Research on Cognitive Load Theory and Its Design Implications for E-Learning

1. Research on Cognitive Load Theory and Its Design Implications for E-Learning Van Merriënboer, J.J.G., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning. Educational Technology, Research and Development, 53(3), 5-13. Advisor : Ming-Puu Chen Reporter : Hui-Lan Juan

2. Outline • Brief description of assumptions regarding memory systems and learning processes. • Different types of cognitive load. • Design implications for (adaptive) e-learning.

3. Cognitive Load Theory • Working memory with a very limited capacity when dealing with novel information. • Long-term memory is not to limitations. • Schemata are used to organize and store knowledge. • Schemata may become automated if they are repeatedly and successful applied.

4. Different types of cognitive load • Intrinsic cognitive load 內在認知負載 • Working memory load may be affected by the intrinsic nature of the learning tasks themselves. • It is determined by the interaction between the nature of the materials being learned and the level of expertise of the learner.

5. Different types of cognitive load (cont.) • Extraneous cognitive load外在認知負載 • It is associated with process that are not directly necessary for learning and can be altered by instructional interventions.

6. Different types of cognitive load (cont.) • Germane cognitive load 增生認真負載 • It is associated with process that are directly relevant to learning, such as schema construction and automation.

7. Contributions to the special issue • There is a shift in focus from studying written material to working on online learning tasks. • Recent studies focus on short laboratory experiments and more on real course. • Instructional methods that work well for novice learners may have no positive or even negative effects when learners acquire more expertise.

8. Dealing with high-element-interactivity materials: intrinsic cognitive load • Many e-learning applications are built around complex learning tasks, which are characterized by a large number of interacting elements. • The contribution to this special issue: • “The Impact of Sequencing and Prior Knowledge on Learning Mathematic Through Spreadsheet Applications”

9. Dealing with learners’ motivation to learn: Germane cognitive load • Increasing the variability of practice is one effective way to provoke students to generalize and discriminate cognitive schemas, which is a schema construction process associated with germane cognitive load. • Several other instructional manipulations that stimulate students’ effortful schema construction processes

10. Dealing with learners’ motivation to learn: Germane cognitive load (cont.) • The contribution to this special issue: • “A motivational perspective on the relation between mental effort and performance: optimizing learners; involvement in instructional conditions.” • “Cognitive load and learning effects of having students organize pictures and words in multimedia environments: the role of student interactivity and feedback.” • “Enabling, facilitating and inhibiting effects of animations in multimedia learning: Why reduction of cognitive load can have negative results on learning.” • “The function of annotations in the comprehension of scientific texts: cognitive load effects and the impact of verbal ability.”

11. Dealing with Expertise Development: toward adaptive e-learning • Expertise reversal effect • This suggests that a good instructional strategy for teaching problem solving starts with the presentation of worked examples and smoothly proceeds to independent problem solving if learners acquire more expertise. • The contribution to this special issue: • “Instructional design for advanced learners: establishing connections between the theoretical frameworks of cognitive load and deliberate practice.” • “Rapid dynamic assessment of expertise to improve the efficiency of adaptive e-learning.”

12. Discussion • Three new lines of CLT research • A first category of studies develops methods that help learners to deal with the high intrinsic complexity of learning tasks. • A second category of studies develops methods that encourage learners to invest effort in learning. • The third category of studies develops dynamic instructional methods to adapt instruction to learners’ individual needs.

13. Discussion (cont.) • CLT is becoming more and more useful for the design of large courses and e-learning programs that are characterized by a high level of interactivity.