Research on Cognitive Load Theory and Its Design Implications for E-Learning Advisor : Ming-Puu Chen Reporter : Hui-Lan Juan 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.

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

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.

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.

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.

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.

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.

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”

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

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.”

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.”

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.

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.