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This presentation explores the relevance of cognitive load theory (CLT) to lifelong learning, discussing the different types of cognitive load and their implications for instructional design in the LLL field. It also highlights the importance of considering both extraneous and intrinsic load in creating optimum learning environments for learners. Additionally, it explores how CLT can inform the design of learning environments based on learners' expertise levels and the use of rapid testing techniques. The presentation also discusses the potential of CLT in explaining less understood educational phenomena and its applications to instructional animations in e-learning.
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The relevance of cognitive load theory to lifelong learningNetherlands Laboratory Lifelong Learning Open University of the Netherlands29 September 2008 Paul Ayres University of New South Wales, Sydney Australia (Visiting NeLLL, OUNL) <p.ayres@unsw.edu.au>
Structure of the presentation • Intro to human cognitive architecture and CLT • Three cognitive loads and different educational emphases • How CLT can guide theory and instructional design in the LLL field • Conclusions
CLT: Human Cognitive Architecture • Long-term memory (LTM) incorporates a massive knowledge base- organised according to schemas • LTM is viewed as the central, dominant structure of human cognition- learning is achieved when a change takes place in LTM- want to develop sophisticated automated schemas. • In contrast Working memory (WM) is very limited both in duration and capacity (especially when processing novel information) • However, when dealing with previously learned information these limitations are reduced. (prior knowledge/ expertise) • To learn we actively process information in WM • CLT is primarily concerned with the interactions between LTM and WM- if learning (processing) requirements exceed WM then learning is retarded.
CLT research emphasis • Reducing extraneous load- Avoiding • Split-attention • Redundancy etc. • Bad designs increase EL~ little learning • EL: Not just the way material is structured but also how we ask students to learn • Early research into problem solving showed it increased EL • Worked-examples very effective (Cooper & Sweller) • Less on reducing intrinsic load • Content too complex ~ little or no learning • Isolating elements (Pollock, Chandler & Sweller, 2003; Ayres, 2006)
Germane load • Little early research on promoting germane load • Variability led to better transfer (Paas & van Merriënboer, 1994) • More recently: • Greater focus- Open university NL • Renkl (self-regulation and worked examples) • Conclusion: CLT (UNSW groups in particular) has tended to emphasize the reduction of EL, assuming that GL will be created ~ reduce EL frees up more WM capacity for GL ~ But is this automatic? • Works well for novices
Other forms of educational theories • In contrast, other educational theories, particular “reform movements” tend to emphasize germane-type activities • Problem-based learning, inquiry or discovery learning, collaborative learning, complex real-life tasks, focus on higher-order knowledge (straight to the top of Bloom’s tree?) • Many of the education reform movements are poorly researched fads (Ayres and Kirschner, in creation) • Conclusion: Too much emphasis on GL with little regard to EL and IL: not the optimum learning conditions • Can work for learners with high prior knowledge
Lifelong Learning • Does LLL generally place too much emphasis on germane load? (write answers on sheet of paper and pass to the front please) How can CLT inform LLL? • Real-life authentic tasks, complex learning environments (important to LLL) creates high WM loads 1.The whole human architecture must be considered • Ignoring EL and IL does not create optimum learning environments
Prior knowledge is everything • Schemas impact on WM and reduce IL and EL • Expertise reversal effect (Kalyuga, Ayres, Chandler & Sweller, 2003) • LPKL learn best from worked examples and highly directed instruction • HPKL can learn from problem solving and less-structured environments • 2. Design learning environments according to expertise
Testing for expertise • Slava Kalyuga’s work on rapid testing particularly relevant for post-school and on-line learning • Combines performance and mental effort • How automated are the schemas? Efficiency concept (Paas and van Merriënboer) • 3. Adopt rapid testing techniques
New advances in CLT • Special issue in EPR (Paas & Ayres, forthcoming) relevant to LLL
Creativity/ Brainstorming • Sweller (EPR, forthcoming) • CLT reconceptualized according to evolutionary biology • Geary’s biological primary and secondary knowledge • Primary (speaking, listening)- little conscious mental effort • Secondary (mathematics)- great conscious effort • Sweller uses the randomness as genesis principle to argue that when faced with a novel problem-solving task humans can only use a ‘random generate and test’ strategy • Creativity is a form of random generate and test influenced by prior knowledge • Brainstorming- freely generating ideas reduces extraneous load and promotes germane load • 4. Differentiate between primary and secondary knowledge • 5. CLT can provide a theory to explain some of the less-understood educational phenomena
Animations and mirror neurons • van Gog, Paas, Marcus, Ayres & Sweller (EPR, forthcoming) • Instructional animations (dynamic representations) have great potential in an e-learning world • Often ineffective compared with equivalent static diagrams • Transient information creates high EL (Ayres & Paas, 2007) • Animations seem to be effective in learning about human movement • Recently discovered mirror neuron system a plausible explanation • Humans have evolved to observe and imitate (primary knowledge) • Can be done with little mental effort • Supporting experimental evidence (Hoffler & Leutner, 2007; Wong et al., Ayres et al., in press) • 6. Animations (without conditions to reduce transitory information) may be more suited to learning about human movement.
4C/ID, CLT & Self-regulation • The 4C/ID model uses CLT (van Merriënboer & Kirschner, 2007) • cycles (simple to complex, next task class) to build knowledge- scaffolding • Paper by van Merriënboer & Sluijsmanns (Special issue) • Combines 4C/ID, CLT & Self-regulation • Intrinsic and extraneous load are managed and germane load promoted • models of self-directed learning stress that these tasks should at least evoke the self-regulative processes of monitoring, evaluating, and planning. • self-assessment and task selection skills are developed as well as task performance • 7. Use CLT in conjunction with other models/theories such as the 4C/ID
Collaboration • Kirschner, Paas & Kirschner (EPR, forthcoming) • Essential to LLL (face-to-face as well as on on-line) • Point out that research is very mixed • Propose a CLT- WM model • Two heads can be better than one if WM resources shared • Most effective with complex tasks • With simple tasks transaction costs are relatively high • Challenge of measuring combined WM • Another example of CLT being useful in explaining/ guiding educational paradoxes 8.CLT inform research into collaboration
AGE • Age impacts on WM capacity (Van Gerven, Paas, van Merriënboer, & Schmidt, 2004; Van Gerven, Paas, & Tabbers, 2006), • However, domain-specific expertise means that there are schemas available to ‘compensate’ for this reduced capacity • Do they balance each other out? • 9. CLT can assist in research into aged education
Conclusions • Use CLT! • ALSTUBLIEFT