitfalls Teachers should avoid increasing multiple interacting elements simultaneously (Paas & van Merriënboer, 1994). Prerequisite elements must be chunked before adding complexity (Cooper & Sweller, 1987). High element interactivity tasks require more instructional time (Sweller, 2010). Expert teachers may underestimate element interactivity for novices (Hinds, 1999). ## Practical examples Quadratic equations involve factorisation patterns, perfect squares, inverse operations, algebraic manipulation, and arithmetic. Students must chunk these components before integration. Essay writing combines paragraph structure, evidence selection, analysis skills, grammar, and vocabulary. Teachers should teach these separately before integration. Reading comprehension requires phonics fluency, vocabulary knowledge, background knowledge, and inference skills. Students should automate decoding before attempting complex comprehension tasks. ## References Catrambone, R. (1998). 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