Differentiated knowledge measures framework: static/dynamic, modality, and quality categories¶

Theory · All theories
Evidence · 3 claims (3 for) · 1 study (1 causal), q2 · 0 of 1 report an effect size · 3 claims rest on one study

Description¶

The article proposes that multimedia learning effects should be evaluated with knowledge measures differentiated along three categories. As printed: "We defined three knowledge categories: static/dynamic (process or facts knowledge), modality (verbal or visual knowledge), and quality (passive or active knowledge)." Static/dynamic distinguishes facts (objects, events, symbols) from processes (flows of interdependent causalities); modality derives from dual coding theory's separate verbal and visual channels; quality contrasts active (production/reconstruction) with passive (recognition) knowledge. The framework let the study show that media effects differ by knowledge category rather than being uniform.

Design Implications¶

Context¶

Requirements¶

• Learning outcome tests must include measures reflecting both static and dynamic knowledge characteristics when the topic contains both

Constraints¶

• The active/passive distinction is described as heuristic and explorative, not tied to hypothesis testing in this study

Target Learners¶

• Adult learners in experimental multimedia-learning research

Target Learning Objectives¶

• Assessing knowledge acquisition of facts and processes across verbal, visual, active and passive knowledge forms

Claims¶

• Media Effects Vary By Knowledge Category [+M]
• No media effect for process knowledge: animation did not improve learning of dynamic content [+W]
• Pre-experimental knowledge and education level relate to specific knowledge categories [+W]

Related Theories¶

Examples¶

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Key Sources¶

• Guttormsen Schär, S., & Zimmermann, P. G. (2007). Investigating Means to Reduce Cognitive Load from Animations: Applying Differentiated Measures of Knowledge Representation. Journal of Research on Technology in Education, 40(1), 64–78. https://eric.ed.gov/?id=EJ826063