Evolutionary Computation-Assisted Brainwriting for Large-Scale Online Ideation
Nobuo Namura, Tatsuya Hasebe

TL;DR
This paper introduces an evolutionary computation-assisted brainwriting method for large-scale online ideation, enabling diverse participant engagement and improving idea quality through evolutionary selection and evaluation.
Contribution
It presents a novel integration of evolutionary computation with online brainwriting to enhance idea diversity and quality in large-scale collaborative ideation sessions.
Findings
Enhanced robustness in idea quality improvement.
Better exposure to high-quality ideas among participants.
Outperformed simple online brainwriting methods.
Abstract
Brainstorming is an effective technique for offline ideation although the number of participants able to join an ideation session and suggest ideas is limited. To increase the diversity and quality of the ideas suggested, many participants with various backgrounds should be able to join the session. We have devised an evolutionary computation-assisted brainwriting method for large-scale online ideation. In this method, participants not only suggest ideas but also evaluate ideas previously suggested by other participants. The evaluation results are used in the evolutionary computation to identify good ideas to which the participants can be exposed via a brainwriting-like interface. We compared the performance of the proposed method with that of a simple online brainwriting method for large-scale online ideation with more than 30 participants. The proposed method enhanced robustness of…
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Taxonomy
TopicsMusic Technology and Sound Studies · Artificial Intelligence in Games · Innovative Teaching and Learning Methods
