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SIMulation based on language and learning (SIMBaLL): the model.
Ellyn Arwood1, Joanna Kaakinen
1University of Portland. arwood@up.edu
This study introduces SIMBaLL, a simulation model based on language learning theory, to effectively assess student learning outcomes. It provides a structured framework for measuring conceptual understanding in educational simulations.
Area of Science:
- Educational Technology
- Learning Sciences
- Simulation-Based Education
Background:
- Effective simulation design requires a theoretical foundation.
- Assessing learning outcomes in simulations is crucial for educational efficacy.
- Existing models may not adequately capture conceptual learning.
Purpose of the Study:
- To highlight the importance of learning theories in simulation development.
- To introduce SIMBaLL (SIMulation Based on Language and Learning), a novel simulation model.
- To establish a hierarchical framework for assessing conceptual learning outcomes.
Main Methods:
- Developed SIMBaLL, a simulation model derived from Arwood's Neurosemantic Language Learning Theory.
- Utilized principles of language learning to structure the simulation.
- Designed a hierarchical framework for assessment.
Main Results:
- The SIMBaLL model offers a structured approach to simulation design.
- The framework facilitates the assessment of conceptual learning within simulations.
- Demonstrated the integration of learning theory into simulation development.
Conclusions:
- Learning theories are essential for robust simulation design and outcome assessment.
- SIMBaLL provides a validated method for measuring conceptual learning in simulations.
- This model enhances the pedagogical value of educational simulations.
