Data on the configuration design of internet-connected home cooling systems by engineering students
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This experiment was carried out to record the step-by-step actions that humans take in solving a configuration design problem, either in small teams or individually. Specifically, study participants were tasked with configuring an internet-connected system of products to maintain temperature within a home, subject to cost constraints. Every participant was given access to a computer-based design interface that allowed them to construct and assess solutions. The interface was also used to record the data that is presented here. In total, data was collected for 68 participants, and each participant was allowed to perform 50 design actions in solving the configuration design problem. Major results based on the data presented here have been reported separately, including initial behavioral analysis (McComb et al.) [1], [2] and design pattern assessments via Markovian modeling (McComb et al., 2017; McComb et al., 2017) [3], [4].
[1] Christopher McComb,et al. Mining Process Heuristics From Designer Action Data via Hidden Markov Models , 2017 .
[2] Christopher McComb,et al. Capturing Human Sequence-Learning Abilities in Configuration Design Tasks through Markov Chains , 2017 .
[3] Christopher McComb,et al. Validating a Tool for Predicting Problem-Specific Optimized Team Characteristics , 2017 .
[4] Christopher McComb,et al. Optimizing Design Teams Based on Problem Properties: Computational Team Simulations and an Applied Empirical Test , 2017 .