Dynamics of automatized measures of creativity: mapping the landscape to quantify creative ideation - Ul Haq, Ijaz; Pifarré, Manoli (Frontiers in Education, 2023)
The growing body of creativity research involves Artificial Intelligence (AI) and Machine learning (ML) approaches to automatically evaluating creative solutions. However, numerous challenges persist in evaluating the creativity dimensions and the methodologies employed for automatic evaluation. This paper contributes to the debate with a scoping review that maps the Natural Language Processing (NLP) approaches to computations of different creativity dimensions. This mapping covers the scope of automatic creativity evaluation in two ways. Firstly, identifying different computational approaches and techniques in creativity evaluation. This paper categorises the automatic creativity research in the reviewed papers into three NLP approaches, namely: text similarity, text classification, and text mining. This categorization and further compilation of computational techniques used in these NLP approaches help ameliorate their application scenarios, research gaps, research limitations, and alternative solutions. Secondly, the paper analyses the automatic evaluation of different creativity dimensions. The papers in the scoping review differentiated the evaluation of 25 different creativity dimensions. Attending similarities in definitions and computations, we characterised seven core creativity dimensions, namely: novelty, value, flexibility, elaboration, fluency, feasibility, and others related to playful aspects of creativity. We hope this scoping review could provide valuable insights for researchers from psychology, education, AI, and others to make evidence-based decisions when developing automated creativity evaluation.