Title:	EXPLORING THE EFFECTS OF STRUCTURAL TRANSPARENCY AND EXPLORATORY GUIDANCE IN SIMULATION-BASED LEARNING ENVIRONMENTS
Author(s):	Carlos Capelo and Ana Lorga
ISBN:	978-989-8533-93-7
Editors:	Demetrios G. Sampson, Dirk Ifenthaler, Pedro Isaías and Maria Lidia Mascia
Year:	2019
Edition:	Single
Keywords:	Management Education, Simulation-Based Learning, System Dynamics, Model Transparency, Instructional Guidance, Supply Chain Management, Bullwhip Effect
Type:	Full Paper
First Page:	151
Last Page:	158
Language:	English
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Paper Abstract:	Simulation-based learning environments are used extensively to support learning on complex business systems. Nevertheless, there exist studies that identify problems and limitations due to cognitive processing difficulties. Particularly, previous research addressed some aspects of model transparency and instructional strategy and produced inconclusive results about their impact on learning effectiveness. This study investigates the learning effects of using transparent simulations (that is, showing users the internal structure of models), and exploratory guidance (that is, guiding learners so they are able to explore the simulation by themselves, supported by specific cognitive aids). We present a set of hypotheses about the influence of the degree of simulator transparency and the degree of exploratory guidance on participants’ model comprehension which is assessed in terms of mental model structure and behaviour similarities. A test based on a simulation experiment with a system dynamics model, representing a supply chain system, was performed. Participants are required to use the simulator to investigate on some issues related to the bullwhip effect and other supply chain coordination concepts. Participants provided with the more transparent strategy and offered the more exploratory guidance demonstrated better understanding of the structure and behaviour of the underlying model. However, our results suggest that while exploratory guidance is a beneficial method for both model structure and behaviour understanding, making solely the model transparent is more limited in its effect.
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