Design Factors for Effective Science Simulations
From unthinkMedia
design factors such as the type of representation of key concepts in the simulation affect the effectiveness of computer simulations when cognitive load is high, and that individual difference variables such as prior knowledge moderate these effects.
Contents |
Simulations
- must take into account the limitations of our perceptual and cognitive systems
- allows learners to engage in processes of scientific reasoning (problem definition, hypothesis generation, experimentation, observation, and data interpretation)
- reveals the underlying computational model to assist learners in interpreting changes in variables.
- can help learners understanding the dynamic relationship between variables and representations.
- simulation's interactivity, especially the possibility to manipulate the content of the visualization by adjusting parameters, improve learning
Disadvantages
- can impose high cognitive load if learners do not possess the required knowledge, cognitive abilities, or metacognitive skills necessary to pursue scientific reasoning through simulations.
Animations
- do not allow for significant user interactions
Design Factors
- information design & interaction design of the material
- level of cognitive load
Types of Cognitive Load
intrinsic cognitive load
- the processing of essential information which is determined by the complexity of the material to be learned.
- the level of element interactivity in learning materials
- the # of items that need to be stored in working memory in order to comprehend the material.
extraneous cognitive load
- refers to processing nonessential information
- is determined by the design of the instruction and the presentation of the materials, which includes the instructional format as well as the format of the representation of information
Instructional designers aim to reduce extraneous cognitive load, especially in situations when intrinsic cognitive load is high.
Methods of Cognitive Load
Verbal
verbal information consists of discreet symbolic representations that are processed sequentially
Visual
visual information is inherently relational and its elements can be encoded simultaneously
Working Memory Models
Prior Knowledge
organized knowledge structures from long-term memory. moderates the effectiveness of content representation
Low Prior Knowledge
- benefit more from static images
- benifit from the use of icons.
High Prior Knowledge
- benefit more from dynamic visualizations
- can reduce working memory limitations by chunking several bits of related information together into a single, higher-level element
- benefit from the use of icons, but not as much as low prior knowledge, yet may sometimes find them distracting.
Visual Representation of Knowledge
- interpretation requires a certain amount of domain-specific knowledge and visual literacy.
- representation that are better for experts may be dificult to novices.
Descriptive
abstract, arbitrary and rely on social conventions for meaning. (symbols)
Cognitive load increases when novice learners have to interpret the meaning of symbolic representations that implicitly assume prior domain-specific knowledge
diagrams depend on student domain-specific knowledge and experience
Depictive
the most basic, rely on physical resemblance to convey meaning (icons)
novices and those with low prior knowledge may benefit more from the use of iconic visuals.
- adding icons that represent key concepts in the simulation display should enhance learning.
- iconic representations reduced cognitive load compared to the written, symbolic information, freeing cognitive resources and allowing students to solve complex tasks.
- feedback in simulations is more effective when it is provided in graphical rather than textual form
- improves a students perception of their own ability to learn, self-efficacy.
icons can facilitate learning and increase self-efficacy in visual learning environments, particularly for low prior knowledge learners, and especially under high cognitive load conditions.
Self-efficacy
- learners’ predictive judgment of their efficacy of performing a task
- relates to self-regulation
- is a predictor of learning success
Reference
Plass, J.L., Homer, B.D., Milne, C., Jordan, T., Kalyuga, S., Kim, M., & Lee, H.J. (in press). Design Factors for Effective Science Simulations: Representation of Information. International Journal of Gaming and Computer-Mediated Simulations, 1(1).
