Difference between revisions of "Learning Approaches For Complex Topics"

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Research on learning preferences challenges traditional assumptions about fixed learning styles while highlighting the importance of adapting presentation methods to audience expertise and context.
 
Research on learning preferences challenges traditional assumptions about fixed learning styles while highlighting the importance of adapting presentation methods to audience expertise and context.
 
== Concrete vs. Abstract Approaches ==
 
== Concrete vs. Abstract Approaches ==
=== Transfer of Scientific Principles ===
+
=== The Transfer of Scientific Principles Using Concrete and Idealized Simulations ===
[[CiteRef::goldstone2005ts]]
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[[CiteRef::goldstone2005th]]
 
{{#scite:
 
{{#scite:
|reference=goldstone2005ts
+
|reference=goldstone2005th
 
|type=journal-article
 
|type=journal-article
 
|title=The Transfer of Scientific Principles Using Concrete and Idealized Simulations
 
|title=The Transfer of Scientific Principles Using Concrete and Idealized Simulations
 
|authors=Robert L. Goldstone;Ji Y. Son
 
|authors=Robert L. Goldstone;Ji Y. Son
|journal=The Journal of the Learning Sciences
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|journal=Journal of the Learning Sciences
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|publisher=Informa UK Limited
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|issn=1050-8406;1532-7809|+sep=;
 
|volume=14
 
|volume=14
 
|pages=69-110
 
|pages=69-110
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|doi=10.1207/s15327809jls1401_4
 
|year=2005
 
|year=2005
|doi=10.1207/s15327809jls1401_4
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|retrieved-from=https://doi.org/
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|retrieved-on=2024-11-09
 
}}
 
}}
 
The effectiveness of concrete versus abstract presentations varies depending on learning objectives and learner expertise. Research suggests that combining both approaches often yields optimal results.
 
The effectiveness of concrete versus abstract presentations varies depending on learning objectives and learner expertise. Research suggests that combining both approaches often yields optimal results.
 
=== Example-Based Learning ===
 
=== Example-Based Learning ===
[[CiteRef::renkl2014lw]]
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=== Learning from Worked‐Out Examples: A Study on Individual Differences ===
 +
[[CiteRef::renkl1997le]]
 
{{#scite:
 
{{#scite:
|reference=renkl2014lw
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|reference=renkl1997le
 
|type=journal-article
 
|type=journal-article
|title=Learning from Worked Examples: How to Prepare Students for Meaningful Problem Solving
+
|title=Learning from Worked‐Out Examples: A Study on Individual Differences
 
|authors=Alexander Renkl
 
|authors=Alexander Renkl
|journal=Policy Insights from the Behavioral and Brain Sciences
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|journal=Cognitive Science
|volume=1
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|publisher=Wiley
|pages=33-40
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|issn=0364-0213;1551-6709|+sep=;
|year=2014
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|volume=21
|doi=10.1177/2372732214548486
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|pages=1-29
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|doi=10.1207/s15516709cog2101_1
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|year=1997
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|retrieved-from=https://doi.org/
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|retrieved-on=2024-11-09
 
}}
 
}}
 
Worked examples serve as an effective bridge between concrete applications and abstract theoretical concepts, particularly for novice learners.
 
Worked examples serve as an effective bridge between concrete applications and abstract theoretical concepts, particularly for novice learners.

Latest revision as of 08:54, 9 November 2024

Learning Approaches for Complex Topics

Introduction

When explaining complex topics, the effectiveness of different presentation orders depends heavily on the target audience. While scientific circles often prefer starting with formalized theoretical frameworks, pedagogical settings may benefit from more flexible approaches that consider audience preferences and learning needs.

Theoretical Foundations

Cognitive Load During Problem Solving: Effects on Learning

1

Cognitive Load Theory provides a fundamental framework for understanding how working memory limitations affect the learning of complex topics. This theory suggests that instructional methods should be designed to optimize cognitive resources during the learning process.

Learning Preferences and Individual Differences

2

Research on learning preferences challenges traditional assumptions about fixed learning styles while highlighting the importance of adapting presentation methods to audience expertise and context.

Concrete vs. Abstract Approaches

The Transfer of Scientific Principles Using Concrete and Idealized Simulations

3

The effectiveness of concrete versus abstract presentations varies depending on learning objectives and learner expertise. Research suggests that combining both approaches often yields optimal results.

Example-Based Learning

Learning from Worked‐Out Examples: A Study on Individual Differences

4

Worked examples serve as an effective bridge between concrete applications and abstract theoretical concepts, particularly for novice learners.

Best Practices

Sequential Approach

For scientific audiences:

    • Begin with theoretical frameworks
    • Follow with concrete applications
    • Emphasize formal relationships between concepts

Adaptive Approach

For pedagogical settings:

    • Consider audience preferences
    • Assess prior knowledge levels
    • Adjust presentation order accordingly
    • Maintain explicit connections between theory and practice

Conclusions

Research suggests that while presentation order matters, the most effective approach often combines both theoretical and practical elements, with explicit connections between them. The optimal sequence may vary based on audience expertise, context, and learning objectives.

⚠️ LLM-generated content notice: Parts of this page may have been created or edited with the assistance of a large language model (LLM). The prompts that have been used might be on the page itself, the discussion page or in straight forward cases the prompt was just "Write a mediawiki page on X" with X being the page name. While the content has been reviewed it might still not be accurate or error-free.

References

  1. ^  John Sweller. (1988) "Cognitive Load During Problem Solving: Effects on Learning" - 257-285 pages. doi: 10.1207/s15516709cog1202_4
  2. ^  Harold Pashler;Mark McDaniel;Doug Rohrer;Robert Bjork. (2008) "Learning Styles" - 105-119 pages. doi: 10.1111/j.1539-6053.2009.01038.x
  3. ^ goldstone2005ts 
  4. ^ renkl2014lw